Compression of Encrypted Images Using Set Partitioning In Hierarchical Trees Algorithm

NASA Astrophysics Data System (ADS)

Sarika, G.; Unnithan, Harikuttan; Peter, Smitha

2011-10-01

When it is desired to transmit redundant data over an insecure channel, it is customary to encrypt the data. For encrypted real world sources such as images, the use of Markova properties in the slepian-wolf decoder does not work well for gray scale images. Here in this paper we propose a method of compression of an encrypted image. In the encoder section, the image is first encrypted and then it undergoes compression in resolution. The cipher function scrambles only the pixel values, but does not shuffle the pixel locations. After down sampling, each sub-image is encoded independently and the resulting syndrome bits are transmitted. The received image undergoes a joint decryption and decompression in the decoder section. By using the local statistics based on the image, it is recovered back. Here the decoder gets only lower resolution version of the image. In addition, this method provides only partial access to the current source at the decoder side, which improves the decoder's learning of the source statistics. The source dependency is exploited to improve the compression efficiency. This scheme provides better coding efficiency and less computational complexity.

Decoding Multiple Sound Categories in the Human Temporal Cortex Using High Resolution fMRI

PubMed Central

Zhang, Fengqing; Wang, Ji-Ping; Kim, Jieun; Parrish, Todd; Wong, Patrick C. M.

2015-01-01

Perception of sound categories is an important aspect of auditory perception. The extent to which the brain’s representation of sound categories is encoded in specialized subregions or distributed across the auditory cortex remains unclear. Recent studies using multivariate pattern analysis (MVPA) of brain activations have provided important insights into how the brain decodes perceptual information. In the large existing literature on brain decoding using MVPA methods, relatively few studies have been conducted on multi-class categorization in the auditory domain. Here, we investigated the representation and processing of auditory categories within the human temporal cortex using high resolution fMRI and MVPA methods. More importantly, we considered decoding multiple sound categories simultaneously through multi-class support vector machine-recursive feature elimination (MSVM-RFE) as our MVPA tool. Results show that for all classifications the model MSVM-RFE was able to learn the functional relation between the multiple sound categories and the corresponding evoked spatial patterns and classify the unlabeled sound-evoked patterns significantly above chance. This indicates the feasibility of decoding multiple sound categories not only within but across subjects. However, the across-subject variation affects classification performance more than the within-subject variation, as the across-subject analysis has significantly lower classification accuracies. Sound category-selective brain maps were identified based on multi-class classification and revealed distributed patterns of brain activity in the superior temporal gyrus and the middle temporal gyrus. This is in accordance with previous studies, indicating that information in the spatially distributed patterns may reflect a more abstract perceptual level of representation of sound categories. Further, we show that the across-subject classification performance can be significantly improved by averaging the fMRI images over items, because the irrelevant variations between different items of the same sound category are reduced and in turn the proportion of signals relevant to sound categorization increases. PMID:25692885

Decoding multiple sound categories in the human temporal cortex using high resolution fMRI.

PubMed

Zhang, Fengqing; Wang, Ji-Ping; Kim, Jieun; Parrish, Todd; Wong, Patrick C M

2015-01-01

Perception of sound categories is an important aspect of auditory perception. The extent to which the brain's representation of sound categories is encoded in specialized subregions or distributed across the auditory cortex remains unclear. Recent studies using multivariate pattern analysis (MVPA) of brain activations have provided important insights into how the brain decodes perceptual information. In the large existing literature on brain decoding using MVPA methods, relatively few studies have been conducted on multi-class categorization in the auditory domain. Here, we investigated the representation and processing of auditory categories within the human temporal cortex using high resolution fMRI and MVPA methods. More importantly, we considered decoding multiple sound categories simultaneously through multi-class support vector machine-recursive feature elimination (MSVM-RFE) as our MVPA tool. Results show that for all classifications the model MSVM-RFE was able to learn the functional relation between the multiple sound categories and the corresponding evoked spatial patterns and classify the unlabeled sound-evoked patterns significantly above chance. This indicates the feasibility of decoding multiple sound categories not only within but across subjects. However, the across-subject variation affects classification performance more than the within-subject variation, as the across-subject analysis has significantly lower classification accuracies. Sound category-selective brain maps were identified based on multi-class classification and revealed distributed patterns of brain activity in the superior temporal gyrus and the middle temporal gyrus. This is in accordance with previous studies, indicating that information in the spatially distributed patterns may reflect a more abstract perceptual level of representation of sound categories. Further, we show that the across-subject classification performance can be significantly improved by averaging the fMRI images over items, because the irrelevant variations between different items of the same sound category are reduced and in turn the proportion of signals relevant to sound categorization increases.

Digital cinema system using JPEG2000 movie of 8-million pixel resolution

NASA Astrophysics Data System (ADS)

Fujii, Tatsuya; Nomura, Mitsuru; Shirai, Daisuke; Yamaguchi, Takahiro; Fujii, Tetsuro; Ono, Sadayasu

2003-05-01

We have developed a prototype digital cinema system that can store, transmit and display extra high quality movies of 8-million pixel resolution, using JPEG2000 coding algorithm. The image quality is 4 times better than HDTV in resolution, and enables us to replace conventional films with digital cinema archives. Using wide-area optical gigabit IP networks, cinema contents are distributed and played back as a video-on-demand (VoD) system. The system consists of three main devices, a video server, a real-time JPEG2000 decoder, and a large-venue LCD projector. All digital movie data are compressed by JPEG2000 and stored in advance. The coded streams of 300~500 Mbps can be continuously transmitted from the PC server using TCP/IP. The decoder can perform the real-time decompression at 24/48 frames per second, using 120 parallel JPEG2000 processing elements. The received streams are expanded into 4.5Gbps raw video signals. The prototype LCD projector uses 3 pieces of 3840×2048 pixel reflective LCD panels (D-ILA) to show RGB 30-bit color movies fed by the decoder. The brightness exceeds 3000 ANSI lumens for a 300-inch screen. The refresh rate is chosen to 96Hz to thoroughly eliminate flickers, while preserving compatibility to cinema movies of 24 frames per second.

A Lower-Cost High-Resolution LYSO Detector Development for Positron Emission Mammography (PEM)

PubMed Central

Ramirez, Rocio A.; Zhang, Yuxuan; Liu, Shitao; Li, Hongdi; Baghaei, Hossain; An, Shaohui; Wang, Chao; Jan, Meei-Ling; Wong, Wai-Hoi

2010-01-01

In photomultiplier-quadrant-sharing (PQS) geometry for positron emission tomography applications, each PMT is shared by four blocks and each detector block is optically coupled to four round PMTs. Although this design reduces the cost of high-resolution PET systems, when the camera consists of detector panels that are made up of square blocks, half of the PMT’s sensitive window remains unused at the detector panel edge. Our goal was to develop a LYSO detector panel which minimizes the unused portion of the PMTs for a low-cost, high-resolution, and high-sensitivity positron emission mammography (PEM) camera. We modified the PQS design by using elongated blocks at panel edges and square blocks in the inner area. For elongated blocks, symmetric and asymmetrical reflector patterns were developed and PQS and PMT-half-sharing (PHS) arrangements were implemented in order to obtain a suitable decoding. The packing fraction was 96.3% for asymmetric block and 95.5% for symmetric block. Both of the blocks have excellent decoding capability with all crystals clearly identified, 156 for asymmetric and 144 for symmetric and peak-to-valley ratio of 3.0 and 2.3 respectively. The average energy resolution was 14.2% for the asymmetric block and 13.1% for the symmetric block. Using a modified PQS geometry and asymmetric block design, we reduced the unused PMT region at detector panel edges, thereby increased the field-of-view and the overall detection sensitivity and minimized the undetected breast region near the chest wall. This detector design and using regular round PMT allowed building a lower-cost, high-resolution and high-sensitivity PEM camera. PMID:20485510

The System Design, Engineering Architecture, and Preliminary Results of a Lower-Cost High-Sensitivity High-Resolution Positron Emission Mammography Camera.

PubMed

Zhang, Yuxuan; Ramirez, Rocio A; Li, Hongdi; Liu, Shitao; An, Shaohui; Wang, Chao; Baghaei, Hossain; Wong, Wai-Hoi

2010-02-01

A lower-cost high-sensitivity high-resolution positron emission mammography (PEM) camera is developed. It consists of two detector modules with the planar detector bank of 20 × 12 cm(2). Each bank has 60 low-cost PMT-Quadrant-Sharing (PQS) LYSO blocks arranged in a 10 × 6 array with two types of geometries. One is the symmetric 19.36 × 19.36 mm(2) block made of 1.5 × 1.5 × 10 mm(3) crystals in a 12 × 12 array. The other is the 19.36 × 26.05 mm(2) asymmetric block made of 1.5 × 1.9 × 10 mm(3) crystals in 12 × 13 array. One row (10) of the elongated blocks are used along one side of the bank to reclaim the half empty PMT photocathode in the regular PQS design to reduce the dead area at the edge of the module. The bank has a high overall crystal packing fraction of 88%, which results in a very high sensitivity. Mechanical design and electronics have been developed for low-cost, compactness, and stability purposes. Each module has four Anger-HYPER decoding electronics that can handle a count-rate of 3 Mcps for single events. A simple two-module coincidence board with a hardware delay window for random coincidences has been developed with an adjustable window of 6 to 15 ns. Some of the performance parameters have been studied by preliminary tests and Monte Carlo simulations, including the crystal decoding map and the 17% energy resolution of the detectors, the point source sensitivity of 11.5% with 50 mm bank-to-bank distance, the 1.2 mm-spatial resolutions, 42 kcps peak Noise Equivalent Count Rate at 7.0-mCi total activity in human body, and the resolution phantom images. Those results show that the design goal of building a lower-cost, high-sensitivity, high-resolution PEM detector is achieved.

A novel depth-of-interaction block detector for positron emission tomography using a dichotomous orthogonal symmetry decoding concept.

PubMed

Zhang, Yuxuan; Yan, Han; Baghaei, Hossain; Wong, Wai-Hoi

2016-02-21

Conventionally, a dual-end depth-of-interaction (DOI) block detector readout requires two two-dimensional silicon photomultiplier (SiPM) arrays, one on top and one on the bottom, to define the XYZ positions. However, because both the top and bottom SiPM arrays are reading the same pixels, this creates information redundancy. We propose a dichotomous orthogonal symmetric (DOS) dual-end readout block detector design, which removes this redundancy by reducing the number of SiPMs and still achieves XY and DOI (Z) decoding for positron emission tomography (PET) block detector. Reflecting films are used within the block detector to channel photons going to the top of the block to go only in the X direction, and photons going to the bottom are channeled along the Y direction. Despite the unidirectional channeling on each end, the top readout provides both X and Y information using two one-dimensional SiPM arrays instead of a two-dimensional SiPM array; similarly, the bottom readout also provides both X and Y information with just two one-dimensional SiPM arrays. Thus, a total of four one-dimensional SiPM arrays (4  ×  N SiPMs) are used to decode the XYZ positions of the firing pixels instead of two two-dimensional SiPM arrays (2  ×  N  ×  N SiPMs), reducing the number of SiPM arrays per block from 2N(2) to 4 N for PET/MR or PET/CT systems. Moreover, the SiPM arrays on one end can be replaced by two regular photomultiplier tubes (PMTs), so that a block needs only 2 N SiPMs  +  2 half-PMTs; this hybrid-DOS DOI block detector can be used in PET/CT systems. Monte Carlo simulations were carried out to study the performance of our DOS DOI block detector design, including the XY-decoding quality, energy resolution, and DOI resolution. Both BGO and LSO scintillators were studied. We found that 4 mm pixels were well decoded for 5  ×  5 BGO and 9  ×  9 LSO arrays with 4 to 5 mm DOI resolution and 16-20% energy resolution. By adding light-channel decoding, we modified the DOS design to a high-resolution design, which resolved scintillator pixels smaller than the SiPM dimensions. Detector pixels of 2.4 mm were decoded for 8  ×  8 BGO and 15  ×  15 LSO arrays with 5 mm DOI resolution and 20-23% energy resolution. Time performance was also studied for the 8  ×  8 BGO and 15  ×  15 LSO HR-DOS arrays. The timing resolution for the corner and central crystals is 986  ±  122 ps and 1.89  ±  0.17 μs respectively with BGO, 137  ±  42 ps and 458  ±  67 ps respectively with LSO. Monte Carlo simulations with GATE/Geant4 demonstrated the feasibility of our DOS DOI block detector design. In conclusion, our novel design achieved good performance except the time performance while using fewer SiPMs and supporting electronic channels than the current non-DOI PET detectors. This novel design can significantly reduce the cost, heat, and readout complexity of DOI block detectors for PET/MR/CT systems that don't require the time-of-flight capability.

High-throughput illumina strand-specific RNA sequencing library preparation

USDA-ARS?s Scientific Manuscript database

Conventional Illumina RNA-Seq does not have the resolution to decode the complex eukaryote transcriptome due to the lack of RNA polarity information. Strand-specific RNA sequencing (ssRNA-Seq) can overcome these limitations and as such is better suited for genome annotation, de novo transcriptome as...

Compact disk error measurements

NASA Technical Reports Server (NTRS)

Howe, D.; Harriman, K.; Tehranchi, B.

1993-01-01

The objectives of this project are as follows: provide hardware and software that will perform simple, real-time, high resolution (single-byte) measurement of the error burst and good data gap statistics seen by a photoCD player read channel when recorded CD write-once discs of variable quality (i.e., condition) are being read; extend the above system to enable measurement of the hard decision (i.e., 1-bit error flags) and soft decision (i.e., 2-bit error flags) decoding information that is produced/used by the Cross Interleaved - Reed - Solomon - Code (CIRC) block decoder employed in the photoCD player read channel; construct a model that uses data obtained via the systems described above to produce meaningful estimates of output error rates (due to both uncorrected ECC words and misdecoded ECC words) when a CD disc having specific (measured) error statistics is read (completion date to be determined); and check the hypothesis that current adaptive CIRC block decoders are optimized for pressed (DAD/ROM) CD discs. If warranted, do a conceptual design of an adaptive CIRC decoder that is optimized for write-once CD discs.

HIGH-RESOLUTION L(Y)SO DETECTORS USING PMT-QUADRANT-SHARING FOR HUMAN & ANIMAL PET CAMERAS

PubMed Central

Ramirez, Rocio A.; Liu, Shitao; Liu, Jiguo; Zhang, Yuxuan; Kim, Soonseok; Baghaei, Hossain; Li, Hongdi; Wang, Yu; Wong, Wai-Hoi

2009-01-01

We developed high resolution L(Y)SO detectors for human and animal PET applications using Photomultiplier-quadrant-sharing (PQS) technology. The crystal sizes were 1.27 × 1.27 × 10 mm3 for the animal PQS-blocks and 3.25 × 3.25 × 20 mm3 for human ones. Polymer mirror film patterns (PMR) were placed between crystals as reflector. The blocks were assembled together using optical grease and wrapped by Teflon tape. The blocks were coupled to regular round PMT’s of 19/51 mm in PQS configuration. List-mode data of Ga-68 source (511 KeV) were acquired with our high yield pileup-event recovery (HYPER) electronics and data acquisition software. The high voltage bias was 1100V. Crystal decoding maps and individual crystal energy resolutions were extracted from the data. To investigate the potential imaging resolution of the PET cameras with these blocks, we used GATE (Geant4 Application for Tomographic Emission) simulation package. GATE is a GEANT4 based software toolkit for realistic simulation of PET and SPECT systems. The packing fractions of these blocks were found to be 95.6% and 98.2%. From the decoding maps, all 196 and 225 crystals were clearly identified. The average energy resolutions were 14.0% and 15.6%. For small animal PET systems, the detector ring diameter was 16.5 cm with an axial field of view (AFOV) of 11.8 cm. The simulation data suggests that a reconstructed radial (tangential) spatial resolution of 1.24 (1.25) mm near the center is potentially achievable. For the wholebody human PET systems, the detector ring diameter was 86 cm. The simulation data suggests that a reconstructed radial (tangential) spatial resolution of 3.09(3.38) mm near the center is potentially achievable. From this study we can conclude that PQS design could achieve high spatial resolutions and excellent energy resolutions on human and animal PET systems with substantially lower production costs and inexpensive readout devices. PMID:19946463

Sparse super-resolution reconstructions of video from mobile devices in digital TV broadcast applications

NASA Astrophysics Data System (ADS)

Boon, Choong S.; Guleryuz, Onur G.; Kawahara, Toshiro; Suzuki, Yoshinori

2006-08-01

We consider the mobile service scenario where video programming is broadcast to low-resolution wireless terminals. In such a scenario, broadcasters utilize simultaneous data services and bi-directional communications capabilities of the terminals in order to offer substantially enriched viewing experiences to users by allowing user participation and user tuned content. While users immediately benefit from this service when using their phones in mobile environments, the service is less appealing in stationary environments where a regular television provides competing programming at much higher display resolutions. We propose a fast super-resolution technique that allows the mobile terminals to show a much enhanced version of the broadcast video on nearby high-resolution devices, extending the appeal and usefulness of the broadcast service. The proposed single frame super-resolution algorithm uses recent sparse recovery results to provide high quality and high-resolution video reconstructions based solely on individual decoded frames provided by the low-resolution broadcast.

Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach

PubMed Central

Miran, Sina; Akram, Sahar; Sheikhattar, Alireza; Simon, Jonathan Z.; Zhang, Tao; Babadi, Behtash

2018-01-01

Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG) and electroencephalography (EEG). To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach) or vice versa (the encoding approach). To produce robust results, these procedures require multiple trials for training purposes. Also, their decoding accuracy drops significantly when operating at high temporal resolutions. Thus, they are not well-suited for emerging real-time applications such as smart hearing aid devices or brain-computer interface systems, where training data might be limited and high temporal resolutions are desired. In this paper, we close this gap by developing an algorithmic pipeline for real-time decoding of the attentional state. Our proposed framework consists of three main modules: (1) Real-time and robust estimation of encoding or decoding coefficients, achieved by sparse adaptive filtering, (2) Extracting reliable markers of the attentional state, and thereby generalizing the widely-used correlation-based measures thereof, and (3) Devising a near real-time state-space estimator that translates the noisy and variable attention markers to robust and statistically interpretable estimates of the attentional state with minimal delay. Our proposed algorithms integrate various techniques including forgetting factor-based adaptive filtering, ℓ1-regularization, forward-backward splitting algorithms, fixed-lag smoothing, and Expectation Maximization. We validate the performance of our proposed framework using comprehensive simulations as well as application to experimentally acquired M/EEG data. Our results reveal that the proposed real-time algorithms perform nearly as accurately as the existing state-of-the-art offline techniques, while providing a significant degree of adaptivity, statistical robustness, and computational savings. PMID:29765298

Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach.

PubMed

Miran, Sina; Akram, Sahar; Sheikhattar, Alireza; Simon, Jonathan Z; Zhang, Tao; Babadi, Behtash

2018-01-01

Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG) and electroencephalography (EEG). To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach) or vice versa (the encoding approach). To produce robust results, these procedures require multiple trials for training purposes. Also, their decoding accuracy drops significantly when operating at high temporal resolutions. Thus, they are not well-suited for emerging real-time applications such as smart hearing aid devices or brain-computer interface systems, where training data might be limited and high temporal resolutions are desired. In this paper, we close this gap by developing an algorithmic pipeline for real-time decoding of the attentional state. Our proposed framework consists of three main modules: (1) Real-time and robust estimation of encoding or decoding coefficients, achieved by sparse adaptive filtering, (2) Extracting reliable markers of the attentional state, and thereby generalizing the widely-used correlation-based measures thereof, and (3) Devising a near real-time state-space estimator that translates the noisy and variable attention markers to robust and statistically interpretable estimates of the attentional state with minimal delay. Our proposed algorithms integrate various techniques including forgetting factor-based adaptive filtering, ℓ 1 -regularization, forward-backward splitting algorithms, fixed-lag smoothing, and Expectation Maximization. We validate the performance of our proposed framework using comprehensive simulations as well as application to experimentally acquired M/EEG data. Our results reveal that the proposed real-time algorithms perform nearly as accurately as the existing state-of-the-art offline techniques, while providing a significant degree of adaptivity, statistical robustness, and computational savings.

Robust decoding of selective auditory attention from MEG in a competing-speaker environment via state-space modeling✩

PubMed Central

Akram, Sahar; Presacco, Alessandro; Simon, Jonathan Z.; Shamma, Shihab A.; Babadi, Behtash

2015-01-01

The underlying mechanism of how the human brain solves the cocktail party problem is largely unknown. Recent neuroimaging studies, however, suggest salient temporal correlations between the auditory neural response and the attended auditory object. Using magnetoencephalography (MEG) recordings of the neural responses of human subjects, we propose a decoding approach for tracking the attentional state while subjects are selectively listening to one of the two speech streams embedded in a competing-speaker environment. We develop a biophysically-inspired state-space model to account for the modulation of the neural response with respect to the attentional state of the listener. The constructed decoder is based on a maximum a posteriori (MAP) estimate of the state parameters via the Expectation Maximization (EM) algorithm. Using only the envelope of the two speech streams as covariates, the proposed decoder enables us to track the attentional state of the listener with a temporal resolution of the order of seconds, together with statistical confidence intervals. We evaluate the performance of the proposed model using numerical simulations and experimentally measured evoked MEG responses from the human brain. Our analysis reveals considerable performance gains provided by the state-space model in terms of temporal resolution, computational complexity and decoding accuracy. PMID:26436490

Design of UAV high resolution image transmission system

NASA Astrophysics Data System (ADS)

Gao, Qiang; Ji, Ming; Pang, Lan; Jiang, Wen-tao; Fan, Pengcheng; Zhang, Xingcheng

2017-02-01

In order to solve the problem of the bandwidth limitation of the image transmission system on UAV, a scheme with image compression technology for mini UAV is proposed, based on the requirements of High-definition image transmission system of UAV. The video codec standard H.264 coding module and key technology was analyzed and studied for UAV area video communication. Based on the research of high-resolution image encoding and decoding technique and wireless transmit method, The high-resolution image transmission system was designed on architecture of Android and video codec chip; the constructed system was confirmed by experimentation in laboratory, the bit-rate could be controlled easily, QoS is stable, the low latency could meets most applied requirement not only for military use but also for industrial applications.

Analysis on the optical aberration effect on spectral resolution of coded aperture spectroscopy

NASA Astrophysics Data System (ADS)

Hao, Peng; Chi, Mingbo; Wu, Yihui

2017-10-01

The coded aperture spectrometer can achieve high throughput and high spectral resolution by replacing the traditional single slit with two-dimensional array slits manufactured by MEMS technology. However, the sampling accuracy of coding spectrum image will be distorted due to the existence of system aberrations, machining error, fixing errors and so on, resulting in the declined spectral resolution. The influence factor of the spectral resolution come from the decode error, the spectral resolution of each column, and the column spectrum offset correction. For the Czerny-Turner spectrometer, the spectral resolution of each column most depend on the astigmatism, in this coded aperture spectroscopy, the uncorrected astigmatism does result in degraded performance. Some methods must be used to reduce or remove the limiting astigmatism. The curvature of field and the spectral curvature can be result in the spectrum revision errors.

Image acquisition system using on sensor compressed sampling technique

NASA Astrophysics Data System (ADS)

Gupta, Pravir Singh; Choi, Gwan Seong

2018-01-01

Advances in CMOS technology have made high-resolution image sensors possible. These image sensors pose significant challenges in terms of the amount of raw data generated, energy efficiency, and frame rate. This paper presents a design methodology for an imaging system and a simplified image sensor pixel design to be used in the system so that the compressed sensing (CS) technique can be implemented easily at the sensor level. This results in significant energy savings as it not only cuts the raw data rate but also reduces transistor count per pixel; decreases pixel size; increases fill factor; simplifies analog-to-digital converter, JPEG encoder, and JPEG decoder design; decreases wiring; and reduces the decoder size by half. Thus, CS has the potential to increase the resolution of image sensors for a given technology and die size while significantly decreasing the power consumption and design complexity. We show that it has potential to reduce power consumption by about 23% to 65%.

Apparatus and method to achieve high-resolution microscopy with non-diffracting or refracting radiation

DOEpatents

Tobin, Jr., Kenneth W.; Bingham, Philip R.; Hawari, Ayman I.

2012-11-06

An imaging system employing a coded aperture mask having multiple pinholes is provided. The coded aperture mask is placed at a radiation source to pass the radiation through. The radiation impinges on, and passes through an object, which alters the radiation by absorption and/or scattering. Upon passing through the object, the radiation is detected at a detector plane to form an encoded image, which includes information on the absorption and/or scattering caused by the material and structural attributes of the object. The encoded image is decoded to provide a reconstructed image of the object. Because the coded aperture mask includes multiple pinholes, the radiation intensity is greater than a comparable system employing a single pinhole, thereby enabling a higher resolution. Further, the decoding of the encoded image can be performed to generate multiple images of the object at different distances from the detector plane. Methods and programs for operating the imaging system are also disclosed.

Decoding the direction of imagined visual motion using 7 T ultra-high field fMRI

PubMed Central

Emmerling, Thomas C.; Zimmermann, Jan; Sorger, Bettina; Frost, Martin A.; Goebel, Rainer

2016-01-01

There is a long-standing debate about the neurocognitive implementation of mental imagery. One form of mental imagery is the imagery of visual motion, which is of interest due to its naturalistic and dynamic character. However, so far only the mere occurrence rather than the specific content of motion imagery was shown to be detectable. In the current study, the application of multi-voxel pattern analysis to high-resolution functional data of 12 subjects acquired with ultra-high field 7 T functional magnetic resonance imaging allowed us to show that imagery of visual motion can indeed activate the earliest levels of the visual hierarchy, but the extent thereof varies highly between subjects. Our approach enabled classification not only of complex imagery, but also of its actual contents, in that the direction of imagined motion out of four options was successfully identified in two thirds of the subjects and with accuracies of up to 91.3% in individual subjects. A searchlight analysis confirmed the local origin of decodable information in striate and extra-striate cortex. These high-accuracy findings not only shed new light on a central question in vision science on the constituents of mental imagery, but also show for the first time that the specific sub-categorical content of visual motion imagery is reliably decodable from brain imaging data on a single-subject level. PMID:26481673

Single-layer HDR video coding with SDR backward compatibility

NASA Astrophysics Data System (ADS)

Lasserre, S.; François, E.; Le Léannec, F.; Touzé, D.

2016-09-01

The migration from High Definition (HD) TV to Ultra High Definition (UHD) is already underway. In addition to an increase of picture spatial resolution, UHD will bring more color and higher contrast by introducing Wide Color Gamut (WCG) and High Dynamic Range (HDR) video. As both Standard Dynamic Range (SDR) and HDR devices will coexist in the ecosystem, the transition from Standard Dynamic Range (SDR) to HDR will require distribution solutions supporting some level of backward compatibility. This paper presents a new HDR content distribution scheme, named SL-HDR1, using a single layer codec design and providing SDR compatibility. The solution is based on a pre-encoding HDR-to-SDR conversion, generating a backward compatible SDR video, with side dynamic metadata. The resulting SDR video is then compressed, distributed and decoded using standard-compliant decoders (e.g. HEVC Main 10 compliant). The decoded SDR video can be directly rendered on SDR displays without adaptation. Dynamic metadata of limited size are generated by the pre-processing and used to reconstruct the HDR signal from the decoded SDR video, using a post-processing that is the functional inverse of the pre-processing. Both HDR quality and artistic intent are preserved. Pre- and post-processing are applied independently per picture, do not involve any inter-pixel dependency, and are codec agnostic. Compression performance, and SDR quality are shown to be solidly improved compared to the non-backward and backward-compatible approaches, respectively using the Perceptual Quantization (PQ) and Hybrid Log Gamma (HLG) Opto-Electronic Transfer Functions (OETF).

High rate concatenated coding systems using bandwidth efficient trellis inner codes

NASA Technical Reports Server (NTRS)

Deng, Robert H.; Costello, Daniel J., Jr.

1989-01-01

High-rate concatenated coding systems with bandwidth-efficient trellis inner codes and Reed-Solomon (RS) outer codes are investigated for application in high-speed satellite communication systems. Two concatenated coding schemes are proposed. In one the inner code is decoded with soft-decision Viterbi decoding, and the outer RS code performs error-correction-only decoding (decoding without side information). In the other, the inner code is decoded with a modified Viterbi algorithm, which produces reliability information along with the decoded output. In this algorithm, path metrics are used to estimate the entire information sequence, whereas branch metrics are used to provide reliability information on the decoded sequence. This information is used to erase unreliable bits in the decoded output. An errors-and-erasures RS decoder is then used for the outer code. The two schemes have been proposed for high-speed data communication on NASA satellite channels. The rates considered are at least double those used in current NASA systems, and the results indicate that high system reliability can still be achieved.

Tracking neural coding of perceptual and semantic features of concrete nouns

PubMed Central

Sudre, Gustavo; Pomerleau, Dean; Palatucci, Mark; Wehbe, Leila; Fyshe, Alona; Salmelin, Riitta; Mitchell, Tom

2015-01-01

We present a methodological approach employing magnetoencephalography (MEG) and machine learning techniques to investigate the flow of perceptual and semantic information decodable from neural activity in the half second during which the brain comprehends the meaning of a concrete noun. Important information about the cortical location of neural activity related to the representation of nouns in the human brain has been revealed by past studies using fMRI. However, the temporal sequence of processing from sensory input to concept comprehension remains unclear, in part because of the poor time resolution provided by fMRI. In this study, subjects answered 20 questions (e.g. is it alive?) about the properties of 60 different nouns prompted by simultaneous presentation of a pictured item and its written name. Our results show that the neural activity observed with MEG encodes a variety of perceptual and semantic features of stimuli at different times relative to stimulus onset, and in different cortical locations. By decoding these features, our MEG-based classifier was able to reliably distinguish between two different concrete nouns that it had never seen before. The results demonstrate that there are clear differences between the time course of the magnitude of MEG activity and that of decodable semantic information. Perceptual features were decoded from MEG activity earlier in time than semantic features, and features related to animacy, size, and manipulability were decoded consistently across subjects. We also observed that regions commonly associated with semantic processing in the fMRI literature may not show high decoding results in MEG. We believe that this type of approach and the accompanying machine learning methods can form the basis for further modeling of the flow of neural information during language processing and a variety of other cognitive processes. PMID:22565201

fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli.

PubMed

Alink, Arjen; Krugliak, Alexandra; Walther, Alexander; Kriegeskorte, Nikolaus

2013-01-01

The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability might alternatively arise from global orientation-preference maps. Such global maps across V1 could result from bottom-up processing, if the preferences of V1 neurons were biased toward particular orientations (e.g., radial from fixation, or cardinal, i.e., vertical or horizontal). Global maps could also arise from local recurrent or top-down processing, reflecting pre-attentive perceptual grouping, attention spreading, or predictive coding of global form. Here we investigate whether fMRI orientation decoding with 2-mm voxels requires (a) globally coherent orientation stimuli and/or (b) global-scale patterns of V1 activity. We used opposite-orientation gratings (balanced about the cardinal orientations) and spirals (balanced about the radial orientation), along with novel patch-swapped variants of these stimuli. The two stimuli of a patch-swapped pair have opposite orientations everywhere (like their globally coherent parent stimuli). However, the two stimuli appear globally similar, a patchwork of opposite orientations. We find that all stimulus pairs are robustly decodable, demonstrating that fMRI orientation decoding does not require globally coherent orientation stimuli. Furthermore, decoding remained robust after spatial high-pass filtering for all stimuli, showing that fine-grained components of the fMRI patterns reflect visual orientations. Consistent with previous studies, we found evidence for global radial and vertical preference maps in V1. However, these were weak or absent for patch-swapped stimuli, suggesting that global preference maps depend on globally coherent orientations and might arise through recurrent or top-down processes related to the perception of global form.

Signal-to-noise ratio of Singer product apertures

NASA Astrophysics Data System (ADS)

Shutler, Paul M. E.; Byard, Kevin

2017-09-01

Formulae for the signal-to-noise ratio (SNR) of Singer product apertures are derived, allowing optimal Singer product apertures to be identified, and the CPU time required to decode them is quantified. This allows a systematic comparison to be made of the performance of Singer product apertures against both conventionally wrapped Singer apertures, and also conventional product apertures such as square uniformly redundant arrays. For very large images, equivalently for images at very high resolution, the SNR of Singer product apertures is asymptotically as good as the best conventional apertures, but Singer product apertures decode faster than any conventional aperture by at least a factor of ten for image sizes up to several megapixels. These theoretical predictions are verified using numerical simulations, demonstrating that coded aperture video is for the first time a realistic possibility.

Decoding of quantum dots encoded microbeads using a hyperspectral fluorescence imaging method.

PubMed

Liu, Yixi; Liu, Le; He, Yonghong; Zhu, Liang; Ma, Hui

2015-05-19

We presented a decoding method of quantum dots encoded microbeads with its fluorescence spectra using line scan hyperspectral fluorescence imaging (HFI) method. A HFI method was developed to attain both the spectra of fluorescence signal and the spatial information of the encoded microbeads. A decoding scheme was adopted to decode the spectra of multicolor microbeads acquired by the HFI system. Comparison experiments between the HFI system and the flow cytometer were conducted. The results showed that the HFI system has higher spectrum resolution; thus, more channels in spectral dimension can be used. The HFI system detection and decoding experiment with the single-stranded DNA (ssDNA) immobilized multicolor beads was done, and the result showed the efficiency of the HFI system. Surface modification of the microbeads by use of the polydopamine was characterized by the scanning electron microscopy and ssDNA immobilization was characterized by the laser confocal microscope. These results indicate that the designed HFI system can be applied to practical biological and medical applications.

Decoding ensemble activity from neurophysiological recordings in the temporal cortex.

PubMed

Kreiman, Gabriel

2011-01-01

We study subjects with pharmacologically intractable epilepsy who undergo semi-chronic implantation of electrodes for clinical purposes. We record physiological activity from tens to more than one hundred electrodes implanted in different parts of neocortex. These recordings provide higher spatial and temporal resolution than non-invasive measures of human brain activity. Here we discuss our efforts to develop hardware and algorithms to interact with the human brain by decoding ensemble activity in single trials. We focus our discussion on decoding visual information during a variety of visual object recognition tasks but the same technologies and algorithms can also be directly applied to other cognitive phenomena.

Real-time distributed video coding for 1K-pixel visual sensor networks

NASA Astrophysics Data System (ADS)

Hanca, Jan; Deligiannis, Nikos; Munteanu, Adrian

2016-07-01

Many applications in visual sensor networks (VSNs) demand the low-cost wireless transmission of video data. In this context, distributed video coding (DVC) has proven its potential to achieve state-of-the-art compression performance while maintaining low computational complexity of the encoder. Despite their proven capabilities, current DVC solutions overlook hardware constraints, and this renders them unsuitable for practical implementations. This paper introduces a DVC architecture that offers highly efficient wireless communication in real-world VSNs. The design takes into account the severe computational and memory constraints imposed by practical implementations on low-resolution visual sensors. We study performance-complexity trade-offs for feedback-channel removal, propose learning-based techniques for rate allocation, and investigate various simplifications of side information generation yielding real-time decoding. The proposed system is evaluated against H.264/AVC intra, Motion-JPEG, and our previously designed DVC prototype for low-resolution visual sensors. Extensive experimental results on various data show significant improvements in multiple configurations. The proposed encoder achieves real-time performance on a 1k-pixel visual sensor mote. Real-time decoding is performed on a Raspberry Pi single-board computer or a low-end notebook PC. To the best of our knowledge, the proposed codec is the first practical DVC deployment on low-resolution VSNs.

Real-time high-resolution PC-based system for measurement of errors on compact disks

NASA Astrophysics Data System (ADS)

Tehranchi, Babak; Howe, Dennis G.

1994-10-01

Hardware and software utilities are developed to directly monitor the Eight-to-Fourteen (EFM) demodulated data bytes at the input of a CD player's Cross-Interleaved Reed-Solomon Code (CIRC) block decoder. The hardware is capable of identifying erroneous data with single-byte resolution in the serial data stream read from a Compact Disc by a CDD 461 Philips CD-ROM drive. In addition, the system produces graphical maps that show the physical location of the measured errors on the entire disc, or via a zooming and planning feature, on user selectable local disc regions.

High-resolution, low-delay, and error-resilient medical ultrasound video communication using H.264/AVC over mobile WiMAX networks.

PubMed

Panayides, Andreas; Antoniou, Zinonas C; Mylonas, Yiannos; Pattichis, Marios S; Pitsillides, Andreas; Pattichis, Constantinos S

2013-05-01

In this study, we describe an effective video communication framework for the wireless transmission of H.264/AVC medical ultrasound video over mobile WiMAX networks. Medical ultrasound video is encoded using diagnostically-driven, error resilient encoding, where quantization levels are varied as a function of the diagnostic significance of each image region. We demonstrate how our proposed system allows for the transmission of high-resolution clinical video that is encoded at the clinical acquisition resolution and can then be decoded with low-delay. To validate performance, we perform OPNET simulations of mobile WiMAX Medium Access Control (MAC) and Physical (PHY) layers characteristics that include service prioritization classes, different modulation and coding schemes, fading channels conditions, and mobility. We encode the medical ultrasound videos at the 4CIF (704 × 576) resolution that can accommodate clinical acquisition that is typically performed at lower resolutions. Video quality assessment is based on both clinical (subjective) and objective evaluations.

Novel positioning method using Gaussian mixture model for a monolithic scintillator-based detector in positron emission tomography

NASA Astrophysics Data System (ADS)

Bae, Seungbin; Lee, Kisung; Seo, Changwoo; Kim, Jungmin; Joo, Sung-Kwan; Joung, Jinhun

2011-09-01

We developed a high precision position decoding method for a positron emission tomography (PET) detector that consists of a thick slab scintillator coupled with a multichannel photomultiplier tube (PMT). The DETECT2000 simulation package was used to validate light response characteristics for a 48.8 mm×48.8 mm×10 mm slab of lutetium oxyorthosilicate coupled to a 64 channel PMT. The data are then combined to produce light collection histograms. We employed a Gaussian mixture model (GMM) to parameterize the composite light response with multiple Gaussian mixtures. In the training step, light photons acquired by N PMT channels was used as an N-dimensional feature vector and were fed into a GMM training model to generate optimal parameters for M mixtures. In the positioning step, we decoded the spatial locations of incident photons by evaluating a sample feature vector with respect to the trained mixture parameters. The average spatial resolutions after positioning with four mixtures were 1.1 mm full width at half maximum (FWHM) at the corner and 1.0 mm FWHM at the center section. This indicates that the proposed algorithm achieved high performance in both spatial resolution and positioning bias, especially at the corner section of the detector.

Telepathology. Long-distance diagnosis.

PubMed

Weinstein, R S; Bloom, K J; Rozek, L S

1989-04-01

Telepathology is defined as the practice of pathology at a distance, by visualizing an image on a video monitor rather than viewing a specimen directly through a microscope. Components of a telepathology system include the following: (1) a workstation equipped with a high-resolution video camera attached to a remote-controlled light microscope; (2) a pathologist workstation incorporating controls for manipulating the robotic microscope as well as a high-resolution video monitor; and (3) a telecommunications link. Progress has been made in designing and constructing telepathology workstations and fully motorized, computer-controlled light microscopes suitable for telepathology. In addition, components such as video signal digital encoders and decoders that produce remarkably stable, high-color fidelity, and high-resolution images have been incorporated into the workstations. Resolution requirements for the video microscopy component of telepathology have been formally examined in receiver operator characteristic (ROC) curve analyses. Test-of-concept demonstrations have been completed with the use of geostationary satellites as the broadband communication linkages for 750-line resolution video. Potential benefits of telepathology include providing a means of conveniently delivering pathology services in real-time to remote sites or underserviced areas, time-sharing of pathologists' services by multiple institutions, and increasing accessibility to specialty pathologists.

Reconstruction of full high-resolution HSQC using signal split in aliased spectra.

PubMed

Foroozandeh, Mohammadali; Jeannerat, Damien

2015-11-01

Resolution enhancement is a long-sought goal in NMR spectroscopy. In conventional multidimensional NMR experiments, such as the (1) H-(13) C HSQC, the resolution in the indirect dimensions is typically 100 times lower as in 1D spectra because it is limited by the experimental time. Reducing the spectral window can significantly increase the resolution but at the cost of ambiguities in frequencies as a result of spectral aliasing. Fortunately, this information is not completely lost and can be retrieved using methods in which chemical shifts are encoded in the aliased spectra and decoded after processing to reconstruct high-resolution (1) H-(13) C HSQC spectrum with full spectral width and a resolution similar to that of 1D spectra. We applied a new reconstruction method, RHUMBA (reconstruction of high-resolution using multiplet built on aliased spectra), to spectra obtained from the differential evolution for non-ambiguous aliasing-HSQC and the new AMNA (additional modulation for non-ambiguous aliasing)-HSQC experiments. The reconstructed spectra significantly facilitate both manual and automated spectral analyses and structure elucidation based on heteronuclear 2D experiments. The resolution is enhanced by two orders of magnitudes without the usual complications due to spectral aliasing. Copyright © 2015 John Wiley & Sons, Ltd.

Visually Lossless JPEG 2000 for Remote Image Browsing

PubMed Central

Oh, Han; Bilgin, Ali; Marcellin, Michael

2017-01-01

Image sizes have increased exponentially in recent years. The resulting high-resolution images are often viewed via remote image browsing. Zooming and panning are desirable features in this context, which result in disparate spatial regions of an image being displayed at a variety of (spatial) resolutions. When an image is displayed at a reduced resolution, the quantization step sizes needed for visually lossless quality generally increase. This paper investigates the quantization step sizes needed for visually lossless display as a function of resolution, and proposes a method that effectively incorporates the resulting (multiple) quantization step sizes into a single JPEG2000 codestream. This codestream is JPEG2000 Part 1 compliant and allows for visually lossless decoding at all resolutions natively supported by the wavelet transform as well as arbitrary intermediate resolutions, using only a fraction of the full-resolution codestream. When images are browsed remotely using the JPEG2000 Interactive Protocol (JPIP), the required bandwidth is significantly reduced, as demonstrated by extensive experimental results. PMID:28748112

Visual perception as retrospective Bayesian decoding from high- to low-level features

PubMed Central

Ding, Stephanie; Cueva, Christopher J.; Tsodyks, Misha; Qian, Ning

2017-01-01

When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. PMID:29073108

Decoding the attended speech stream with multi-channel EEG: implications for online, daily-life applications

NASA Astrophysics Data System (ADS)

Mirkovic, Bojana; Debener, Stefan; Jaeger, Manuela; De Vos, Maarten

2015-08-01

Objective. Recent studies have provided evidence that temporal envelope driven speech decoding from high-density electroencephalography (EEG) and magnetoencephalography recordings can identify the attended speech stream in a multi-speaker scenario. The present work replicated the previous high density EEG study and investigated the necessary technical requirements for practical attended speech decoding with EEG. Approach. Twelve normal hearing participants attended to one out of two simultaneously presented audiobook stories, while high density EEG was recorded. An offline iterative procedure eliminating those channels contributing the least to decoding provided insight into the necessary channel number and optimal cross-subject channel configuration. Aiming towards the future goal of near real-time classification with an individually trained decoder, the minimum duration of training data necessary for successful classification was determined by using a chronological cross-validation approach. Main results. Close replication of the previously reported results confirmed the method robustness. Decoder performance remained stable from 96 channels down to 25. Furthermore, for less than 15 min of training data, the subject-independent (pre-trained) decoder performed better than an individually trained decoder did. Significance. Our study complements previous research and provides information suggesting that efficient low-density EEG online decoding is within reach.

Encoding and decoding amplitude-modulated cochlear implant stimuli—a point process analysis

PubMed Central

Shea-Brown, Eric; Rubinstein, Jay T.

2010-01-01

Cochlear implant speech processors stimulate the auditory nerve by delivering amplitude-modulated electrical pulse trains to intracochlear electrodes. Studying how auditory nerve cells encode modulation information is of fundamental importance, therefore, to understanding cochlear implant function and improving speech perception in cochlear implant users. In this paper, we analyze simulated responses of the auditory nerve to amplitude-modulated cochlear implant stimuli using a point process model. First, we quantify the information encoded in the spike trains by testing an ideal observer’s ability to detect amplitude modulation in a two-alternative forced-choice task. We vary the amount of information available to the observer to probe how spike timing and averaged firing rate encode modulation. Second, we construct a neural decoding method that predicts several qualitative trends observed in psychophysical tests of amplitude modulation detection in cochlear implant listeners. We find that modulation information is primarily available in the sequence of spike times. The performance of an ideal observer, however, is inconsistent with observed trends in psychophysical data. Using a neural decoding method that jitters spike times to degrade its temporal resolution and then computes a common measure of phase locking from spike trains of a heterogeneous population of model nerve cells, we predict the correct qualitative dependence of modulation detection thresholds on modulation frequency and stimulus level. The decoder does not predict the observed loss of modulation sensitivity at high carrier pulse rates, but this framework can be applied to future models that better represent auditory nerve responses to high carrier pulse rate stimuli. The supplemental material of this article contains the article’s data in an active, re-usable format. PMID:20177761

Emerging Object Representations in the Visual System Predict Reaction Times for Categorization

PubMed Central

Ritchie, J. Brendan; Tovar, David A.; Carlson, Thomas A.

2015-01-01

Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or “brain decoding”, methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of object categories that underlie our capacity for rapid recognition. Shortly after stimulus onset, object exemplars cluster by category in a high-dimensional activation space in the brain. In this emerging activation space, the decodability of exemplar category varies over time, reflecting the brain’s transformation of visual inputs into coherent category representations. How do these emerging representations relate to categorization behavior? Recently it has been proposed that the distance of an exemplar representation from a categorical boundary in an activation space is critical for perceptual decision-making, and that reaction times should therefore correlate with distance from the boundary. The predictions of this distance hypothesis have been born out in human inferior temporal cortex (IT), an area of the brain crucial for the representation of object categories. When viewed in the context of a time varying neural signal, the optimal time to “read out” category information is when category representations in the brain are most decodable. Here, we show that the distance from a decision boundary through activation space, as measured using MEG decoding methods, correlates with reaction times for visual categorization during the period of peak decodability. Our results suggest that the brain begins to read out information about exemplar category at the optimal time for use in choice behaviour, and support the hypothesis that the structure of the representation for objects in the visual system is partially constitutive of the decision process in recognition. PMID:26107634

Lensfree fluorescent on-chip imaging of transgenic Caenorhabditis elegans over an ultra-wide field-of-view.

PubMed

Coskun, Ahmet F; Sencan, Ikbal; Su, Ting-Wei; Ozcan, Aydogan

2011-01-06

We demonstrate lensfree on-chip fluorescent imaging of transgenic Caenorhabditis elegans (C. elegans) over an ultra-wide field-of-view (FOV) of e.g., >2-8 cm(2) with a spatial resolution of ∼10 µm. This is the first time that a lensfree on-chip platform has successfully imaged fluorescent C. elegans samples. In our wide-field lensfree imaging platform, the transgenic samples are excited using a prism interface from the side, where the pump light is rejected through total internal reflection occurring at the bottom facet of the substrate. The emitted fluorescent signal from C. elegans samples is then recorded on a large area opto-electronic sensor-array over an FOV of e.g., >2-8 cm(2), without the use of any lenses, thin-film interference filters or mechanical scanners. Because fluorescent emission rapidly diverges, such lensfree fluorescent images recorded on a chip look blurred due to broad point-spread-function of our platform. To combat this resolution challenge, we use a compressive sampling algorithm to uniquely decode the recorded lensfree fluorescent patterns into higher resolution images, demonstrating ∼10 µm resolution. We tested the efficacy of this compressive decoding approach with different types of opto-electronic sensors to achieve a similar resolution level, independent of the imaging chip. We further demonstrate that this wide FOV lensfree fluorescent imaging platform can also perform sequential bright-field imaging of the same samples using partially-coherent lensfree digital in-line holography that is coupled from the top facet of the same prism used in fluorescent excitation. This unique combination permits ultra-wide field dual-mode imaging of C. elegans on a chip which could especially provide a useful tool for high-throughput screening applications in biomedical research.

Lensfree Fluorescent On-Chip Imaging of Transgenic Caenorhabditis elegans Over an Ultra-Wide Field-of-View

PubMed Central

Ozcan, Aydogan

2011-01-01

We demonstrate lensfree on-chip fluorescent imaging of transgenic Caenorhabditis elegans (C. elegans) over an ultra-wide field-of-view (FOV) of e.g., >2–8 cm2 with a spatial resolution of ∼10µm. This is the first time that a lensfree on-chip platform has successfully imaged fluorescent C. elegans samples. In our wide-field lensfree imaging platform, the transgenic samples are excited using a prism interface from the side, where the pump light is rejected through total internal reflection occurring at the bottom facet of the substrate. The emitted fluorescent signal from C. elegans samples is then recorded on a large area opto-electronic sensor-array over an FOV of e.g., >2–8 cm2, without the use of any lenses, thin-film interference filters or mechanical scanners. Because fluorescent emission rapidly diverges, such lensfree fluorescent images recorded on a chip look blurred due to broad point-spread-function of our platform. To combat this resolution challenge, we use a compressive sampling algorithm to uniquely decode the recorded lensfree fluorescent patterns into higher resolution images, demonstrating ∼10 µm resolution. We tested the efficacy of this compressive decoding approach with different types of opto-electronic sensors to achieve a similar resolution level, independent of the imaging chip. We further demonstrate that this wide FOV lensfree fluorescent imaging platform can also perform sequential bright-field imaging of the same samples using partially-coherent lensfree digital in-line holography that is coupled from the top facet of the same prism used in fluorescent excitation. This unique combination permits ultra-wide field dual-mode imaging of C. elegans on a chip which could especially provide a useful tool for high-throughput screening applications in biomedical research. PMID:21253611

Visual perception as retrospective Bayesian decoding from high- to low-level features.

PubMed

Ding, Stephanie; Cueva, Christopher J; Tsodyks, Misha; Qian, Ning

2017-10-24

When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. Published under the PNAS license.

HEVC real-time decoding

NASA Astrophysics Data System (ADS)

Bross, Benjamin; Alvarez-Mesa, Mauricio; George, Valeri; Chi, Chi Ching; Mayer, Tobias; Juurlink, Ben; Schierl, Thomas

2013-09-01

The new High Efficiency Video Coding Standard (HEVC) was finalized in January 2013. Compared to its predecessor H.264 / MPEG4-AVC, this new international standard is able to reduce the bitrate by 50% for the same subjective video quality. This paper investigates decoder optimizations that are needed to achieve HEVC real-time software decoding on a mobile processor. It is shown that HEVC real-time decoding up to high definition video is feasible using instruction extensions of the processor while decoding 4K ultra high definition video in real-time requires additional parallel processing. For parallel processing, a picture-level parallel approach has been chosen because it is generic and does not require bitstreams with special indication.

Decoding small surface codes with feedforward neural networks

NASA Astrophysics Data System (ADS)

Varsamopoulos, Savvas; Criger, Ben; Bertels, Koen

2018-01-01

Surface codes reach high error thresholds when decoded with known algorithms, but the decoding time will likely exceed the available time budget, especially for near-term implementations. To decrease the decoding time, we reduce the decoding problem to a classification problem that a feedforward neural network can solve. We investigate quantum error correction and fault tolerance at small code distances using neural network-based decoders, demonstrating that the neural network can generalize to inputs that were not provided during training and that they can reach similar or better decoding performance compared to previous algorithms. We conclude by discussing the time required by a feedforward neural network decoder in hardware.

Systolic VLSI Reed-Solomon Decoder

NASA Technical Reports Server (NTRS)

Shao, H. M.; Truong, T. K.; Deutsch, L. J.; Yuen, J. H.

1986-01-01

Decoder for digital communications provides high-speed, pipelined ReedSolomon (RS) error-correction decoding of data streams. Principal new feature of proposed decoder is modification of Euclid greatest-common-divisor algorithm to avoid need for time-consuming computations of inverse of certain Galois-field quantities. Decoder architecture suitable for implementation on very-large-scale integrated (VLSI) chips with negative-channel metaloxide/silicon circuitry.

Sensitivity and specificity considerations for fMRI encoding, decoding, and mapping of auditory cortex at ultra-high field.

PubMed

Moerel, Michelle; De Martino, Federico; Kemper, Valentin G; Schmitter, Sebastian; Vu, An T; Uğurbil, Kâmil; Formisano, Elia; Yacoub, Essa

2018-01-01

Following rapid technological advances, ultra-high field functional MRI (fMRI) enables exploring correlates of neuronal population activity at an increasing spatial resolution. However, as the fMRI blood-oxygenation-level-dependent (BOLD) contrast is a vascular signal, the spatial specificity of fMRI data is ultimately determined by the characteristics of the underlying vasculature. At 7T, fMRI measurement parameters determine the relative contribution of the macro- and microvasculature to the acquired signal. Here we investigate how these parameters affect relevant high-end fMRI analyses such as encoding, decoding, and submillimeter mapping of voxel preferences in the human auditory cortex. Specifically, we compare a T 2 * weighted fMRI dataset, obtained with 2D gradient echo (GE) EPI, to a predominantly T 2 weighted dataset obtained with 3D GRASE. We first investigated the decoding accuracy based on two encoding models that represented different hypotheses about auditory cortical processing. This encoding/decoding analysis profited from the large spatial coverage and sensitivity of the T 2 * weighted acquisitions, as evidenced by a significantly higher prediction accuracy in the GE-EPI dataset compared to the 3D GRASE dataset for both encoding models. The main disadvantage of the T 2 * weighted GE-EPI dataset for encoding/decoding analyses was that the prediction accuracy exhibited cortical depth dependent vascular biases. However, we propose that the comparison of prediction accuracy across the different encoding models may be used as a post processing technique to salvage the spatial interpretability of the GE-EPI cortical depth-dependent prediction accuracy. Second, we explored the mapping of voxel preferences. Large-scale maps of frequency preference (i.e., tonotopy) were similar across datasets, yet the GE-EPI dataset was preferable due to its larger spatial coverage and sensitivity. However, submillimeter tonotopy maps revealed biases in assigned frequency preference and selectivity for the GE-EPI dataset, but not for the 3D GRASE dataset. Thus, a T 2 weighted acquisition is recommended if high specificity in tonotopic maps is required. In conclusion, different fMRI acquisitions were better suited for different analyses. It is therefore critical that any sequence parameter optimization considers the eventual intended fMRI analyses and the nature of the neuroscience questions being asked. Copyright © 2017 Elsevier Inc. All rights reserved.

Image interpolation used in three-dimensional range data compression.

PubMed

Zhang, Shaoze; Zhang, Jianqi; Huang, Xi; Liu, Delian

2016-05-20

Advances in the field of three-dimensional (3D) scanning have made the acquisition of 3D range data easier and easier. However, with the large size of 3D range data comes the challenge of storing and transmitting it. To address this challenge, this paper presents a framework to further compress 3D range data using image interpolation. We first use a virtual fringe-projection system to store 3D range data as images, and then apply the interpolation algorithm to the images to reduce their resolution to further reduce the data size. When the 3D range data are needed, the low-resolution image is scaled up to its original resolution by applying the interpolation algorithm, and then the scaled-up image is decoded and the 3D range data are recovered according to the decoded result. Experimental results show that the proposed method could further reduce the data size while maintaining a low rate of error.

Resolution Of Phase Ambiguities In QPSK

NASA Technical Reports Server (NTRS)

Nguyen, Tien M.

1992-01-01

Report discusses several techniques for resolution of phase ambiguities in detection and decoding of radio signals modulated by coherent quadrature phase-shift keying (QPSK) and offset QPSK (OQPSK). Eight ambiguities: four associated with phase of carrier signal in absence of ambiguity in direction of rotation of carrier phase, and another four associated with carrier phase in presence of phase-rotation ambiguity.

Systems and methods for integrating ion mobility and ion trap mass spectrometers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibrahim, Yehia M.; Garimella, Sandilya; Prost, Spencer A.

Described herein are examples of systems and methods for integrating IMS and MS systems. In certain examples, systems and methods for decoding double multiplexed data are described. The systems and methods can also perform multiple refining procedures in order to minimize the demultiplexing artifacts. The systems and methods can be used, for example, for the analysis of proteomic and petroleum samples, where the integration of IMS and high mass resolution are used for accurate assignment of molecular formulae.

Research on coding and decoding method for digital levels.

PubMed

Tu, Li-fen; Zhong, Si-dong

2011-01-20

A new coding and decoding method for digital levels is proposed. It is based on an area-array CCD sensor and adopts mixed coding technology. By taking advantage of redundant information in a digital image signal, the contradiction that the field of view and image resolution restrict each other in a digital level measurement is overcome, and the geodetic leveling becomes easier. The experimental results demonstrate that the uncertainty of measurement is 1 mm when the measuring range is between 2 m and 100 m, which can meet practical needs.

Elegant Grapheme-Phoneme Correspondence: A Periodic Chart and Singularity Generalization Unify Decoding

ERIC Educational Resources Information Center

Gates, Louis

2018-01-01

The accompanying article introduces highly transparent grapheme-phoneme relationships embodied within a Periodic table of decoding cells, which arguably presents the quintessential transparent decoding elements. The study then folds these cells into one highly transparent but simply stated singularity generalization--this generalization unifies…

Successful decoding of famous faces in the fusiform face area.

PubMed

Axelrod, Vadim; Yovel, Galit

2015-01-01

What are the neural mechanisms of face recognition? It is believed that the network of face-selective areas, which spans the occipital, temporal, and frontal cortices, is important in face recognition. A number of previous studies indeed reported that face identity could be discriminated based on patterns of multivoxel activity in the fusiform face area and the anterior temporal lobe. However, given the difficulty in localizing the face-selective area in the anterior temporal lobe, its role in face recognition is still unknown. Furthermore, previous studies limited their analysis to occipito-temporal regions without testing identity decoding in more anterior face-selective regions, such as the amygdala and prefrontal cortex. In the current high-resolution functional Magnetic Resonance Imaging study, we systematically examined the decoding of the identity of famous faces in the temporo-frontal network of face-selective and adjacent non-face-selective regions. A special focus has been put on the face-area in the anterior temporal lobe, which was reliably localized using an optimized scanning protocol. We found that face-identity could be discriminated above chance level only in the fusiform face area. Our results corroborate the role of the fusiform face area in face recognition. Future studies are needed to further explore the role of the more recently discovered anterior face-selective areas in face recognition.

Direct migration motion estimation and mode decision to decoder for a low-complexity decoder Wyner-Ziv video coding

NASA Astrophysics Data System (ADS)

Lei, Ted Chih-Wei; Tseng, Fan-Shuo

2017-07-01

This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.

Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics.

PubMed

Pietzke, Matthias; Zasada, Christin; Mudrich, Susann; Kempa, Stefan

2014-01-01

Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade.

Enabling MPEG-2 video playback in embedded systems through improved data cache efficiency

NASA Astrophysics Data System (ADS)

Soderquist, Peter; Leeser, Miriam E.

1999-01-01

Digital video decoding, enabled by the MPEG-2 Video standard, is an important future application for embedded systems, particularly PDAs and other information appliances. Many such system require portability and wireless communication capabilities, and thus face severe limitations in size and power consumption. This places a premium on integration and efficiency, and favors software solutions for video functionality over specialized hardware. The processors in most embedded system currently lack the computational power needed to perform video decoding, but a related and equally important problem is the required data bandwidth, and the need to cost-effectively insure adequate data supply. MPEG data sets are very large, and generate significant amounts of excess memory traffic for standard data caches, up to 100 times the amount required for decoding. Meanwhile, cost and power limitations restrict cache sizes in embedded systems. Some systems, including many media processors, eliminate caches in favor of memories under direct, painstaking software control in the manner of digital signal processors. Yet MPEG data has locality which caches can exploit if properly optimized, providing fast, flexible, and automatic data supply. We propose a set of enhancements which target the specific needs of the heterogeneous types within the MPEG decoder working set. These optimizations significantly improve the efficiency of small caches, reducing cache-memory traffic by almost 70 percent, and can make an enhanced 4 KB cache perform better than a standard 1 MB cache. This performance improvement can enable high-resolution, full frame rate video playback in cheaper, smaller system than woudl otherwise be possible.

Categorical discrimination of human body parts by magnetoencephalography

PubMed Central

Nakamura, Misaki; Yanagisawa, Takufumi; Okamura, Yumiko; Fukuma, Ryohei; Hirata, Masayuki; Araki, Toshihiko; Kamitani, Yukiyasu; Yorifuji, Shiro

2015-01-01

Humans recognize body parts in categories. Previous studies have shown that responses in the fusiform body area (FBA) and extrastriate body area (EBA) are evoked by the perception of the human body, when presented either as whole or as isolated parts. These responses occur approximately 190 ms after body images are visualized. The extent to which body-sensitive responses show specificity for different body part categories remains to be largely clarified. We used a decoding method to quantify neural responses associated with the perception of different categories of body parts. Nine subjects underwent measurements of their brain activities by magnetoencephalography (MEG) while viewing 14 images of feet, hands, mouths, and objects. We decoded categories of the presented images from the MEG signals using a support vector machine (SVM) and calculated their accuracy by 10-fold cross-validation. For each subject, a response that appeared to be a body-sensitive response was observed and the MEG signals corresponding to the three types of body categories were classified based on the signals in the occipitotemporal cortex. The accuracy in decoding body-part categories (with a peak at approximately 48%) was above chance (33.3%) and significantly higher than that for random categories. According to the time course and location, the responses are suggested to be body-sensitive and to include information regarding the body-part category. Finally, this non-invasive method can decode category information of a visual object with high temporal and spatial resolution and this result may have a significant impact in the field of brain–machine interface research. PMID:26582986

Categorical discrimination of human body parts by magnetoencephalography.

PubMed

Nakamura, Misaki; Yanagisawa, Takufumi; Okamura, Yumiko; Fukuma, Ryohei; Hirata, Masayuki; Araki, Toshihiko; Kamitani, Yukiyasu; Yorifuji, Shiro

2015-01-01

Humans recognize body parts in categories. Previous studies have shown that responses in the fusiform body area (FBA) and extrastriate body area (EBA) are evoked by the perception of the human body, when presented either as whole or as isolated parts. These responses occur approximately 190 ms after body images are visualized. The extent to which body-sensitive responses show specificity for different body part categories remains to be largely clarified. We used a decoding method to quantify neural responses associated with the perception of different categories of body parts. Nine subjects underwent measurements of their brain activities by magnetoencephalography (MEG) while viewing 14 images of feet, hands, mouths, and objects. We decoded categories of the presented images from the MEG signals using a support vector machine (SVM) and calculated their accuracy by 10-fold cross-validation. For each subject, a response that appeared to be a body-sensitive response was observed and the MEG signals corresponding to the three types of body categories were classified based on the signals in the occipitotemporal cortex. The accuracy in decoding body-part categories (with a peak at approximately 48%) was above chance (33.3%) and significantly higher than that for random categories. According to the time course and location, the responses are suggested to be body-sensitive and to include information regarding the body-part category. Finally, this non-invasive method can decode category information of a visual object with high temporal and spatial resolution and this result may have a significant impact in the field of brain-machine interface research.

A high speed sequential decoder

NASA Technical Reports Server (NTRS)

Lum, H., Jr.

1972-01-01

The performance and theory of operation for the High Speed Hard Decision Sequential Decoder are delineated. The decoder is a forward error correction system which is capable of accepting data from binary-phase-shift-keyed and quadriphase-shift-keyed modems at input data rates up to 30 megabits per second. Test results show that the decoder is capable of maintaining a composite error rate of 0.00001 at an input E sub b/N sub o of 5.6 db. This performance has been obtained with minimum circuit complexity.

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao

1991-01-01

Various types of multistage decoding for multilevel block modulation codes, in which the decoding of a component code at each stage can be either soft decision or hard decision, maximum likelihood or bounded distance are discussed. Error performance for codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. It was found that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. It was found that the difference in performance between the suboptimum multi-stage soft decision maximum likelihood decoding of a modulation code and the single stage optimum decoding of the overall code is very small, only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

High-throughput GPU-based LDPC decoding

NASA Astrophysics Data System (ADS)

Chang, Yang-Lang; Chang, Cheng-Chun; Huang, Min-Yu; Huang, Bormin

2010-08-01

Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.

Reading skills of students with speech sound disorders at three stages of literacy development.

PubMed

Skebo, Crysten M; Lewis, Barbara A; Freebairn, Lisa A; Tag, Jessica; Avrich Ciesla, Allison; Stein, Catherine M

2013-10-01

The relationship between phonological awareness, overall language, vocabulary, and nonlinguistic cognitive skills to decoding and reading comprehension was examined for students at 3 stages of literacy development (i.e., early elementary school, middle school, and high school). Students with histories of speech sound disorders (SSD) with and without language impairment (LI) were compared to students without histories of SSD or LI (typical language; TL). In a cross-sectional design, students ages 7;0 (years;months) to 17;9 completed tests that measured reading, language, and nonlinguistic cognitive skills. For the TL group, phonological awareness predicted decoding at early elementary school, and overall language predicted reading comprehension at early elementary school and both decoding and reading comprehension at middle school and high school. For the SSD-only group, vocabulary predicted both decoding and reading comprehension at early elementary school, and overall language predicted both decoding and reading comprehension at middle school and decoding at high school. For the SSD and LI group, overall language predicted decoding at all 3 literacy stages and reading comprehension at early elementary school and middle school, and vocabulary predicted reading comprehension at high school. Although similar skills contribute to reading across the age span, the relative importance of these skills changes with children's literacy stages.

Reading Skills of Students With Speech Sound Disorders at Three Stages of Literacy Development

PubMed Central

Skebo, Crysten M.; Lewis, Barbara A.; Freebairn, Lisa A.; Tag, Jessica; Ciesla, Allison Avrich; Stein, Catherine M.

2015-01-01

Purpose The relationship between phonological awareness, overall language, vocabulary, and nonlinguistic cognitive skills to decoding and reading comprehension was examined for students at 3 stages of literacy development (i.e., early elementary school, middle school, and high school). Students with histories of speech sound disorders (SSD) with and without language impairment (LI) were compared to students without histories of SSD or LI (typical language; TL). Method In a cross-sectional design, students ages 7;0 (years; months) to 17;9 completed tests that measured reading, language, and nonlinguistic cognitive skills. Results For the TL group, phonological awareness predicted decoding at early elementary school, and overall language predicted reading comprehension at early elementary school and both decoding and reading comprehension at middle school and high school. For the SSD-only group, vocabulary predicted both decoding and reading comprehension at early elementary school, and overall language predicted both decoding and reading comprehension at middle school and decoding at high school. For the SSD and LI group, overall language predicted decoding at all 3 literacy stages and reading comprehension at early elementary school and middle school, and vocabulary predicted reading comprehension at high school. Conclusion Although similar skills contribute to reading across the age span, the relative importance of these skills changes with children’s literacy stages. PMID:23833280

High-resolution structure of the Escherichia coli ribosome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noeske, Jonas; Wasserman, Michael R.; Terry, Daniel S.

Protein synthesis by the ribosome is highly dependent on the ionic conditions in the cellular environment, but the roles of ribosome solvation remain poorly understood. Moreover, the function of modifications to ribosomal RNA and ribosomal proteins are unclear. Here we present the structure of the Escherichia coli 70S ribosome to 2.4 Å resolution. The structure reveals details of the ribosomal subunit interface that are conserved in all domains of life, and suggest how solvation contributes to ribosome integrity and function. The structure also suggests how the conformation of ribosomal protein uS12 likely impacts its contribution to messenger RNA decoding. Inmore » conclusion, this structure helps to explain the phylogenetic conservation of key elements of the ribosome, including posttranscriptional and posttranslational modifications and should serve as a basis for future antibiotic development.« less

High-resolution structure of the Escherichia coli ribosome

DOE PAGES

Noeske, Jonas; Wasserman, Michael R.; Terry, Daniel S.; ...

2015-03-16

Protein synthesis by the ribosome is highly dependent on the ionic conditions in the cellular environment, but the roles of ribosome solvation remain poorly understood. Moreover, the function of modifications to ribosomal RNA and ribosomal proteins are unclear. Here we present the structure of the Escherichia coli 70S ribosome to 2.4 Å resolution. The structure reveals details of the ribosomal subunit interface that are conserved in all domains of life, and suggest how solvation contributes to ribosome integrity and function. The structure also suggests how the conformation of ribosomal protein uS12 likely impacts its contribution to messenger RNA decoding. Inmore » conclusion, this structure helps to explain the phylogenetic conservation of key elements of the ribosome, including posttranscriptional and posttranslational modifications and should serve as a basis for future antibiotic development.« less

Performance analysis of algorithms for retrieval of magnetic resonance images for interactive teleradiology

NASA Astrophysics Data System (ADS)

Atkins, M. Stella; Hwang, Robert; Tang, Simon

2001-05-01

We have implemented a prototype system consisting of a Java- based image viewer and a web server extension component for transmitting Magnetic Resonance Images (MRI) to an image viewer, to test the performance of different image retrieval techniques. We used full-resolution images, and images compressed/decompressed using the Set Partitioning in Hierarchical Trees (SPIHT) image compression algorithm. We examined the SPIHT decompression algorithm using both non- progressive and progressive transmission, focusing on the running times of the algorithm, client memory usage and garbage collection. We also compared the Java implementation with a native C++ implementation of the non- progressive SPIHT decompression variant. Our performance measurements showed that for uncompressed image retrieval using a 10Mbps Ethernet, a film of 16 MR images can be retrieved and displayed almost within interactive times. The native C++ code implementation of the client-side decoder is twice as fast as the Java decoder. If the network bandwidth is low, the high communication time for retrieving uncompressed images may be reduced by use of SPIHT-compressed images, although the image quality is then degraded. To provide diagnostic quality images, we also investigated the retrieval of up to 3 images on a MR film at full-resolution, using progressive SPIHT decompression. The Java-based implementation of progressive decompression performed badly, mainly due to the memory requirements for maintaining the image states, and the high cost of execution of the Java garbage collector. Hence, in systems where the bandwidth is high, such as found in a hospital intranet, SPIHT image compression does not provide advantages for image retrieval performance.

Optimal patch code design via device characterization

NASA Astrophysics Data System (ADS)

Wu, Wencheng; Dalal, Edul N.

2012-01-01

In many color measurement applications, such as those for color calibration and profiling, "patch code" has been used successfully for job identification and automation to reduce operator errors. A patch code is similar to a barcode, but is intended primarily for use in measurement devices that cannot read barcodes due to limited spatial resolution, such as spectrophotometers. There is an inherent tradeoff between decoding robustness and the number of code levels available for encoding. Previous methods have attempted to address this tradeoff, but those solutions have been sub-optimal. In this paper, we propose a method to design optimal patch codes via device characterization. The tradeoff between decoding robustness and the number of available code levels is optimized in terms of printing and measurement efforts, and decoding robustness against noises from the printing and measurement devices. Effort is drastically reduced relative to previous methods because print-and-measure is minimized through modeling and the use of existing printer profiles. Decoding robustness is improved by distributing the code levels in CIE Lab space rather than in CMYK space.

Error-trellis Syndrome Decoding Techniques for Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1984-01-01

An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decoding is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

FPGA implementation of low complexity LDPC iterative decoder

NASA Astrophysics Data System (ADS)

Verma, Shivani; Sharma, Sanjay

2016-07-01

Low-density parity-check (LDPC) codes, proposed by Gallager, emerged as a class of codes which can yield very good performance on the additive white Gaussian noise channel as well as on the binary symmetric channel. LDPC codes have gained lots of importance due to their capacity achieving property and excellent performance in the noisy channel. Belief propagation (BP) algorithm and its approximations, most notably min-sum, are popular iterative decoding algorithms used for LDPC and turbo codes. The trade-off between the hardware complexity and the decoding throughput is a critical factor in the implementation of the practical decoder. This article presents introduction to LDPC codes and its various decoding algorithms followed by realisation of LDPC decoder by using simplified message passing algorithm and partially parallel decoder architecture. Simplified message passing algorithm has been proposed for trade-off between low decoding complexity and decoder performance. It greatly reduces the routing and check node complexity of the decoder. Partially parallel decoder architecture possesses high speed and reduced complexity. The improved design of the decoder possesses a maximum symbol throughput of 92.95 Mbps and a maximum of 18 decoding iterations. The article presents implementation of 9216 bits, rate-1/2, (3, 6) LDPC decoder on Xilinx XC3D3400A device from Spartan-3A DSP family.

A high data rate universal lattice decoder on FPGA

NASA Astrophysics Data System (ADS)

Ma, Jing; Huang, Xinming; Kura, Swapna

2005-06-01

This paper presents the architecture design of a high data rate universal lattice decoder for MIMO channels on FPGA platform. A phost strategy based lattice decoding algorithm is modified in this paper to reduce the complexity of the closest lattice point search. The data dependency of the improved algorithm is examined and a parallel and pipeline architecture is developed with the iterative decoding function on FPGA and the division intensive channel matrix preprocessing on DSP. Simulation results demonstrate that the improved lattice decoding algorithm provides better bit error rate and less iteration number compared with the original algorithm. The system prototype of the decoder shows that it supports data rate up to 7Mbit/s on a Virtex2-1000 FPGA, which is about 8 times faster than the original algorithm on FPGA platform and two-orders of magnitude better than its implementation on a DSP platform.

Non-tables look-up search algorithm for efficient H.264/AVC context-based adaptive variable length coding decoding

NASA Astrophysics Data System (ADS)

Han, Yishi; Luo, Zhixiao; Wang, Jianhua; Min, Zhixuan; Qin, Xinyu; Sun, Yunlong

2014-09-01

In general, context-based adaptive variable length coding (CAVLC) decoding in H.264/AVC standard requires frequent access to the unstructured variable length coding tables (VLCTs) and significant memory accesses are consumed. Heavy memory accesses will cause high power consumption and time delays, which are serious problems for applications in portable multimedia devices. We propose a method for high-efficiency CAVLC decoding by using a program instead of all the VLCTs. The decoded codeword from VLCTs can be obtained without any table look-up and memory access. The experimental results show that the proposed algorithm achieves 100% memory access saving and 40% decoding time saving without degrading video quality. Additionally, the proposed algorithm shows a better performance compared with conventional CAVLC decoding, such as table look-up by sequential search, table look-up by binary search, Moon's method, and Kim's method.

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

A High-Performance Neural Prosthesis Incorporating Discrete State Selection With Hidden Markov Models.

PubMed

Kao, Jonathan C; Nuyujukian, Paul; Ryu, Stephen I; Shenoy, Krishna V

2017-04-01

Communication neural prostheses aim to restore efficient communication to people with motor neurological injury or disease by decoding neural activity into control signals. These control signals are both analog (e.g., the velocity of a computer mouse) and discrete (e.g., clicking an icon with a computer mouse) in nature. Effective, high-performing, and intuitive-to-use communication prostheses should be capable of decoding both analog and discrete state variables seamlessly. However, to date, the highest-performing autonomous communication prostheses rely on precise analog decoding and typically do not incorporate high-performance discrete decoding. In this report, we incorporated a hidden Markov model (HMM) into an intracortical communication prosthesis to enable accurate and fast discrete state decoding in parallel with analog decoding. In closed-loop experiments with nonhuman primates implanted with multielectrode arrays, we demonstrate that incorporating an HMM into a neural prosthesis can increase state-of-the-art achieved bitrate by 13.9% and 4.2% in two monkeys ( ). We found that the transition model of the HMM is critical to achieving this performance increase. Further, we found that using an HMM resulted in the highest achieved peak performance we have ever observed for these monkeys, achieving peak bitrates of 6.5, 5.7, and 4.7 bps in Monkeys J, R, and L, respectively. Finally, we found that this neural prosthesis was robustly controllable for the duration of entire experimental sessions. These results demonstrate that high-performance discrete decoding can be beneficially combined with analog decoding to achieve new state-of-the-art levels of performance.

Broadband interferometric characterisation of nano-positioning stages with sub-10 pm resolution

NASA Astrophysics Data System (ADS)

Li, Zhi; Brand, Uwe; Wolff, Helmut; Koenders, Ludger; Yacoot, Andrew; Puranto, Prabowo

2017-06-01

A traceable calibration setup for investigation of the quasi-static and the dynamic performance of nano-positioning stages is detailed, which utilizes a differential plane-mirror interferometer with double-pass configuration from the National Physical Laboratory (NPL). An NPL-developed FPGA-based interferometric data acquisition and decoding system has been used to enable traceable quasi-static calibration of nano-positioning stages with high resolution. A lockin based modulation technique is further introduced to quantitatively calibrate the dynamic response of moving stages with a bandwidth up to 100 kHz and picometer resolution. First experimental results have proven that the calibration setup can achieve under nearly open-air conditions a noise floor lower than 10 pm/sqrt(Hz). A pico-positioning stage, that is used for nanoindentation with indentation depths down to a few picometers, has been characterized with this calibration setup.

Multi-stage decoding of multi-level modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

Error control techniques for satellite and space communications

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.

1986-01-01

High rate concatenated coding systems with trellis inner codes and Reed-Solomon (RS) outer codes for application in satellite communication systems are considered. Two types of inner codes are studied: high rate punctured binary convolutional codes which result in overall effective information rates between 1/2 and 1 bit per channel use; and bandwidth efficient signal space trellis codes which can achieve overall effective information rates greater than 1 bit per channel use. Channel capacity calculations with and without side information performed for the concatenated coding system. Concatenated coding schemes are investigated. In Scheme 1, the inner code is decoded with the Viterbi algorithm and the outer RS code performs error-correction only (decoding without side information). In scheme 2, the inner code is decoded with a modified Viterbi algorithm which produces reliability information along with the decoded output. In this algorithm, path metrics are used to estimate the entire information sequence, while branch metrics are used to provide the reliability information on the decoded sequence. This information is used to erase unreliable bits in the decoded output. An errors-and-erasures RS decoder is then used for the outer code. These two schemes are proposed for use on NASA satellite channels. Results indicate that high system reliability can be achieved with little or no bandwidth expansion.

Mapping of H.264 decoding on a multiprocessor architecture

NASA Astrophysics Data System (ADS)

van der Tol, Erik B.; Jaspers, Egbert G.; Gelderblom, Rob H.

2003-05-01

Due to the increasing significance of development costs in the competitive domain of high-volume consumer electronics, generic solutions are required to enable reuse of the design effort and to increase the potential market volume. As a result from this, Systems-on-Chip (SoCs) contain a growing amount of fully programmable media processing devices as opposed to application-specific systems, which offered the most attractive solutions due to a high performance density. The following motivates this trend. First, SoCs are increasingly dominated by their communication infrastructure and embedded memory, thereby making the cost of the functional units less significant. Moreover, the continuously growing design costs require generic solutions that can be applied over a broad product range. Hence, powerful programmable SoCs are becoming increasingly attractive. However, to enable power-efficient designs, that are also scalable over the advancing VLSI technology, parallelism should be fully exploited. Both task-level and instruction-level parallelism can be provided by means of e.g. a VLIW multiprocessor architecture. To provide the above-mentioned scalability, we propose to partition the data over the processors, instead of traditional functional partitioning. An advantage of this approach is the inherent locality of data, which is extremely important for communication-efficient software implementations. Consequently, a software implementation is discussed, enabling e.g. SD resolution H.264 decoding with a two-processor architecture, whereas High-Definition (HD) decoding can be achieved with an eight-processor system, executing the same software. Experimental results show that the data communication considerably reduces up to 65% directly improving the overall performance. Apart from considerable improvement in memory bandwidth, this novel concept of partitioning offers a natural approach for optimally balancing the load of all processors, thereby further improving the overall speedup.

Successful Decoding of Famous Faces in the Fusiform Face Area

PubMed Central

Axelrod, Vadim; Yovel, Galit

2015-01-01

What are the neural mechanisms of face recognition? It is believed that the network of face-selective areas, which spans the occipital, temporal, and frontal cortices, is important in face recognition. A number of previous studies indeed reported that face identity could be discriminated based on patterns of multivoxel activity in the fusiform face area and the anterior temporal lobe. However, given the difficulty in localizing the face-selective area in the anterior temporal lobe, its role in face recognition is still unknown. Furthermore, previous studies limited their analysis to occipito-temporal regions without testing identity decoding in more anterior face-selective regions, such as the amygdala and prefrontal cortex. In the current high-resolution functional Magnetic Resonance Imaging study, we systematically examined the decoding of the identity of famous faces in the temporo-frontal network of face-selective and adjacent non-face-selective regions. A special focus has been put on the face-area in the anterior temporal lobe, which was reliably localized using an optimized scanning protocol. We found that face-identity could be discriminated above chance level only in the fusiform face area. Our results corroborate the role of the fusiform face area in face recognition. Future studies are needed to further explore the role of the more recently discovered anterior face-selective areas in face recognition. PMID:25714434

Electronics for a prototype variable field of view PET camera using the PMT-quadrant-sharing detector array

NASA Astrophysics Data System (ADS)

Li, H.; Wong, Wai-Hoi; Zhang, N.; Wang, J.; Uribe, J.; Baghaei, H.; Yokoyama, S.

1999-06-01

Electronics for a prototype high-resolution PET camera with eight position-sensitive detector modules has been developed. Each module has 16 BGO (Bi/sub 4/Ge/sub 3/O/sub 12/) blocks (each block is composed of 49 crystals). The design goals are component and space reduction. The electronics is composed of five parts: front-end analog processing, digital position decoding, fast timing, coincidence processing and master data acquisition. The front-end analog circuit is a zone-based structure (each zone has 3/spl times/3 PMTs). Nine ADCs digitize integration signals of an active zone identified by eight trigger clusters; each cluster is composed of six photomultiplier tubes (PMTs). A trigger corresponding to a gamma ray is sent to a fast timing board to obtain a time-mark, and the nine digitized signals are passed to the position decoding board, where a real block (four PMTs) can be picked out from the zone for position decoding. Lookup tables are used for energy discrimination and to identify the gamma-hit crystal location. The coincidence board opens a 70-ns initial timing window, followed by two 20-ns true/accidental time-mark lookup table windows. The data output from the coincidence board can be acquired either in sinogram mode or in list mode with a Motorola/IRONICS VME-based system.

Dynamic configuration management of a multi-standard and multi-mode reconfigurable multi-ASIP architecture for turbo decoding

NASA Astrophysics Data System (ADS)

Lapotre, Vianney; Gogniat, Guy; Baghdadi, Amer; Diguet, Jean-Philippe

2017-12-01

The multiplication of connected devices goes along with a large variety of applications and traffic types needing diverse requirements. Accompanying this connectivity evolution, the last years have seen considerable evolutions of wireless communication standards in the domain of mobile telephone networks, local/wide wireless area networks, and Digital Video Broadcasting (DVB). In this context, intensive research has been conducted to provide flexible turbo decoder targeting high throughput, multi-mode, multi-standard, and power consumption efficiency. However, flexible turbo decoder implementations have not often considered dynamic reconfiguration issues in this context that requires high speed configuration switching. Starting from this assessment, this paper proposes the first solution that allows frame-by-frame run-time configuration management of a multi-processor turbo decoder without compromising the decoding performances.

A low-complexity and high performance concatenated coding scheme for high-speed satellite communications

NASA Technical Reports Server (NTRS)

Lin, Shu; Rhee, Dojun; Rajpal, Sandeep

1993-01-01

This report presents a low-complexity and high performance concatenated coding scheme for high-speed satellite communications. In this proposed scheme, the NASA Standard Reed-Solomon (RS) code over GF(2(exp 8) is used as the outer code and the second-order Reed-Muller (RM) code of Hamming distance 8 is used as the inner code. The RM inner code has a very simple trellis structure and is decoded with the soft-decision Viterbi decoding algorithm. It is shown that the proposed concatenated coding scheme achieves an error performance which is comparable to that of the NASA TDRS concatenated coding scheme in which the NASA Standard rate-1/2 convolutional code of constraint length 7 and d sub free = 10 is used as the inner code. However, the proposed RM inner code has much smaller decoding complexity, less decoding delay, and much higher decoding speed. Consequently, the proposed concatenated coding scheme is suitable for reliable high-speed satellite communications, and it may be considered as an alternate coding scheme for the NASA TDRS system.

Error-trellis syndrome decoding techniques for convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1985-01-01

An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decordig is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

High-speed architecture for the decoding of trellis-coded modulation

NASA Technical Reports Server (NTRS)

Osborne, William P.

1992-01-01

Since 1971, when the Viterbi Algorithm was introduced as the optimal method of decoding convolutional codes, improvements in circuit technology, especially VLSI, have steadily increased its speed and practicality. Trellis-Coded Modulation (TCM) combines convolutional coding with higher level modulation (non-binary source alphabet) to provide forward error correction and spectral efficiency. For binary codes, the current stare-of-the-art is a 64-state Viterbi decoder on a single CMOS chip, operating at a data rate of 25 Mbps. Recently, there has been an interest in increasing the speed of the Viterbi Algorithm by improving the decoder architecture, or by reducing the algorithm itself. Designs employing new architectural techniques are now in existence, however these techniques are currently applied to simpler binary codes, not to TCM. The purpose of this report is to discuss TCM architectural considerations in general, and to present the design, at the logic gate level, or a specific TCM decoder which applies these considerations to achieve high-speed decoding.

An Optimized Three-Level Design of Decoder Based on Nanoscale Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Seyedi, Saeid; Navimipour, Nima Jafari

2018-03-01

Quantum-dot Cellular Automata (QCA) has been potentially considered as a supersede to Complementary Metal-Oxide-Semiconductor (CMOS) because of its inherent advantages. Many QCA-based logic circuits with smaller feature size, improved operating frequency, and lower power consumption than CMOS have been offered. This technology works based on electron relations inside quantum-dots. Due to the importance of designing an optimized decoder in any digital circuit, in this paper, we design, implement and simulate a new 2-to-4 decoder based on QCA with low delay, area, and complexity. The logic functionality of the 2-to-4 decoder is verified using the QCADesigner tool. The results have shown that the proposed QCA-based decoder has high performance in terms of a number of cells, covered area, and time delay. Due to the lower clock pulse frequency, the proposed 2-to-4 decoder is helpful for building QCA-based sequential digital circuits with high performance.

On the reduced-complexity of LDPC decoders for ultra-high-speed optical transmission.

PubMed

Djordjevic, Ivan B; Xu, Lei; Wang, Ting

2010-10-25

We propose two reduced-complexity (RC) LDPC decoders, which can be used in combination with large-girth LDPC codes to enable ultra-high-speed serial optical transmission. We show that optimally attenuated RC min-sum sum algorithm performs only 0.46 dB (at BER of 10(-9)) worse than conventional sum-product algorithm, while having lower storage memory requirements and much lower latency. We further study the use of RC LDPC decoding algorithms in multilevel coded modulation with coherent detection and show that with RC decoding algorithms we can achieve the net coding gain larger than 11 dB at BERs below 10(-9).

Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities

NASA Astrophysics Data System (ADS)

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3

NASA Technical Reports Server (NTRS)

Lin, Shu

1998-01-01

Decoding algorithms based on the trellis representation of a code (block or convolutional) drastically reduce decoding complexity. The best known and most commonly used trellis-based decoding algorithm is the Viterbi algorithm. It is a maximum likelihood decoding algorithm. Convolutional codes with the Viterbi decoding have been widely used for error control in digital communications over the last two decades. This chapter is concerned with the application of the Viterbi decoding algorithm to linear block codes. First, the Viterbi algorithm is presented. Then, optimum sectionalization of a trellis to minimize the computational complexity of a Viterbi decoder is discussed and an algorithm is presented. Some design issues for IC (integrated circuit) implementation of a Viterbi decoder are considered and discussed. Finally, a new decoding algorithm based on the principle of compare-select-add is presented. This new algorithm can be applied to both block and convolutional codes and is more efficient than the conventional Viterbi algorithm based on the add-compare-select principle. This algorithm is particularly efficient for rate 1/n antipodal convolutional codes and their high-rate punctured codes. It reduces computational complexity by one-third compared with the Viterbi algorithm.

Application of source biasing technique for energy efficient DECODER circuit design: memory array application

NASA Astrophysics Data System (ADS)

Gupta, Neha; Parihar, Priyanka; Neema, Vaibhav

2018-04-01

Researchers have proposed many circuit techniques to reduce leakage power dissipation in memory cells. If we want to reduce the overall power in the memory system, we have to work on the input circuitry of memory architecture i.e. row and column decoder. In this research work, low leakage power with a high speed row and column decoder for memory array application is designed and four new techniques are proposed. In this work, the comparison of cluster DECODER, body bias DECODER, source bias DECODER, and source coupling DECODER are designed and analyzed for memory array application. Simulation is performed for the comparative analysis of different DECODER design parameters at 180 nm GPDK technology file using the CADENCE tool. Simulation results show that the proposed source bias DECODER circuit technique decreases the leakage current by 99.92% and static energy by 99.92% at a supply voltage of 1.2 V. The proposed circuit also improves dynamic power dissipation by 5.69%, dynamic PDP/EDP 65.03% and delay 57.25% at 1.2 V supply voltage.

Locating and decoding barcodes in fuzzy images captured by smart phones

NASA Astrophysics Data System (ADS)

Deng, Wupeng; Hu, Jiwei; Liu, Quan; Lou, Ping

2017-07-01

With the development of barcodes for commercial use, people's requirements for detecting barcodes by smart phone become increasingly pressing. The low quality of barcode image captured by mobile phone always affects the decoding and recognition rates. This paper focuses on locating and decoding EAN-13 barcodes in fuzzy images. We present a more accurate locating algorithm based on segment length and high fault-tolerant rate algorithm for decoding barcodes. Unlike existing approaches, location algorithm is based on the edge segment length of EAN -13 barcodes, while our decoding algorithm allows the appearance of fuzzy region in barcode image. Experimental results are performed on damaged, contaminated and scratched digital images, and provide a quite promising result for EAN -13 barcode location and decoding.

Cortical processing of pitch: Model-based encoding and decoding of auditory fMRI responses to real-life sounds.

PubMed

De Angelis, Vittoria; De Martino, Federico; Moerel, Michelle; Santoro, Roberta; Hausfeld, Lars; Formisano, Elia

2017-11-13

Pitch is a perceptual attribute related to the fundamental frequency (or periodicity) of a sound. So far, the cortical processing of pitch has been investigated mostly using synthetic sounds. However, the complex harmonic structure of natural sounds may require different mechanisms for the extraction and analysis of pitch. This study investigated the neural representation of pitch in human auditory cortex using model-based encoding and decoding analyses of high field (7 T) functional magnetic resonance imaging (fMRI) data collected while participants listened to a wide range of real-life sounds. Specifically, we modeled the fMRI responses as a function of the sounds' perceived pitch height and salience (related to the fundamental frequency and the harmonic structure respectively), which we estimated with a computational algorithm of pitch extraction (de Cheveigné and Kawahara, 2002). First, using single-voxel fMRI encoding, we identified a pitch-coding region in the antero-lateral Heschl's gyrus (HG) and adjacent superior temporal gyrus (STG). In these regions, the pitch representation model combining height and salience predicted the fMRI responses comparatively better than other models of acoustic processing and, in the right hemisphere, better than pitch representations based on height/salience alone. Second, we assessed with model-based decoding that multi-voxel response patterns of the identified regions are more informative of perceived pitch than the remainder of the auditory cortex. Further multivariate analyses showed that complementing a multi-resolution spectro-temporal sound representation with pitch produces a small but significant improvement to the decoding of complex sounds from fMRI response patterns. In sum, this work extends model-based fMRI encoding and decoding methods - previously employed to examine the representation and processing of acoustic sound features in the human auditory system - to the representation and processing of a relevant perceptual attribute such as pitch. Taken together, the results of our model-based encoding and decoding analyses indicated that the pitch of complex real life sounds is extracted and processed in lateral HG/STG regions, at locations consistent with those indicated in several previous fMRI studies using synthetic sounds. Within these regions, pitch-related sound representations reflect the modulatory combination of height and the salience of the pitch percept. Copyright © 2017 Elsevier Inc. All rights reserved.

High data rate Reed-Solomon encoding and decoding using VLSI technology

NASA Technical Reports Server (NTRS)

Miller, Warner; Morakis, James

1987-01-01

Presented as an implementation of a Reed-Solomon encode and decoder, which is 16-symbol error correcting, each symbol is 8 bits. This Reed-Solomon (RS) code is an efficient error correcting code that the National Aeronautics and Space Administration (NASA) will use in future space communications missions. A Very Large Scale Integration (VLSI) implementation of the encoder and decoder accepts data rates up 80 Mbps. A total of seven chips are needed for the decoder (four of the seven decoding chips are customized using 3-micron Complementary Metal Oxide Semiconduction (CMOS) technology) and one chip is required for the encoder. The decoder operates with the symbol clock being the system clock for the chip set. Approximately 1.65 billion Galois Field (GF) operations per second are achieved with the decoder chip set and 640 MOPS are achieved with the encoder chip.

Highly efficient simulation environment for HDTV video decoder in VLSI design

NASA Astrophysics Data System (ADS)

Mao, Xun; Wang, Wei; Gong, Huimin; He, Yan L.; Lou, Jian; Yu, Lu; Yao, Qingdong; Pirsch, Peter

2002-01-01

With the increase of the complex of VLSI such as the SoC (System on Chip) of MPEG-2 Video decoder with HDTV scalability especially, simulation and verification of the full design, even as high as the behavior level in HDL, often proves to be very slow, costly and it is difficult to perform full verification until late in the design process. Therefore, they become bottleneck of the procedure of HDTV video decoder design, and influence it's time-to-market mostly. In this paper, the architecture of Hardware/Software Interface of HDTV video decoder is studied, and a Hardware-Software Mixed Simulation (HSMS) platform is proposed to check and correct error in the early design stage, based on the algorithm of MPEG-2 video decoding. The application of HSMS to target system could be achieved by employing several introduced approaches. Those approaches speed up the simulation and verification task without decreasing performance.

Flexible High Speed Codec (FHSC)

NASA Technical Reports Server (NTRS)

Segallis, G. P.; Wernlund, J. V.

1991-01-01

The ongoing NASA/Harris Flexible High Speed Codec (FHSC) program is described. The program objectives are to design and build an encoder decoder that allows operation in either burst or continuous modes at data rates of up to 300 megabits per second. The decoder handles both hard and soft decision decoding and can switch between modes on a burst by burst basis. Bandspreading is low since the code rate is greater than or equal to 7/8. The encoder and a hard decision decoder fit on a single application specific integrated circuit (ASIC) chip. A soft decision applique is implemented using 300 K emitter coupled logic (ECL) which can be easily translated to an ECL gate array.

Real-time SHVC software decoding with multi-threaded parallel processing

NASA Astrophysics Data System (ADS)

Gudumasu, Srinivas; He, Yuwen; Ye, Yan; He, Yong; Ryu, Eun-Seok; Dong, Jie; Xiu, Xiaoyu

2014-09-01

This paper proposes a parallel decoding framework for scalable HEVC (SHVC). Various optimization technologies are implemented on the basis of SHVC reference software SHM-2.0 to achieve real-time decoding speed for the two layer spatial scalability configuration. SHVC decoder complexity is analyzed with profiling information. The decoding process at each layer and the up-sampling process are designed in parallel and scheduled by a high level application task manager. Within each layer, multi-threaded decoding is applied to accelerate the layer decoding speed. Entropy decoding, reconstruction, and in-loop processing are pipeline designed with multiple threads based on groups of coding tree units (CTU). A group of CTUs is treated as a processing unit in each pipeline stage to achieve a better trade-off between parallelism and synchronization. Motion compensation, inverse quantization, and inverse transform modules are further optimized with SSE4 SIMD instructions. Simulations on a desktop with an Intel i7 processor 2600 running at 3.4 GHz show that the parallel SHVC software decoder is able to decode 1080p spatial 2x at up to 60 fps (frames per second) and 1080p spatial 1.5x at up to 50 fps for those bitstreams generated with SHVC common test conditions in the JCT-VC standardization group. The decoding performance at various bitrates with different optimization technologies and different numbers of threads are compared in terms of decoding speed and resource usage, including processor and memory.

Brain-state classification and a dual-state decoder dramatically improve the control of cursor movement through a brain-machine interface

NASA Astrophysics Data System (ADS)

Sachs, Nicholas A.; Ruiz-Torres, Ricardo; Perreault, Eric J.; Miller, Lee E.

2016-02-01

Objective. It is quite remarkable that brain machine interfaces (BMIs) can be used to control complex movements with fewer than 100 neurons. Success may be due in part to the limited range of dynamical conditions under which most BMIs are tested. Achieving high-quality control that spans these conditions with a single linear mapping will be more challenging. Even for simple reaching movements, existing BMIs must reduce the stochastic noise of neurons by averaging the control signals over time, instead of over the many neurons that normally control movement. This forces a compromise between a decoder with dynamics allowing rapid movement and one that allows postures to be maintained with little jitter. Our current work presents a method for addressing this compromise, which may also generalize to more highly varied dynamical situations, including movements with more greatly varying speed. Approach. We have developed a system that uses two independent Wiener filters as individual components in a single decoder, one optimized for movement, and the other for postural control. We computed an LDA classifier using the same neural inputs. The decoder combined the outputs of the two filters in proportion to the likelihood assigned by the classifier to each state. Main results. We have performed online experiments with two monkeys using this neural-classifier, dual-state decoder, comparing it to a standard, single-state decoder as well as to a dual-state decoder that switched states automatically based on the cursor’s proximity to a target. The performance of both monkeys using the classifier decoder was markedly better than that of the single-state decoder and comparable to the proximity decoder. Significance. We have demonstrated a novel strategy for dealing with the need to make rapid movements while also maintaining precise cursor control when approaching and stabilizing within targets. Further gains can undoubtedly be realized by optimizing the performance of the individual movement and posture decoders.

Brain-state classification and a dual-state decoder dramatically improve the control of cursor movement through a brain-machine interface.

PubMed

Sachs, Nicholas A; Ruiz-Torres, Ricardo; Perreault, Eric J; Miller, Lee E

2016-02-01

It is quite remarkable that brain machine interfaces (BMIs) can be used to control complex movements with fewer than 100 neurons. Success may be due in part to the limited range of dynamical conditions under which most BMIs are tested. Achieving high-quality control that spans these conditions with a single linear mapping will be more challenging. Even for simple reaching movements, existing BMIs must reduce the stochastic noise of neurons by averaging the control signals over time, instead of over the many neurons that normally control movement. This forces a compromise between a decoder with dynamics allowing rapid movement and one that allows postures to be maintained with little jitter. Our current work presents a method for addressing this compromise, which may also generalize to more highly varied dynamical situations, including movements with more greatly varying speed. We have developed a system that uses two independent Wiener filters as individual components in a single decoder, one optimized for movement, and the other for postural control. We computed an LDA classifier using the same neural inputs. The decoder combined the outputs of the two filters in proportion to the likelihood assigned by the classifier to each state. We have performed online experiments with two monkeys using this neural-classifier, dual-state decoder, comparing it to a standard, single-state decoder as well as to a dual-state decoder that switched states automatically based on the cursor's proximity to a target. The performance of both monkeys using the classifier decoder was markedly better than that of the single-state decoder and comparable to the proximity decoder. We have demonstrated a novel strategy for dealing with the need to make rapid movements while also maintaining precise cursor control when approaching and stabilizing within targets. Further gains can undoubtedly be realized by optimizing the performance of the individual movement and posture decoders.

Comparison of incoming dental school patients with and without disabilities.

PubMed

Stiefel, D J; Truelove, E L; Martin, M D; Mandel, L S

1997-01-01

A survey of incoming dental school patients compared 64 adult patients (DECOD) and 73 patients without disability (ND), regarding past dental experience, current needs, and basis for selecting the school's clinics. The responses indicated that, for DECOD patients, clinic selection was based largely on Medicaid acceptance, staff experience, and inability of other dentists to manage their disability; for ND patients, selection was based on lower fee structure. Both groups expressed high treatment need, but the rate was lower for DECOD than for ND patients. More DECOD patients reported severe dental anxiety and adverse effects of dental problems on general health. Chart records revealed that clinical findings exceeded perceived need for both DECOD and ND patients. While both groups had high periodontal disease rates (91%), DECOD patients had significantly poorer oral hygiene and less restorative need than ND patients. The findings suggest differences between persons with disabilities and other patient groups in difficulty of access to dental services in the community, reasons for entering the dental school system, and in presenting treatment need and/or treatment planning.

Design of a digital compression technique for shuttle television

NASA Technical Reports Server (NTRS)

Habibi, A.; Fultz, G.

1976-01-01

The determination of the performance and hardware complexity of data compression algorithms applicable to color television signals, were studied to assess the feasibility of digital compression techniques for shuttle communications applications. For return link communications, it is shown that a nonadaptive two dimensional DPCM technique compresses the bandwidth of field-sequential color TV to about 13 MBPS and requires less than 60 watts of secondary power. For forward link communications, a facsimile coding technique is recommended which provides high resolution slow scan television on a 144 KBPS channel. The onboard decoder requires about 19 watts of secondary power.

The Rich Color Variations of Pluto

NASA Image and Video Library

2015-09-24

NASA's New Horizons spacecraft captured this high-resolution enhanced color view of Pluto on July 14, 2015. The image combines blue, red and infrared images taken by the Ralph/Multispectral Visual Imaging Camera (MVIC). Pluto's surface sports a remarkable range of subtle colors, enhanced in this view to a rainbow of pale blues, yellows, oranges, and deep reds. Many landforms have their own distinct colors, telling a complex geological and climatological story that scientists have only just begun to decode. The image resolves details and colors on scales as small as 0.8 miles (1.3 kilometers). http://photojournal.jpl.nasa.gov/catalog/PIA19952

Is phase measurement necessary for incoherent holographic 3D imaging?

NASA Astrophysics Data System (ADS)

Rosen, Joseph; Vijayakumar, A.; Rai, Mani Ratnam; Mukherjee, Saswata

2018-02-01

Incoherent digital holography can be used for several applications, among which are high resolution fluorescence microscopy and imaging through a scattering medium. Historically, an incoherent digital hologram has been usually recorded by self-interference systems in which both interfering beams are originated from the same observed object. The self-interference system enables to read the phase distribution of the wavefronts propagating from an object and consequently to decode the 3D location of the object points. In this presentation, we survey several cases in which 3D holographic imaging can be done without the phase information and without two-wave interference.

A Novel 2D Image Compression Algorithm Based on Two Levels DWT and DCT Transforms with Enhanced Minimize-Matrix-Size Algorithm for High Resolution Structured Light 3D Surface Reconstruction

NASA Astrophysics Data System (ADS)

Siddeq, M. M.; Rodrigues, M. A.

2015-09-01

Image compression techniques are widely used on 2D image 2D video 3D images and 3D video. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level discrete cosine transform (DCT) and a two level discrete wavelet transform (DWT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of four steps. (1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix, respectively, (2) apply a second level DCT on the DC-Matrix to generate two arrays, namely nonzero-array and zero-array, (3) apply the Minimize-Matrix-Size algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT, (4) apply arithmetic coding to the output of previous steps. A novel decompression algorithm, Fast-Match-Search algorithm (FMS), is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined in one matrix followed by inverse two levels DCT with two levels DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D root-mean-square-error following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.

Word-Decoding Skill Interacts with Working Memory Capacity to Influence Inference Generation during Reading

ERIC Educational Resources Information Center

Hamilton, Stephen; Freed, Erin; Long, Debra L.

2016-01-01

The aim of this study was to examine predictions derived from a proposal about the relation between word-decoding skill and working memory capacity, called verbal efficiency theory. The theory states that poor word representations and slow decoding processes consume resources in working memory that would otherwise be used to execute high-level…

Multivariate pattern analysis for MEG: A comparison of dissimilarity measures.

PubMed

Guggenmos, Matthias; Sterzer, Philipp; Cichy, Radoslaw Martin

2018-06-01

Multivariate pattern analysis (MVPA) methods such as decoding and representational similarity analysis (RSA) are growing rapidly in popularity for the analysis of magnetoencephalography (MEG) data. However, little is known about the relative performance and characteristics of the specific dissimilarity measures used to describe differences between evoked activation patterns. Here we used a multisession MEG data set to qualitatively characterize a range of dissimilarity measures and to quantitatively compare them with respect to decoding accuracy (for decoding) and between-session reliability of representational dissimilarity matrices (for RSA). We tested dissimilarity measures from a range of classifiers (Linear Discriminant Analysis - LDA, Support Vector Machine - SVM, Weighted Robust Distance - WeiRD, Gaussian Naïve Bayes - GNB) and distances (Euclidean distance, Pearson correlation). In addition, we evaluated three key processing choices: 1) preprocessing (noise normalisation, removal of the pattern mean), 2) weighting decoding accuracies by decision values, and 3) computing distances in three different partitioning schemes (non-cross-validated, cross-validated, within-class-corrected). Four main conclusions emerged from our results. First, appropriate multivariate noise normalization substantially improved decoding accuracies and the reliability of dissimilarity measures. Second, LDA, SVM and WeiRD yielded high peak decoding accuracies and nearly identical time courses. Third, while using decoding accuracies for RSA was markedly less reliable than continuous distances, this disadvantage was ameliorated by decision-value-weighting of decoding accuracies. Fourth, the cross-validated Euclidean distance provided unbiased distance estimates and highly replicable representational dissimilarity matrices. Overall, we strongly advise the use of multivariate noise normalisation as a general preprocessing step, recommend LDA, SVM and WeiRD as classifiers for decoding and highlight the cross-validated Euclidean distance as a reliable and unbiased default choice for RSA. Copyright © 2018 Elsevier Inc. All rights reserved.

Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

PubMed Central

Jones, Michael N.

2017-01-01

A central goal of cognitive neuroscience is to decode human brain activity—that is, to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive—that is, capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a probabilistic decoding framework based on a novel topic model—Generalized Correspondence Latent Dirichlet Allocation—that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text—enabling researchers, for the first time, to generate quantitative, context-sensitive interpretations of whole-brain patterns of brain activity. PMID:29059185

Volumetric Medical Image Coding: An Object-based, Lossy-to-lossless and Fully Scalable Approach

PubMed Central

Danyali, Habibiollah; Mertins, Alfred

2011-01-01

In this article, an object-based, highly scalable, lossy-to-lossless 3D wavelet coding approach for volumetric medical image data (e.g., magnetic resonance (MR) and computed tomography (CT)) is proposed. The new method, called 3DOBHS-SPIHT, is based on the well-known set partitioning in the hierarchical trees (SPIHT) algorithm and supports both quality and resolution scalability. The 3D input data is grouped into groups of slices (GOS) and each GOS is encoded and decoded as a separate unit. The symmetric tree definition of the original 3DSPIHT is improved by introducing a new asymmetric tree structure. While preserving the compression efficiency, the new tree structure allows for a small size of each GOS, which not only reduces memory consumption during the encoding and decoding processes, but also facilitates more efficient random access to certain segments of slices. To achieve more compression efficiency, the algorithm only encodes the main object of interest in each 3D data set, which can have any arbitrary shape, and ignores the unnecessary background. The experimental results on some MR data sets show the good performance of the 3DOBHS-SPIHT algorithm for multi-resolution lossy-to-lossless coding. The compression efficiency, full scalability, and object-based features of the proposed approach, beside its lossy-to-lossless coding support, make it a very attractive candidate for volumetric medical image information archiving and transmission applications. PMID:22606653

A /31,15/ Reed-Solomon Code for large memory systems

NASA Technical Reports Server (NTRS)

Lim, R. S.

1979-01-01

This paper describes the encoding and the decoding of a (31,15) Reed-Solomon Code for multiple-burst error correction for large memory systems. The decoding procedure consists of four steps: (1) syndrome calculation, (2) error-location polynomial calculation, (3) error-location numbers calculation, and (4) error values calculation. The principal features of the design are the use of a hardware shift register for both high-speed encoding and syndrome calculation, and the use of a commercially available (31,15) decoder for decoding Steps 2, 3 and 4.

A novel unbalanced multiple description coder for robust video transmission over ad hoc wireless networks

NASA Astrophysics Data System (ADS)

Huang, Feng; Sun, Lifeng; Zhong, Yuzhuo

2006-01-01

Robust transmission of live video over ad hoc wireless networks presents new challenges: high bandwidth requirements are coupled with delay constraints; even a single packet loss causes error propagation until a complete video frame is coded in the intra-mode; ad hoc wireless networks suffer from bursty packet losses that drastically degrade the viewing experience. Accordingly, we propose a novel UMD coder capable of quickly recovering from losses and ensuring continuous playout. It uses 'peg' frames to prevent error propagation in the High-Resolution (HR) description and improve the robustness of key frames. The Low-Resolution (LR) coder works independent of the HR one, but they can also help each other recover from losses. Like many UMD coders, our UMD coder is drift-free, disruption-tolerant and able to make good use of the asymmetric available bandwidths of multiple paths. The simulation results under different conditions show that the proposed UMD coder has the highest decoded quality and lowest probability of pause when compared with concurrent UMDC techniques. The coder also has a comparable decoded quality, lower startup delay and lower probability of pause than a state-of-the-art FEC-based scheme. To provide robustness for video multicast applications, we propose non-end-to-end UMDC-based video distribution over a multi-tree multicast network. The multiplicity of parents decorrelates losses and the non-end-to-end feature increases the throughput of UMDC video data. We deploy an application-level service of LR description reconstruction in some intermediate nodes of the LR multicast tree. The principle behind this is to reconstruct the disrupted LR frames by the correctly received HR frames. As a result, the viewing experience at the downstream nodes benefits from the protection reconstruction at the upstream nodes.

High-dimensional structured light coding/decoding for free-space optical communications free of obstructions.

PubMed

Du, Jing; Wang, Jian

2015-11-01

Bessel beams carrying orbital angular momentum (OAM) with helical phase fronts exp(ilφ)(l=0;±1;±2;…), where φ is the azimuthal angle and l corresponds to the topological number, are orthogonal with each other. This feature of Bessel beams provides a new dimension to code/decode data information on the OAM state of light, and the theoretical infinity of topological number enables possible high-dimensional structured light coding/decoding for free-space optical communications. Moreover, Bessel beams are nondiffracting beams having the ability to recover by themselves in the face of obstructions, which is important for free-space optical communications relying on line-of-sight operation. By utilizing the OAM and nondiffracting characteristics of Bessel beams, we experimentally demonstrate 12 m distance obstruction-free optical m-ary coding/decoding using visible Bessel beams in a free-space optical communication system. We also study the bit error rate (BER) performance of hexadecimal and 32-ary coding/decoding based on Bessel beams with different topological numbers. After receiving 500 symbols at the receiver side, a zero BER of hexadecimal coding/decoding is observed when the obstruction is placed along the propagation path of light.

Bandwidth efficient coding for satellite communications

NASA Technical Reports Server (NTRS)

Lin, Shu; Costello, Daniel J., Jr.; Miller, Warner H.; Morakis, James C.; Poland, William B., Jr.

1992-01-01

An error control coding scheme was devised to achieve large coding gain and high reliability by using coded modulation with reduced decoding complexity. To achieve a 3 to 5 dB coding gain and moderate reliability, the decoding complexity is quite modest. In fact, to achieve a 3 dB coding gain, the decoding complexity is quite simple, no matter whether trellis coded modulation or block coded modulation is used. However, to achieve coding gains exceeding 5 dB, the decoding complexity increases drastically, and the implementation of the decoder becomes very expensive and unpractical. The use is proposed of coded modulation in conjunction with concatenated (or cascaded) coding. A good short bandwidth efficient modulation code is used as the inner code and relatively powerful Reed-Solomon code is used as the outer code. With properly chosen inner and outer codes, a concatenated coded modulation scheme not only can achieve large coding gains and high reliability with good bandwidth efficiency but also can be practically implemented. This combination of coded modulation and concatenated coding really offers a way of achieving the best of three worlds, reliability and coding gain, bandwidth efficiency, and decoding complexity.

High-Throughput Bit-Serial LDPC Decoder LSI Based on Multiple-Valued Asynchronous Interleaving

NASA Astrophysics Data System (ADS)

Onizawa, Naoya; Hanyu, Takahiro; Gaudet, Vincent C.

This paper presents a high-throughput bit-serial low-density parity-check (LDPC) decoder that uses an asynchronous interleaver. Since consecutive log-likelihood message values on the interleaver are similar, node computations are continuously performed by using the most recently arrived messages without significantly affecting bit-error rate (BER) performance. In the asynchronous interleaver, each message's arrival rate is based on the delay due to the wire length, so that the decoding throughput is not restricted by the worst-case latency, which results in a higher average rate of computation. Moreover, the use of a multiple-valued data representation makes it possible to multiplex control signals and data from mutual nodes, thus minimizing the number of handshaking steps in the asynchronous interleaver and eliminating the clock signal entirely. As a result, the decoding throughput becomes 1.3 times faster than that of a bit-serial synchronous decoder under a 90nm CMOS technology, at a comparable BER.

A zero power harmonic transponder sensor for ubiquitous wireless μL liquid-volume monitoring

NASA Astrophysics Data System (ADS)

Huang, Haiyu; Chen, Pai-Yen; Hung, Cheng-Hsien; Gharpurey, Ranjit; Akinwande, Deji

2016-01-01

Autonomous liquid-volume monitoring is crucial in ubiquitous healthcare. However, conventional approach is based on either human visual observation or expensive detectors, which are costly for future pervasive monitoring. Here we introduce a novel approach based on passive harmonic transponder antenna sensor and frequency hopping spread spectrum (FHSS) pattern analysis, to provide a very low cost wireless μL-resolution liquid-volume monitoring without battery or digital circuits. In our conceptual demonstration, the harmonic transponder comprises of a passive nonlinear frequency multiplier connected to a metamaterial-inspired 3-D antenna designed to be highly sensitive to the liquid-volume within a confined region. The transponder first receives some FHSS signal from an interrogator, then converts such signal to its harmonic band and re-radiates through the antenna sensor. The harmonic signal is picked up by a sniffer receiver and decoded through pattern analysis of the high dimensional FHSS signal strength data. A robust, zero power, absolute accuracy wireless liquid-volume monitoring is realized in the presence of strong direct coupling, background scatters, distance variance as well as near-field human-body interference. The concepts of passive harmonic transponder sensor, metamaterial-inspired antenna sensor, and FHSS pattern analysis based sensor decoding may help establishing cost-effective, energy-efficient and intelligent wireless pervasive healthcare monitoring platforms.

A zero power harmonic transponder sensor for ubiquitous wireless μL liquid-volume monitoring.

PubMed

Huang, Haiyu; Chen, Pai-Yen; Hung, Cheng-Hsien; Gharpurey, Ranjit; Akinwande, Deji

2016-01-06

Autonomous liquid-volume monitoring is crucial in ubiquitous healthcare. However, conventional approach is based on either human visual observation or expensive detectors, which are costly for future pervasive monitoring. Here we introduce a novel approach based on passive harmonic transponder antenna sensor and frequency hopping spread spectrum (FHSS) pattern analysis, to provide a very low cost wireless μL-resolution liquid-volume monitoring without battery or digital circuits. In our conceptual demonstration, the harmonic transponder comprises of a passive nonlinear frequency multiplier connected to a metamaterial-inspired 3-D antenna designed to be highly sensitive to the liquid-volume within a confined region. The transponder first receives some FHSS signal from an interrogator, then converts such signal to its harmonic band and re-radiates through the antenna sensor. The harmonic signal is picked up by a sniffer receiver and decoded through pattern analysis of the high dimensional FHSS signal strength data. A robust, zero power, absolute accuracy wireless liquid-volume monitoring is realized in the presence of strong direct coupling, background scatters, distance variance as well as near-field human-body interference. The concepts of passive harmonic transponder sensor, metamaterial-inspired antenna sensor, and FHSS pattern analysis based sensor decoding may help establishing cost-effective, energy-efficient and intelligent wireless pervasive healthcare monitoring platforms.

A zero power harmonic transponder sensor for ubiquitous wireless μL liquid-volume monitoring

PubMed Central

Huang, Haiyu; Chen, Pai-Yen; Hung, Cheng-Hsien; Gharpurey, Ranjit; Akinwande, Deji

2016-01-01

Autonomous liquid-volume monitoring is crucial in ubiquitous healthcare. However, conventional approach is based on either human visual observation or expensive detectors, which are costly for future pervasive monitoring. Here we introduce a novel approach based on passive harmonic transponder antenna sensor and frequency hopping spread spectrum (FHSS) pattern analysis, to provide a very low cost wireless μL-resolution liquid-volume monitoring without battery or digital circuits. In our conceptual demonstration, the harmonic transponder comprises of a passive nonlinear frequency multiplier connected to a metamaterial-inspired 3-D antenna designed to be highly sensitive to the liquid-volume within a confined region. The transponder first receives some FHSS signal from an interrogator, then converts such signal to its harmonic band and re-radiates through the antenna sensor. The harmonic signal is picked up by a sniffer receiver and decoded through pattern analysis of the high dimensional FHSS signal strength data. A robust, zero power, absolute accuracy wireless liquid-volume monitoring is realized in the presence of strong direct coupling, background scatters, distance variance as well as near-field human-body interference. The concepts of passive harmonic transponder sensor, metamaterial-inspired antenna sensor, and FHSS pattern analysis based sensor decoding may help establishing cost-effective, energy-efficient and intelligent wireless pervasive healthcare monitoring platforms. PMID:26732251

An architecture of entropy decoder, inverse quantiser and predictor for multi-standard video decoding

NASA Astrophysics Data System (ADS)

Liu, Leibo; Chen, Yingjie; Yin, Shouyi; Lei, Hao; He, Guanghui; Wei, Shaojun

2014-07-01

A VLSI architecture for entropy decoder, inverse quantiser and predictor is proposed in this article. This architecture is used for decoding video streams of three standards on a single chip, i.e. H.264/AVC, AVS (China National Audio Video coding Standard) and MPEG2. The proposed scheme is called MPMP (Macro-block-Parallel based Multilevel Pipeline), which is intended to improve the decoding performance to satisfy the real-time requirements while maintaining a reasonable area and power consumption. Several techniques, such as slice level pipeline, MB (Macro-Block) level pipeline, MB level parallel, etc., are adopted. Input and output buffers for the inverse quantiser and predictor are shared by the decoding engines for H.264, AVS and MPEG2, therefore effectively reducing the implementation overhead. Simulation shows that decoding process consumes 512, 435 and 438 clock cycles per MB in H.264, AVS and MPEG2, respectively. Owing to the proposed techniques, the video decoder can support H.264 HP (High Profile) 1920 × 1088@30fps (frame per second) streams, AVS JP (Jizhun Profile) 1920 × 1088@41fps streams and MPEG2 MP (Main Profile) 1920 × 1088@39fps streams when exploiting a 200 MHz working frequency.

Grasp movement decoding from premotor and parietal cortex.

PubMed

Townsend, Benjamin R; Subasi, Erk; Scherberger, Hansjörg

2011-10-05

Despite recent advances in harnessing cortical motor-related activity to control computer cursors and robotic devices, the ability to decode and execute different grasping patterns remains a major obstacle. Here we demonstrate a simple Bayesian decoder for real-time classification of grip type and wrist orientation in macaque monkeys that uses higher-order planning signals from anterior intraparietal cortex (AIP) and ventral premotor cortex (area F5). Real-time decoding was based on multiunit signals, which had similar tuning properties to cells in previous single-unit recording studies. Maximum decoding accuracy for two grasp types (power and precision grip) and five wrist orientations was 63% (chance level, 10%). Analysis of decoder performance showed that grip type decoding was highly accurate (90.6%), with most errors occurring during orientation classification. In a subsequent off-line analysis, we found small but significant performance improvements (mean, 6.25 percentage points) when using an optimized spike-sorting method (superparamagnetic clustering). Furthermore, we observed significant differences in the contributions of F5 and AIP for grasp decoding, with F5 being better suited for classification of the grip type and AIP contributing more toward decoding of object orientation. However, optimum decoding performance was maximal when using neural activity simultaneously from both areas. Overall, these results highlight quantitative differences in the functional representation of grasp movements in AIP and F5 and represent a first step toward using these signals for developing functional neural interfaces for hand grasping.

High-Speed Soft-Decision Decoding of Two Reed-Muller Codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Uehara, Gregory T.

1996-01-01

In this research, we have proposed the (64, 40, 8) subcode of the third-order Reed-Muller (RM) code to NASA for high-speed satellite communications. This RM subcode can be used either alone or as an inner code of a concatenated coding system with the NASA standard (255, 233, 33) Reed-Solomon (RS) code as the outer code to achieve high performance (or low bit-error rate) with reduced decoding complexity. It can also be used as a component code in a multilevel bandwidth efficient coded modulation system to achieve reliable bandwidth efficient data transmission. This report will summarize the key progress we have made toward achieving our eventual goal of implementing, a decoder system based upon this code. In the first phase of study, we investigated the complexities of various sectionalized trellis diagrams for the proposed (64, 40, 8) RM subcode. We found a specific 8-trellis diagram for this code which requires the least decoding complexity with a high possibility of achieving a decoding speed of 600 M bits per second (Mbps). The combination of a large number of states and a high data rate will be made possible due to the utilization of a high degree of parallelism throughout the architecture. This trellis diagram will be presented and briefly described. In the second phase of study, which was carried out through the past year, we investigated circuit architectures to determine the feasibility of VLSI implementation of a high-speed Viterbi decoder based on this 8-section trellis diagram. We began to examine specific design and implementation approaches to implement a fully custom integrated circuit (IC) which will be a key building block for a decoder system implementation. The key results will be presented in this report. This report will be divided into three primary sections. First, we will briefly describe the system block diagram in which the proposed decoder is assumed to be operating, and present some of the key architectural approaches being used to implement the system at high speed. Second, we will describe details of the 8-trellis diagram we found to best meet the trade-offs between chip and overall system complexity. The chosen approach implements the trellis for the (64, 40, 8) RM subcode with 32 independent sub-trellises. And third, we will describe results of our feasibility study on the implementation of such an IC chip in CMOS technology to implement one of these sub-trellises.

Wavefront coding for fast, high-resolution light-sheet microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Olarte, Omar E.; Licea-Rodriguez, Jacob; Loza-Alvarez, Pablo

2017-02-01

Some biological experiments demand the observation of dynamics processes in 3D with high spatiotemporal resolution. The use of wavefront coding to extend the depth-of-field (DOF) of the collection arm of a light-sheet microscope is an interesting alternative for fast 3D imaging. Under this scheme, the 3D features of the sample are captured at high volumetric rates while the light sheet is swept rapidly within the extended DOF. The DOF is extended by coding the pupil function of the imaging lens by using a custom-designed phase mask. A posterior restoration step is required to decode the information of the captured images based on the applied phase mask [1]. This hybrid optical-digital approach is known as wavefront coding (WFC). Previously, we have demonstrated this method for performing fast 3D imaging of biological samples at medium resolution [2]. In this work, we present the extension of this approach for high-resolution microscopes. Under these conditions, the effective DOF of a standard high NA objective is of a few micrometers. Here we demonstrate that by the use of WFC, we can extend the DOF more than one order of magnitude keeping the high-resolution imaging. This is demonstrated for two designed phase masks using Zebrafish and C. elegans samples. [1] Olarte, O.E., Andilla, J., Artigas, D., and Loza-Alvarez, P., "Decoupled Illumination-Detection Microscopy. Selected Optics in Year 2105," in Optics and Photonics news 26, p. 41 (2015). [2] Olarte, O.E., Andilla, J., Artigas, D., and Loza-Alvarez, P., "Decoupled illumination detection in light sheet microscopy for fast volumetric imaging," Optica 2(8), 702 (2015).

Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions.

PubMed

Contini, Erika W; Wardle, Susan G; Carlson, Thomas A

2017-10-01

Visual object recognition is a complex, dynamic process. Multivariate pattern analysis methods, such as decoding, have begun to reveal how the brain processes complex visual information. Recently, temporal decoding methods for EEG and MEG have offered the potential to evaluate the temporal dynamics of object recognition. Here we review the contribution of M/EEG time-series decoding methods to understanding visual object recognition in the human brain. Consistent with the current understanding of the visual processing hierarchy, low-level visual features dominate decodable object representations early in the time-course, with more abstract representations related to object category emerging later. A key finding is that the time-course of object processing is highly dynamic and rapidly evolving, with limited temporal generalisation of decodable information. Several studies have examined the emergence of object category structure, and we consider to what degree category decoding can be explained by sensitivity to low-level visual features. Finally, we evaluate recent work attempting to link human behaviour to the neural time-course of object processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Microanatomy of the cochlear hook

NASA Astrophysics Data System (ADS)

Kwan, Changyow Claire; Tan, Xiaodong; Stock, Stuart R.; Soriano, Carmen; Xiao, Xianghui; Richter, Claus-Peter

2017-09-01

Communication among humans occurs through coding and decoding of acoustic information. The inner ear or cochlea acts as a frequency analyzer and divides the acoustic signal into small frequency bands, which are processed at different sites along the cochlea. The mechano-electrical conversion is accomplished by the soft tissue structures in the cochlea. While the anatomy for most of the cochlea has been well described, a detailed description of the very high frequency and vulnerable cochlear hook region is missing. To study the cochlear hook, mice cochleae were imaged with synchrotron radiation and high-resolution reconstructions have been made from the tomographic scans. This is the first detailed description of the bony and soft tissues of the hook region of the mammalian cochlea.

High-performance software-only H.261 video compression on PC

NASA Astrophysics Data System (ADS)

Kasperovich, Leonid

1996-03-01

This paper describes an implementation of a software H.261 codec for PC, that takes an advantage of the fast computational algorithms for DCT-based video compression, which have been presented by the author at the February's 1995 SPIE/IS&T meeting. The motivation for developing the H.261 prototype system is to demonstrate a feasibility of real time software- only videoconferencing solution to operate across a wide range of network bandwidth, frame rate, and resolution of the input video. As the bandwidths of current network technology will be increased, the higher frame rate and resolution of video to be transmitted is allowed, that requires, in turn, a software codec to be able to compress pictures of CIF (352 X 288) resolution at up to 30 frame/sec. Running on Pentium 133 MHz PC the codec presented is capable to compress video in CIF format at 21 - 23 frame/sec. This result is comparable to the known hardware-based H.261 solutions, but it doesn't require any specific hardware. The methods to achieve high performance, the program optimization technique for Pentium microprocessor along with the performance profile, showing the actual contribution of the different encoding/decoding stages to the overall computational process, are presented.

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PubMed

Zafar, Raheel; Dass, Sarat C; Malik, Aamir Saeed

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method.

Submicrometre geometrically encoded fluorescent barcodes self-assembled from DNA

NASA Astrophysics Data System (ADS)

Lin, Chenxiang; Jungmann, Ralf; Leifer, Andrew M.; Li, Chao; Levner, Daniel; Church, George M.; Shih, William M.; Yin, Peng

2012-10-01

The identification and differentiation of a large number of distinct molecular species with high temporal and spatial resolution is a major challenge in biomedical science. Fluorescence microscopy is a powerful tool, but its multiplexing ability is limited by the number of spectrally distinguishable fluorophores. Here, we used (deoxy)ribonucleic acid (DNA)-origami technology to construct submicrometre nanorods that act as fluorescent barcodes. We demonstrate that spatial control over the positioning of fluorophores on the surface of a stiff DNA nanorod can produce 216 distinct barcodes that can be decoded unambiguously using epifluorescence or total internal reflection fluorescence microscopy. Barcodes with higher spatial information density were demonstrated via the construction of super-resolution barcodes with features spaced by ˜40 nm. One species of the barcodes was used to tag yeast surface receptors, which suggests their potential applications as in situ imaging probes for diverse biomolecular and cellular entities in their native environments.

Wavelet/scalar quantization compression standard for fingerprint images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brislawn, C.M.

1996-06-12

US Federal Bureau of Investigation (FBI) has recently formulated a national standard for digitization and compression of gray-scale fingerprint images. Fingerprints are scanned at a spatial resolution of 500 dots per inch, with 8 bits of gray-scale resolution. The compression algorithm for the resulting digital images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition (wavelet/scalar quantization method). The FBI standard produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. The compression standard specifies a class ofmore » potential encoders and a universal decoder with sufficient generality to reconstruct compressed images produced by any compliant encoder, allowing flexibility for future improvements in encoder technology. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations.« less

Sub-micrometer Geometrically Encoded Fluorescent Barcodes Self-Assembled from DNA

PubMed Central

Lin, Chenxiang; Jungmann, Ralf; Leifer, Andrew M.; Li, Chao; Levner, Daniel; Church, George M.; Shih, William M.; Yin, Peng

2012-01-01

The identification and differentiation of a large number of distinct molecular species with high temporal and spatial resolution is a major challenge in biomedical science. Fluorescence microscopy is a powerful tool, but its multiplexing ability is limited by the number of spectrally distinguishable fluorophores. Here we use DNA-origami technology to construct sub-micrometer nanorods that act as fluorescent barcodes. We demonstrate that spatial control over the positioning of fluorophores on the surface of a stiff DNA nanorod can produce 216 distinct barcodes that can be unambiguously decoded using epifluorescence or total internal reflection fluorescence (TIRF) microscopy. Barcodes with higher spatial information density were demonstrated via the construction of super-resolution barcodes with features spaced by ~40 nm. One species of the barcodes was used to tag yeast surface receptors, suggesting their potential applications as in situ imaging probes for diverse biomolecular and cellular entities in their native environments. PMID:23000997

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects.

PubMed

Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

2016-01-01

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future.

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects

PubMed Central

Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

2017-01-01

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future. PMID:28167896

A high performing brain-machine interface driven by low-frequency local field potentials alone and together with spikes

NASA Astrophysics Data System (ADS)

Stavisky, Sergey D.; Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V.

2015-06-01

Objective. Brain-machine interfaces (BMIs) seek to enable people with movement disabilities to directly control prosthetic systems with their neural activity. Current high performance BMIs are driven by action potentials (spikes), but access to this signal often diminishes as sensors degrade over time. Decoding local field potentials (LFPs) as an alternative or complementary BMI control signal may improve performance when there is a paucity of spike signals. To date only a small handful of LFP decoding methods have been tested online; there remains a need to test different LFP decoding approaches and improve LFP-driven performance. There has also not been a reported demonstration of a hybrid BMI that decodes kinematics from both LFP and spikes. Here we first evaluate a BMI driven by the local motor potential (LMP), a low-pass filtered time-domain LFP amplitude feature. We then combine decoding of both LMP and spikes to implement a hybrid BMI. Approach. Spikes and LFP were recorded from two macaques implanted with multielectrode arrays in primary and premotor cortex while they performed a reaching task. We then evaluated closed-loop BMI control using biomimetic decoders driven by LMP, spikes, or both signals together. Main results. LMP decoding enabled quick and accurate cursor control which surpassed previously reported LFP BMI performance. Hybrid decoding of both spikes and LMP improved performance when spikes signal quality was mediocre to poor. Significance. These findings show that LMP is an effective BMI control signal which requires minimal power to extract and can substitute for or augment impoverished spikes signals. Use of this signal may lengthen the useful lifespan of BMIs and is therefore an important step towards clinically viable BMIs.

Large constraint length high speed viterbi decoder based on a modular hierarchial decomposition of the deBruijn graph

NASA Technical Reports Server (NTRS)

Collins, Oliver (Inventor); Dolinar, Jr., Samuel J. (Inventor); Hus, In-Shek (Inventor); Bozzola, Fabrizio P. (Inventor); Olson, Erlend M. (Inventor); Statman, Joseph I. (Inventor); Zimmerman, George A. (Inventor)

1991-01-01

A method of formulating and packaging decision-making elements into a long constraint length Viterbi decoder which involves formulating the decision-making processors as individual Viterbi butterfly processors that are interconnected in a deBruijn graph configuration. A fully distributed architecture, which achieves high decoding speeds, is made feasible by novel wiring and partitioning of the state diagram. This partitioning defines universal modules, which can be used to build any size decoder, such that a large number of wires is contained inside each module, and a small number of wires is needed to connect modules. The total system is modular and hierarchical, and it implements a large proportion of the required wiring internally within modules and may include some external wiring to fully complete the deBruijn graph. pg,14.

Distinct neural patterns enable grasp types decoding in monkey dorsal premotor cortex.

PubMed

Hao, Yaoyao; Zhang, Qiaosheng; Controzzi, Marco; Cipriani, Christian; Li, Yue; Li, Juncheng; Zhang, Shaomin; Wang, Yiwen; Chen, Weidong; Chiara Carrozza, Maria; Zheng, Xiaoxiang

2014-12-01

Recent studies have shown that dorsal premotor cortex (PMd), a cortical area in the dorsomedial grasp pathway, is involved in grasp movements. However, the neural ensemble firing property of PMd during grasp movements and the extent to which it can be used for grasp decoding are still unclear. To address these issues, we used multielectrode arrays to record both spike and local field potential (LFP) signals in PMd in macaque monkeys performing reaching and grasping of one of four differently shaped objects. Single and population neuronal activity showed distinct patterns during execution of different grip types. Cluster analysis of neural ensemble signals indicated that the grasp related patterns emerged soon (200-300 ms) after the go cue signal, and faded away during the hold period. The timing and duration of the patterns varied depending on the behaviors of individual monkey. Application of support vector machine model to stable activity patterns revealed classification accuracies of 94% and 89% for each of the two monkeys, indicating a robust, decodable grasp pattern encoded in the PMd. Grasp decoding using LFPs, especially the high-frequency bands, also produced high decoding accuracies. This study is the first to specify the neuronal population encoding of grasp during the time course of grasp. We demonstrate high grasp decoding performance in PMd. These findings, combined with previous evidence for reach related modulation studies, suggest that PMd may play an important role in generation and maintenance of grasp action and may be a suitable locus for brain-machine interface applications.

High-Speed Soft-Decision Decoding of Two Reed-Muller Codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Uehara, Gregory T.

1996-01-01

In his research, we have proposed the (64, 40, 8) subcode of the third-order Reed-Muller (RM) code to NASA for high-speed satellite communications. This RM subcode can be used either alone or as an inner code of a concatenated coding system with the NASA standard (255, 233, 33) Reed-Solomon (RS) code as the outer code to achieve high performance (or low bit-error rate) with reduced decoding complexity. It can also be used as a component code in a multilevel bandwidth efficient coded modulation system to achieve reliable bandwidth efficient data transmission. This report will summarize the key progress we have made toward achieving our eventual goal of implementing a decoder system based upon this code. In the first phase of study, we investigated the complexities of various sectionalized trellis diagrams for the proposed (64, 40, 8) RNI subcode. We found a specific 8-trellis diagram for this code which requires the least decoding complexity with a high possibility of achieving a decoding speed of 600 M bits per second (Mbps). The combination of a large number of states and a hi ch data rate will be made possible due to the utilization of a high degree of parallelism throughout the architecture. This trellis diagram will be presented and briefly described. In the second phase of study which was carried out through the past year, we investigated circuit architectures to determine the feasibility of VLSI implementation of a high-speed Viterbi decoder based on this 8-section trellis diagram. We began to examine specific design and implementation approaches to implement a fully custom integrated circuit (IC) which will be a key building block for a decoder system implementation. The key results will be presented in this report. This report will be divided into three primary sections. First, we will briefly describe the system block diagram in which the proposed decoder is assumed to be operating and present some of the key architectural approaches being used to implement the system at high speed. Second, we will describe details of the 8-trellis diagram we found to best meet the trade-offs between chip and overall system complexity. The chosen approach implements the trellis for the (64, 40, 8) RM subcode with 32 independent sub-trellises. And third, we will describe results of our feasibility study on the implementation of such an IC chip in CMOS technology to implement one of these sub-trellises.

Decoding illusory self-location from activity in the human hippocampus.

PubMed

Guterstam, Arvid; Björnsdotter, Malin; Bergouignan, Loretxu; Gentile, Giovanni; Li, Tie-Qiang; Ehrsson, H Henrik

2015-01-01

Decades of research have demonstrated a role for the hippocampus in spatial navigation and episodic and spatial memory. However, empirical evidence linking hippocampal activity to the perceptual experience of being physically located at a particular place in the environment is lacking. In this study, we used a multisensory out-of-body illusion to perceptually 'teleport' six healthy participants between two different locations in the scanner room during high-resolution functional magnetic resonance imaging (fMRI). The participants were fitted with MRI-compatible head-mounted displays that changed their first-person visual perspective to that of a pair of cameras placed in one of two corners of the scanner room. To elicit the illusion of being physically located in this position, we delivered synchronous visuo-tactile stimulation in the form of an object moving toward the cameras coupled with touches applied to the participant's chest. Asynchronous visuo-tactile stimulation did not induce the illusion and served as a control condition. We found that illusory self-location could be successfully decoded from patterns of activity in the hippocampus in all of the participants in the synchronous (P < 0.05) but not in the asynchronous condition (P > 0.05). At the group-level, the decoding accuracy was significantly higher in the synchronous than in the asynchronous condition (P = 0.012). These findings associate hippocampal activity with the perceived location of the bodily self in space, which suggests that the human hippocampus is involved not only in spatial navigation and memory but also in the construction of our sense of bodily self-location.

Decoding illusory self-location from activity in the human hippocampus

PubMed Central

Guterstam, Arvid; Björnsdotter, Malin; Bergouignan, Loretxu; Gentile, Giovanni; Li, Tie-Qiang; Ehrsson, H. Henrik

2015-01-01

Decades of research have demonstrated a role for the hippocampus in spatial navigation and episodic and spatial memory. However, empirical evidence linking hippocampal activity to the perceptual experience of being physically located at a particular place in the environment is lacking. In this study, we used a multisensory out-of-body illusion to perceptually ‘teleport’ six healthy participants between two different locations in the scanner room during high-resolution functional magnetic resonance imaging (fMRI). The participants were fitted with MRI-compatible head-mounted displays that changed their first-person visual perspective to that of a pair of cameras placed in one of two corners of the scanner room. To elicit the illusion of being physically located in this position, we delivered synchronous visuo-tactile stimulation in the form of an object moving toward the cameras coupled with touches applied to the participant’s chest. Asynchronous visuo-tactile stimulation did not induce the illusion and served as a control condition. We found that illusory self-location could be successfully decoded from patterns of activity in the hippocampus in all of the participants in the synchronous (P < 0.05) but not in the asynchronous condition (P > 0.05). At the group-level, the decoding accuracy was significantly higher in the synchronous than in the asynchronous condition (P = 0.012). These findings associate hippocampal activity with the perceived location of the bodily self in space, which suggests that the human hippocampus is involved not only in spatial navigation and memory but also in the construction of our sense of bodily self-location. PMID:26236222

Decoding the Semantic Content of Natural Movies from Human Brain Activity

PubMed Central

Huth, Alexander G.; Lee, Tyler; Nishimoto, Shinji; Bilenko, Natalia Y.; Vu, An T.; Gallant, Jack L.

2016-01-01

One crucial test for any quantitative model of the brain is to show that the model can be used to accurately decode information from evoked brain activity. Several recent neuroimaging studies have decoded the structure or semantic content of static visual images from human brain activity. Here we present a decoding algorithm that makes it possible to decode detailed information about the object and action categories present in natural movies from human brain activity signals measured by functional MRI. Decoding is accomplished using a hierarchical logistic regression (HLR) model that is based on labels that were manually assigned from the WordNet semantic taxonomy. This model makes it possible to simultaneously decode information about both specific and general categories, while respecting the relationships between them. Our results show that we can decode the presence of many object and action categories from averaged blood-oxygen level-dependent (BOLD) responses with a high degree of accuracy (area under the ROC curve > 0.9). Furthermore, we used this framework to test whether semantic relationships defined in the WordNet taxonomy are represented the same way in the human brain. This analysis showed that hierarchical relationships between general categories and atypical examples, such as organism and plant, did not seem to be reflected in representations measured by BOLD fMRI. PMID:27781035

Elegant grapheme-phoneme correspondence: a periodic chart and singularity generalization unify decoding.

PubMed

Gates, Louis

2018-04-01

The accompanying article introduces highly transparent grapheme-phoneme relationships embodied within a Periodic table of decoding cells, which arguably presents the quintessential transparent decoding elements. The study then folds these cells into one highly transparent but simply stated singularity generalization-this generalization unifies the decoding cells (97% transparency). Deeper, the periodic table and singularity generalization together highlight the connectivity of the periodic cells. Moreover, these interrelated cells, coupled with the singularity generalization, clarify teaching targets and enable efficient learning of the letter-sound code. This singularity generalization, in turn, serves as a model for creating unified but easily stated subordinate generalizations for any one of the transparent cells or groups of cells shown within the tables. The article then expands the periodic cells into two tables of teacher-ready sample word lists-one table includes sample words for the basic and phonogram vowel cells, and the other table embraces word samples for the transparent consonant cells. The paper concludes with suggestions for teaching the cellular transparency embedded within reoccurring isolated words and running text to promote decoding automaticity of the periodic cells.

Swept Impact Seismic Technique (SIST)

USGS Publications Warehouse

Park, C.B.; Miller, R.D.; Steeples, D.W.; Black, R.A.

1996-01-01

A coded seismic technique is developed that can result in a higher signal-to-noise ratio than a conventional single-pulse method does. The technique is cost-effective and time-efficient and therefore well suited for shallow-reflection surveys where high resolution and cost-effectiveness are critical. A low-power impact source transmits a few to several hundred high-frequency broad-band seismic pulses during several seconds of recording time according to a deterministic coding scheme. The coding scheme consists of a time-encoded impact sequence in which the rate of impact (cycles/s) changes linearly with time providing a broad range of impact rates. Impact times used during the decoding process are recorded on one channel of the seismograph. The coding concept combines the vibroseis swept-frequency and the Mini-Sosie random impact concepts. The swept-frequency concept greatly improves the suppression of correlation noise with much fewer impacts than normally used in the Mini-Sosie technique. The impact concept makes the technique simple and efficient in generating high-resolution seismic data especially in the presence of noise. The transfer function of the impact sequence simulates a low-cut filter with the cutoff frequency the same as the lowest impact rate. This property can be used to attenuate low-frequency ground-roll noise without using an analog low-cut filter or a spatial source (or receiver) array as is necessary with a conventional single-pulse method. Because of the discontinuous coding scheme, the decoding process is accomplished by a "shift-and-stacking" method that is much simpler and quicker than cross-correlation. The simplicity of the coding allows the mechanical design of the source to remain simple. Several different types of mechanical systems could be adapted to generate a linear impact sweep. In addition, the simplicity of the coding also allows the technique to be used with conventional acquisition systems, with only minor modifications.

Real-time classification of auditory sentences using evoked cortical activity in humans

NASA Astrophysics Data System (ADS)

Moses, David A.; Leonard, Matthew K.; Chang, Edward F.

2018-06-01

Objective. Recent research has characterized the anatomical and functional basis of speech perception in the human auditory cortex. These advances have made it possible to decode speech information from activity in brain regions like the superior temporal gyrus, but no published work has demonstrated this ability in real-time, which is necessary for neuroprosthetic brain-computer interfaces. Approach. Here, we introduce a real-time neural speech recognition (rtNSR) software package, which was used to classify spoken input from high-resolution electrocorticography signals in real-time. We tested the system with two human subjects implanted with electrode arrays over the lateral brain surface. Subjects listened to multiple repetitions of ten sentences, and rtNSR classified what was heard in real-time from neural activity patterns using direct sentence-level and HMM-based phoneme-level classification schemes. Main results. We observed single-trial sentence classification accuracies of 90% or higher for each subject with less than 7 minutes of training data, demonstrating the ability of rtNSR to use cortical recordings to perform accurate real-time speech decoding in a limited vocabulary setting. Significance. Further development and testing of the package with different speech paradigms could influence the design of future speech neuroprosthetic applications.

A hidden Markov model for decoding and the analysis of replay in spike trains.

PubMed

Box, Marc; Jones, Matt W; Whiteley, Nick

2016-12-01

We present a hidden Markov model that describes variation in an animal's position associated with varying levels of activity in action potential spike trains of individual place cell neurons. The model incorporates a coarse-graining of position, which we find to be a more parsimonious description of the system than other models. We use a sequential Monte Carlo algorithm for Bayesian inference of model parameters, including the state space dimension, and we explain how to estimate position from spike train observations (decoding). We obtain greater accuracy over other methods in the conditions of high temporal resolution and small neuronal sample size. We also present a novel, model-based approach to the study of replay: the expression of spike train activity related to behaviour during times of motionlessness or sleep, thought to be integral to the consolidation of long-term memories. We demonstrate how we can detect the time, information content and compression rate of replay events in simulated and real hippocampal data recorded from rats in two different environments, and verify the correlation between the times of detected replay events and of sharp wave/ripples in the local field potential.

A forward error correction technique using a high-speed, high-rate single chip codec

NASA Astrophysics Data System (ADS)

Boyd, R. W.; Hartman, W. F.; Jones, Robert E.

The authors describe an error-correction coding approach that allows operation in either burst or continuous modes at data rates of multiple hundreds of megabits per second. Bandspreading is low since the code rate is 7/8 or greater, which is consistent with high-rate link operation. The encoder, along with a hard-decision decoder, fits on a single application-specific integrated circuit (ASIC) chip. Soft-decision decoding is possible utilizing applique hardware in conjunction with the hard-decision decoder. Expected coding gain is a function of the application and is approximately 2.5 dB for hard-decision decoding at 10-5 bit-error rate with phase-shift-keying modulation and additive Gaussian white noise interference. The principal use envisioned for this technique is to achieve a modest amount of coding gain on high-data-rate, bandwidth-constrained channels. Data rates of up to 300 Mb/s can be accommodated by the codec chip. The major objective is burst-mode communications, where code words are composed of 32 n data bits followed by 32 overhead bits.

Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features.

PubMed

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-01-01

Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed objects can be predicted from brain activity during sleep using statistical decoders trained with stimulus-induced brain activity. However, it remains unclear whether and how visual image features associated with dreamed objects are represented in the brain. In this study, we used a deep neural network (DNN) model for object recognition as a proxy for hierarchical visual feature representation, and DNN features for dreamed objects were analyzed with brain decoding of fMRI data collected during dreaming. The decoders were first trained with stimulus-induced brain activity labeled with the feature values of the stimulus image from multiple DNN layers. The decoders were then used to decode DNN features from the dream fMRI data, and the decoded features were compared with the averaged features of each object category calculated from a large-scale image database. We found that the feature values decoded from the dream fMRI data positively correlated with those associated with dreamed object categories at mid- to high-level DNN layers. Using the decoded features, the dreamed object category could be identified at above-chance levels by matching them to the averaged features for candidate categories. The results suggest that dreaming recruits hierarchical visual feature representations associated with objects, which may support phenomenal aspects of dream experience.

Visual coding with a population of direction-selective neurons.

PubMed

Fiscella, Michele; Franke, Felix; Farrow, Karl; Müller, Jan; Roska, Botond; da Silveira, Rava Azeredo; Hierlemann, Andreas

2015-10-01

The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions. Copyright © 2015 the American Physiological Society.

Visual coding with a population of direction-selective neurons

PubMed Central

Farrow, Karl; Müller, Jan; Roska, Botond; Azeredo da Silveira, Rava; Hierlemann, Andreas

2015-01-01

The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions. PMID:26289471

Decoding 3-D Reach and Grasp Kinematics from High-Frequency Local Field Potentials in Primate Primary Motor Cortex

PubMed Central

Zhuang, Jun; Vargas-Irwin, Carlos; Donoghue, John P.

2011-01-01

Intracortical microelectrode array recordings generate a variety of neural signals with potential application as control signals in neural interface systems. Previous studies have focused on single and multiunit activity, as well as low frequency local field potentials (LFPs), but have not explored higher frequency (>200 Hz) LFPs. In addition, the potential to decode three dimensional (3-D) reach and grasp kinematics based on LFPs has not been demonstrated. Here, we use mutual information and decoding analyses to probe the information content about 3-D reaching and grasping of 7 different LFP frequency bands in the range of 0.3 Hz – 400 Hz. LFPs were recorded via 96-microelectrode arrays in primary motor cortex (M1) of two monkeys performing free reaching to grasp moving objects. Mutual information analyses revealed that higher frequency bands (e.g. 100 – 200 Hz and 200 – 400 Hz) carried the most information about the examined kinematics. Furthermore, Kalman filter decoding revealed that broadband high frequency LFPs, likely reflecting multiunit activity, provided the best decoding performance as well as substantial accuracy in reconstructing reach kinematics, grasp aperture and aperture velocity. These results indicate that LFPs, especially high frequency bands, could be useful signals for neural interfaces controlling 3-D reach and grasp kinematics. PMID:20403782

Cache-Oblivious parallel SIMD Viterbi decoding for sequence search in HMMER.

PubMed

Ferreira, Miguel; Roma, Nuno; Russo, Luis M S

2014-05-30

HMMER is a commonly used bioinformatics tool based on Hidden Markov Models (HMMs) to analyze and process biological sequences. One of its main homology engines is based on the Viterbi decoding algorithm, which was already highly parallelized and optimized using Farrar's striped processing pattern with Intel SSE2 instruction set extension. A new SIMD vectorization of the Viterbi decoding algorithm is proposed, based on an SSE2 inter-task parallelization approach similar to the DNA alignment algorithm proposed by Rognes. Besides this alternative vectorization scheme, the proposed implementation also introduces a new partitioning of the Markov model that allows a significantly more efficient exploitation of the cache locality. Such optimization, together with an improved loading of the emission scores, allows the achievement of a constant processing throughput, regardless of the innermost-cache size and of the dimension of the considered model. The proposed optimized vectorization of the Viterbi decoding algorithm was extensively evaluated and compared with the HMMER3 decoder to process DNA and protein datasets, proving to be a rather competitive alternative implementation. Being always faster than the already highly optimized ViterbiFilter implementation of HMMER3, the proposed Cache-Oblivious Parallel SIMD Viterbi (COPS) implementation provides a constant throughput and offers a processing speedup as high as two times faster, depending on the model's size.

DNA Base-Calling from a Nanopore Using a Viterbi Algorithm

PubMed Central

Timp, Winston; Comer, Jeffrey; Aksimentiev, Aleksei

2012-01-01

Nanopore-based DNA sequencing is the most promising third-generation sequencing method. It has superior read length, speed, and sample requirements compared with state-of-the-art second-generation methods. However, base-calling still presents substantial difficulty because the resolution of the technique is limited compared with the measured signal/noise ratio. Here we demonstrate a method to decode 3-bp-resolution nanopore electrical measurements into a DNA sequence using a Hidden Markov model. This method shows tremendous potential for accuracy (∼98%), even with a poor signal/noise ratio. PMID:22677395

Edge-Related Activity Is Not Necessary to Explain Orientation Decoding in Human Visual Cortex.

PubMed

Wardle, Susan G; Ritchie, J Brendan; Seymour, Kiley; Carlson, Thomas A

2017-02-01

Multivariate pattern analysis is a powerful technique; however, a significant theoretical limitation in neuroscience is the ambiguity in interpreting the source of decodable information used by classifiers. This is exemplified by the continued controversy over the source of orientation decoding from fMRI responses in human V1. Recently Carlson (2014) identified a potential source of decodable information by modeling voxel responses based on the Hubel and Wiesel (1972) ice-cube model of visual cortex. The model revealed that activity associated with the edges of gratings covaries with orientation and could potentially be used to discriminate orientation. Here we empirically evaluate whether "edge-related activity" underlies orientation decoding from patterns of BOLD response in human V1. First, we systematically mapped classifier performance as a function of stimulus location using population receptive field modeling to isolate each voxel's overlap with a large annular grating stimulus. Orientation was decodable across the stimulus; however, peak decoding performance occurred for voxels with receptive fields closer to the fovea and overlapping with the inner edge. Critically, we did not observe the expected second peak in decoding performance at the outer stimulus edge as predicted by the edge account. Second, we evaluated whether voxels that contribute most to classifier performance have receptive fields that cluster in cortical regions corresponding to the retinotopic location of the stimulus edge. Instead, we find the distribution of highly weighted voxels to be approximately random, with a modest bias toward more foveal voxels. Our results demonstrate that edge-related activity is likely not necessary for orientation decoding. A significant theoretical limitation of multivariate pattern analysis in neuroscience is the ambiguity in interpreting the source of decodable information used by classifiers. For example, orientation can be decoded from BOLD activation patterns in human V1, even though orientation columns are at a finer spatial scale than 3T fMRI. Consequently, the source of decodable information remains controversial. Here we test the proposal that information related to the stimulus edges underlies orientation decoding. We map voxel population receptive fields in V1 and evaluate orientation decoding performance as a function of stimulus location in retinotopic cortex. We find orientation is decodable from voxels whose receptive fields do not overlap with the stimulus edges, suggesting edge-related activity does not substantially drive orientation decoding. Copyright © 2017 the authors 0270-6474/17/371187-10$15.00/0.

Distinct neural patterns enable grasp types decoding in monkey dorsal premotor cortex

NASA Astrophysics Data System (ADS)

Hao, Yaoyao; Zhang, Qiaosheng; Controzzi, Marco; Cipriani, Christian; Li, Yue; Li, Juncheng; Zhang, Shaomin; Wang, Yiwen; Chen, Weidong; Chiara Carrozza, Maria; Zheng, Xiaoxiang

2014-12-01

Objective. Recent studies have shown that dorsal premotor cortex (PMd), a cortical area in the dorsomedial grasp pathway, is involved in grasp movements. However, the neural ensemble firing property of PMd during grasp movements and the extent to which it can be used for grasp decoding are still unclear. Approach. To address these issues, we used multielectrode arrays to record both spike and local field potential (LFP) signals in PMd in macaque monkeys performing reaching and grasping of one of four differently shaped objects. Main results. Single and population neuronal activity showed distinct patterns during execution of different grip types. Cluster analysis of neural ensemble signals indicated that the grasp related patterns emerged soon (200-300 ms) after the go cue signal, and faded away during the hold period. The timing and duration of the patterns varied depending on the behaviors of individual monkey. Application of support vector machine model to stable activity patterns revealed classification accuracies of 94% and 89% for each of the two monkeys, indicating a robust, decodable grasp pattern encoded in the PMd. Grasp decoding using LFPs, especially the high-frequency bands, also produced high decoding accuracies. Significance. This study is the first to specify the neuronal population encoding of grasp during the time course of grasp. We demonstrate high grasp decoding performance in PMd. These findings, combined with previous evidence for reach related modulation studies, suggest that PMd may play an important role in generation and maintenance of grasp action and may be a suitable locus for brain-machine interface applications.

Neuron selection based on deflection coefficient maximization for the neural decoding of dexterous finger movements.

PubMed

Kim, Yong-Hee; Thakor, Nitish V; Schieber, Marc H; Kim, Hyoung-Nam

2015-05-01

Future generations of brain-machine interface (BMI) will require more dexterous motion control such as hand and finger movements. Since a population of neurons in the primary motor cortex (M1) area is correlated with finger movements, neural activities recorded in M1 area are used to reconstruct an intended finger movement. In a BMI system, decoding discrete finger movements from a large number of input neurons does not guarantee a higher decoding accuracy in spite of the increase in computational burden. Hence, we hypothesize that selecting neurons important for coding dexterous flexion/extension of finger movements would improve the BMI performance. In this paper, two metrics are presented to quantitatively measure the importance of each neuron based on Bayes risk minimization and deflection coefficient maximization in a statistical decision problem. Since motor cortical neurons are active with movements of several different fingers, the proposed method is more suitable for a discrete decoding of flexion-extension finger movements than the previous methods for decoding reaching movements. In particular, the proposed metrics yielded high decoding accuracies across all subjects and also in the case of including six combined two-finger movements. While our data acquisition and analysis was done off-line and post processing, our results point to the significance of highly coding neurons in improving BMI performance.

Neuron Selection Based on Deflection Coefficient Maximization for the Neural Decoding of Dexterous Finger Movements

PubMed Central

Kim, Yong-Hee; Thakor, Nitish V.; Schieber, Marc H.; Kim, Hyoung-Nam

2015-01-01

Future generations of brain-machine interface (BMI) will require more dexterous motion control such as hand and finger movements. Since a population of neurons in the primary motor cortex (M1) area is correlated with finger movements, neural activities recorded in M1 area are used to reconstruct an intended finger movement. In a BMI system, decoding discrete finger movements from a large number of input neurons does not guarantee a higher decoding accuracy in spite of the increase in computational burden. Hence, we hypothesize that selecting neurons important for coding dexterous flexion/extension of finger movements would improve the BMI performance. In this paper, two metrics are presented to quantitatively measure the importance of each neuron based on Bayes risk minimization and deflection coefficient maximization in a statistical decision problem. Since motor cortical neurons are active with movements of several different fingers, the proposed method is more suitable for a discrete decoding of flexion-extension finger movements than the previous methods for decoding reaching movements. In particular, the proposed metrics yielded high decoding accuracies across all subjects and also in the case of including six combined two-finger movements. While our data acquisition and analysis was done off-line and post processing, our results point to the significance of highly coding neurons in improving BMI performance. PMID:25347884

Application of System Identification Methods for Decoding Imagined Single-Joint Movements in an Individual with High Tetraplegia

PubMed Central

Ajiboye, A. Bolu; Hochberg, Leigh R.; Donoghue, John P.; Kirsch, Robert F.

2013-01-01

This study investigated the decoding of imagined arm movements from M1 in an individual with high level tetraplegia. The participant was instructed to imagine herself performing a series of single-joint arm movements, aided by the visual cue of an animate character performing these movements. System identification was used offline to predict the trajectories of the imagined movements and compare these predictions to the trajectories of the actual movements. We report rates of 25 – 50% for predicting completely imagined arm movements in the absence of a priori movements to aid in decoder building. PMID:21096197

High bit rate convolutional channel encoder/decoder

NASA Technical Reports Server (NTRS)

1977-01-01

A detailed description of the design approach and tradeoffs encountered during the development of the 50 MBPS decoder system is presented. A functional analysis of each of the major logical functions is given, and the system's major components are listed.

Wave optics theory and 3-D deconvolution for the light field microscope

PubMed Central

Broxton, Michael; Grosenick, Logan; Yang, Samuel; Cohen, Noy; Andalman, Aaron; Deisseroth, Karl; Levoy, Marc

2013-01-01

Light field microscopy is a new technique for high-speed volumetric imaging of weakly scattering or fluorescent specimens. It employs an array of microlenses to trade off spatial resolution against angular resolution, thereby allowing a 4-D light field to be captured using a single photographic exposure without the need for scanning. The recorded light field can then be used to computationally reconstruct a full volume. In this paper, we present an optical model for light field microscopy based on wave optics, instead of previously reported ray optics models. We also present a 3-D deconvolution method for light field microscopy that is able to reconstruct volumes at higher spatial resolution, and with better optical sectioning, than previously reported. To accomplish this, we take advantage of the dense spatio-angular sampling provided by a microlens array at axial positions away from the native object plane. This dense sampling permits us to decode aliasing present in the light field to reconstruct high-frequency information. We formulate our method as an inverse problem for reconstructing the 3-D volume, which we solve using a GPU-accelerated iterative algorithm. Theoretical limits on the depth-dependent lateral resolution of the reconstructed volumes are derived. We show that these limits are in good agreement with experimental results on a standard USAF 1951 resolution target. Finally, we present 3-D reconstructions of pollen grains that demonstrate the improvements in fidelity made possible by our method. PMID:24150383

Representational dynamics of object recognition: Feedforward and feedback information flows.

PubMed

Goddard, Erin; Carlson, Thomas A; Dermody, Nadene; Woolgar, Alexandra

2016-03-01

Object perception involves a range of visual and cognitive processes, and is known to include both a feedfoward flow of information from early visual cortical areas to higher cortical areas, along with feedback from areas such as prefrontal cortex. Previous studies have found that low and high spatial frequency information regarding object identity may be processed over different timescales. Here we used the high temporal resolution of magnetoencephalography (MEG) combined with multivariate pattern analysis to measure information specifically related to object identity in peri-frontal and peri-occipital areas. Using stimuli closely matched in their low-level visual content, we found that activity in peri-occipital cortex could be used to decode object identity from ~80ms post stimulus onset, and activity in peri-frontal cortex could also be used to decode object identity from a later time (~265ms post stimulus onset). Low spatial frequency information related to object identity was present in the MEG signal at an earlier time than high spatial frequency information for peri-occipital cortex, but not for peri-frontal cortex. We additionally used Granger causality analysis to compare feedforward and feedback influences on representational content, and found evidence of both an early feedfoward flow and later feedback flow of information related to object identity. We discuss our findings in relation to existing theories of object processing and propose how the methods we use here could be used to address further questions of the neural substrates underlying object perception. Copyright © 2016 Elsevier Inc. All rights reserved.

Generic decoding of seen and imagined objects using hierarchical visual features.

PubMed

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-05-22

Object recognition is a key function in both human and machine vision. While brain decoding of seen and imagined objects has been achieved, the prediction is limited to training examples. We present a decoding approach for arbitrary objects using the machine vision principle that an object category is represented by a set of features rendered invariant through hierarchical processing. We show that visual features, including those derived from a deep convolutional neural network, can be predicted from fMRI patterns, and that greater accuracy is achieved for low-/high-level features with lower-/higher-level visual areas, respectively. Predicted features are used to identify seen/imagined object categories (extending beyond decoder training) from a set of computed features for numerous object images. Furthermore, decoding of imagined objects reveals progressive recruitment of higher-to-lower visual representations. Our results demonstrate a homology between human and machine vision and its utility for brain-based information retrieval.

Spatial resampling of IDR frames for low bitrate video coding with HEVC

NASA Astrophysics Data System (ADS)

Hosking, Brett; Agrafiotis, Dimitris; Bull, David; Easton, Nick

2015-03-01

As the demand for higher quality and higher resolution video increases, many applications fail to meet this demand due to low bandwidth restrictions. One factor contributing to this problem is the high bitrate requirement of the intra-coded Instantaneous Decoding Refresh (IDR) frames featuring in all video coding standards. Frequent coding of IDR frames is essential for error resilience in order to prevent the occurrence of error propagation. However, as each one consumes a huge portion of the available bitrate, the quality of future coded frames is hindered by high levels of compression. This work presents a new technique, known as Spatial Resampling of IDR Frames (SRIF), and shows how it can increase the rate distortion performance by providing a higher and more consistent level of video quality at low bitrates.

Prioritized LT Codes

NASA Technical Reports Server (NTRS)

Woo, Simon S.; Cheng, Michael K.

2011-01-01

The original Luby Transform (LT) coding scheme is extended to account for data transmissions where some information symbols in a message block are more important than others. Prioritized LT codes provide unequal error protection (UEP) of data on an erasure channel by modifying the original LT encoder. The prioritized algorithm improves high-priority data protection without penalizing low-priority data recovery. Moreover, low-latency decoding is also obtained for high-priority data due to fast encoding. Prioritized LT codes only require a slight change in the original encoding algorithm, and no changes at all at the decoder. Hence, with a small complexity increase in the LT encoder, an improved UEP and low-decoding latency performance for high-priority data can be achieved. LT encoding partitions a data stream into fixed-sized message blocks each with a constant number of information symbols. To generate a code symbol from the information symbols in a message, the Robust-Soliton probability distribution is first applied in order to determine the number of information symbols to be used to compute the code symbol. Then, the specific information symbols are chosen uniform randomly from the message block. Finally, the selected information symbols are XORed to form the code symbol. The Prioritized LT code construction includes an additional restriction that code symbols formed by a relatively small number of XORed information symbols select some of these information symbols from the pool of high-priority data. Once high-priority data are fully covered, encoding continues with the conventional LT approach where code symbols are generated by selecting information symbols from the entire message block including all different priorities. Therefore, if code symbols derived from high-priority data experience an unusual high number of erasures, Prioritized LT codes can still reliably recover both high- and low-priority data. This hybrid approach decides not only "how to encode" but also "what to encode" to achieve UEP. Another advantage of the priority encoding process is that the majority of high-priority data can be decoded sooner since only a small number of code symbols are required to reconstruct high-priority data. This approach increases the likelihood that high-priority data is decoded first over low-priority data. The Prioritized LT code scheme achieves an improvement in high-priority data decoding performance as well as overall information recovery without penalizing the decoding of low-priority data, assuming high-priority data is no more than half of a message block. The cost is in the additional complexity required in the encoder. If extra computation resource is available at the transmitter, image, voice, and video transmission quality in terrestrial and space communications can benefit from accurate use of redundancy in protecting data with varying priorities.

Real-Time fMRI Pattern Decoding and Neurofeedback Using FRIEND: An FSL-Integrated BCI Toolbox

PubMed Central

Sato, João R.; Basilio, Rodrigo; Paiva, Fernando F.; Garrido, Griselda J.; Bramati, Ivanei E.; Bado, Patricia; Tovar-Moll, Fernanda; Zahn, Roland; Moll, Jorge

2013-01-01

The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI)-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM), fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity) and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available. PMID:24312569

Robust pattern decoding in shape-coded structured light

NASA Astrophysics Data System (ADS)

Tang, Suming; Zhang, Xu; Song, Zhan; Song, Lifang; Zeng, Hai

2017-09-01

Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.

Continuous Force Decoding from Local Field Potentials of the Primary Motor Cortex in Freely Moving Rats.

PubMed

Khorasani, Abed; Heydari Beni, Nargess; Shalchyan, Vahid; Daliri, Mohammad Reza

2016-10-21

Local field potential (LFP) signals recorded by intracortical microelectrodes implanted in primary motor cortex can be used as a high informative input for decoding of motor functions. Recent studies show that different kinematic parameters such as position and velocity can be inferred from multiple LFP signals as precisely as spiking activities, however, continuous decoding of the force magnitude from the LFP signals in freely moving animals has remained an open problem. Here, we trained three rats to press a force sensor for getting a drop of water as a reward. A 16-channel micro-wire array was implanted in the primary motor cortex of each trained rat, and obtained LFP signals were used for decoding of the continuous values recorded by the force sensor. Average coefficient of correlation and the coefficient of determination between decoded and actual force signals were r = 0.66 and R 2  = 0.42, respectively. We found that LFP signal on gamma frequency bands (30-120 Hz) had the most contribution in the trained decoding model. This study suggests the feasibility of using low number of LFP channels for the continuous force decoding in freely moving animals resembling BMI systems in real life applications.

Optimizations of a Hardware Decoder for Deep-Space Optical Communications

NASA Technical Reports Server (NTRS)

Cheng, Michael K.; Nakashima, Michael A.; Moision, Bruce E.; Hamkins, Jon

2007-01-01

The National Aeronautics and Space Administration has developed a capacity approaching modulation and coding scheme that comprises a serial concatenation of an inner accumulate pulse-position modulation (PPM) and an outer convolutional code [or serially concatenated PPM (SCPPM)] for deep-space optical communications. Decoding of this code uses the turbo principle. However, due to the nonbinary property of SCPPM, a straightforward application of classical turbo decoding is very inefficient. Here, we present various optimizations applicable in hardware implementation of the SCPPM decoder. More specifically, we feature a Super Gamma computation to efficiently handle parallel trellis edges, a pipeline-friendly 'maxstar top-2' circuit that reduces the max-only approximation penalty, a low-latency cyclic redundancy check circuit for window-based decoders, and a high-speed algorithmic polynomial interleaver that leads to memory savings. Using the featured optimizations, we implement a 6.72 megabits-per-second (Mbps) SCPPM decoder on a single field-programmable gate array (FPGA). Compared to the current data rate of 256 kilobits per second from Mars, the SCPPM coded scheme represents a throughput increase of more than twenty-six fold. Extension to a 50-Mbps decoder on a board with multiple FPGAs follows naturally. We show through hardware simulations that the SCPPM coded system can operate within 1 dB of the Shannon capacity at nominal operating conditions.

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion

PubMed Central

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain–computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method. PMID:28558002

Cache-Oblivious parallel SIMD Viterbi decoding for sequence search in HMMER

PubMed Central

2014-01-01

Background HMMER is a commonly used bioinformatics tool based on Hidden Markov Models (HMMs) to analyze and process biological sequences. One of its main homology engines is based on the Viterbi decoding algorithm, which was already highly parallelized and optimized using Farrar’s striped processing pattern with Intel SSE2 instruction set extension. Results A new SIMD vectorization of the Viterbi decoding algorithm is proposed, based on an SSE2 inter-task parallelization approach similar to the DNA alignment algorithm proposed by Rognes. Besides this alternative vectorization scheme, the proposed implementation also introduces a new partitioning of the Markov model that allows a significantly more efficient exploitation of the cache locality. Such optimization, together with an improved loading of the emission scores, allows the achievement of a constant processing throughput, regardless of the innermost-cache size and of the dimension of the considered model. Conclusions The proposed optimized vectorization of the Viterbi decoding algorithm was extensively evaluated and compared with the HMMER3 decoder to process DNA and protein datasets, proving to be a rather competitive alternative implementation. Being always faster than the already highly optimized ViterbiFilter implementation of HMMER3, the proposed Cache-Oblivious Parallel SIMD Viterbi (COPS) implementation provides a constant throughput and offers a processing speedup as high as two times faster, depending on the model’s size. PMID:24884826

Error Control Coding Techniques for Space and Satellite Communications

NASA Technical Reports Server (NTRS)

Lin, Shu

2000-01-01

This paper presents a concatenated turbo coding system in which a Reed-Solomom outer code is concatenated with a binary turbo inner code. In the proposed system, the outer code decoder and the inner turbo code decoder interact to achieve both good bit error and frame error performances. The outer code decoder helps the inner turbo code decoder to terminate its decoding iteration while the inner turbo code decoder provides soft-output information to the outer code decoder to carry out a reliability-based soft-decision decoding. In the case that the outer code decoding fails, the outer code decoder instructs the inner code decoder to continue its decoding iterations until the outer code decoding is successful or a preset maximum number of decoding iterations is reached. This interaction between outer and inner code decoders reduces decoding delay. Also presented in the paper are an effective criterion for stopping the iteration process of the inner code decoder and a new reliability-based decoding algorithm for nonbinary codes.

An Interactive Concatenated Turbo Coding System

NASA Technical Reports Server (NTRS)

Liu, Ye; Tang, Heng; Lin, Shu; Fossorier, Marc

1999-01-01

This paper presents a concatenated turbo coding system in which a Reed-Solomon outer code is concatenated with a binary turbo inner code. In the proposed system, the outer code decoder and the inner turbo code decoder interact to achieve both good bit error and frame error performances. The outer code decoder helps the inner turbo code decoder to terminate its decoding iteration while the inner turbo code decoder provides soft-output information to the outer code decoder to carry out a reliability-based soft- decision decoding. In the case that the outer code decoding fails, the outer code decoder instructs the inner code decoder to continue its decoding iterations until the outer code decoding is successful or a preset maximum number of decoding iterations is reached. This interaction between outer and inner code decoders reduces decoding delay. Also presented in the paper are an effective criterion for stopping the iteration process of the inner code decoder and a new reliability-based decoding algorithm for nonbinary codes.

A reduced complexity highly power/bandwidth efficient coded FQPSK system with iterative decoding

NASA Technical Reports Server (NTRS)

Simon, M. K.; Divsalar, D.

2001-01-01

Based on a representation of FQPSK as a trellis-coded modulation, this paper investigates the potential improvement in power efficiency obtained from the application of simple outer codes to form a concatenated coding arrangement with iterative decoding.

General Purpose Graphics Processing Unit Based High-Rate Rice Decompression and Reed-Solomon Decoding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loughry, Thomas A.

As the volume of data acquired by space-based sensors increases, mission data compression/decompression and forward error correction code processing performance must likewise scale. This competency development effort was explored using the General Purpose Graphics Processing Unit (GPGPU) to accomplish high-rate Rice Decompression and high-rate Reed-Solomon (RS) decoding at the satellite mission ground station. Each algorithm was implemented and benchmarked on a single GPGPU. Distributed processing across one to four GPGPUs was also investigated. The results show that the GPGPU has considerable potential for performing satellite communication Data Signal Processing, with three times or better performance improvements and up to tenmore » times reduction in cost over custom hardware, at least in the case of Rice Decompression and Reed-Solomon Decoding.« less

Architecture and implementation considerations of a high-speed Viterbi decoder for a Reed-Muller subcode

NASA Technical Reports Server (NTRS)

Lin, Shu (Principal Investigator); Uehara, Gregory T.; Nakamura, Eric; Chu, Cecilia W. P.

1996-01-01

The (64, 40, 8) subcode of the third-order Reed-Muller (RM) code for high-speed satellite communications is proposed. The RM subcode can be used either alone or as an inner code of a concatenated coding system with the NASA standard (255, 233, 33) Reed-Solomon (RS) code as the outer code to achieve high performance (or low bit-error rate) with reduced decoding complexity. It can also be used as a component code in a multilevel bandwidth efficient coded modulation system to achieve reliable bandwidth efficient data transmission. The progress made toward achieving the goal of implementing a decoder system based upon this code is summarized. The development of the integrated circuit prototype sub-trellis IC, particularly focusing on the design methodology, is addressed.

Three-dimensional high-resolution second-harmonic generation imaging of endogenous structural proteins in biological tissues.

PubMed Central

Campagnola, Paul J; Millard, Andrew C; Terasaki, Mark; Hoppe, Pamela E; Malone, Christian J; Mohler, William A

2002-01-01

We find that several key endogenous protein structures give rise to intense second-harmonic generation (SHG)-nonabsorptive frequency doubling of an excitation laser line. Second-harmonic imaging microscopy (SHIM) on a laser-scanning system proves, therefore, to be a powerful and unique tool for high-resolution, high-contrast, three-dimensional studies of live cell and tissue architecture. Unlike fluorescence, SHG suffers no inherent photobleaching or toxicity and does not require exogenous labels. Unlike polarization microscopy, SHIM provides intrinsic confocality and deep sectioning in complex tissues. In this study, we demonstrate the clarity of SHIM optical sectioning within unfixed, unstained thick specimens. SHIM and two-photon excited fluorescence (TPEF) were combined in a dual-mode nonlinear microscopy to elucidate the molecular sources of SHG in live cells and tissues. SHG arose not only from coiled-coil complexes within connective tissues and muscle thick filaments, but also from microtubule arrays within interphase and mitotic cells. Both polarization dependence and a local symmetry cancellation effect of SHG allowed the signal from species generating the second harmonic to be decoded, by ratiometric correlation with TPEF, to yield information on local structure below optical resolution. The physical origin of SHG within these tissues is addressed and is attributed to the laser interaction with dipolar protein structures that is enhanced by the intrinsic chirality of the protein helices. PMID:11751336

Fast decoding techniques for extended single-and-double-error-correcting Reed Solomon codes

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.; Deng, H.; Lin, S.

1984-01-01

A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. For example, some 256K-bit dynamic random access memories are organized as 32K x 8 bit-bytes. Byte-oriented codes such as Reed Solomon (RS) codes provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. Some special high speed decoding techniques for extended single and double error correcting RS codes. These techniques are designed to find the error locations and the error values directly from the syndrome without having to form the error locator polynomial and solve for its roots.

Integrated Performance of Next Generation High Data Rate Receiver and AR4JA LDPC Codec for Space Communications

NASA Technical Reports Server (NTRS)

Cheng, Michael K.; Lyubarev, Mark; Nakashima, Michael A.; Andrews, Kenneth S.; Lee, Dennis

2008-01-01

Low-density parity-check (LDPC) codes are the state-of-the-art in forward error correction (FEC) technology that exhibits capacity approaching performance. The Jet Propulsion Laboratory (JPL) has designed a family of LDPC codes that are similar in structure and therefore, leads to a single decoder implementation. The Accumulate-Repeat-by-4-Jagged- Accumulate (AR4JA) code design offers a family of codes with rates 1/2, 2/3, 4/5 and lengths 1024, 4096, 16384 information bits. Performance is less than one dB from capacity for all combinations.Integrating a stand-alone LDPC decoder with a commercial-off-the-shelf (COTS) receiver faces additional challenges than building a single receiver-decoder unit from scratch. In this work, we outline the issues and show that these additional challenges can be over-come by simple solutions. To demonstrate that an LDPC decoder can be made to work seamlessly with a COTS receiver, we interface an AR4JA LDPC decoder developed on a field-programmable gate array (FPGA) with a modern high data rate receiver and mea- sure the combined receiver-decoder performance. Through optimizations that include an improved frame synchronizer and different soft-symbol scaling algorithms, we show that a combined implementation loss of less than one dB is possible and therefore, most of the coding gain evidence in theory can also be obtained in practice. Our techniques can benefit any modem that utilizes an advanced FEC code.

Optical control system for high-voltage terminals

DOEpatents

Bicek, John J.

1978-01-01

An optical control system for the control of devices in the terminal of an electrostatic accelerator includes a laser that is modulated by a series of preselected codes produced by an encoder. A photodiode receiver is placed in the laser beam at the high-voltage terminal of an electrostatic accelerator. A decoder connected to the photodiode decodes the signals to provide control impulses for a plurality of devices at the high voltage of the terminal.

Circuit Design Approaches for Implementation of a Subtrellis IC for a Reed-Muller Subcode

NASA Technical Reports Server (NTRS)

Lin, Shu; Uehara, Gregory T.; Nakamura, Eric B.; Chu, Cecilia W. P.

1996-01-01

In his research, we have proposed the (64, 40, 8) subcode of the third-order Reed-Muller (RM) code to NASA for high-speed satellite communications. This RM subcode can be used either alone or as an inner code of a concatenated coding system with the NASA standard (255, 233, 33) Reed-Solomon (RS) code as the outer code to achieve high performance (or low bit-error rate) with reduced decoding complexity. It can also be used as a component code in a multilevel bandwidth efficient coded modulation system to achieve reliable bandwidth efficient data transmission. This report will summarize the key progress we have made toward achieving our eventual goal of implementing a decoder system based upon this code. In the first phase of study, we investigated the complexities of various sectionalized trellis diagrams for the proposed (64, 40, 8) RM subcode. We found a specific 8-trellis diagram for this code which requires the least decoding complexity with a high possibility of achieving a decoding speed of 600 M bits per second(Mbps). The combination of a large number of states and a high data rate will be made possible due to the utilization of a high degree of parallelism throughout the architecture. This trellis diagram will be presented and briefly described. In the second phase of study which was carried out through the past year, we investigated circuit architectures to determine the feasibility of VLSI implementation of a high- speed Viterbi decoder based on this 8-section trellis diagram. We began to examine specific design and implementation approaches to implement a fully custom integrated circuit (IC) which will be a key building block for a decoder system implementation. The key results will be presented in this report. This report will be divided into three primary sections. First, we will briefly describe the system block diagram in which the proposed decoder is assumed to be operating and present some of the key architectural approaches being used to implement the system at high speed. Second, we will describe details of the 8-trellis diagram we found to best meet the trade-offs between chip and overall system complexity. The chosen approach implements the trellis for the (64, 40, 8) RM subcode with 32 independent sub-trellises. And third, we will describe results of our feasibility study on the implementation of such an IC chip in CMOS technology to implement one of these subtrellises.

Circuit Design Approaches for Implementation of a Subtrellis IC for a Reed-Muller Subcode

NASA Technical Reports Server (NTRS)

Lin, Shu; Uehara, Gregory T.; Nakamura, Eric B.; Chu, Cecilia W. P.

1996-01-01

In this research, we have proposed the (64, 40, 8) subcode of the third-order Reed-Muller (RM) code to NASA for high-speed satellite communications. This RM subcode can be used either alone or as an inner code of a concatenated coding system with the NASA standard (255, 233, 33) Reed-Solomon (RS) code as the outer code to achieve high performance (or low bit-error rate) with reduced decoding complexity. It can also be used as a component code in a multilevel bandwidth efficient coded modulation system to achieve reliable bandwidth efficient data transmission. This report will summarize the key progress we have made toward achieving our eventual goal of implementing a decoder system based upon this code. In the first phase of study, we investigated the complexities of various sectionalized trellis diagrams for the proposed (64, 40, 8) RM subcode. We found a specific 8-trellis diagram for this code which requires the least decoding complexity with a high possibility of achieving a decoding speed of 600 M bits per second (Mbps). The combination of a large number of states and a high data rate will be made possible due to the utilization of a high degree of parallelism throughout the architecture. This trellis diagram will be presented and briefly described. In the second phase of study which was carried out through the past year, we investigated circuit architectures to determine the feasibility of VLSI implementation of a high-speed Viterbi decoder based on this 8-section trellis diagram. We began to examine specific design and implementation approaches to implement a fully custom integrated circuit (IC) which will be a key building block for a decoder system implementation. The key results will be presented in this report. This report will be divided into three primary sections. First, we will briefly describe the system block diagram in which the proposed decoder is assumed to be operating and present some of the key architectural approaches being used to implement the system at high speed. Second, we will describe details of the 8-trellis diagram we found to best meet the trade-offs between chip and overall system complexity. The chosen approach implements the trellis for the (64, 40, 8) RM subcode with 32 independent sub-trellises. And third, we will describe results of our feasibility study on the implementation of such an IC chip in CMOS technology to implement one of these subtrellises.

DNA base-calling from a nanopore using a Viterbi algorithm.

PubMed

Timp, Winston; Comer, Jeffrey; Aksimentiev, Aleksei

2012-05-16

Nanopore-based DNA sequencing is the most promising third-generation sequencing method. It has superior read length, speed, and sample requirements compared with state-of-the-art second-generation methods. However, base-calling still presents substantial difficulty because the resolution of the technique is limited compared with the measured signal/noise ratio. Here we demonstrate a method to decode 3-bp-resolution nanopore electrical measurements into a DNA sequence using a Hidden Markov model. This method shows tremendous potential for accuracy (~98%), even with a poor signal/noise ratio. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Parallel processing architecture for H.264 deblocking filter on multi-core platforms

NASA Astrophysics Data System (ADS)

Prasad, Durga P.; Sonachalam, Sekar; Kunchamwar, Mangesh K.; Gunupudi, Nageswara Rao

2012-03-01

Massively parallel computing (multi-core) chips offer outstanding new solutions that satisfy the increasing demand for high resolution and high quality video compression technologies such as H.264. Such solutions not only provide exceptional quality but also efficiency, low power, and low latency, previously unattainable in software based designs. While custom hardware and Application Specific Integrated Circuit (ASIC) technologies may achieve lowlatency, low power, and real-time performance in some consumer devices, many applications require a flexible and scalable software-defined solution. The deblocking filter in H.264 encoder/decoder poses difficult implementation challenges because of heavy data dependencies and the conditional nature of the computations. Deblocking filter implementations tend to be fixed and difficult to reconfigure for different needs. The ability to scale up for higher quality requirements such as 10-bit pixel depth or a 4:2:2 chroma format often reduces the throughput of a parallel architecture designed for lower feature set. A scalable architecture for deblocking filtering, created with a massively parallel processor based solution, means that the same encoder or decoder will be deployed in a variety of applications, at different video resolutions, for different power requirements, and at higher bit-depths and better color sub sampling patterns like YUV, 4:2:2, or 4:4:4 formats. Low power, software-defined encoders/decoders may be implemented using a massively parallel processor array, like that found in HyperX technology, with 100 or more cores and distributed memory. The large number of processor elements allows the silicon device to operate more efficiently than conventional DSP or CPU technology. This software programing model for massively parallel processors offers a flexible implementation and a power efficiency close to that of ASIC solutions. This work describes a scalable parallel architecture for an H.264 compliant deblocking filter for multi core platforms such as HyperX technology. Parallel techniques such as parallel processing of independent macroblocks, sub blocks, and pixel row level are examined in this work. The deblocking architecture consists of a basic cell called deblocking filter unit (DFU) and dependent data buffer manager (DFM). The DFU can be used in several instances, catering to different performance needs the DFM serves the data required for the different number of DFUs, and also manages all the neighboring data required for future data processing of DFUs. This approach achieves the scalability, flexibility, and performance excellence required in deblocking filters.

Clusterless Decoding of Position From Multiunit Activity Using A Marked Point Process Filter

PubMed Central

Deng, Xinyi; Liu, Daniel F.; Kay, Kenneth; Frank, Loren M.; Eden, Uri T.

2016-01-01

Point process filters have been applied successfully to decode neural signals and track neural dynamics. Traditionally, these methods assume that multiunit spiking activity has already been correctly spike-sorted. As a result, these methods are not appropriate for situations where sorting cannot be performed with high precision such as real-time decoding for brain-computer interfaces. As the unsupervised spike-sorting problem remains unsolved, we took an alternative approach that takes advantage of recent insights about clusterless decoding. Here we present a new point process decoding algorithm that does not require multiunit signals to be sorted into individual units. We use the theory of marked point processes to construct a function that characterizes the relationship between a covariate of interest (in this case, the location of a rat on a track) and features of the spike waveforms. In our example, we use tetrode recordings, and the marks represent a four-dimensional vector of the maximum amplitudes of the spike waveform on each of the four electrodes. In general, the marks may represent any features of the spike waveform. We then use Bayes’ rule to estimate spatial location from hippocampal neural activity. We validate our approach with a simulation study and with experimental data recorded in the hippocampus of a rat moving through a linear environment. Our decoding algorithm accurately reconstructs the rat’s position from unsorted multiunit spiking activity. We then compare the quality of our decoding algorithm to that of a traditional spike-sorting and decoding algorithm. Our analyses show that the proposed decoding algorithm performs equivalently or better than algorithms based on sorted single-unit activity. These results provide a path toward accurate real-time decoding of spiking patterns that could be used to carry out content-specific manipulations of population activity in hippocampus or elsewhere in the brain. PMID:25973549

Real-Time Reed-Solomon Decoder

NASA Technical Reports Server (NTRS)

Maki, Gary K.; Cameron, Kelly B.; Owsley, Patrick A.

1994-01-01

Generic Reed-Solomon decoder fast enough to correct errors in real time in practical applications designed to be implemented in fewer and smaller very-large-scale integrated, VLSI, circuit chips. Configured to operate in pipelined manner. One outstanding aspect of decoder design is that Euclid multiplier and divider modules contain Galoisfield multipliers configured as combinational-logic cells. Operates at speeds greater than older multipliers. Cellular configuration highly regular and requires little interconnection area, making it ideal for implementation in extraordinarily dense VLSI circuitry. Flight electronics single chip version of this technology implemented and available.

A four-dimensional virtual hand brain-machine interface using active dimension selection.

PubMed

Rouse, Adam G

2016-06-01

Brain-machine interfaces (BMI) traditionally rely on a fixed, linear transformation from neural signals to an output state-space. In this study, the assumption that a BMI must control a fixed, orthogonal basis set was challenged and a novel active dimension selection (ADS) decoder was explored. ADS utilizes a two stage decoder by using neural signals to both (i) select an active dimension being controlled and (ii) control the velocity along the selected dimension. ADS decoding was tested in a monkey using 16 single units from premotor and primary motor cortex to successfully control a virtual hand avatar to move to eight different postures. Following training with the ADS decoder to control 2, 3, and then 4 dimensions, each emulating a grasp shape of the hand, performance reached 93% correct with a bit rate of 2.4 bits s(-1) for eight targets. Selection of eight targets using ADS control was more efficient, as measured by bit rate, than either full four-dimensional control or computer assisted one-dimensional control. ADS decoding allows a user to quickly and efficiently select different hand postures. This novel decoding scheme represents a potential method to reduce the complexity of high-dimension BMI control of the hand.

Decoding DNA labels by melting curve analysis using real-time PCR.

PubMed

Balog, József A; Fehér, Liliána Z; Puskás, László G

2017-12-01

Synthetic DNA has been used as an authentication code for a diverse number of applications. However, existing decoding approaches are based on either DNA sequencing or the determination of DNA length variations. Here, we present a simple alternative protocol for labeling different objects using a small number of short DNA sequences that differ in their melting points. Code amplification and decoding can be done in two steps using quantitative PCR (qPCR). To obtain a DNA barcode with high complexity, we defined 8 template groups, each having 4 different DNA templates, yielding 158 (>2.5 billion) combinations of different individual melting temperature (Tm) values and corresponding ID codes. The reproducibility and specificity of the decoding was confirmed by using the most complex template mixture, which had 32 different products in 8 groups with different Tm values. The industrial applicability of our protocol was also demonstrated by labeling a drone with an oil-based paint containing a predefined DNA code, which was then successfully decoded. The method presented here consists of a simple code system based on a small number of synthetic DNA sequences and a cost-effective, rapid decoding protocol using a few qPCR reactions, enabling a wide range of authentication applications.

Bit Error Probability for Maximum Likelihood Decoding of Linear Block Codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc P. C.; Rhee, Dojun

1996-01-01

In this paper, the bit error probability P(sub b) for maximum likelihood decoding of binary linear codes is investigated. The contribution of each information bit to P(sub b) is considered. For randomly generated codes, it is shown that the conventional approximation at high SNR P(sub b) is approximately equal to (d(sub H)/N)P(sub s), where P(sub s) represents the block error probability, holds for systematic encoding only. Also systematic encoding provides the minimum P(sub b) when the inverse mapping corresponding to the generator matrix of the code is used to retrieve the information sequence. The bit error performances corresponding to other generator matrix forms are also evaluated. Although derived for codes with a generator matrix randomly generated, these results are shown to provide good approximations for codes used in practice. Finally, for decoding methods which require a generator matrix with a particular structure such as trellis decoding or algebraic-based soft decision decoding, equivalent schemes that reduce the bit error probability are discussed.

The decoding of Reed-Solomon codes

NASA Technical Reports Server (NTRS)

Mceliece, R. J.

1988-01-01

Reed-Solomon (RS) codes form an important part of the high-rate downlink telemetry system for the Magellan mission, and the RS decoding function for this project will be done by DSN. Although the basic idea behind all Reed-Solomon decoding algorithms was developed by Berlekamp in 1968, there are dozens of variants of Berlekamp's algorithm in current use. An attempt to restore order is made by presenting a mathematical theory which explains the working of almost all known RS decoding algorithms. The key innovation that makes this possible is the unified approach to the solution of the key equation, which simultaneously describes the Berlekamp, Berlekamp-Massey, Euclid, and continued fractions approaches. Additionally, a detailed analysis is made of what can happen to a generic RS decoding algorithm when the number of errors and erasures exceeds the code's designed correction capability, and it is shown that while most published algorithms do not detect as many of these error-erasure patterns as possible, by making a small change in the algorithms, this problem can be overcome.

PSEUDO-CODEWORD LANDSCAPE

DOE Office of Scientific and Technical Information (OSTI.GOV)

CHERTKOV, MICHAEL; STEPANOV, MIKHAIL

2007-01-10

The authors discuss performance of Low-Density-Parity-Check (LDPC) codes decoded by Linear Programming (LP) decoding at moderate and large Signal-to-Noise-Ratios (SNR). Frame-Error-Rate (FER) dependence on SNR and the noise space landscape of the coding/decoding scheme are analyzed by a combination of the previously introduced instanton/pseudo-codeword-search method and a new 'dendro' trick. To reduce complexity of the LP decoding for a code with high-degree checks, {ge} 5, they introduce its dendro-LDPC counterpart, that is the code performing identifically to the original one under Maximum-A-Posteriori (MAP) decoding but having reduced (down to three) check connectivity degree. Analyzing number of popular LDPC codes andmore » their dendro versions performing over the Additive-White-Gaussian-Noise (AWGN) channel, they observed two qualitatively different regimes: (i) error-floor sets early, at relatively low SNR, and (ii) FER decays with SNR increase faster at moderate SNR than at the largest SNR. They explain these regimes in terms of the pseudo-codeword spectra of the codes.« less

Spiking Neural Network Decoder for Brain-Machine Interfaces.

PubMed

Dethier, Julie; Gilja, Vikash; Nuyujukian, Paul; Elassaad, Shauki A; Shenoy, Krishna V; Boahen, Kwabena

2011-01-01

We used a spiking neural network (SNN) to decode neural data recorded from a 96-electrode array in premotor/motor cortex while a rhesus monkey performed a point-to-point reaching arm movement task. We mapped a Kalman-filter neural prosthetic decode algorithm developed to predict the arm's velocity on to the SNN using the Neural Engineering Framework and simulated it using Nengo , a freely available software package. A 20,000-neuron network matched the standard decoder's prediction to within 0.03% (normalized by maximum arm velocity). A 1,600-neuron version of this network was within 0.27%, and run in real-time on a 3GHz PC. These results demonstrate that a SNN can implement a statistical signal processing algorithm widely used as the decoder in high-performance neural prostheses (Kalman filter), and achieve similar results with just a few thousand neurons. Hardware SNN implementations-neuromorphic chips-may offer power savings, essential for realizing fully-implantable cortically controlled prostheses.

Cortical Decoding of Individual Finger and Wrist Kinematics for an Upper-Limb Neuroprosthesis

PubMed Central

Aggarwal, Vikram; Tenore, Francesco; Acharya, Soumyadipta; Schieber, Marc H.; Thakor, Nitish V.

2010-01-01

Previous research has shown that neuronal activity can be used to continuously decode the kinematics of gross movements involving arm and hand trajectory. However, decoding the kinematics of fine motor movements, such as the manipulation of individual fingers, has not been demonstrated. In this study, single unit activities were recorded from task-related neurons in M1 of two trained rhesus monkey as they performed individuated movements of the fingers and wrist. The primates’ hand was placed in a manipulandum, and strain gauges at the tips of each finger were used to track the digit’s position. Both linear and non-linear filters were designed to simultaneously predict kinematics of each digit and the wrist, and their performance compared using mean squared error and correlation coefficients. All models had high decoding accuracy, but the feedforward ANN (R=0.76–0.86, MSE=0.04–0.05) and Kalman filter (R=0.68–0.86, MSE=0.04–0.07) performed better than a simple linear regression filter (0.58–0.81, 0.05–0.07). These results suggest that individual finger and wrist kinematics can be decoded with high accuracy, and be used to control a multi-fingered prosthetic hand in real-time. PMID:19964645

Revealing hidden states in visual working memory using electroencephalography

PubMed Central

Wolff, Michael J.; Ding, Jacqueline; Myers, Nicholas E.; Stokes, Mark G.

2015-01-01

It is often assumed that information in visual working memory (vWM) is maintained via persistent activity. However, recent evidence indicates that information in vWM could be maintained in an effectively “activity-silent” neural state. Silent vWM is consistent with recent cognitive and neural models, but poses an important experimental problem: how can we study these silent states using conventional measures of brain activity? We propose a novel approach that is analogous to echolocation: using a high-contrast visual stimulus, it may be possible to drive brain activity during vWM maintenance and measure the vWM-dependent impulse response. We recorded electroencephalography (EEG) while participants performed a vWM task in which a randomly oriented grating was remembered. Crucially, a high-contrast, task-irrelevant stimulus was shown in the maintenance period in half of the trials. The electrophysiological response from posterior channels was used to decode the orientations of the gratings. While orientations could be decoded during and shortly after stimulus presentation, decoding accuracy dropped back close to baseline in the delay. However, the visual evoked response from the task-irrelevant stimulus resulted in a clear re-emergence in decodability. This result provides important proof-of-concept for a promising and relatively simple approach to decode “activity-silent” vWM content using non-invasive EEG. PMID:26388748

Structural and functional connectivity of the subthalamic nucleus during vocal emotion decoding

PubMed Central

Frühholz, Sascha; Ceravolo, Leonardo; Grandjean, Didier

2016-01-01

Our understanding of the role played by the subthalamic nucleus (STN) in human emotion has recently advanced with STN deep brain stimulation, a neurosurgical treatment for Parkinson’s disease and obsessive-compulsive disorder. However, the potential presence of several confounds related to pathological models raises the question of how much they affect the relevance of observations regarding the physiological function of the STN itself. This underscores the crucial importance of obtaining evidence from healthy participants. In this study, we tested the structural and functional connectivity between the STN and other brain regions related to vocal emotion in a healthy population by combining diffusion tensor imaging and psychophysiological interaction analysis from a high-resolution functional magnetic resonance imaging study. As expected, we showed that the STN is functionally connected to the structures involved in emotional prosody decoding, notably the orbitofrontal cortex, inferior frontal gyrus, auditory cortex, pallidum and amygdala. These functional results were corroborated by probabilistic fiber tracking, which revealed that the left STN is structurally connected to the amygdala and the orbitofrontal cortex. These results confirm, in healthy participants, the role played by the STN in human emotion and its structural and functional connectivity with the brain network involved in vocal emotions. PMID:26400857

Single-Cell in Situ RNA Analysis With Switchable Fluorescent Oligonucleotides.

PubMed

Xiao, Lu; Guo, Jia

2018-01-01

Comprehensive RNA analyses in individual cells in their native spatial contexts promise to transform our understanding of normal physiology and disease pathogenesis. Here we report a single-cell in situ RNA analysis approach using switchable fluorescent oligonucleotides (SFO). In this method, transcripts are first hybridized by pre-decoding oligonucleotides. These oligonucleotides subsequently recruit SFO to stain their corresponding RNA targets. After fluorescence imaging, all the SFO in the whole specimen are simultaneously removed by DNA strand displacement reactions. Through continuous cycles of target staining, fluorescence imaging, and SFO removal, a large number of different transcripts can be identified by unique fluorophore sequences and visualized at the optical resolution. To demonstrate the feasibility of this approach, we show that the hybridized SFO can be efficiently stripped by strand displacement reactions within 30 min. We also demonstrate that this SFO removal process maintains the integrity of the RNA targets and the pre-decoding oligonucleotides, and keeps them hybridized. Applying this approach, we show that transcripts can be restained in at least eight hybridization cycles with high analysis accuracy, which theoretically would enable the whole transcriptome to be quantified at the single molecule sensitivity in individual cells. This in situ RNA analysis technology will have wide applications in systems biology, molecular diagnosis, and targeted therapies.

A model for the study of ligand binding to the ribosomal RNA helix h44

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dibrov, Sergey M.; Parsons, Jerod; Hermann, Thomas

2010-09-02

Oligonucleotide models of ribosomal RNA domains are powerful tools to study the binding and molecular recognition of antibiotics that interfere with bacterial translation. Techniques such as selective chemical modification, fluorescence labeling and mutations are cumbersome for the whole ribosome but readily applicable to model RNAs, which are readily crystallized and often give rise to higher resolution crystal structures suitable for detailed analysis of ligand-RNA interactions. Here, we have investigated the HX RNA construct which contains two adjacent ligand binding regions of helix h44 in 16S ribosomal RNA. High-resolution crystal structure analysis confirmed that the HX RNA is a faithful structuralmore » model of the ribosomal target. Solution studies showed that HX RNA carrying a fluorescent 2-aminopurine modification provides a model system that can be used to monitor ligand binding to both the ribosomal decoding site and, through an indirect effect, the hygromycin B interaction region.« less

A Synchronization Algorithm and Implementation for High-Speed Block Codes Applications. Part 4

NASA Technical Reports Server (NTRS)

Lin, Shu; Zhang, Yu; Nakamura, Eric B.; Uehara, Gregory T.

1998-01-01

Block codes have trellis structures and decoders amenable to high speed CMOS VLSI implementation. For a given CMOS technology, these structures enable operating speeds higher than those achievable using convolutional codes for only modest reductions in coding gain. As a result, block codes have tremendous potential for satellite trunk and other future high-speed communication applications. This paper describes a new approach for implementation of the synchronization function for block codes. The approach utilizes the output of the Viterbi decoder and therefore employs the strength of the decoder. Its operation requires no knowledge of the signal-to-noise ratio of the received signal, has a simple implementation, adds no overhead to the transmitted data, and has been shown to be effective in simulation for received SNR greater than 2 dB.

Hamming and Accumulator Codes Concatenated with MPSK or QAM

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Dolinar, Samuel

2009-01-01

In a proposed coding-and-modulation scheme, a high-rate binary data stream would be processed as follows: 1. The input bit stream would be demultiplexed into multiple bit streams. 2. The multiple bit streams would be processed simultaneously into a high-rate outer Hamming code that would comprise multiple short constituent Hamming codes a distinct constituent Hamming code for each stream. 3. The streams would be interleaved. The interleaver would have a block structure that would facilitate parallelization for high-speed decoding. 4. The interleaved streams would be further processed simultaneously into an inner two-state, rate-1 accumulator code that would comprise multiple constituent accumulator codes - a distinct accumulator code for each stream. 5. The resulting bit streams would be mapped into symbols to be transmitted by use of a higher-order modulation - for example, M-ary phase-shift keying (MPSK) or quadrature amplitude modulation (QAM). The novelty of the scheme lies in the concatenation of the multiple-constituent Hamming and accumulator codes and the corresponding parallel architectures of the encoder and decoder circuitry (see figure) needed to process the multiple bit streams simultaneously. As in the cases of other parallel-processing schemes, one advantage of this scheme is that the overall data rate could be much greater than the data rate of each encoder and decoder stream and, hence, the encoder and decoder could handle data at an overall rate beyond the capability of the individual encoder and decoder circuits.

FEC decoder design optimization for mobile satellite communications

NASA Technical Reports Server (NTRS)

Roy, Ashim; Lewi, Leng

1990-01-01

A new telecommunications service for location determination via satellite is being proposed for the continental USA and Europe, which provides users with the capability to find the location of, and communicate from, a moving vehicle to a central hub and vice versa. This communications system is expected to operate in an extremely noisy channel in the presence of fading. In order to achieve high levels of data integrity, it is essential to employ forward error correcting (FEC) encoding and decoding techniques in such mobile satellite systems. A constraint length k = 7 FEC decoder has been implemented in a single chip for such systems. The single chip implementation of the maximum likelihood decoder helps to minimize the cost, size, and power consumption, and improves the bit error rate (BER) performance of the mobile earth terminal (MET).

Dynamic plasmonic colour display

NASA Astrophysics Data System (ADS)

Duan, Xiaoyang; Kamin, Simon; Liu, Na

2017-02-01

Plasmonic colour printing based on engineered metasurfaces has revolutionized colour display science due to its unprecedented subwavelength resolution and high-density optical data storage. However, advanced plasmonic displays with novel functionalities including dynamic multicolour printing, animations, and highly secure encryption have remained in their infancy. Here we demonstrate a dynamic plasmonic colour display technique that enables all the aforementioned functionalities using catalytic magnesium metasurfaces. Controlled hydrogenation and dehydrogenation of the constituent magnesium nanoparticles, which serve as dynamic pixels, allow for plasmonic colour printing, tuning, erasing and restoration of colour. Different dynamic pixels feature distinct colour transformation kinetics, enabling plasmonic animations. Through smart material processing, information encoded on selected pixels, which are indiscernible to both optical and scanning electron microscopies, can only be read out using hydrogen as a decoding key, suggesting a new generation of information encryption and anti-counterfeiting applications.

Dynamic plasmonic colour display.

PubMed

Duan, Xiaoyang; Kamin, Simon; Liu, Na

2017-02-24

Plasmonic colour printing based on engineered metasurfaces has revolutionized colour display science due to its unprecedented subwavelength resolution and high-density optical data storage. However, advanced plasmonic displays with novel functionalities including dynamic multicolour printing, animations, and highly secure encryption have remained in their infancy. Here we demonstrate a dynamic plasmonic colour display technique that enables all the aforementioned functionalities using catalytic magnesium metasurfaces. Controlled hydrogenation and dehydrogenation of the constituent magnesium nanoparticles, which serve as dynamic pixels, allow for plasmonic colour printing, tuning, erasing and restoration of colour. Different dynamic pixels feature distinct colour transformation kinetics, enabling plasmonic animations. Through smart material processing, information encoded on selected pixels, which are indiscernible to both optical and scanning electron microscopies, can only be read out using hydrogen as a decoding key, suggesting a new generation of information encryption and anti-counterfeiting applications.

Dynamic plasmonic colour display

PubMed Central

Duan, Xiaoyang; Kamin, Simon; Liu, Na

2017-01-01

Plasmonic colour printing based on engineered metasurfaces has revolutionized colour display science due to its unprecedented subwavelength resolution and high-density optical data storage. However, advanced plasmonic displays with novel functionalities including dynamic multicolour printing, animations, and highly secure encryption have remained in their infancy. Here we demonstrate a dynamic plasmonic colour display technique that enables all the aforementioned functionalities using catalytic magnesium metasurfaces. Controlled hydrogenation and dehydrogenation of the constituent magnesium nanoparticles, which serve as dynamic pixels, allow for plasmonic colour printing, tuning, erasing and restoration of colour. Different dynamic pixels feature distinct colour transformation kinetics, enabling plasmonic animations. Through smart material processing, information encoded on selected pixels, which are indiscernible to both optical and scanning electron microscopies, can only be read out using hydrogen as a decoding key, suggesting a new generation of information encryption and anti-counterfeiting applications. PMID:28232722

Conjunctions between motion and disparity are encoded with the same spatial resolution as disparity alone.

PubMed

Allenmark, Fredrik; Read, Jenny C A

2012-10-10

Neurons in cortical area MT respond well to transparent streaming motion in distinct depth planes, such as caused by observer self-motion, but do not contain subregions excited by opposite directions of motion. We therefore predicted that spatial resolution for transparent motion/disparity conjunctions would be limited by the size of MT receptive fields, just as spatial resolution for disparity is limited by the much smaller receptive fields found in primary visual cortex, V1. We measured this using a novel "joint motion/disparity grating," on which human observers detected motion/disparity conjunctions in transparent random-dot patterns containing dots streaming in opposite directions on two depth planes. Surprisingly, observers showed the same spatial resolution for these as for pure disparity gratings. We estimate the limiting receptive field diameter at 11 arcmin, similar to V1 and much smaller than MT. Higher internal noise for detecting joint motion/disparity produces a slightly lower high-frequency cutoff of 2.5 cycles per degree (cpd) versus 3.3 cpd for disparity. This suggests that information on motion/disparity conjunctions is available in the population activity of V1 and that this information can be decoded for perception even when it is invisible to neurons in MT.

Spatial co-adaptation of cortical control columns in a micro-ECoG brain-computer interface

NASA Astrophysics Data System (ADS)

Rouse, A. G.; Williams, J. J.; Wheeler, J. J.; Moran, D. W.

2016-10-01

Objective. Electrocorticography (ECoG) has been used for a range of applications including electrophysiological mapping, epilepsy monitoring, and more recently as a recording modality for brain-computer interfaces (BCIs). Studies that examine ECoG electrodes designed and implanted chronically solely for BCI applications remain limited. The present study explored how two key factors influence chronic, closed-loop ECoG BCI: (i) the effect of inter-electrode distance on BCI performance and (ii) the differences in neural adaptation and performance when fixed versus adaptive BCI decoding weights are used. Approach. The amplitudes of epidural micro-ECoG signals between 75 and 105 Hz with 300 μm diameter electrodes were used for one-dimensional and two-dimensional BCI tasks. The effect of inter-electrode distance on BCI control was tested between 3 and 15 mm. Additionally, the performance and cortical modulation differences between constant, fixed decoding using a small subset of channels versus adaptive decoding weights using the entire array were explored. Main results. Successful BCI control was possible with two electrodes separated by 9 and 15 mm. Performance decreased and the signals became more correlated when the electrodes were only 3 mm apart. BCI performance in a 2D BCI task improved significantly when using adaptive decoding weights (80%-90%) compared to using constant, fixed weights (50%-60%). Additionally, modulation increased for channels previously unavailable for BCI control under the fixed decoding scheme upon switching to the adaptive, all-channel scheme. Significance. Our results clearly show that neural activity under a BCI recording electrode (which we define as a ‘cortical control column’) readily adapts to generate an appropriate control signal. These results show that the practical minimal spatial resolution of these control columns with micro-ECoG BCI is likely on the order of 3 mm. Additionally, they show that the combination and interaction between neural adaptation and machine learning are critical to optimizing ECoG BCI performance.

EEG resolutions in detecting and decoding finger movements from spectral analysis

PubMed Central

Xiao, Ran; Ding, Lei

2015-01-01

Mu/beta rhythms are well-studied brain activities that originate from sensorimotor cortices. These rhythms reveal spectral changes in alpha and beta bands induced by movements of different body parts, e.g., hands and limbs, in electroencephalography (EEG) signals. However, less can be revealed in them about movements of different fine body parts that activate adjacent brain regions, such as individual fingers from one hand. Several studies have reported spatial and temporal couplings of rhythmic activities at different frequency bands, suggesting the existence of well-defined spectral structures across multiple frequency bands. In the present study, spectral principal component analysis (PCA) was applied on EEG data, obtained from a finger movement task, to identify cross-frequency spectral structures. Features from identified spectral structures were examined in their spatial patterns, cross-condition pattern changes, detection capability of finger movements from resting, and decoding performance of individual finger movements in comparison to classic mu/beta rhythms. These new features reveal some similar, but more different spatial and spectral patterns as compared with classic mu/beta rhythms. Decoding results further indicate that these new features (91%) can detect finger movements much better than classic mu/beta rhythms (75.6%). More importantly, these new features reveal discriminative information about movements of different fingers (fine body-part movements), which is not available in classic mu/beta rhythms. The capability in decoding fingers (and hand gestures in the future) from EEG will contribute significantly to the development of non-invasive BCI and neuroprosthesis with intuitive and flexible controls. PMID:26388720

Performance evaluation of neuro-PET using silicon photomultipliers

NASA Astrophysics Data System (ADS)

Jung, Jiwoong; Choi, Yong; Jung, Jin Ho; Kim, Sangsu; Im, Ki Chun

2016-05-01

Recently, we have developed the second prototype Silicon photomultiplier (SiPM) based positron emission tomography (PET) scanner for human brain imaging. The PET system was comprised of detector block which consisted of 4×4 SiPMs and 4×4 Lutetium Yttrium Orthosilicate arrays, charge signal transmission method, high density position decoder circuit and FPGA-embedded ADC boards. The purpose of this study was to evaluate the performance of the newly developed neuro-PET system. The energy resolution, timing resolution, spatial resolution, sensitivity, stability of the photo-peak position and count rate performance were measured. Tomographic image of 3D Hoffman brain phantom was also acquired to evaluate imaging capability of the neuro-PET. The average energy and timing resolutions measured for 511 keV gamma rays were 17±0.1% and 3±0.3 ns, respectively. Spatial resolution and sensitivity at the center of field of view (FOV) were 3.1 mm and 0.8%, respectively. The average scatter fraction was 0.4 with an energy window of 350-650 keV. The maximum true count rate and maximum NECR were measured as 43.3 kcps and 6.5 kcps at an activity concentration of 16.7 kBq/ml and 5.5 kBq/ml, respectively. Long-term stability results show that there was no significant change in the photo-peak position, energy resolution and count rate for 60 days. Phantom imaging studies were performed and they demonstrated the feasibility for high quality brain imaging. The performance tests and imaging results indicate that the newly developed PET is useful for brain imaging studies, if the axial FOV is extended to improve the system sensitivity.

Enhanced decoding for the Galileo low-gain antenna mission: Viterbi redecoding with four decoding stages

NASA Technical Reports Server (NTRS)

Dolinar, S.; Belongie, M.

1995-01-01

The Galileo low-gain antenna mission will be supported by a coding system that uses a (14,1/4) inner convolutional code concatenated with Reed-Solomon codes of four different redundancies. Decoding for this code is designed to proceed in four distinct stages of Viterbi decoding followed by Reed-Solomon decoding. In each successive stage, the Reed-Solomon decoder only tries to decode the highest redundancy codewords not yet decoded in previous stages, and the Viterbi decoder redecodes its data utilizing the known symbols from previously decoded Reed-Solomon codewords. A previous article analyzed a two-stage decoding option that was not selected by Galileo. The present article analyzes the four-stage decoding scheme and derives the near-optimum set of redundancies selected for use by Galileo. The performance improvements relative to one- and two-stage decoding systems are evaluated.

High data rate coding for the space station telemetry links.

NASA Technical Reports Server (NTRS)

Lumb, D. R.; Viterbi, A. J.

1971-01-01

Coding systems for high data rates were examined from the standpoint of potential application in space-station telemetry links. Approaches considered included convolutional codes with sequential, Viterbi, and cascaded-Viterbi decoding. It was concluded that a high-speed (40 Mbps) sequential decoding system best satisfies the requirements for the assumed growth potential and specified constraints. Trade-off studies leading to this conclusion are viewed, and some sequential (Fano) algorithm improvements are discussed, together with real-time simulation results.

A flood map based DOI decoding method for block detector: a GATE simulation study.

PubMed

Shi, Han; Du, Dong; Su, Zhihong; Peng, Qiyu

2014-01-01

Positron Emission Tomography (PET) systems using detectors with Depth of Interaction (DOI) capabilities could achieve higher spatial resolution and better image quality than those without DOI. Up till now, most DOI methods developed are not cost-efficient for a whole body PET system. In this paper, we present a DOI decoding method based on flood map for low-cost conventional block detector with four-PMT readout. Using this method, the DOI information can be directly extracted from the DOI-related crystal spot deformation in the flood map. GATE simulations are then carried out to validate the method, confirming a DOI sorting accuracy of 85.27%. Therefore, we conclude that this method has the potential to be applied in conventional detectors to achieve a reasonable DOI measurement without dramatically increasing their complexity and cost of an entire PET system.

Multimodal decoding and congruent sensory information enhance reaching performance in subjects with cervical spinal cord injury.

PubMed

Corbett, Elaine A; Sachs, Nicholas A; Körding, Konrad P; Perreault, Eric J

2014-01-01

Cervical spinal cord injury (SCI) paralyzes muscles of the hand and arm, making it difficult to perform activities of daily living. Restoring the ability to reach can dramatically improve quality of life for people with cervical SCI. Any reaching system requires a user interface to decode parameters of an intended reach, such as trajectory and target. A challenge in developing such decoders is that often few physiological signals related to the intended reach remain under voluntary control, especially in patients with high cervical injuries. Furthermore, the decoding problem changes when the user is controlling the motion of their limb, as opposed to an external device. The purpose of this study was to investigate the benefits of combining disparate signal sources to control reach in people with a range of impairments, and to consider the effect of two feedback approaches. Subjects with cervical SCI performed robot-assisted reaching, controlling trajectories with either shoulder electromyograms (EMGs) or EMGs combined with gaze. We then evaluated how reaching performance was influenced by task-related sensory feedback, testing the EMG-only decoder in two conditions. The first involved moving the arm with the robot, providing congruent sensory feedback through their remaining sense of proprioception. In the second, the subjects moved the robot without the arm attached, as in applications that control external devices. We found that the multimodal-decoding algorithm worked well for all subjects, enabling them to perform straight, accurate reaches. The inclusion of gaze information, used to estimate target location, was especially important for the most impaired subjects. In the absence of gaze information, congruent sensory feedback improved performance. These results highlight the importance of proprioceptive feedback, and suggest that multi-modal decoders are likely to be most beneficial for highly impaired subjects and in tasks where such feedback is unavailable.

Towards Efficient Decoding of Multiple Classes of Motor Imagery Limb Movements Based on EEG Spectral and Time Domain Descriptors.

PubMed

Samuel, Oluwarotimi Williams; Geng, Yanjuan; Li, Xiangxin; Li, Guanglin

2017-10-28

To control multiple degrees of freedom (MDoF) upper limb prostheses, pattern recognition (PR) of electromyogram (EMG) signals has been successfully applied. This technique requires amputees to provide sufficient EMG signals to decode their limb movement intentions (LMIs). However, amputees with neuromuscular disorder/high level amputation often cannot provide sufficient EMG control signals, and thus the applicability of the EMG-PR technique is limited especially to this category of amputees. As an alternative approach, electroencephalograph (EEG) signals recorded non-invasively from the brain have been utilized to decode the LMIs of humans. However, most of the existing EEG based limb movement decoding methods primarily focus on identifying limited classes of upper limb movements. In addition, investigation on EEG feature extraction methods for the decoding of multiple classes of LMIs has rarely been considered. Therefore, 32 EEG feature extraction methods (including 12 spectral domain descriptors (SDDs) and 20 time domain descriptors (TDDs)) were used to decode multiple classes of motor imagery patterns associated with different upper limb movements based on 64-channel EEG recordings. From the obtained experimental results, the best individual TDD achieved an accuracy of 67.05 ± 3.12% as against 87.03 ± 2.26% for the best SDD. By applying a linear feature combination technique, an optimal set of combined TDDs recorded an average accuracy of 90.68% while that of the SDDs achieved an accuracy of 99.55% which were significantly higher than those of the individual TDD and SDD at p < 0.05. Our findings suggest that optimal feature set combination would yield a relatively high decoding accuracy that may improve the clinical robustness of MDoF neuroprosthesis. The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Semantic vs. Phonetic Decoding Strategies in Non-Native Readers of Chinese

ERIC Educational Resources Information Center

Williams, Clay H.

2010-01-01

This dissertation examines the effects of semantic and phonetic radicals on Chinese character decoding by high-intermediate level Chinese as a Foreign Language (CFL) learners. The results of the main study (discussed in Chapter #5) suggest that the CFL learners tested have a well-developed semantic pathway to recognition; however, their…

47 CFR 15.119 - Closed caption decoder requirements for analog television receivers.

Code of Federal Regulations, 2010 CFR

2010-10-01

... character or space may appear. A cell is one row high and one column wide. (5) Column: One of 32 vertical... television receivers. 15.119 Section 15.119 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL RADIO FREQUENCY DEVICES Unintentional Radiators § 15.119 Closed caption decoder requirements for analog television...

47 CFR 15.119 - Closed caption decoder requirements for analog television receivers.

Code of Federal Regulations, 2011 CFR

2011-10-01

... character or space may appear. A cell is one row high and one column wide. (5) Column: One of 32 vertical... television receivers. 15.119 Section 15.119 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL RADIO FREQUENCY DEVICES Unintentional Radiators § 15.119 Closed caption decoder requirements for analog television...

Teaching Rural Students with Learning Disabilities: A Paraphrasing Strategy to Increase Comprehension of Main Ideas.

ERIC Educational Resources Information Center

Ellis, Edwin S.; Graves, Anne W.

1990-01-01

Among 68 rural learning-disabled students in grades 5-7 having moderate decoding fluency and high decoding accuracy, a paraphrasing cognitive strategy increased reading comprehension of main ideas more effectively than repeated readings or control training. Paraphrasing plus repeated readings was no more effective than paraphrasing alone. Contains…

Intermediate Decoding Skills. NetNews. Volume 4, Number 4

ERIC Educational Resources Information Center

LDA of Minnesota, 2004

2004-01-01

Intermediate decoding refers to word analysis skills that are beyond a beginning, one-syllable level as described in an earlier NetNews issue, yet are just as important for building adult level reading proficiency. Research from secondary settings indicates that struggling readers in middle school or high school programs often read between the…

Effects of a Decoding Program on a Child with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Infantino, Josephine; Hempenstall, Kerry

2006-01-01

This case study examined the effects of a parent-presented Direct Instruction decoding program on the reading and language skills of a child with high functioning Autism Spectrum Disorder. Following the 23 hour intervention, reading comprehension, listening comprehension and fluency skills improved to grade level, whilst statistically significant…

Scalable SCPPM Decoder

NASA Technical Reports Server (NTRS)

Quir, Kevin J.; Gin, Jonathan W.; Nguyen, Danh H.; Nguyen, Huy; Nakashima, Michael A.; Moision, Bruce E.

2012-01-01

A decoder was developed that decodes a serial concatenated pulse position modulation (SCPPM) encoded information sequence. The decoder takes as input a sequence of four bit log-likelihood ratios (LLR) for each PPM slot in a codeword via a XAUI 10-Gb/s quad optical fiber interface. If the decoder is unavailable, it passes the LLRs on to the next decoder via a XAUI 10-Gb/s quad optical fiber interface. Otherwise, it decodes the sequence and outputs information bits through a 1-GB/s Ethernet UDP/IP (User Datagram Protocol/Internet Protocol) interface. The throughput for a single decoder unit is 150-Mb/s at an average of four decoding iterations; by connecting a number of decoder units in series, a decoding rate equal to that of the aggregate rate is achieved. The unit is controlled through a 1-GB/s Ethernet UDP/IP interface. This ground station decoder was developed to demonstrate a deep space optical communication link capability, and is unique in the scalable design to achieve real-time SCPP decoding at the aggregate data rate.

A four-dimensional virtual hand brain-machine interface using active dimension selection

NASA Astrophysics Data System (ADS)

Rouse, Adam G.

2016-06-01

Objective. Brain-machine interfaces (BMI) traditionally rely on a fixed, linear transformation from neural signals to an output state-space. In this study, the assumption that a BMI must control a fixed, orthogonal basis set was challenged and a novel active dimension selection (ADS) decoder was explored. Approach. ADS utilizes a two stage decoder by using neural signals to both (i) select an active dimension being controlled and (ii) control the velocity along the selected dimension. ADS decoding was tested in a monkey using 16 single units from premotor and primary motor cortex to successfully control a virtual hand avatar to move to eight different postures. Main results. Following training with the ADS decoder to control 2, 3, and then 4 dimensions, each emulating a grasp shape of the hand, performance reached 93% correct with a bit rate of 2.4 bits s-1 for eight targets. Selection of eight targets using ADS control was more efficient, as measured by bit rate, than either full four-dimensional control or computer assisted one-dimensional control. Significance. ADS decoding allows a user to quickly and efficiently select different hand postures. This novel decoding scheme represents a potential method to reduce the complexity of high-dimension BMI control of the hand.

A four-dimensional virtual hand brain-machine interface using active dimension selection

PubMed Central

Rouse, Adam G.

2018-01-01

Objective Brain-machine interfaces (BMI) traditionally rely on a fixed, linear transformation from neural signals to an output state-space. In this study, the assumption that a BMI must control a fixed, orthogonal basis set was challenged and a novel active dimension selection (ADS) decoder was explored. Approach ADS utilizes a two stage decoder by using neural signals to both i) select an active dimension being controlled and ii) control the velocity along the selected dimension. ADS decoding was tested in a monkey using 16 single units from premotor and primary motor cortex to successfully control a virtual hand avatar to move to eight different postures. Main Results Following training with the ADS decoder to control 2, 3, and then 4 dimensions, each emulating a grasp shape of the hand, performance reached 93% correct with a bit rate of 2.4 bits/s for eight targets. Selection of eight targets using ADS control was more efficient, as measured by bit rate, than either full four-dimensional control or computer assisted one-dimensional control. Significance ADS decoding allows a user to quickly and efficiently select different hand postures. This novel decoding scheme represents a potential method to reduce the complexity of high-dimension BMI control of the hand. PMID:27171896

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection.

PubMed

Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang

2018-01-15

In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes' (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10 -5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced.

One-shot and aberration-tolerable homodyne detection for holographic storage readout through double-frequency grating-based lateral shearing interferometry.

PubMed

Yu, Yeh-Wei; Xiao, Shuai; Cheng, Chih-Yuan; Sun, Ching-Cherng

2016-05-16

A simple method to decode the stored phase signal of volume holographic data storage with adequate wave aberration tolerance is highly demanded. We proposed and demonstrated a one-shot scheme to decode a binary-phase encoding signal through double-frequency-grating based shearing interferometry (DFGSI). The lateral shearing amount is dependent on the focal length of the collimated lens and the frequency difference between the gratings. Diffracted waves with phase encoding were successfully decoded through experimentation. An optical model for the DFGSI was built to analyze phase-error induction and phase-difference control by shifting the double-frequency grating longitudinally and laterally, respectively. The optical model was demonstrated experimentally. Finally, a high aberration tolerance of the DFGSI was demonstrated using the optical model.

A novel parallel pipeline structure of VP9 decoder

NASA Astrophysics Data System (ADS)

Qin, Huabiao; Chen, Wu; Yi, Sijun; Tan, Yunfei; Yi, Huan

2018-04-01

To improve the efficiency of VP9 decoder, a novel parallel pipeline structure of VP9 decoder is presented in this paper. According to the decoding workflow, VP9 decoder can be divided into sub-modules which include entropy decoding, inverse quantization, inverse transform, intra prediction, inter prediction, deblocking and pixel adaptive compensation. By analyzing the computing time of each module, hotspot modules are located and the causes of low efficiency of VP9 decoder can be found. Then, a novel pipeline decoder structure is designed by using mixed parallel decoding methods of data division and function division. The experimental results show that this structure can greatly improve the decoding efficiency of VP9.

Singer product apertures-A coded aperture system with a fast decoding algorithm

NASA Astrophysics Data System (ADS)

Byard, Kevin; Shutler, Paul M. E.

2017-06-01

A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.

Hardware multiplier processor

DOEpatents

Pierce, Paul E.

1986-01-01

A hardware processor is disclosed which in the described embodiment is a memory mapped multiplier processor that can operate in parallel with a 16 bit microcomputer. The multiplier processor decodes the address bus to receive specific instructions so that in one access it can write and automatically perform single or double precision multiplication involving a number written to it with or without addition or subtraction with a previously stored number. It can also, on a single read command automatically round and scale a previously stored number. The multiplier processor includes two concatenated 16 bit multiplier registers, two 16 bit concatenated 16 bit multipliers, and four 16 bit product registers connected to an internal 16 bit data bus. A high level address decoder determines when the multiplier processor is being addressed and first and second low level address decoders generate control signals. In addition, certain low order address lines are used to carry uncoded control signals. First and second control circuits coupled to the decoders generate further control signals and generate a plurality of clocking pulse trains in response to the decoded and address control signals.

Continuous movement decoding using a target-dependent model with EMG inputs.

PubMed

Sachs, Nicholas A; Corbett, Elaine A; Miller, Lee E; Perreault, Eric J

2011-01-01

Trajectory-based models that incorporate target position information have been shown to accurately decode reaching movements from bio-control signals, such as muscle (EMG) and cortical activity (neural spikes). One major hurdle in implementing such models for neuroprosthetic control is that they are inherently designed to decode single reaches from a position of origin to a specific target. Gaze direction can be used to identify appropriate targets, however information regarding movement intent is needed to determine when a reach is meant to begin and when it has been completed. We used linear discriminant analysis to classify limb states into movement classes based on recorded EMG from a sparse set of shoulder muscles. We then used the detected state transitions to update target information in a mixture of Kalman filters that incorporated target position explicitly in the state, and used EMG activity to decode arm movements. Updating the target position initiated movement along new trajectories, allowing a sequence of appropriately timed single reaches to be decoded in series and enabling highly accurate continuous control.

Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations

PubMed Central

Wang, Nancy X. R.; Olson, Jared D.; Ojemann, Jeffrey G.; Rao, Rajesh P. N.; Brunton, Bingni W.

2016-01-01

Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing. Implementing Brain Computer Interfaces (BCIs) outside carefully controlled experiments in laboratory settings requires adaptive and scalable strategies with minimal supervision. Here we describe an unsupervised approach to decoding neural states from naturalistic human brain recordings. We analyzed continuous, long-term electrocorticography (ECoG) data recorded over many days from the brain of subjects in a hospital room, with simultaneous audio and video recordings. We discovered coherent clusters in high-dimensional ECoG recordings using hierarchical clustering and automatically annotated them using speech and movement labels extracted from audio and video. To our knowledge, this represents the first time techniques from computer vision and speech processing have been used for natural ECoG decoding. Interpretable behaviors were decoded from ECoG data, including moving, speaking and resting; the results were assessed by comparison with manual annotation. Discovered clusters were projected back onto the brain revealing features consistent with known functional areas, opening the door to automated functional brain mapping in natural settings. PMID:27148018

Hardware multiplier processor

DOEpatents

Pierce, P.E.

A hardware processor is disclosed which in the described embodiment is a memory mapped multiplier processor that can operate in parallel with a 16 bit microcomputer. The multiplier processor decodes the address bus to receive specific instructions so that in one access it can write and automatically perform single or double precision multiplication involving a number written to it with or without addition or subtraction with a previously stored number. It can also, on a single read command automatically round and scale a previously stored number. The multiplier processor includes two concatenated 16 bit multiplier registers, two 16 bit concatenated 16 bit multipliers, and four 16 bit product registers connected to an internal 16 bit data bus. A high level address decoder determines when the multiplier processor is being addressed and first and second low level address decoders generate control signals. In addition, certain low order address lines are used to carry uncoded control signals. First and second control circuits coupled to the decoders generate further control signals and generate a plurality of clocking pulse trains in response to the decoded and address control signals.

Random Walk Graph Laplacian-Based Smoothness Prior for Soft Decoding of JPEG Images.

PubMed

Liu, Xianming; Cheung, Gene; Wu, Xiaolin; Zhao, Debin

2017-02-01

Given the prevalence of joint photographic experts group (JPEG) compressed images, optimizing image reconstruction from the compressed format remains an important problem. Instead of simply reconstructing a pixel block from the centers of indexed discrete cosine transform (DCT) coefficient quantization bins (hard decoding), soft decoding reconstructs a block by selecting appropriate coefficient values within the indexed bins with the help of signal priors. The challenge thus lies in how to define suitable priors and apply them effectively. In this paper, we combine three image priors-Laplacian prior for DCT coefficients, sparsity prior, and graph-signal smoothness prior for image patches-to construct an efficient JPEG soft decoding algorithm. Specifically, we first use the Laplacian prior to compute a minimum mean square error initial solution for each code block. Next, we show that while the sparsity prior can reduce block artifacts, limiting the size of the overcomplete dictionary (to lower computation) would lead to poor recovery of high DCT frequencies. To alleviate this problem, we design a new graph-signal smoothness prior (desired signal has mainly low graph frequencies) based on the left eigenvectors of the random walk graph Laplacian matrix (LERaG). Compared with the previous graph-signal smoothness priors, LERaG has desirable image filtering properties with low computation overhead. We demonstrate how LERaG can facilitate recovery of high DCT frequencies of a piecewise smooth signal via an interpretation of low graph frequency components as relaxed solutions to normalized cut in spectral clustering. Finally, we construct a soft decoding algorithm using the three signal priors with appropriate prior weights. Experimental results show that our proposal outperforms the state-of-the-art soft decoding algorithms in both objective and subjective evaluations noticeably.

Multiparameter imaging of calcium and abscisic acid and high-resolution quantitative calcium measurements using R-GECO1-mTurquoise in Arabidopsis.

PubMed

Waadt, Rainer; Krebs, Melanie; Kudla, Jörg; Schumacher, Karin

2017-10-01

Calcium signals occur in specific spatio-temporal patterns in response to various stimuli and are coordinated with, for example, hormonal signals, for physiological and developmental adaptations. Quantification of calcium together with other signalling molecules is required for correlative analyses and to decipher downstream calcium-decoding mechanisms. Simultaneous in vivo imaging of calcium and abscisic acid has been performed here to investigate the interdependence of the respective signalling processes in Arabidopsis thaliana roots. Advanced ratiometric genetically encoded calcium indicators have been generated and in vivo calcium calibration protocols were established to determine absolute calcium concentration changes in response to auxin and ATP. In roots, abscisic acid induced long-term basal calcium concentration increases, while auxin triggered rapid signals in the elongation zone. The advanced ratiometric calcium indicator R-GECO1-mTurquoise exhibited an increased calcium signal resolution compared to commonly used Förster resonance energy transfer-based indicators. Quantitative calcium measurements in Arabidopsis root tips using R-GECO1-mTurquoise revealed detailed maps of absolute calcium concentration changes in response to auxin and ATP. Calcium calibration protocols using R-GECO1-mTurquoise enabled high-resolution quantitative imaging of resting cytosolic calcium concentrations and their dynamic changes that revealed distinct hormonal and ATP responses in roots. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Correlated components of ongoing EEG point to emotionally laden attention - a possible marker of engagement?

PubMed

Dmochowski, Jacek P; Sajda, Paul; Dias, Joao; Parra, Lucas C

2012-01-01

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity.

Correlated Components of Ongoing EEG Point to Emotionally Laden Attention – A Possible Marker of Engagement?

PubMed Central

Dmochowski, Jacek P.; Sajda, Paul; Dias, Joao; Parra, Lucas C.

2012-01-01

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity. PMID:22623915

Differences in the Predictors of Reading Comprehension in First Graders from Low Socio-Economic Status Families with Either Good or Poor Decoding Skills

PubMed Central

Gentaz, Edouard; Sprenger-Charolles, Liliane; Theurel, Anne

2015-01-01

Based on the assumption that good decoding skills constitute a bootstrapping mechanism for reading comprehension, the present study investigated the relative contribution of the former skill to the latter compared to that of three other predictors of reading comprehension (listening comprehension, vocabulary and phonemic awareness) in 392 French-speaking first graders from low SES families. This large sample was split into three groups according to their level of decoding skills assessed by pseudoword reading. Using a cutoff of 1 SD above or below the mean of the entire population, there were 63 good decoders, 267 average decoders and 62 poor decoders. 58% of the variance in reading comprehension was explained by our four predictors, with decoding skills proving to be the best predictor (12.1%, 7.3% for listening comprehension, 4.6% for vocabulary and 3.3% for phonemic awareness). Interaction between group versus decoding skills, listening comprehension and phonemic awareness accounted for significant additional variance (3.6%, 1.1% and 1.0%, respectively). The effects on reading comprehension of decoding skills and phonemic awareness were higher in poor and average decoders than in good decoders whereas listening comprehension accounted for more variance in good and average decoders than in poor decoders. Furthermore, the percentage of children with impaired reading comprehension skills was higher in the group of poor decoders (55%) than in the two other groups (average decoders: 7%; good decoders: 0%) and only 6 children (1.5%) had impaired reading comprehension skills with unimpaired decoding skills, listening comprehension or vocabulary. These results challenge the outcomes of studies on “poor comprehenders” by showing that, at least in first grade, poor reading comprehension is strongly linked to the level of decoding skills. PMID:25793519

Differences in the predictors of reading comprehension in first graders from low socio-economic status families with either good or poor decoding skills.

PubMed

Gentaz, Edouard; Sprenger-Charolles, Liliane; Theurel, Anne

2015-01-01

Based on the assumption that good decoding skills constitute a bootstrapping mechanism for reading comprehension, the present study investigated the relative contribution of the former skill to the latter compared to that of three other predictors of reading comprehension (listening comprehension, vocabulary and phonemic awareness) in 392 French-speaking first graders from low SES families. This large sample was split into three groups according to their level of decoding skills assessed by pseudoword reading. Using a cutoff of 1 SD above or below the mean of the entire population, there were 63 good decoders, 267 average decoders and 62 poor decoders. 58% of the variance in reading comprehension was explained by our four predictors, with decoding skills proving to be the best predictor (12.1%, 7.3% for listening comprehension, 4.6% for vocabulary and 3.3% for phonemic awareness). Interaction between group versus decoding skills, listening comprehension and phonemic awareness accounted for significant additional variance (3.6%, 1.1% and 1.0%, respectively). The effects on reading comprehension of decoding skills and phonemic awareness were higher in poor and average decoders than in good decoders whereas listening comprehension accounted for more variance in good and average decoders than in poor decoders. Furthermore, the percentage of children with impaired reading comprehension skills was higher in the group of poor decoders (55%) than in the two other groups (average decoders: 7%; good decoders: 0%) and only 6 children (1.5%) had impaired reading comprehension skills with unimpaired decoding skills, listening comprehension or vocabulary. These results challenge the outcomes of studies on "poor comprehenders" by showing that, at least in first grade, poor reading comprehension is strongly linked to the level of decoding skills.

Mpeg2 codec HD improvements with medical and robotic imaging benefits

NASA Astrophysics Data System (ADS)

Picard, Wayne F. J.

2010-02-01

In this report, we propose an efficient scheme to use High Definition Television (HDTV) in a console or notebook format as a computer terminal in addition to their role as TV display unit. In the proposed scheme, we assume that the main computer is situated at a remote location. The computer raster in the remote server is compressed using an HD E- >Mpeg2 encoder and transmitted to the terminal at home. The built-in E->Mpeg2 decoder in the terminal decompresses the compressed bit stream, and displays the raster. The terminal will be fitted with a mouse and keyboard, through which the interaction with the remote computer server can be performed via a communications back channel. The terminal in a notebook format can thus be used as a high resolution computer and multimedia device. We will consider developments such as the required HD enhanced Mpeg2 resolution (E->Mpeg2) and its medical ramifications due to improvements on compressed image quality with 2D to 3D conversion (Mpeg3) and using the compressed Discrete Cosine Transform coefficients in the reality compression of vision and control of medical robotic surgeons.

Research on compression performance of ultrahigh-definition videos

NASA Astrophysics Data System (ADS)

Li, Xiangqun; He, Xiaohai; Qing, Linbo; Tao, Qingchuan; Wu, Di

2017-11-01

With the popularization of high-definition (HD) images and videos (1920×1080 pixels and above), there are even 4K (3840×2160) television signals and 8 K (8192×4320) ultrahigh-definition videos. The demand for HD images and videos is increasing continuously, along with the increasing data volume. The storage and transmission cannot be properly solved only by virtue of the expansion capacity of hard disks and the update and improvement of transmission devices. Based on the full use of the coding standard high-efficiency video coding (HEVC), super-resolution reconstruction technology, and the correlation between the intra- and the interprediction, we first put forward a "division-compensation"-based strategy to further improve the compression performance of a single image and frame I. Then, by making use of the above thought and HEVC encoder and decoder, a video compression coding frame is designed. HEVC is used inside the frame. Last, with the super-resolution reconstruction technology, the reconstructed video quality is further improved. The experiment shows that by the proposed compression method for a single image (frame I) and video sequence here, the performance is superior to that of HEVC in a low bit rate environment.

Design and implementation of a channel decoder with LDPC code

NASA Astrophysics Data System (ADS)

Hu, Diqing; Wang, Peng; Wang, Jianzong; Li, Tianquan

2008-12-01

Because Toshiba quit the competition, there is only one standard of blue-ray disc: BLU-RAY DISC, which satisfies the demands of high-density video programs. But almost all the patents are gotten by big companies such as Sony, Philips. As a result we must pay much for these patents when our productions use BD. As our own high-density optical disk storage system, Next-Generation Versatile Disc(NVD) which proposes a new data format and error correction code with independent intellectual property rights and high cost performance owns higher coding efficiency than DVD and 12GB which could meet the demands of playing the high-density video programs. In this paper, we develop Low-Density Parity-Check Codes (LDPC): a new channel encoding process and application scheme using Q-matrix based on LDPC encoding has application in NVD's channel decoder. And combined with the embedded system portable feature of SOPC system, we have completed all the decoding modules by FPGA. In the NVD experiment environment, tests are done. Though there are collisions between LDPC and Run-Length-Limited modulation codes (RLL) which are used in optical storage system frequently, the system is provided as a suitable solution. At the same time, it overcomes the defects of the instability and inextensibility, which occurred in the former decoding system of NVD--it was implemented by hardware.

The Relationship among Oral Language, Decoding Skills, and Reading Comprehension in Children with Autism

ERIC Educational Resources Information Center

Cronin, Kathleen A.

2014-01-01

The purpose of this study was to examine the relationship among oral language, decoding, and reading comprehension for children with autism. Participants included 13 English-speaking children with a diagnosis of high-functioning autism (IQ > 70) who were included in a typical classroom, and who had parents who spoke English. Parts of the…

Architecture for time or transform domain decoding of reed-solomon codes

NASA Technical Reports Server (NTRS)

Hsu, In-Shek (Inventor); Truong, Trieu-Kie (Inventor); Deutsch, Leslie J. (Inventor); Shao, Howard M. (Inventor)

1989-01-01

Two pipeline (255,233) RS decoders, one a time domain decoder and the other a transform domain decoder, use the same first part to develop an errata locator polynomial .tau.(x), and an errata evaluator polynominal A(x). Both the time domain decoder and transform domain decoder have a modified GCD that uses an input multiplexer and an output demultiplexer to reduce the number of GCD cells required. The time domain decoder uses a Chien search and polynomial evaluator on the GCD outputs .tau.(x) and A(x), for the final decoding steps, while the transform domain decoder uses a transform error pattern algorithm operating on .tau.(x) and the initial syndrome computation S(x), followed by an inverse transform algorithm in sequence for the final decoding steps prior to adding the received RS coded message to produce a decoded output message.

Multi-DSP and FPGA based Multi-channel Direct IF/RF Digital receiver for atmospheric radar

NASA Astrophysics Data System (ADS)

Yasodha, Polisetti; Jayaraman, Achuthan; Kamaraj, Pandian; Durga rao, Meka; Thriveni, A.

2016-07-01

Modern phased array radars depend highly on digital signal processing (DSP) to extract the echo signal information and to accomplish reliability along with programmability and flexibility. The advent of ASIC technology has made various digital signal processing steps to be realized in one DSP chip, which can be programmed as per the application and can handle high data rates, to be used in the radar receiver to process the received signal. Further, recent days field programmable gate array (FPGA) chips, which can be re-programmed, also present an opportunity to utilize them to process the radar signal. A multi-channel direct IF/RF digital receiver (MCDRx) is developed at NARL, taking the advantage of high speed ADCs and high performance DSP chips/FPGAs, to be used for atmospheric radars working in HF/VHF bands. Multiple channels facilitate the radar t be operated in multi-receiver modes and also to obtain the wind vector with improved time resolution, without switching the antenna beam. MCDRx has six channels, implemented on a custom built digital board, which is realized using six numbers of ADCs for simultaneous processing of the six input signals, Xilinx vertex5 FPGA and Spartan6 FPGA, and two ADSPTS201 DSP chips, each of which performs one phase of processing. MCDRx unit interfaces with the data storage/display computer via two gigabit ethernet (GbE) links. One of the six channels is used for Doppler beam swinging (DBS) mode and the other five channels are used for multi-receiver mode operations, dedicatedly. Each channel has (i) ADC block, to digitize RF/IF signal, (ii) DDC block for digital down conversion of the digitized signal, (iii) decoding block to decode the phase coded signal, and (iv) coherent integration block for integrating the data preserving phase intact. ADC block consists of Analog devices make AD9467 16-bit ADCs, to digitize the input signal at 80 MSPS. The output of ADC is centered around (80 MHz - input frequency). The digitized data is fed to DDC block, which down converts the data to base-band. The DDC block has NCO, mixer and two chains of Bessel filters (fifth order cascaded integration comb filter, two FIR filters, two half band filters and programmable FIR filters) for in-phase (I) and Quadrature phase (Q) channels. The NCO has 32 bits and is set to match the output frequency of ADC. Further, DDC down samples (decimation) the data and reduces the data rate to 16 MSPS. This data is further decimated and the data rate is reduced down to 4/2/1/0.5/0.25/0.125/0.0625 MSPS for baud lengths 0.25/0.5/1/2/4/8/16 μs respectively. The down sampled data is then fed to decoding block, which performs cross correlation to achieve pulse compression of the binary-phase coded data to obtain better range resolution with maximum possible height coverage. This step improves the signal power by a factor equal to the length of the code. Coherent integration block integrates the decoded data coherently for successive pulses, which improves the signal to noise ratio and reduces the data volume. DDC, decoding and coherent integration blocks are implemented in Xilinx vertex5 FPGA. Till this point, function of all six channels is same for DBS mode and multi-receiver modes. Data from vertex5 FPGA is transferred to PC via GbE-1 interface for multi-modes or to two Analog devices make ADSP-TS201 DSP chips (A and B), via link port for DBS mode. ADSP-TS201 chips perform the normalization, DC removal, windowing, FFT computation and spectral averaging on the data, which is transferred to storage/display PC via GbE-2 interface for real-time data display and data storing. Physical layer of GbE interface is implemented in an external chip (Marvel 88E1111) and MAC layer is implemented internal to vertex5 FPGA. The MCDRx has total 4 GB of DDR2 memory for data storage. Spartan6 FPGA is used for generating timing signals, required for basic operation of the radar and testing of the MCDRx.

Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements.

PubMed

Wang, W; Degenhart, A D; Collinger, J L; Vinjamuri, R; Sudre, G P; Adelson, P D; Holder, D L; Leuthardt, E C; Moran, D W; Boninger, M L; Schwartz, A B; Crammond, D J; Tyler-Kabara, E C; Weber, D J

2009-01-01

In this study human motor cortical activity was recorded with a customized micro-ECoG grid during individual finger movements. The quality of the recorded neural signals was characterized in the frequency domain from three different perspectives: (1) coherence between neural signals recorded from different electrodes, (2) modulation of neural signals by finger movement, and (3) accuracy of finger movement decoding. It was found that, for the high frequency band (60-120 Hz), coherence between neighboring micro-ECoG electrodes was 0.3. In addition, the high frequency band showed significant modulation by finger movement both temporally and spatially, and a classification accuracy of 73% (chance level: 20%) was achieved for individual finger movement using neural signals recorded from the micro-ECoG grid. These results suggest that the micro-ECoG grid presented here offers sufficient spatial and temporal resolution for the development of minimally-invasive brain-computer interface applications.

Choice of Reading Comprehension Test Influences the Outcomes of Genetic Analyses

PubMed Central

Betjemann, Rebecca S.; Keenan, Janice M.; Olson, Richard K.; DeFries, John C.

2010-01-01

Does the choice of test for assessing reading comprehension influence the outcome of genetic analyses? A twin design compared two types of reading comprehension tests classified as primarily associated with word decoding (RC-D) or listening comprehension (RC-LC). For both types of tests, the overall genetic influence is high and nearly identical. However, the tests differed significantly in how they covary with the genes associated with decoding and listening comprehension. Although Cholesky decomposition showed that both types of comprehension tests shared significant genetic influence with both decoding and listening comprehension, RC-D tests shared most genetic variance with decoding, and RC-LC tests shared most with listening comprehension. Thus, different tests used to measure the same construct may manifest very different patterns of genetic covariation. These results suggest that the apparent discrepancies among the findings of previous twin studies of reading comprehension could be due at least in part to test differences. PMID:21804757

Method and system for efficient video compression with low-complexity encoder

NASA Technical Reports Server (NTRS)

Chen, Jun (Inventor); He, Dake (Inventor); Sheinin, Vadim (Inventor); Jagmohan, Ashish (Inventor); Lu, Ligang (Inventor)

2012-01-01

Disclosed are a method and system for video compression, wherein the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a video decoder, wherein the method for encoding includes the steps of converting a source frame into a space-frequency representation; estimating conditional statistics of at least one vector of space-frequency coefficients; estimating encoding rates based on the said conditional statistics; and applying Slepian-Wolf codes with the said computed encoding rates. The preferred method for decoding includes the steps of; generating a side-information vector of frequency coefficients based on previously decoded source data, encoder statistics, and previous reconstructions of the source frequency vector; and performing Slepian-Wolf decoding of at least one source frequency vector based on the generated side-information, the Slepian-Wolf code bits and the encoder statistics.

Decoding of DBEC-TBED Reed-Solomon codes. [Double-Byte-Error-Correcting, Triple-Byte-Error-Detecting

NASA Technical Reports Server (NTRS)

Deng, Robert H.; Costello, Daniel J., Jr.

1987-01-01

A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. In LSI and VLSI technology, memories are often organized on a multiple bit (or byte) per chip basis. For example, some 256 K bit DRAM's are organized in 32 K x 8 bit-bytes. Byte-oriented codes such as Reed-Solomon (RS) codes can provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. The paper presents a special decoding technique for double-byte-error-correcting, triple-byte-error-detecting RS codes which is capable of high-speed operation. This technique is designed to find the error locations and the error values directly from the syndrome without having to use the iterative algorithm to find the error locator polynomial.

Studies on image compression and image reconstruction

NASA Technical Reports Server (NTRS)

Sayood, Khalid; Nori, Sekhar; Araj, A.

1994-01-01

During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.

Delay-Encoded Harmonic Imaging (DE-HI) in Multiplane-Wave Compounding.

PubMed

Gong, Ping; Song, Pengfei; Chen, Shigao

2017-04-01

The development of ultrafast ultrasound imaging brings great opportunities to improve imaging technologies such as shear wave elastography and ultrafast Doppler imaging. In ultrafast imaging, several tilted plane or diverging wave images are coherently combined to form a compounded image, leading to trade-offs among image signal-to-noise ratio (SNR), resolution, and post-compounded frame rate. Multiplane wave (MW) imaging is proposed to solve this trade-off by encoding multiple plane waves with Hadamard matrix during one transmission event (i.e. pulse-echo event), to improve image SNR without sacrificing the resolution or frame rate. However, it suffers from stronger reverberation artifacts in B-mode images compared to standard plane wave compounding due to longer transmitted pulses. If harmonic imaging can be combined with MW imaging, the reverberation artifacts and other clutter noises such as sidelobes and multipath scattering clutters should be suppressed. The challenge, however, is that the Hadamard codes used in MW imaging cannot encode the 2 nd harmonic component by inversing the pulse polarity. In this paper, we propose a delay-encoded harmonic imaging (DE-HI) technique to encode the 2 nd harmonic with a one quarter period delay calculated at the transmit center frequency, rather than reversing the pulse polarity during multiplane wave emissions. Received DE-HI signals can then be decoded in the frequency domain to recover the signals as in single plane wave emissions, but mainly with improved SNR at the 2 nd harmonic component instead of the fundamental component. DE-HI was tested experimentally with a point target, a B-mode imaging phantom, and in-vivo human liver imaging. Improvements in image contrast-to-noise ratio (CNR), spatial resolution, and lesion-signal-to-noise ratio ( l SNR) have been achieved compared to standard plane wave compounding, MW imaging, and standard harmonic imaging (maximal improvement of 116% on CNR and 115% on l SNR as compared to standard HI around 55 mm depth in the B-mode imaging phantom study). The potential high frame rate and the stability of encoding and decoding processes of DE-HI were also demonstrated, which made DE-HI promising for a wide spectrum of imaging applications.

A low-power, high-throughput maximum-likelihood convolutional decoder chip for NASA's 30/20 GHz program

NASA Technical Reports Server (NTRS)

Mccallister, R. D.; Crawford, J. J.

1981-01-01

It is pointed out that the NASA 30/20 GHz program will place in geosynchronous orbit a technically advanced communication satellite which can process time-division multiple access (TDMA) information bursts with a data throughput in excess of 4 GBPS. To guarantee acceptable data quality during periods of signal attenuation it will be necessary to provide a significant forward error correction (FEC) capability. Convolutional decoding (utilizing the maximum-likelihood techniques) was identified as the most attractive FEC strategy. Design trade-offs regarding a maximum-likelihood convolutional decoder (MCD) in a single-chip CMOS implementation are discussed.

Modulation and coding for satellite and space communications

NASA Technical Reports Server (NTRS)

Yuen, Joseph H.; Simon, Marvin K.; Pollara, Fabrizio; Divsalar, Dariush; Miller, Warner H.; Morakis, James C.; Ryan, Carl R.

1990-01-01

Several modulation and coding advances supported by NASA are summarized. To support long-constraint-length convolutional code, a VLSI maximum-likelihood decoder, utilizing parallel processing techniques, which is being developed to decode convolutional codes of constraint length 15 and a code rate as low as 1/6 is discussed. A VLSI high-speed 8-b Reed-Solomon decoder which is being developed for advanced tracking and data relay satellite (ATDRS) applications is discussed. A 300-Mb/s modem with continuous phase modulation (CPM) and codings which is being developed for ATDRS is discussed. Trellis-coded modulation (TCM) techniques are discussed for satellite-based mobile communication applications.

Good Trellises for IC Implementation of Viterbi Decoders for Linear Block Codes

NASA Technical Reports Server (NTRS)

Moorthy, Hari T.; Lin, Shu; Uehara, Gregory T.

1997-01-01

This paper investigates trellis structures of linear block codes for the integrated circuit (IC) implementation of Viterbi decoders capable of achieving high decoding speed while satisfying a constraint on the structural complexity of the trellis in terms of the maximum number of states at any particular depth. Only uniform sectionalizations of the code trellis diagram are considered. An upper-bound on the number of parallel and structurally identical (or isomorphic) subtrellises in a proper trellis for a code without exceeding the maximum state complexity of the minimal trellis of the code is first derived. Parallel structures of trellises with various section lengths for binary BCH and Reed-Muller (RM) codes of lengths 32 and 64 are analyzed. Next, the complexity of IC implementation of a Viterbi decoder based on an L-section trellis diagram for a code is investigated. A structural property of a Viterbi decoder called add-compare-select (ACS)-connectivity which is related to state connectivity is introduced. This parameter affects the complexity of wire-routing (interconnections within the IC). The effect of five parameters namely: (1) effective computational complexity; (2) complexity of the ACS-circuit; (3) traceback complexity; (4) ACS-connectivity; and (5) branch complexity of a trellis diagram on the very large scale integration (VISI) complexity of a Viterbi decoder is investigated. It is shown that an IC implementation of a Viterbi decoder based on a nonminimal trellis requires less area and is capable of operation at higher speed than one based on the minimal trellis when the commonly used ACS-array architecture is considered.

Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex.

PubMed

Ibayashi, Kenji; Kunii, Naoto; Matsuo, Takeshi; Ishishita, Yohei; Shimada, Seijiro; Kawai, Kensuke; Saito, Nobuhito

2018-01-01

Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs) is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA), local field potential (LFP), and electrocorticography (ECoG) are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC), we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs.

Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex

PubMed Central

Ibayashi, Kenji; Kunii, Naoto; Matsuo, Takeshi; Ishishita, Yohei; Shimada, Seijiro; Kawai, Kensuke; Saito, Nobuhito

2018-01-01

Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs) is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA), local field potential (LFP), and electrocorticography (ECoG) are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC), we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs. PMID:29674950

Good trellises for IC implementation of viterbi decoders for linear block codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Moorthy, Hari T.; Uehara, Gregory T.

1996-01-01

This paper investigates trellis structures of linear block codes for the IC (integrated circuit) implementation of Viterbi decoders capable of achieving high decoding speed while satisfying a constraint on the structural complexity of the trellis in terms of the maximum number of states at any particular depth. Only uniform sectionalizations of the code trellis diagram are considered. An upper bound on the number of parallel and structurally identical (or isomorphic) subtrellises in a proper trellis for a code without exceeding the maximum state complexity of the minimal trellis of the code is first derived. Parallel structures of trellises with various section lengths for binary BCH and Reed-Muller (RM) codes of lengths 32 and 64 are analyzed. Next, the complexity of IC implementation of a Viterbi decoder based on an L-section trellis diagram for a code is investigated. A structural property of a Viterbi decoder called ACS-connectivity which is related to state connectivity is introduced. This parameter affects the complexity of wire-routing (interconnections within the IC). The effect of five parameters namely: (1) effective computational complexity; (2) complexity of the ACS-circuit; (3) traceback complexity; (4) ACS-connectivity; and (5) branch complexity of a trellis diagram on the VLSI complexity of a Viterbi decoder is investigated. It is shown that an IC implementation of a Viterbi decoder based on a non-minimal trellis requires less area and is capable of operation at higher speed than one based on the minimal trellis when the commonly used ACS-array architecture is considered.

Time multiplexing super-resolution nanoscopy based on the Brownian motion of gold nanoparticles

NASA Astrophysics Data System (ADS)

Ilovitsh, Tali; Ilovitsh, Asaf; Wagner, Omer; Zalevsky, Zeev

2017-02-01

Super-resolution localization microscopy can overcome the diffraction limit and achieve a tens of order improvement in resolution. It requires labeling the sample with fluorescent probes followed with their repeated cycles of activation and photobleaching. This work presents an alternative approach that is free from direct labeling and does not require the activation and photobleaching cycles. Fluorescently labeled gold nanoparticles in a solution are distributed on top of the sample. The nanoparticles move in a random Brownian motion, and interact with the sample. By obscuring different areas in the sample, the nanoparticles encode the sub-wavelength features. A sequence of images of the sample is captured and decoded by digital post processing to create the super-resolution image. The achievable resolution is limited by the additive noise and the size of the nanoparticles. Regular nanoparticles with diameter smaller than 100nm are barely seen in a conventional bright field microscope, thus fluorescently labeled gold nanoparticles were used, with proper

The design plan of a VLSI single chip (255, 223) Reed-Solomon decoder

NASA Technical Reports Server (NTRS)

Hsu, I. S.; Shao, H. M.; Deutsch, L. J.

1987-01-01

The very large-scale integration (VLSI) architecture of a single chip (255, 223) Reed-Solomon decoder for decoding both errors and erasures is described. A decoding failure detection capability is also included in this system so that the decoder will recognize a failure to decode instead of introducing additional errors. This could happen whenever the received word contains too many errors and erasures for the code to correct. The number of transistors needed to implement this decoder is estimated at about 75,000 if the delay for received message is not included. This is in contrast to the older transform decoding algorithm which needs about 100,000 transistors. However, the transform decoder is simpler in architecture than the time decoder. It is therefore possible to implement a single chip (255, 223) Reed-Solomon decoder with today's VLSI technology. An implementation strategy for the decoder system is presented. This represents the first step in a plan to take advantage of advanced coding techniques to realize a 2.0 dB coding gain for future space missions.

Development of a multiplexed readout with high position resolution for positron emission tomography

NASA Astrophysics Data System (ADS)

Lee, Sangwon; Choi, Yong; Kang, Jihoon; Jung, Jin Ho

2017-04-01

Detector signals for positron emission tomography (PET) are commonly multiplexed to reduce the number of digital processing channels so that the system can remain cost effective while also maintaining imaging performance. In this work, a multiplexed readout combining Anger position estimation algorithm and position decoder circuit (PDC) was developed to reduce the number of readout channels by a factor of 24, 96-to-4. The data acquisition module consisted of a TDC (50 ps resolution), 4-channel ADCs (12 bit, 105 MHz sampling rate), 2 GB SDRAM and USB3.0. The performance of the multiplexed readout was assessed with a high-resolution PET detector block composed of 2×3 detector modules, each consisting of an 8×8 array of 1.52×1.52×6 mm3 LYSO, a 4×4 array of 3×3 mm2 silicon photomultiplier (SiPM) and 13.4×13.4 mm2 light guide with 0.7 mm thickness. The acquired flood histogram showed that all 384 crystals could be resolved. The average energy resolution at 511 keV was 13.7±1.6% full-width-at-half-maximum (FWHM) and the peak-to-valley ratios of the flood histogram on the horizontal and vertical lines were 18.8±0.8 and 22.8±1.3, respectively. The coincidence resolving time of a pair of detector blocks was 6.2 ns FWHM. The reconstructed phantom image showed that rods down to a diameter of 1.6 mm could be resolved. The results of this study indicate that the multiplexed readout would be useful in developing a PET with a spatial resolution less than the pixel size of the photosensor, such as a SiPM array.

Decoding word and category-specific spatiotemporal representations from MEG and EEG

PubMed Central

Chan, Alexander M.; Halgren, Eric; Marinkovic, Ksenija; Cash, Sydney S.

2010-01-01

The organization and localization of lexico-semantic information in the brain has been debated for many years. Specifically, lesion and imaging studies have attempted to map the brain areas representing living versus non-living objects, however, results remain variable. This may be due, in part, to the fact that the univariate statistical mapping analyses used to detect these brain areas are typically insensitive to subtle, but widespread, effects. Decoding techniques, on the other hand, allow for a powerful multivariate analysis of multichannel neural data. In this study, we utilize machine-learning algorithms to first demonstrate that semantic category, as well as individual words, can be decoded from EEG and MEG recordings of subjects performing a language task. Mean accuracies of 76% (chance = 50%) and 83% (chance = 20%) were obtained for the decoding of living vs. non-living category or individual words respectively. Furthermore, we utilize this decoding analysis to demonstrate that the representations of words and semantic category are highly distributed both spatially and temporally. In particular, bilateral anterior temporal, bilateral inferior frontal, and left inferior temporal-occipital sensors are most important for discrimination. Successful intersubject and intermodality decoding shows that semantic representations between stimulus modalities and individuals are reasonably consistent. These results suggest that both word and category-specific information are present in extracranially recorded neural activity and that these representations may be more distributed, both spatially and temporally, than previous studies suggest. PMID:21040796

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection

PubMed Central

Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang

2018-01-01

In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes’ (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10−5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced. PMID:29342963

Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision.

PubMed

Wen, Haiguang; Shi, Junxing; Zhang, Yizhen; Lu, Kun-Han; Cao, Jiayue; Liu, Zhongming

2017-10-20

Convolutional neural network (CNN) driven by image recognition has been shown to be able to explain cortical responses to static pictures at ventral-stream areas. Here, we further showed that such CNN could reliably predict and decode functional magnetic resonance imaging data from humans watching natural movies, despite its lack of any mechanism to account for temporal dynamics or feedback processing. Using separate data, encoding and decoding models were developed and evaluated for describing the bi-directional relationships between the CNN and the brain. Through the encoding models, the CNN-predicted areas covered not only the ventral stream, but also the dorsal stream, albeit to a lesser degree; single-voxel response was visualized as the specific pixel pattern that drove the response, revealing the distinct representation of individual cortical location; cortical activation was synthesized from natural images with high-throughput to map category representation, contrast, and selectivity. Through the decoding models, fMRI signals were directly decoded to estimate the feature representations in both visual and semantic spaces, for direct visual reconstruction and semantic categorization, respectively. These results corroborate, generalize, and extend previous findings, and highlight the value of using deep learning, as an all-in-one model of the visual cortex, to understand and decode natural vision. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities.

PubMed

da Rocha, Edroaldo Lummertz; Ung, Choong Yong; McGehee, Cordelia D; Correia, Cristina; Li, Hu

2016-06-02

The sequential chain of interactions altering the binary state of a biomolecule represents the 'information flow' within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein-protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes-network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code (http://www.NetDecoder.org) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

The serial message-passing schedule for LDPC decoding algorithms

NASA Astrophysics Data System (ADS)

Liu, Mingshan; Liu, Shanshan; Zhou, Yuan; Jiang, Xue

2015-12-01

The conventional message-passing schedule for LDPC decoding algorithms is the so-called flooding schedule. It has the disadvantage that the updated messages cannot be used until next iteration, thus reducing the convergence speed . In this case, the Layered Decoding algorithm (LBP) based on serial message-passing schedule is proposed. In this paper the decoding principle of LBP algorithm is briefly introduced, and then proposed its two improved algorithms, the grouped serial decoding algorithm (Grouped LBP) and the semi-serial decoding algorithm .They can improve LBP algorithm's decoding speed while maintaining a good decoding performance.

Mapping visual stimuli to perceptual decisions via sparse decoding of mesoscopic neural activity.

PubMed

Sajda, Paul

2010-01-01

In this talk I will describe our work investigating sparse decoding of neural activity, given a realistic mapping of the visual scene to neuronal spike trains generated by a model of primary visual cortex (V1). We use a linear decoder which imposes sparsity via an L1 norm. The decoder can be viewed as a decoding neuron (linear summation followed by a sigmoidal nonlinearity) in which there are relatively few non-zero synaptic weights. We find: (1) the best decoding performance is for a representation that is sparse in both space and time, (2) decoding of a temporal code results in better performance than a rate code and is also a better fit to the psychophysical data, (3) the number of neurons required for decoding increases monotonically as signal-to-noise in the stimulus decreases, with as little as 1% of the neurons required for decoding at the highest signal-to-noise levels, and (4) sparse decoding results in a more accurate decoding of the stimulus and is a better fit to psychophysical performance than a distributed decoding, for example one imposed by an L2 norm. We conclude that sparse coding is well-justified from a decoding perspective in that it results in a minimum number of neurons and maximum accuracy when sparse representations can be decoded from the neural dynamics.

Data processing techniques used with MST radars: A review

NASA Technical Reports Server (NTRS)

Rastogi, P. K.

1983-01-01

The data processing methods used in high power radar probing of the middle atmosphere are examined. The radar acts as a spatial filter on the small scale refractivity fluctuations in the medium. The characteristics of the received signals are related to the statistical properties of these fluctuations. A functional outline of the components of a radar system is given. Most computation intensive tasks are carried out by the processor. The processor computes a statistical function of the received signals, simultaneously for a large number of ranges. The slow fading of atmospheric signals is used to reduce the data input rate to the processor by coherent integration. The inherent range resolution of the radar experiments can be improved significant with the use of pseudonoise phase codes to modulate the transmitted pulses and a corresponding decoding operation on the received signals. Commutability of the decoding and coherent integration operations is used to obtain a significant reduction in computations. The limitations of the processors are outlined. At the next level of data reduction, the measured function is parameterized by a few spectral moments that can be related to physical processes in the medium. The problems encountered in estimating the spectral moments in the presence of strong ground clutter, external interference, and noise are discussed. The graphical and statistical analysis of the inferred parameters are outlined. The requirements for special purpose processors for MST radars are discussed.

Evidence of translation efficiency adaptation of the coding regions of the bacteriophage lambda.

PubMed

Goz, Eli; Mioduser, Oriah; Diament, Alon; Tuller, Tamir

2017-08-01

Deciphering the way gene expression regulatory aspects are encoded in viral genomes is a challenging mission with ramifications related to all biomedical disciplines. Here, we aimed to understand how the evolution shapes the bacteriophage lambda genes by performing a high resolution analysis of ribosomal profiling data and gene expression related synonymous/silent information encoded in bacteriophage coding regions.We demonstrated evidence of selection for distinct compositions of synonymous codons in early and late viral genes related to the adaptation of translation efficiency to different bacteriophage developmental stages. Specifically, we showed that evolution of viral coding regions is driven, among others, by selection for codons with higher decoding rates; during the initial/progressive stages of infection the decoding rates in early/late genes were found to be superior to those in late/early genes, respectively. Moreover, we argued that selection for translation efficiency could be partially explained by adaptation to Escherichia coli tRNA pool and the fact that it can change during the bacteriophage life cycle.An analysis of additional aspects related to the expression of viral genes, such as mRNA folding and more complex/longer regulatory signals in the coding regions, is also reported. The reported conclusions are likely to be relevant also to additional viruses. © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

A novel decoding algorithm based on the hierarchical reliable strategy for SCG-LDPC codes in optical communications

NASA Astrophysics Data System (ADS)

Yuan, Jian-guo; Tong, Qing-zhen; Huang, Sheng; Wang, Yong

2013-11-01

An effective hierarchical reliable belief propagation (HRBP) decoding algorithm is proposed according to the structural characteristics of systematically constructed Gallager low-density parity-check (SCG-LDPC) codes. The novel decoding algorithm combines the layered iteration with the reliability judgment, and can greatly reduce the number of the variable nodes involved in the subsequent iteration process and accelerate the convergence rate. The result of simulation for SCG-LDPC(3969,3720) code shows that the novel HRBP decoding algorithm can greatly reduce the computing amount at the condition of ensuring the performance compared with the traditional belief propagation (BP) algorithm. The bit error rate (BER) of the HRBP algorithm is considerable at the threshold value of 15, but in the subsequent iteration process, the number of the variable nodes for the HRBP algorithm can be reduced by about 70% at the high signal-to-noise ratio (SNR) compared with the BP algorithm. When the threshold value is further increased, the HRBP algorithm will gradually degenerate into the layered-BP algorithm, but at the BER of 10-7 and the maximal iteration number of 30, the net coding gain (NCG) of the HRBP algorithm is 0.2 dB more than that of the BP algorithm, and the average iteration times can be reduced by about 40% at the high SNR. Therefore, the novel HRBP decoding algorithm is more suitable for optical communication systems.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex.

PubMed

Tong, Frank; Harrison, Stephenie A; Dewey, John A; Kamitani, Yukiyasu

2012-11-15

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. Copyright © 2012 Elsevier Inc. All rights reserved.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex

PubMed Central

Tong, Frank; Harrison, Stephenie A.; Dewey, John A.; Kamitani, Yukiyasu

2012-01-01

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. PMID:22917989

Image transmission system using adaptive joint source and channel decoding

NASA Astrophysics Data System (ADS)

Liu, Weiliang; Daut, David G.

2005-03-01

In this paper, an adaptive joint source and channel decoding method is designed to accelerate the convergence of the iterative log-dimain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec, which makes it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. Due to the error resilience modes, some bits are known to be either correct or in error. The positions of these bits are then fed back to the channel decoder. The log-likelihood ratios (LLR) of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. That is, for lower channel SNR, a larger factor is assigned, and vice versa. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the non-source controlled decoding method up to 5dB in terms of PSNR for various reconstructed images.

A long constraint length VLSI Viterbi decoder for the DSN

NASA Technical Reports Server (NTRS)

Statman, J. I.; Zimmerman, G.; Pollara, F.; Collins, O.

1988-01-01

A Viterbi decoder, capable of decoding convolutional codes with constraint lengths up to 15, is under development for the Deep Space Network (DSN). The objective is to complete a prototype of this decoder by late 1990, and demonstrate its performance using the (15, 1/4) encoder in Galileo. The decoder is expected to provide 1 to 2 dB improvement in bit SNR, compared to the present (7, 1/2) code and existing Maximum Likelihood Convolutional Decoder (MCD). The decoder will be fully programmable for any code up to constraint length 15, and code rate 1/2 to 1/6. The decoder architecture and top-level design are described.

Extracting an evaluative feedback from the brain for adaptation of motor neuroprosthetic decoders.

PubMed

Mahmoudi, Babak; Principe, Jose C; Sanchez, Justin C

2010-01-01

The design of Brain-Machine Interface (BMI) neural decoders that have robust performance in changing environments encountered in daily life activity is a challenging problem. One solution to this problem is the design of neural decoders that are able to assist and adapt to the user by participating in their perception-action-reward cycle (PARC). Using inspiration both from artificial intelligence and neurobiology reinforcement learning theories, we have designed a novel decoding architecture that enables a symbiotic relationship between the user and an Intelligent Assistant (IA). By tapping into the motor and reward centers in the brain, the IA adapts the process of decoding neural motor commands into prosthetic actions based on the user's goals. The focus of this paper is on extraction of goal information directly from the brain and making it accessible to the IA as an evaluative feedback for adaptation. We have recorded the neural activity of the Nucleus Accumbens in behaving rats during a reaching task. The peri-event time histograms demonstrate a rich representation of the reward prediction in this subcortical structure that can be modeled on a single trial basis as a scalar evaluative feedback with high precision.

Offline decoding of end-point forces using neural ensembles: application to a brain-machine interface.

PubMed

Gupta, Rahul; Ashe, James

2009-06-01

Brain-machine interfaces (BMIs) hold a lot of promise for restoring some level of motor function to patients with neuronal disease or injury. Current BMI approaches fall into two broad categories--those that decode discrete properties of limb movement (such as movement direction and movement intent) and those that decode continuous variables (such as position and velocity). However, to enable the prosthetic devices to be useful for common everyday tasks, precise control of the forces applied by the end-point of the prosthesis (e.g., the hand) is also essential. Here, we used linear regression and Kalman filter methods to show that neural activity recorded from the motor cortex of the monkey during movements in a force field can be used to decode the end-point forces applied by the subject successfully and with high fidelity. Furthermore, the models exhibit some generalization to novel task conditions. We also demonstrate how the simultaneous prediction of kinematics and kinetics can be easily achieved using the same framework, without any degradation in decoding quality. Our results represent a useful extension of the current BMI technology, making dynamic control of a prosthetic device a distinct possibility in the near future.

Adaptive Offset Correction for Intracortical Brain Computer Interfaces

PubMed Central

Homer, Mark L.; Perge, János A.; Black, Michael J.; Harrison, Matthew T.; Cash, Sydney S.; Hochberg, Leigh R.

2014-01-01

Intracortical brain computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user’s ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called MOCA, was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors (10.6 ±10.1%; p<0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs. PMID:24196868

Adaptive offset correction for intracortical brain-computer interfaces.

PubMed

Homer, Mark L; Perge, Janos A; Black, Michael J; Harrison, Matthew T; Cash, Sydney S; Hochberg, Leigh R

2014-03-01

Intracortical brain-computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user's ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called multiple offset correction algorithm (MOCA), was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors ( 10.6 ± 10.1% ; p < 0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs.

Linear feature projection-based real-time decoding of limb state from dorsal root ganglion recordings.

PubMed

Han, Sungmin; Chu, Jun-Uk; Park, Jong Woong; Youn, Inchan

2018-05-15

Proprioceptive afferent activities recorded by a multichannel microelectrode have been used to decode limb movements to provide sensory feedback signals for closed-loop control in a functional electrical stimulation (FES) system. However, analyzing the high dimensionality of neural activity is one of the major challenges in real-time applications. This paper proposes a linear feature projection method for the real-time decoding of ankle and knee joint angles. Single-unit activity was extracted as a feature vector from proprioceptive afferent signals that were recorded from the L7 dorsal root ganglion during passive movements of ankle and knee joints. The dimensionality of this feature vector was then reduced using a linear feature projection composed of projection pursuit and negentropy maximization (PP/NEM). Finally, a time-delayed Kalman filter was used to estimate the ankle and knee joint angles. The PP/NEM approach had a better decoding performance than did other feature projection methods, and all processes were completed within the real-time constraints. These results suggested that the proposed method could be a useful decoding method to provide real-time feedback signals in closed-loop FES systems.

Decoding synchronized oscillations within the brain: phase-delayed inhibition provides a robust mechanism for creating a sharp synchrony filter.

PubMed

Patel, Mainak; Joshi, Badal

2013-10-07

The widespread presence of synchronized neuronal oscillations within the brain suggests that a mechanism must exist that is capable of decoding such activity. Two realistic designs for such a decoder include: (1) a read-out neuron with a high spike threshold, or (2) a phase-delayed inhibition network motif. Despite requiring a more elaborate network architecture, phase-delayed inhibition has been observed in multiple systems, suggesting that it may provide inherent advantages over simply imposing a high spike threshold. In this work, we use a computational and mathematical approach to investigate the efficacy of the phase-delayed inhibition motif in detecting synchronized oscillations. We show that phase-delayed inhibition is capable of creating a synchrony detector with sharp synchrony filtering properties that depend critically on the time course of inputs. Additionally, we show that phase-delayed inhibition creates a synchrony filter that is far more robust than that created by a high spike threshold. Copyright © 2013 Elsevier Ltd. All rights reserved.

Adaptive decoding of convolutional codes

NASA Astrophysics Data System (ADS)

Hueske, K.; Geldmacher, J.; Götze, J.

2007-06-01

Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.

Codestream-Based Identification of JPEG 2000 Images with Different Coding Parameters

NASA Astrophysics Data System (ADS)

Watanabe, Osamu; Fukuhara, Takahiro; Kiya, Hitoshi

A method of identifying JPEG 2000 images with different coding parameters, such as code-block sizes, quantization-step sizes, and resolution levels, is presented. It does not produce false-negative matches regardless of different coding parameters (compression rate, code-block size, and discrete wavelet transform (DWT) resolutions levels) or quantization step sizes. This feature is not provided by conventional methods. Moreover, the proposed approach is fast because it uses the number of zero-bit-planes that can be extracted from the JPEG 2000 codestream by only parsing the header information without embedded block coding with optimized truncation (EBCOT) decoding. The experimental results revealed the effectiveness of image identification based on the new method.

Adaptive neuron-to-EMG decoder training for FES neuroprostheses

NASA Astrophysics Data System (ADS)

Ethier, Christian; Acuna, Daniel; Solla, Sara A.; Miller, Lee E.

2016-08-01

Objective. We have previously demonstrated a brain-machine interface neuroprosthetic system that provided continuous control of functional electrical stimulation (FES) and restoration of grasp in a primate model of spinal cord injury (SCI). Predicting intended EMG directly from cortical recordings provides a flexible high-dimensional control signal for FES. However, no peripheral signal such as force or EMG is available for training EMG decoders in paralyzed individuals. Approach. Here we present a method for training an EMG decoder in the absence of muscle activity recordings; the decoder relies on mapping behaviorally relevant cortical activity to the inferred EMG activity underlying an intended action. Monkeys were trained at a 2D isometric wrist force task to control a computer cursor by applying force in the flexion, extension, ulnar, and radial directions and execute a center-out task. We used a generic muscle force-to-endpoint force model based on muscle pulling directions to relate each target force to an optimal EMG pattern that attained the target force while minimizing overall muscle activity. We trained EMG decoders during the target hold periods using a gradient descent algorithm that compared EMG predictions to optimal EMG patterns. Main results. We tested this method both offline and online. We quantified both the accuracy of offline force predictions and the ability of a monkey to use these real-time force predictions for closed-loop cursor control. We compared both offline and online results to those obtained with several other direct force decoders, including an optimal decoder computed from concurrently measured neural and force signals. Significance. This novel approach to training an adaptive EMG decoder could make a brain-control FES neuroprosthesis an effective tool to restore the hand function of paralyzed individuals. Clinical implementation would make use of individualized EMG-to-force models. Broad generalization could be achieved by including data from multiple grasping tasks in the training of the neuron-to-EMG decoder. Our approach would make it possible for persons with SCI to grasp objects with their own hands, using near-normal motor intent.

Brain basis of cognitive resilience: Prefrontal cortex predicts better reading comprehension in relation to decoding

PubMed Central

Patael, Smadar Z.; Farris, Emily A.; Black, Jessica M.; Hancock, Roeland; Gabrieli, John D. E.; Cutting, Laurie E.; Hoeft, Fumiko

2018-01-01

Objective The ultimate goal of reading is to understand written text. To accomplish this, children must first master decoding, the ability to translate printed words into sounds. Although decoding and reading comprehension are highly interdependent, some children struggle to decode but comprehend well, whereas others with good decoding skills fail to comprehend. The neural basis underlying individual differences in this discrepancy between decoding and comprehension abilities is virtually unknown. Methods We investigated the neural basis underlying reading discrepancy, defined as the difference between reading comprehension and decoding skills, in a three-part study: 1) The neuroanatomical basis of reading discrepancy in a cross-sectional sample of school-age children with a wide range of reading abilities (Experiment-1; n = 55); 2) Whether a discrepancy-related neural signature is present in beginning readers and predictive of future discrepancy (Experiment-2; n = 43); and 3) Whether discrepancy-related regions are part of a domain-general or a language specialized network, utilizing the 1000 Functional Connectome data and large-scale reverse inference from Neurosynth.org (Experiment-3). Results Results converged onto the left dorsolateral prefrontal cortex (DLPFC), as related to having discrepantly higher reading comprehension relative to decoding ability. Increased gray matter volume (GMV) was associated with greater discrepancy (Experiment-1). Region-of-interest (ROI) analyses based on the left DLPFC cluster identified in Experiment-1 revealed that regional GMV within this ROI in beginning readers predicted discrepancy three years later (Experiment-2). This region was associated with the fronto-parietal network that is considered fundamental for working memory and cognitive control (Experiment-3). Interpretation Processes related to the prefrontal cortex might be linked to reading discrepancy. The findings may be important for understanding cognitive resilience, which we operationalize as those individuals with greater higher-order reading skills such as reading comprehension compared to lower-order reading skills such as decoding skills. Our study provides insights into reading development, existing theories of reading, and cognitive processes that are potentially significant to a wide range of reading disorders. PMID:29902208

Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory.

PubMed

Emrich, Stephen M; Riggall, Adam C; Larocque, Joshua J; Postle, Bradley R

2013-04-10

Traditionally, load sensitivity of sustained, elevated activity has been taken as an index of storage for a limited number of items in visual short-term memory (VSTM). Recently, studies have demonstrated that the contents of a single item held in VSTM can be decoded from early visual cortex, despite the fact that these areas do not exhibit elevated, sustained activity. It is unknown, however, whether the patterns of neural activity decoded from sensory cortex change as a function of load, as one would expect from a region storing multiple representations. Here, we use multivoxel pattern analysis to examine the neural representations of VSTM in humans across multiple memory loads. In an important extension of previous findings, our results demonstrate that the contents of VSTM can be decoded from areas that exhibit a transient response to visual stimuli, but not from regions that exhibit elevated, sustained load-sensitive delay-period activity. Moreover, the neural information present in these transiently activated areas decreases significantly with increasing load, indicating load sensitivity of the patterns of activity that support VSTM maintenance. Importantly, the decrease in classification performance as a function of load is correlated with within-subject changes in mnemonic resolution. These findings indicate that distributed patterns of neural activity in putatively sensory visual cortex support the representation and precision of information in VSTM.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibrahim, Yehia M.; Garimella, Sandilya V. B.; Prost, Spencer A.

Complex samples benefit from multidimensional measurements where higher resolution enables more complete characterization of biological and environmental systems. To address this challenge, we developed a drift tube-based ion mobility spectrometry-Orbitrap mass spectrometer (IMS-Orbitrap MS) platform. To circumvent the time scale disparity between the fast IMS separation and the much slower Orbitrap MS acquisition, we utilized a dual gate and pseudorandom sequences to multiplexed injection of ions and allowing operation in signal averaging (SA), single multiplexing (SM) and double multiplexing (DM) IMS modes to optimize the signal-to-noise ratio of the measurements. For the SM measurements, a previously developed algorithm was usedmore » to reconstruct the IMS data. A new algorithm was developed for the DM analyses involving a two-step process that first recovers the SM data and then decodes the SM data. The algorithm also performs multiple refining procedures in order to minimize demultiplexing artifacts. The new IMS-Orbitrap MS platform was demonstrated by the analysis of proteomic and petroleum samples, where the integration of IMS and high mass resolution proved essential for accurate assignment of molecular formulae.« less

State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements

PubMed Central

Mollazadeh, Mohsen; Davidson, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

2013-01-01

The performance of brain-machine interfaces (BMIs) that continuously control upper limb neuroprostheses may benefit from distinguishing periods of posture and movement so as to prevent inappropriate movement of the prosthesis. Few studies, however, have investigated how decoding behavioral states and detecting the transitions between posture and movement could be used autonomously to trigger a kinematic decoder. We recorded simultaneous neuronal ensemble and local field potential (LFP) activity from microelectrode arrays in primary motor cortex (M1) and dorsal (PMd) and ventral (PMv) premotor areas of two male rhesus monkeys performing a center-out reach-and-grasp task, while upper limb kinematics were tracked with a motion capture system with markers on the dorsal aspect of the forearm, hand, and fingers. A state decoder was trained to distinguish four behavioral states (baseline, reaction, movement, hold), while a kinematic decoder was trained to continuously decode hand end point position and 18 joint angles of the wrist and fingers. LFP amplitude most accurately predicted transition into the reaction (62%) and movement (73%) states, while spikes most accurately decoded arm, hand, and finger kinematics during movement. Using an LFP-based state decoder to trigger a spike-based kinematic decoder [r = 0.72, root mean squared error (RMSE) = 0.15] significantly improved decoding of reach-to-grasp movements from baseline to final hold, compared with either a spike-based state decoder combined with a spike-based kinematic decoder (r = 0.70, RMSE = 0.17) or a spike-based kinematic decoder alone (r = 0.67, RMSE = 0.17). Combining LFP-based state decoding with spike-based kinematic decoding may be a valuable step toward the realization of BMI control of a multifingered neuroprosthesis performing dexterous manipulation. PMID:23536714

Decoding of intended saccade direction in an oculomotor brain-computer interface

NASA Astrophysics Data System (ADS)

Jia, Nan; Brincat, Scott L.; Salazar-Gómez, Andrés F.; Panko, Mikhail; Guenther, Frank H.; Miller, Earl K.

2017-08-01

Objective. To date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from the hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication (AAC) application. Here we aimed to demonstrate the feasibility of a BCI utilizing the oculomotor system. Approach. We developed a chronic intracortical BCI in monkeys to decode intended saccadic eye movement direction using activity from multiple frontal cortical areas. Main results. Intended saccade direction could be decoded in real time with high accuracy, particularly at contralateral locations. Accurate decoding was evident even at the beginning of the BCI session; no extensive BCI experience was necessary. High-frequency (80-500 Hz) local field potential magnitude provided the best performance, even over spiking activity, thus simplifying future BCI applications. Most of the information came from the frontal and supplementary eye fields, with relatively little contribution from dorsolateral prefrontal cortex. Significance. Our results support the feasibility of high-accuracy intracortical oculomotor BCIs that require little or no practice to operate and may be ideally suited for ‘point and click’ computer operation as used in most current AAC systems.

Advanced modulation technology development for earth station demodulator applications. Coded modulation system development

NASA Technical Reports Server (NTRS)

Miller, Susan P.; Kappes, J. Mark; Layer, David H.; Johnson, Peter N.

1990-01-01

A jointly optimized coded modulation system is described which was designed, built, and tested by COMSAT Laboratories for NASA LeRC which provides a bandwidth efficiency of 2 bits/s/Hz at an information rate of 160 Mbit/s. A high speed rate 8/9 encoder with a Viterbi decoder and an Octal PSK modem are used to achieve this. The BER performance is approximately 1 dB from the theoretically calculated value for this system at a BER of 5 E-7 under nominal conditions. The system operates in burst mode for downlink applications and tests have demonstrated very little degradation in performance with frequency and level offset. Unique word miss rate measurements were conducted which demonstrate reliable acquisition at low values of Eb/No. Codec self tests have verified the performance of this subsystem in a stand alone mode. The codec is capable of operation at a 200 Mbit/s information rate as demonstrated using a codec test set which introduces noise digitally. The measured performance is within 0.2 dB of the computer simulated predictions. A gate array implementation of the most time critical element of the high speed Viterbi decoder was completed. This gate array add-compare-select chip significantly reduces the power consumption and improves the manufacturability of the decoder. This chip has general application in the implementation of high speed Viterbi decoders.

Real-time minimal-bit-error probability decoding of convolutional codes

NASA Technical Reports Server (NTRS)

Lee, L.-N.

1974-01-01

A recursive procedure is derived for decoding of rate R = 1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit, subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e., fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications, such as in the inner coding system for concatenated coding.

Real-time minimal bit error probability decoding of convolutional codes

NASA Technical Reports Server (NTRS)

Lee, L. N.

1973-01-01

A recursive procedure is derived for decoding of rate R=1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e. fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications such as in the inner coding system for concatenated coding.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

PubMed

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder

PubMed Central

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive. PMID:28018162

Deep learning with convolutional neural networks for EEG decoding and visualization

PubMed Central

Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-01-01

Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

Deep learning with convolutional neural networks for EEG decoding and visualization.

PubMed

Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-11-01

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Global cortical activity predicts shape of hand during grasping

PubMed Central

Agashe, Harshavardhan A.; Paek, Andrew Y.; Zhang, Yuhang; Contreras-Vidal, José L.

2015-01-01

Recent studies show that the amplitude of cortical field potentials is modulated in the time domain by grasping kinematics. However, it is unknown if these low frequency modulations persist and contain enough information to decode grasp kinematics in macro-scale activity measured at the scalp via electroencephalography (EEG). Further, it is unclear as to whether joint angle velocities or movement synergies are the optimal kinematics spaces to decode. In this offline decoding study, we infer from human EEG, hand joint angular velocities as well as synergistic trajectories as subjects perform natural reach-to-grasp movements. Decoding accuracy, measured as the correlation coefficient (r) between the predicted and actual movement kinematics, was r = 0.49 ± 0.02 across 15 hand joints. Across the first three kinematic synergies, decoding accuracies were r = 0.59 ± 0.04, 0.47 ± 0.06, and 0.32 ± 0.05. The spatial-temporal pattern of EEG channel recruitment showed early involvement of contralateral frontal-central scalp areas followed by later activation of central electrodes over primary sensorimotor cortical areas. Information content in EEG about the grasp type peaked at 250 ms after movement onset. The high decoding accuracies in this study are significant not only as evidence for time-domain modulation in macro-scale brain activity, but for the field of brain-machine interfaces as well. Our decoding strategy, which harnesses the neural “symphony” as opposed to local members of the neural ensemble (as in intracranial approaches), may provide a means of extracting information about motor intent for grasping without the need for penetrating electrodes and suggests that it may be soon possible to develop non-invasive neural interfaces for the control of prosthetic limbs. PMID:25914616

Improving zero-training brain-computer interfaces by mixing model estimators

NASA Astrophysics Data System (ADS)

Verhoeven, T.; Hübner, D.; Tangermann, M.; Müller, K. R.; Dambre, J.; Kindermans, P. J.

2017-06-01

Objective. Brain-computer interfaces (BCI) based on event-related potentials (ERP) incorporate a decoder to classify recorded brain signals and subsequently select a control signal that drives a computer application. Standard supervised BCI decoders require a tedious calibration procedure prior to every session. Several unsupervised classification methods have been proposed that tune the decoder during actual use and as such omit this calibration. Each of these methods has its own strengths and weaknesses. Our aim is to improve overall accuracy of ERP-based BCIs without calibration. Approach. We consider two approaches for unsupervised classification of ERP signals. Learning from label proportions (LLP) was recently shown to be guaranteed to converge to a supervised decoder when enough data is available. In contrast, the formerly proposed expectation maximization (EM) based decoding for ERP-BCI does not have this guarantee. However, while this decoder has high variance due to random initialization of its parameters, it obtains a higher accuracy faster than LLP when the initialization is good. We introduce a method to optimally combine these two unsupervised decoding methods, letting one method’s strengths compensate for the weaknesses of the other and vice versa. The new method is compared to the aforementioned methods in a resimulation of an experiment with a visual speller. Main results. Analysis of the experimental results shows that the new method exceeds the performance of the previous unsupervised classification approaches in terms of ERP classification accuracy and symbol selection accuracy during the spelling experiment. Furthermore, the method shows less dependency on random initialization of model parameters and is consequently more reliable. Significance. Improving the accuracy and subsequent reliability of calibrationless BCIs makes these systems more appealing for frequent use.

Bayesian decoding using unsorted spikes in the rat hippocampus

PubMed Central

Layton, Stuart P.; Chen, Zhe; Wilson, Matthew A.

2013-01-01

A fundamental task in neuroscience is to understand how neural ensembles represent information. Population decoding is a useful tool to extract information from neuronal populations based on the ensemble spiking activity. We propose a novel Bayesian decoding paradigm to decode unsorted spikes in the rat hippocampus. Our approach uses a direct mapping between spike waveform features and covariates of interest and avoids accumulation of spike sorting errors. Our decoding paradigm is nonparametric, encoding model-free for representing stimuli, and extracts information from all available spikes and their waveform features. We apply the proposed Bayesian decoding algorithm to a position reconstruction task for freely behaving rats based on tetrode recordings of rat hippocampal neuronal activity. Our detailed decoding analyses demonstrate that our approach is efficient and better utilizes the available information in the nonsortable hash than the standard sorting-based decoding algorithm. Our approach can be adapted to an online encoding/decoding framework for applications that require real-time decoding, such as brain-machine interfaces. PMID:24089403

Image translation for single-shot focal tomography

DOE PAGES

Llull, Patrick; Yuan, Xin; Carin, Lawrence; ...

2015-01-01

Focus and depth of field are conventionally addressed by adjusting longitudinal lens position. More recently, combinations of deliberate blur and computational processing have been used to extend depth of field. Here we show that dynamic control of transverse and longitudinal lens position can be used to decode focus and extend depth of field without degrading static resolution. Our results suggest that optical image stabilization systems may be used for autofocus, extended depth of field, and 3D imaging.

Superimpose methods for uncooled infrared camera applied to the micro-scale thermal characterization of composite materials

NASA Astrophysics Data System (ADS)

Morikawa, Junko

2015-05-01

The mobile type apparatus for a quantitative micro-scale thermography using a micro-bolometer was developed based on our original techniques such as an achromatic lens design to capture a micro-scale image in long-wave infrared, a video signal superimposing for the real time emissivity correction, and a pseudo acceleration of a timeframe. The total size of the instrument was designed as it was put in the 17 cm x 28 cm x 26 cm size carrying box. The video signal synthesizer enabled to record a direct digital signal of monitoring temperature or positioning data. The encoded digital signal data embedded in each image was decoded to read out. The protocol to encode/decode the measured data was originally defined. The mixed signals of IR camera and the imposed data were applied to the pixel by pixel emissivity corrections and the pseudo-acceleration of the periodical thermal phenomena. Because the emissivity of industrial materials and biological tissues were usually inhomogeneous, it has the different temperature dependence on each pixel. The time-scale resolution for the periodic thermal event was improved with the algorithm for "pseudoacceleration". It contributes to reduce the noise by integrating the multiple image data, keeping a time resolution. The anisotropic thermal properties of some composite materials such as thermal insulating materials of cellular plastics and the biometric composite materials were analyzed using these techniques.

Sub-millimetre DOI detector based on monolithic LYSO and digital SiPM for a dedicated small-animal PET system.

PubMed

Marcinkowski, Radosław; Mollet, Pieter; Van Holen, Roel; Vandenberghe, Stefaan

2016-03-07

The mouse model is widely used in a vast range of biomedical and preclinical studies. Thanks to the ability to detect and quantify biological processes at the molecular level in vivo, PET has become a well-established tool in these investigations. However, the need to visualize and quantify radiopharmaceuticals in anatomic structures of millimetre or less requires good spatial resolution and sensitivity from small-animal PET imaging systems.In previous work we have presented a proof-of-concept of a dedicated high-resolution small-animal PET scanner based on thin monolithic scintillator crystals and Digital Photon Counter photosensor. The combination of thin monolithic crystals and MLE positioning algorithm resulted in an excellent spatial resolution of 0.7 mm uniform in the entire field of view (FOV). However, the limitation of the scanner was its low sensitivity due to small thickness of the lutetium-yttrium oxyorthosilicate (LYSO) crystals (2 mm).Here we present an improved detector design for a small-animal PET system that simultaneously achieves higher sensitivity and sustains a sub-millimetre spatial resolution. The proposed detector consists of a 5 mm thick monolithic LYSO crystal optically coupled to a Digital Photon Counter. Mean nearest neighbour (MNN) positioning combined with depth of interaction (DOI) decoding was employed to achieve sub-millimetre spatial resolution. To evaluate detector performance the intrinsic spatial resolution, energy resolution and coincidence resolving time (CRT) were measured. The average intrinsic spatial resolution of the detector was 0.60 mm full-width-at-half-maximum (FWHM). A DOI resolution of 1.66 mm was achieved. The energy resolution was 23% FWHM at 511 keV and CRT of 529 ps were measured. The improved detector design overcomes the sensitivity limitation of the previous design by increasing the nominal sensitivity of the detector block and retains an excellent intrinsic spatial resolution.

Achievable Information Rates for Coded Modulation With Hard Decision Decoding for Coherent Fiber-Optic Systems

NASA Astrophysics Data System (ADS)

Sheikh, Alireza; Amat, Alexandre Graell i.; Liva, Gianluigi

2017-12-01

We analyze the achievable information rates (AIRs) for coded modulation schemes with QAM constellations with both bit-wise and symbol-wise decoders, corresponding to the case where a binary code is used in combination with a higher-order modulation using the bit-interleaved coded modulation (BICM) paradigm and to the case where a nonbinary code over a field matched to the constellation size is used, respectively. In particular, we consider hard decision decoding, which is the preferable option for fiber-optic communication systems where decoding complexity is a concern. Recently, Liga \\emph{et al.} analyzed the AIRs for bit-wise and symbol-wise decoders considering what the authors called \\emph{hard decision decoder} which, however, exploits \\emph{soft information} of the transition probabilities of discrete-input discrete-output channel resulting from the hard detection. As such, the complexity of the decoder is essentially the same as the complexity of a soft decision decoder. In this paper, we analyze instead the AIRs for the standard hard decision decoder, commonly used in practice, where the decoding is based on the Hamming distance metric. We show that if standard hard decision decoding is used, bit-wise decoders yield significantly higher AIRs than symbol-wise decoders. As a result, contrary to the conclusion by Liga \\emph{et al.}, binary decoders together with the BICM paradigm are preferable for spectrally-efficient fiber-optic systems. We also design binary and nonbinary staircase codes and show that, in agreement with the AIRs, binary codes yield better performance.

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Kalia, Subodh; Li, Shuang; Michaelis, Andrew; Nemani, Ramakrishna R.; Saatchi, Sassan A

2017-01-01

Uncertainties in input land cover estimates contribute to a significant bias in modeled above ground biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Ganguly, S.; Kalia, S.; Li, S.; Michaelis, A.; Nemani, R. R.; Saatchi, S.

2017-12-01

Uncertainties in input land cover estimates contribute to a significant bias in modeled above gound biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition/ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree/non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial/satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

A real-time inverse quantised transform for multi-standard with dynamic resolution support

NASA Astrophysics Data System (ADS)

Sun, Chi-Chia; Lin, Chun-Ying; Zhang, Ce

2016-06-01

In this paper, a real-time configurable intelligent property (IP) core is presented for image/video decoding process in compatibility with the standard MPEG-4 Visual and the standard H.264/AVC. The inverse quantised discrete cosine and integer transform can be used to perform inverse quantised discrete cosine transform and inverse quantised inverse integer transforms which only required shift and add operations. Meanwhile, COordinate Rotation DIgital Computer iterations and compensation steps are adjustable in order to compensate for the video compression quality regarding various data throughput. The implementations are embedded in publicly available software XVID Codes 1.2.2 for the standard MPEG-4 Visual and the H.264/AVC reference software JM 16.1, where the experimental results show that the balance between the computational complexity and video compression quality is retained. At the end, FPGA synthesised results show that the proposed IP core can bring advantages to low hardware costs and also provide real-time performance for Full HD and 4K-2K video decoding.

Coded excitation with spectrum inversion (CEXSI) for ultrasound array imaging.

PubMed

Wang, Yao; Metzger, Kurt; Stephens, Douglas N; Williams, Gregory; Brownlie, Scott; O'Donnell, Matthew

2003-07-01

In this paper, a scheme called coded excitation with spectrum inversion (CEXSI) is presented. An established optimal binary code whose spectrum has no nulls and possesses the least variation is encoded as a burst for transmission. Using this optimal code, the decoding filter can be derived directly from its inverse spectrum. Various transmission techniques can be used to improve energy coupling within the system pass-band. We demonstrate its potential to achieve excellent decoding with very low (< 80 dB) side-lobes. For a 2.6 micros code, an array element with a center frequency of 10 MHz and fractional bandwidth of 38%, range side-lobes of about 40 dB have been achieved experimentally with little compromise in range resolution. The signal-to-noise ratio (SNR) improvement also has been characterized at about 14 dB. Along with simulations and experimental data, we present a formulation of the scheme, according to which CEXSI can be extended to improve SNR in sparse array imaging in general.

A novel design of optical CDMA system based on TCM and FFH

NASA Astrophysics Data System (ADS)

Fang, Jun-Bin; Xu, Zhi-Hai; Huang, Hong-bin; Zheng, Liming; Chen, Shun-er; Liu, Wei-ping

2005-02-01

For the application in Passive Optical Network (PON), a novel design of OCDMA system scheme is proposed in this paper. There are two key components included in this scheme: a new kind of OCDMA encoder/decoder system based on TCM and FFH and an improved Optical Line Terminal (OLT) receiving system with improved anti-interference performance by the use of Long Period Fiber Grating (LPFG). In the encoder/decoder system, Trellis Coded Modulation (TCM) encoder is applied in front of the FFH modulator. Original signal firstly is encoded through TCM encoder, and then the redundant code out of the TCM encoder will be mapped into one of the FFH modulation signal subsets for transmission. On the receiver (decoder) side, transmitting signal is demodulated through FFH and decoded by trellis decoder. Owing to the fact that high coding gain can be acquired by TCM without adding transmitting band and reducing transmitting speed, TCM is utilized to ameliorate bit error performance and reduce multi-user interference. In the OLT receiving system, EDFA and LPFG are placed in front of decoder to get excellent gain flatness on a large bandwidth, and Optical Hard Limiter (OHL) is also deployed to improve detection performance, through which the anti-interference performance of receiving system can be greatly enhanced. At the same time, some software is used to simulate the system performance for further analysis and authentication. The related work in this paper provides a valuable reference to the research.

47 CFR 11.33 - EAS Decoder.

Code of Federal Regulations, 2010 CFR

2010-10-01

... decoders manufactured after August 1, 2003 must provide a means to permit the selective display and logging... upgrade their decoders on an optional basis to include a selective display and logging capability for EAS... decoders after February 1, 2004 must install decoders that provide a means to permit the selective display...

A real-time MPEG software decoder using a portable message-passing library

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kwong, Man Kam; Tang, P.T. Peter; Lin, Biquan

1995-12-31

We present a real-time MPEG software decoder that uses message-passing libraries such as MPL, p4 and MPI. The parallel MPEG decoder currently runs on the IBM SP system but can be easil ported to other parallel machines. This paper discusses our parallel MPEG decoding algorithm as well as the parallel programming environment under which it uses. Several technical issues are discussed, including balancing of decoding speed, memory limitation, 1/0 capacities, and optimization of MPEG decoding components. This project shows that a real-time portable software MPEG decoder is feasible in a general-purpose parallel machine.

NP-hardness of decoding quantum error-correction codes

NASA Astrophysics Data System (ADS)

Hsieh, Min-Hsiu; Le Gall, François

2011-05-01

Although the theory of quantum error correction is intimately related to classical coding theory and, in particular, one can construct quantum error-correction codes (QECCs) from classical codes with the dual-containing property, this does not necessarily imply that the computational complexity of decoding QECCs is the same as their classical counterparts. Instead, decoding QECCs can be very much different from decoding classical codes due to the degeneracy property. Intuitively, one expects degeneracy would simplify the decoding since two different errors might not and need not be distinguished in order to correct them. However, we show that general quantum decoding problem is NP-hard regardless of the quantum codes being degenerate or nondegenerate. This finding implies that no considerably fast decoding algorithm exists for the general quantum decoding problems and suggests the existence of a quantum cryptosystem based on the hardness of decoding QECCs.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; The Map and Related Decoding Algirithms

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc

1998-01-01

In a coded communication system with equiprobable signaling, MLD minimizes the word error probability and delivers the most likely codeword associated with the corresponding received sequence. This decoding has two drawbacks. First, minimization of the word error probability is not equivalent to minimization of the bit error probability. Therefore, MLD becomes suboptimum with respect to the bit error probability. Second, MLD delivers a hard-decision estimate of the received sequence, so that information is lost between the input and output of the ML decoder. This information is important in coded schemes where the decoded sequence is further processed, such as concatenated coding schemes, multi-stage and iterative decoding schemes. In this chapter, we first present a decoding algorithm which both minimizes bit error probability, and provides the corresponding soft information at the output of the decoder. This algorithm is referred to as the MAP (maximum aposteriori probability) decoding algorithm.

More than meets the eye: the role of self-identity in decoding complex emotional states.

PubMed

Stevenson, Michael T; Soto, José A; Adams, Reginald B

2012-10-01

Folk wisdom asserts that "the eyes are the window to the soul," and empirical science corroborates a prominent role for the eyes in the communication of emotion. Herein we examine variation in the ability to "read" the eyes of others as a function of social group membership, employing a widely used emotional state decoding task: "Reading the Mind in Eyes." This task has documented impaired emotional state decoding across racial groups, with cross-race performance on par with that previously reported as a function of autism spectrum disorders. The present study extended this work by examining the moderating role of social identity in such impairments. For college students more highly identified with their university, cross-race performance differences were not found for judgments of "same-school" eyes but remained for "rival-school" eyes. These findings suggest that impaired emotional state decoding across groups may thus be more amenable to remediation than previously realized.

Decoding flexion of individual fingers using electrocorticographic signals in humans

NASA Astrophysics Data System (ADS)

Kubánek, J.; Miller, K. J.; Ojemann, J. G.; Wolpaw, J. R.; Schalk, G.

2009-12-01

Brain signals can provide the basis for a non-muscular communication and control system, a brain-computer interface (BCI), for people with motor disabilities. A common approach to creating BCI devices is to decode kinematic parameters of movements using signals recorded by intracortical microelectrodes. Recent studies have shown that kinematic parameters of hand movements can also be accurately decoded from signals recorded by electrodes placed on the surface of the brain (electrocorticography (ECoG)). In the present study, we extend these results by demonstrating that it is also possible to decode the time course of the flexion of individual fingers using ECoG signals in humans, and by showing that these flexion time courses are highly specific to the moving finger. These results provide additional support for the hypothesis that ECoG could be the basis for powerful clinically practical BCI systems, and also indicate that ECoG is useful for studying cortical dynamics related to motor function.

Signal acquisition and analysis for cortical control of neuroprosthetics.

PubMed

Tillery, Stephen I Helms; Taylor, Dawn M

2004-12-01

Work in cortically controlled neuroprosthetic systems has concentrated on decoding natural behaviors from neural activity, with the idea that if the behavior could be fully decoded it could be duplicated using an artificial system. Initial estimates from this approach suggested that a high-fidelity signal comprised of many hundreds of neurons would be required to control a neuroprosthetic system successfully. However, recent studies are showing hints that these systems can be controlled effectively using only a few tens of neurons. Attempting to decode the pre-existing relationship between neural activity and natural behavior is not nearly as important as choosing a decoding scheme that can be more readily deployed and trained to generate the desired actions of the artificial system. These artificial systems need not resemble or behave similarly to any natural biological system. Effective matching of discrete and continuous neural command signals to appropriately configured device functions will enable effective control of both natural and abstract artificial systems using compatible thought processes.

Kernel Temporal Differences for Neural Decoding

PubMed Central

Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2015-01-01

We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504

Reliability of directional information in unsorted spikes and local field potentials recorded in human motor cortex.

PubMed

Perge, János A; Zhang, Shaomin; Malik, Wasim Q; Homer, Mark L; Cash, Sydney; Friehs, Gerhard; Eskandar, Emad N; Donoghue, John P; Hochberg, Leigh R

2014-08-01

Action potentials and local field potentials (LFPs) recorded in primary motor cortex contain information about the direction of movement. LFPs are assumed to be more robust to signal instabilities than action potentials, which makes LFPs, along with action potentials, a promising signal source for brain-computer interface applications. Still, relatively little research has directly compared the utility of LFPs to action potentials in decoding movement direction in human motor cortex. We conducted intracortical multi-electrode recordings in motor cortex of two persons (T2 and [S3]) as they performed a motor imagery task. We then compared the offline decoding performance of LFPs and spiking extracted from the same data recorded across a one-year period in each participant. We obtained offline prediction accuracy of movement direction and endpoint velocity in multiple LFP bands, with the best performance in the highest (200-400 Hz) LFP frequency band, presumably also containing low-pass filtered action potentials. Cross-frequency correlations of preferred directions and directional modulation index showed high similarity of directional information between action potential firing rates (spiking) and high frequency LFPs (70-400 Hz), and increasing disparity with lower frequency bands (0-7, 10-40 and 50-65 Hz). Spikes predicted the direction of intended movement more accurately than any individual LFP band, however combined decoding of all LFPs was statistically indistinguishable from spike-based performance. As the quality of spiking signals (i.e. signal amplitude) and the number of significantly modulated spiking units decreased, the offline decoding performance decreased 3.6[5.65]%/month (for T2 and [S3] respectively). The decrease in the number of significantly modulated LFP signals and their decoding accuracy followed a similar trend (2.4[2.85]%/month, ANCOVA, p = 0.27[0.03]). Field potentials provided comparable offline decoding performance to unsorted spikes. Thus, LFPs may provide useful external device control using current human intracortical recording technology. ( NCT00912041.).

A Symbiotic Brain-Machine Interface through Value-Based Decision Making

PubMed Central

Mahmoudi, Babak; Sanchez, Justin C.

2011-01-01

Background In the development of Brain Machine Interfaces (BMIs), there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC). Methodology The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc) contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1) and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. Conclusions Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and reward interdependency in the brain. PMID:21423797

JWST DD ERS Team Update: Decoding Smoke Signals from WR140 using NIRISS+AMI and MIRI/MRS

NASA Astrophysics Data System (ADS)

Lau, Ryan M.; Hankins, Matt; WR DustERS Team

2018-06-01

Dust is a key component of the interstellar medium and plays and important role in the formation of stars and planets. However, the dominant channels of dust production throughout cosmic time are uncertain. With its unprecedented sensitivity and spatial resolution in the mid-IR, the James Webb Space Telescope (JWST) is the ideal platform to address this issue by investigating the dust abundance, composition, and production rates of various dusty sources. In particular, colliding-wind Wolf-Rayet (WR) binaries are known to be efficient dust producers in the local Universe and likely existed in the earliest galaxies. In our Early Release Science (ERS) program, we will use JWST to observe the archetypal colliding-wind binary, WR 140, to study its dust composition, abundance, and formation mechanisms. We will utilize two key JWST observing modes with the medium-resolution spectrometer (MRS) on the Mid-Infrared Instrument (MIRI) and the Aperture Masking Interferometry (AMI) mode with the Near Infrared Imager and Slitless Spectrograph (NIRISS).Our planned observations will establish a benchmark for key observing modes for imaging bright sources with faint extended emission at high spatial resolutions. This will be valuable in various astrophysical contexts including mass-loss from evolved stars, dusty tori around active galactic nuclei, and protoplanetary disks. We are committed to delivering science-enabling products for the JWST community that include high-level pipeline tools to mitigate bright source artifacts and image reconstruction tools compatible with NIRISS+AMI data.

Laterality of Temporoparietal Causal Connectivity during the Prestimulus Period Correlates with Phonological Decoding Task Performance in Dyslexic and Typical Readers

PubMed Central

Liederman, Jacqueline; McGraw Fisher, Janet; Wu, Meng-Hung

2012-01-01

We examined how effective connectivity into and out of the left and right temporoparietal areas (TPAs) to/from other key cortical areas affected phonological decoding in 7 dyslexic readers (DRs) and 10 typical readers (TRs) who were young adults. Granger causality was used to compute the effective connectivity of the preparatory network 500 ms prior to presentation of nonwords that required phonological decoding. Neuromagnetic activity was analyzed within the low, medium, and high beta and gamma subbands. A mixed-model analysis determined whether connectivity to or from the left and right TPAs differed across connectivity direction (in vs. out), brain areas (right and left inferior frontal and ventral occipital–temporal and the contralateral TPA), reading group (DR vs. TR), and/or task performance. Within the low beta subband, better performance was associated with increased influence of the left TPA on other brain areas across both reading groups and poorer performance was associated with increased influence of the right TPA on other brain areas for DRs only. DRs were also found to have an increase in high gamma connectivity between the left TPA and other brain areas. This study suggests that hierarchal network structure rather than connectivity per se is important in determining phonological decoding performance. PMID:21980019

Hidden Markov Model and Support Vector Machine based decoding of finger movements using Electrocorticography

PubMed Central

Wissel, Tobias; Pfeiffer, Tim; Frysch, Robert; Knight, Robert T.; Chang, Edward F.; Hinrichs, Hermann; Rieger, Jochem W.; Rose, Georg

2013-01-01

Objective Support Vector Machines (SVM) have developed into a gold standard for accurate classification in Brain-Computer-Interfaces (BCI). The choice of the most appropriate classifier for a particular application depends on several characteristics in addition to decoding accuracy. Here we investigate the implementation of Hidden Markov Models (HMM)for online BCIs and discuss strategies to improve their performance. Approach We compare the SVM, serving as a reference, and HMMs for classifying discrete finger movements obtained from the Electrocorticograms of four subjects doing a finger tapping experiment. The classifier decisions are based on a subset of low-frequency time domain and high gamma oscillation features. Main results We show that decoding optimization between the two approaches is due to the way features are extracted and selected and less dependent on the classifier. An additional gain in HMM performance of up to 6% was obtained by introducing model constraints. Comparable accuracies of up to 90% were achieved with both SVM and HMM with the high gamma cortical response providing the most important decoding information for both techniques. Significance We discuss technical HMM characteristics and adaptations in the context of the presented data as well as for general BCI applications. Our findings suggest that HMMs and their characteristics are promising for efficient online brain-computer interfaces. PMID:24045504

Bounded-Angle Iterative Decoding of LDPC Codes

NASA Technical Reports Server (NTRS)

Dolinar, Samuel; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush

2009-01-01

Bounded-angle iterative decoding is a modified version of conventional iterative decoding, conceived as a means of reducing undetected-error rates for short low-density parity-check (LDPC) codes. For a given code, bounded-angle iterative decoding can be implemented by means of a simple modification of the decoder algorithm, without redesigning the code. Bounded-angle iterative decoding is based on a representation of received words and code words as vectors in an n-dimensional Euclidean space (where n is an integer).

Synthetic phonics and decodable instructional reading texts: How far do these support poor readers?

PubMed

Price-Mohr, Ruth Maria; Price, Colin Bernard

2018-05-01

This paper presents data from a quasi-experimental trial with paired randomisation that emerged during the development of a reading scheme for children in England. This trial was conducted with a group of 12 children, aged 5-6, and considered to be falling behind their peers in reading ability and a matched control group. There were two intervention conditions (A: using mixed teaching methods and a high percentage of non-phonically decodable vocabulary; P: using mixed teaching methods and low percentage of non-decodable vocabulary); allocation to these was randomised. Children were assessed at pre- and post-test on standardised measures of receptive vocabulary, phoneme awareness, word reading, and comprehension. Two class teachers in the same school each selected 6 children, who they considered to be poor readers, to participate (n = 12). A control group (using synthetic phonics only and phonically decodable vocabulary) was selected from the same 2 classes based on pre-test scores for word reading (n = 16). Results from the study show positive benefits for poor readers from using both additional teaching methods (such as analytic phonics, sight word vocabulary, and oral vocabulary extension) in addition to synthetic phonics, and also non-decodable vocabulary in instructional reading text. Copyright © 2018 John Wiley & Sons, Ltd.

Off-axis points encoding/decoding with orbital angular momentum spectrum

PubMed Central

Chu, Jiaqi; Chu, Daping; Smithwitck, Quinn

2017-01-01

Encoding/decoding off-axis points with discrete orbital angular momentum (OAM) modes is investigated. On-axis Laguerre-Gaussian (LG) beams are expanded into off-axis OAM spectra, with which off-axis points are encoded. The influence of the mode and the displacement of the LG beam on the spread of the OAM spectrum is analysed. The results show that not only the conventional on-axis point, but also off-axis points, can be encoded and decoded with OAM of light. This is confirmed experimentally. The analytical result here provides a solid foundation to use OAM modes to encode two-dimensional high density information for multiplexing and to analyse the effect of mis-alignment in practical OAM applications. PMID:28272543

Development of a new ion mobility time-of-flight mass spectrometer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibrahim, Yehia M.; Baker, Erin S.; Danielson, William F.

2015-02-01

Complex samples require multidimensional measurements with high resolution for full characterization of biological and environmental systems. To address this challenge, we developed a drift tube-based ion mobility spectrometry-Orbitrap mass spectrometry (IMS-Orbitrap MS) platform. To circumvent the timing difference between the fast IMS separation and the slow Orbitrap MS acquisition, we utilized a dual gate and pseudorandom sequence to multiplex ions into the drift tube and Orbitrap. The instrument was designed to operate in signal averaging (SA), single multiplexing (SM) and double multiplexing (DM) IMS modes to fully optimize the signal-to-ratio of the measurements. For the SM measurements, a previously developedmore » algorithm was used to reconstruct the IMS data, while a new algorithm was developed for the DM analyses. The new algorithm is a two-step process that first recovers the SM data from the encoded DM data and then decoded the SM data. The algorithm also performs multiple refining procedures in order to minimize the demultiplexing artifacts traditionally observed in such scheme. The new IMS-Orbitrap MS platform was demonstrated for the analysis of proteomic and petroleum samples, where the integration of IMS and high mass resolution proved essential for accurate assignment of molecular formulae.« less

Iterative channel decoding of FEC-based multiple-description codes.

PubMed

Chang, Seok-Ho; Cosman, Pamela C; Milstein, Laurence B

2012-03-01

Multiple description coding has been receiving attention as a robust transmission framework for multimedia services. This paper studies the iterative decoding of FEC-based multiple description codes. The proposed decoding algorithms take advantage of the error detection capability of Reed-Solomon (RS) erasure codes. The information of correctly decoded RS codewords is exploited to enhance the error correction capability of the Viterbi algorithm at the next iteration of decoding. In the proposed algorithm, an intradescription interleaver is synergistically combined with the iterative decoder. The interleaver does not affect the performance of noniterative decoding but greatly enhances the performance when the system is iteratively decoded. We also address the optimal allocation of RS parity symbols for unequal error protection. For the optimal allocation in iterative decoding, we derive mathematical equations from which the probability distributions of description erasures can be generated in a simple way. The performance of the algorithm is evaluated over an orthogonal frequency-division multiplexing system. The results show that the performance of the multiple description codes is significantly enhanced.

High performance MPEG-audio decoder IC

NASA Technical Reports Server (NTRS)

Thorn, M.; Benbassat, G.; Cyr, K.; Li, S.; Gill, M.; Kam, D.; Walker, K.; Look, P.; Eldridge, C.; Ng, P.

1993-01-01

The emerging digital audio and video compression technology brings both an opportunity and a new challenge to IC design. The pervasive application of compression technology to consumer electronics will require high volume, low cost IC's and fast time to market of the prototypes and production units. At the same time, the algorithms used in the compression technology result in complex VLSI IC's. The conflicting challenges of algorithm complexity, low cost, and fast time to market have an impact on device architecture and design methodology. The work presented in this paper is about the design of a dedicated, high precision, Motion Picture Expert Group (MPEG) audio decoder.

Protograph LDPC Codes Over Burst Erasure Channels

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Dolinar, Sam; Jones, Christopher

2006-01-01

In this paper we design high rate protograph based LDPC codes suitable for binary erasure channels. To simplify the encoder and decoder implementation for high data rate transmission, the structure of codes are based on protographs and circulants. These LDPC codes can improve data link and network layer protocols in support of communication networks. Two classes of codes were designed. One class is designed for large block sizes with an iterative decoding threshold that approaches capacity of binary erasure channels. The other class is designed for short block sizes based on maximizing minimum stopping set size. For high code rates and short blocks the second class outperforms the first class.

Hierarchical image coding with diamond-shaped sub-bands

NASA Technical Reports Server (NTRS)

Li, Xiaohui; Wang, Jie; Bauer, Peter; Sauer, Ken

1992-01-01

We present a sub-band image coding/decoding system using a diamond-shaped pyramid frequency decomposition to more closely match visual sensitivities than conventional rectangular bands. Filter banks are composed of simple, low order IIR components. The coder is especially designed to function in a multiple resolution reconstruction setting, in situations such as variable capacity channels or receivers, where images must be reconstructed without the entire pyramid of sub-bands. We use a nonlinear interpolation technique for lost subbands to compensate for loss of aliasing cancellation.

Temporal Response Properties of Accessory Olfactory Bulb Neurons: Limitations and Opportunities for Decoding.

PubMed

Yoles-Frenkel, Michal; Kahan, Anat; Ben-Shaul, Yoram

2018-05-23

The vomeronasal system (VNS) is a major vertebrate chemosensory system that functions in parallel to the main olfactory system (MOS). Despite many similarities, the two systems dramatically differ in the temporal domain. While MOS responses are governed by breathing and follow a subsecond temporal scale, VNS responses are uncoupled from breathing and evolve over seconds. This suggests that the contribution of response dynamics to stimulus information will differ between these systems. While temporal dynamics in the MOS are widely investigated, similar analyses in the accessory olfactory bulb (AOB) are lacking. Here, we have addressed this issue using controlled stimulus delivery to the vomeronasal organ of male and female mice. We first analyzed the temporal properties of AOB projection neurons and demonstrated that neurons display prolonged, variable, and neuron-specific characteristics. We then analyzed various decoding schemes using AOB population responses. We showed that compared with the simplest scheme (i.e., integration of spike counts over the entire response period), the division of this period into smaller temporal bins actually yields poorer decoding accuracy. However, optimal classification accuracy can be achieved well before the end of the response period by integrating spike counts within temporally defined windows. Since VNS stimulus uptake is variable, we analyzed decoding using limited information about stimulus uptake time, and showed that with enough neurons, such time-invariant decoding is feasible. Finally, we conducted simulations that demonstrated that, unlike the main olfactory bulb, the temporal features of AOB neurons disfavor decoding with high temporal accuracy, and, rather, support decoding without precise knowledge of stimulus uptake time. SIGNIFICANCE STATEMENT A key goal in sensory system research is to identify which metrics of neuronal activity are relevant for decoding stimulus features. Here, we describe the first systematic analysis of temporal coding in the vomeronasal system (VNS), a chemosensory system devoted to socially relevant cues. Compared with the main olfactory system, timescales of VNS function are inherently slower and variable. Using various analyses of real and simulated data, we show that the consideration of response times relative to stimulus uptake can aid the decoding of stimulus information from neuronal activity. However, response properties of accessory olfactory bulb neurons favor decoding schemes that do not rely on the precise timing of stimulus uptake. Such schemes are consistent with the variable nature of VNS stimulus uptake. Copyright © 2018 the authors 0270-6474/18/384957-20$15.00/0.

Efficient Decoding of Compressed Data.

ERIC Educational Resources Information Center

Bassiouni, Mostafa A.; Mukherjee, Amar

1995-01-01

Discusses the problem of enhancing the speed of Huffman decoding of compressed data. Topics addressed include the Huffman decoding tree; multibit decoding; binary string mapping problems; and algorithms for solving mapping problems. (22 references) (LRW)

A new VLSI architecture for a single-chip-type Reed-Solomon decoder

NASA Technical Reports Server (NTRS)

Hsu, I. S.; Truong, T. K.

1989-01-01

A new very large scale integration (VLSI) architecture for implementing Reed-Solomon (RS) decoders that can correct both errors and erasures is described. This new architecture implements a Reed-Solomon decoder by using replication of a single VLSI chip. It is anticipated that this single chip type RS decoder approach will save substantial development and production costs. It is estimated that reduction in cost by a factor of four is possible with this new architecture. Furthermore, this Reed-Solomon decoder is programmable between 8 bit and 10 bit symbol sizes. Therefore, both an 8 bit Consultative Committee for Space Data Systems (CCSDS) RS decoder and a 10 bit decoder are obtained at the same time, and when concatenated with a (15,1/6) Viterbi decoder, provide an additional 2.1-dB coding gain.

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

Iterative Code-Aided ML Phase Estimation and Phase Ambiguity Resolution

NASA Astrophysics Data System (ADS)

Wymeersch, Henk; Moeneclaey, Marc

2005-12-01

As many coded systems operate at very low signal-to-noise ratios, synchronization becomes a very difficult task. In many cases, conventional algorithms will either require long training sequences or result in large BER degradations. By exploiting code properties, these problems can be avoided. In this contribution, we present several iterative maximum-likelihood (ML) algorithms for joint carrier phase estimation and ambiguity resolution. These algorithms operate on coded signals by accepting soft information from the MAP decoder. Issues of convergence and initialization are addressed in detail. Simulation results are presented for turbo codes, and are compared to performance results of conventional algorithms. Performance comparisons are carried out in terms of BER performance and mean square estimation error (MSEE). We show that the proposed algorithm reduces the MSEE and, more importantly, the BER degradation. Additionally, phase ambiguity resolution can be performed without resorting to a pilot sequence, thus improving the spectral efficiency.

Feature Selection Methods for Robust Decoding of Finger Movements in a Non-human Primate

PubMed Central

Padmanaban, Subash; Baker, Justin; Greger, Bradley

2018-01-01

Objective: The performance of machine learning algorithms used for neural decoding of dexterous tasks may be impeded due to problems arising when dealing with high-dimensional data. The objective of feature selection algorithms is to choose a near-optimal subset of features from the original feature space to improve the performance of the decoding algorithm. The aim of our study was to compare the effects of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis (PCA), and Mutual Information Maximization on SVM classification performance for a dexterous decoding task. Approach: A nonhuman primate (NHP) was trained to perform small coordinated movements—similar to typing. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials (AP) during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon AP firing rates. We used the SVM classification to examine the functional parameters of (i) robustness to simulated failure and (ii) longevity of classification. We also compared the effect of using isolated-neuron and multi-unit firing rates as the feature vector supplied to the SVM. Main results: The average decoding accuracy for multi-unit features and single-unit features using Mutual Information Maximization (MIM) across 47 sessions was 96.74 ± 3.5% and 97.65 ± 3.36% respectively. The reduction in decoding accuracy between using 100% of the features and 10% of features based on MIM was 45.56% (from 93.7 to 51.09%) and 4.75% (from 95.32 to 90.79%) for multi-unit and single-unit features respectively. MIM had best performance compared to other feature selection methods. Significance: These results suggest improved decoding performance can be achieved by using optimally selected features. The results based on clinically relevant performance metrics also suggest that the decoding algorithm can be made robust by using optimal features and feature selection algorithms. We believe that even a few percent increase in performance is important and improves the decoding accuracy of the machine learning algorithm potentially increasing the ease of use of a brain machine interface. PMID:29467602

Decoding the Dopamine Signal in Macaque Prefrontal Cortex: A Simulation Study Using the Cx3Dp Simulator

PubMed Central

Spühler, Isabelle Ayumi; Hauri, Andreas

2013-01-01

Dopamine transmission in the prefrontal cortex plays an important role in reward based learning, working memory and attention. Dopamine is thought to be released non-synaptically into the extracellular space and to reach distant receptors through diffusion. This simulation study examines how the dopamine signal might be decoded by the recipient neuron. The simulation was based on parameters from the literature and on our own quantified, structural data from macaque prefrontal area 10. The change in extracellular dopamine concentration was estimated at different distances from release sites and related to the affinity of the dopamine receptors. Due to the sparse and random distribution of release sites, a transient heterogeneous pattern of dopamine concentration emerges. Our simulation predicts, however, that at any point in the simulation volume there is sufficient dopamine to bind and activate high-affinity dopamine receptors. We propose that dopamine is broadcast to its distant receptors and any change from the local baseline concentration might be decoded by a transient change in the binding probability of dopamine receptors. Dopamine could thus provide a graduated ‘teaching’ signal to reinforce concurrently active synapses and cell assemblies. In conditions of highly reduced or highly elevated dopamine levels the simulations predict that relative changes in the dopamine signal can no longer be decoded, which might explain why cognitive deficits are observed in patients with Parkinson’s disease, or induced through drugs blocking dopamine reuptake. PMID:23951205

The VLSI design of an error-trellis syndrome decoder for certain convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Jensen, J. M.; Hsu, I.-S.; Truong, T. K.

1986-01-01

A recursive algorithm using the error-trellis decoding technique is developed to decode convolutional codes (CCs). An example, illustrating the very large scale integration (VLSI) architecture of such a decode, is given for a dual-K CC. It is demonstrated that such a decoder can be realized readily on a single chip with metal-nitride-oxide-semiconductor technology.

The VLSI design of error-trellis syndrome decoding for convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Jensen, J. M.; Truong, T. K.; Hsu, I. S.

1985-01-01

A recursive algorithm using the error-trellis decoding technique is developed to decode convolutional codes (CCs). An example, illustrating the very large scale integration (VLSI) architecture of such a decode, is given for a dual-K CC. It is demonstrated that such a decoder can be realized readily on a single chip with metal-nitride-oxide-semiconductor technology.

Image Decoding of Photonic Crystal Beads Array in the Microfluidic Chip for Multiplex Assays

PubMed Central

Yuan, Junjie; Zhao, Xiangwei; Wang, Xiaoxia; Gu, Zhongze

2014-01-01

Along with the miniaturization and intellectualization of biomedical instruments, the increasing demand of health monitoring at anywhere and anytime elevates the need for the development of point of care testing (POCT). Photonic crystal beads (PCBs) as one kind of good encoded microcarriers can be integrated with microfluidic chips in order to realize cost-effective and high sensitive multiplex bioassays. However, there are difficulties in analyzing them towards automated analysis due to the characters of the PCBs and the unique detection manner. In this paper, we propose a strategy to take advantage of automated image processing for the color decoding of the PCBs array in the microfluidic chip for multiplex assays. By processing and alignment of two modal images of epi-fluorescence and epi-white light, every intact bead in the image is accurately extracted and decoded by PC colors, which stand for the target species. This method, which shows high robustness and accuracy under various configurations, eliminates the high hardware requirement of spectroscopy analysis and user-interaction software, and provides adequate supports for the general automated analysis of POCT based on PCBs array. PMID:25341876

Hybrid WDM/OCDMA for next generation access network

NASA Astrophysics Data System (ADS)

Wang, Xu; Wada, Naoya; Miyazaki, T.; Cincotti, G.; Kitayama, Ken-ichi

2007-11-01

Hybrid wavelength division multiplexing/optical code division multiple access (WDM/OCDMA) passive optical network (PON), where asynchronous OCDMA traffic transmits over WDM network, can be one potential candidate for gigabit-symmetric fiber-to-the-home (FTTH) services. In a cost-effective WDM/OCDMA network, a large scale multi-port encoder/decoder can be employed in the central office, and a low cost encoder/decoder will be used in optical network unit (ONU). The WDM/OCDMA system could be one promising solution to the symmetric high capacity access network with high spectral efficiency, cost effective, good flexibility and enhanced security. Asynchronous WDM/OCDMA systems have been experimentally demonstrated using superstructured fiber Bragg gratings (SSFBG) and muti-port OCDMA en/decoders. The total throughput has reached above Tera-bit/s with spectral efficiency of about 0.41. The key enabling techniques include ultra-long SSFBG, multi-port E/D with high power contrast ratio, optical thresholding, differential phase shift keying modulation with balanced detection, forward error correction, and etc. Using multi-level modulation formats to carry multi-bit information with single pulse, the total capacity and spectral efficiency could be further enhanced.

Backwards compatible high dynamic range video compression

NASA Astrophysics Data System (ADS)

Dolzhenko, Vladimir; Chesnokov, Vyacheslav; Edirisinghe, Eran A.

2014-02-01

This paper presents a two layer CODEC architecture for high dynamic range video compression. The base layer contains the tone mapped video stream encoded with 8 bits per component which can be decoded using conventional equipment. The base layer content is optimized for rendering on low dynamic range displays. The enhancement layer contains the image difference, in perceptually uniform color space, between the result of inverse tone mapped base layer content and the original video stream. Prediction of the high dynamic range content reduces the redundancy in the transmitted data while still preserves highlights and out-of-gamut colors. Perceptually uniform colorspace enables using standard ratedistortion optimization algorithms. We present techniques for efficient implementation and encoding of non-uniform tone mapping operators with low overhead in terms of bitstream size and number of operations. The transform representation is based on human vision system model and suitable for global and local tone mapping operators. The compression techniques include predicting the transform parameters from previously decoded frames and from already decoded data for current frame. Different video compression techniques are compared: backwards compatible and non-backwards compatible using AVC and HEVC codecs.

A test of the role of the medial temporal lobe in single-word decoding.

PubMed

Osipowicz, Karol; Rickards, Tyler; Shah, Atif; Sharan, Ashwini; Sperling, Michael; Kahn, Waseem; Tracy, Joseph

2011-01-15

The degree to which the MTL system contributes to effective language skills is not well delineated. We sought to determine if the MTL plays a role in single-word decoding in healthy, normal skilled readers. The experiment follows from the implications of the dual-process model of single-word decoding, which provides distinct predictions about the nature of MTL involvement. The paradigm utilized word (regular and irregularly spelled words) and pseudoword (phonetically regular) stimuli that differed in their demand for non-lexical as opposed lexical decoding. The data clearly showed that the MTL system was not involved in single word decoding in skilled, native English readers. Neither the hippocampus nor the MTL system as a whole showed significant activation during lexical or non-lexical based decoding. The results provide evidence that lexical and non-lexical decoding are implemented by distinct but overlapping neuroanatomical networks. Non-lexical decoding appeared most uniquely associated with cuneus and fusiform gyrus activation biased toward the left hemisphere. In contrast, lexical decoding appeared associated with right middle frontal and supramarginal, and bilateral cerebellar activation. Both these decoding operations appeared in the context of a shared widespread network of activations including bilateral occipital cortex and superior frontal regions. These activations suggest that the absence of MTL involvement in either lexical or non-lexical decoding appears likely a function of the skilled reading ability of our sample such that whole-word recognition and retrieval processes do not utilize the declarative memory system, in the case of lexical decoding, and require only minimal analysis and recombination of the phonetic elements of a word, in the case of non-lexical decoding. Copyright © 2010 Elsevier Inc. All rights reserved.

A Test of the Role of the Medial Temporal Lobe in Single-Word Decoding

PubMed Central

Osipowicz, Karol; Rickards, Tyler; Shah, Atif; Sharan, Ashwini; Sperling, Michael; Kahn, Waseem; Tracy, Joseph

2012-01-01

The degree to which the MTL system contributes to effective language skills is not well delineated. We sought to determine if the MTL plays a role in single-word decoding in healthy, normal skilled readers. The experiment follows from the implications of the dual-process model of single-word decoding, which provides distinct predictions about the nature of MTL involvement. The paradigm utilized word (regular and irregularly spelled words) and pseudoword (phonetically regular) stimuli that differed in their demand for non-lexical as opposed lexical decoding. The data clearly showed that the MTL system was not involved in single word decoding in skilled, native English readers. Neither the hippocampus, nor the MTL system as a whole showed significant activation during lexical or non-lexical based decoding. The results provide evidence that lexical and non-lexical decoding are implemented by distinct but overlapping neuroanatomical networks. Non-lexical decoding appeared most uniquely associated with cuneus and fusiform gyrus activation biased toward the left hemisphere. In contrast, lexical decoding appeared associated with right middle frontal and supramarginal, and bilateral cerebellar activation. Both these decoding operations appeared in the context of a shared widespread network of activations including bilateral occipital cortex and superior frontal regions. These activations suggest that the absence of MTL involvement in either lexical or non-lexical decoding appears likely a function of the skilled reading ability of our sample such that whole-word recognition and retrieval processes do not utilize the declarative memory system, in the case of lexical decoding, and require only minimal analysis and recombination of the phonetic elements of a word, in the case of non-lexical decoding. PMID:20884357

LDPC-based iterative joint source-channel decoding for JPEG2000.

PubMed

Pu, Lingling; Wu, Zhenyu; Bilgin, Ali; Marcellin, Michael W; Vasic, Bane

2007-02-01

A framework is proposed for iterative joint source-channel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error-resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. Decoding is carried out jointly in an iterative fashion. Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance.

Belief propagation decoding of quantum channels by passing quantum messages

NASA Astrophysics Data System (ADS)

Renes, Joseph M.

2017-07-01

The belief propagation (BP) algorithm is a powerful tool in a wide range of disciplines from statistical physics to machine learning to computational biology, and is ubiquitous in decoding classical error-correcting codes. The algorithm works by passing messages between nodes of the factor graph associated with the code and enables efficient decoding of the channel, in some cases even up to the Shannon capacity. Here we construct the first BP algorithm which passes quantum messages on the factor graph and is capable of decoding the classical-quantum channel with pure state outputs. This gives explicit decoding circuits whose number of gates is quadratic in the code length. We also show that this decoder can be modified to work with polar codes for the pure state channel and as part of a decoder for transmitting quantum information over the amplitude damping channel. These represent the first explicit capacity-achieving decoders for non-Pauli channels.

Low Power LDPC Code Decoder Architecture Based on Intermediate Message Compression Technique

NASA Astrophysics Data System (ADS)

Shimizu, Kazunori; Togawa, Nozomu; Ikenaga, Takeshi; Goto, Satoshi

Reducing the power dissipation for LDPC code decoder is a major challenging task to apply it to the practical digital communication systems. In this paper, we propose a low power LDPC code decoder architecture based on an intermediate message-compression technique which features as follows: (i) An intermediate message compression technique enables the decoder to reduce the required memory capacity and write power dissipation. (ii) A clock gated shift register based intermediate message memory architecture enables the decoder to decompress the compressed messages in a single clock cycle while reducing the read power dissipation. The combination of the above two techniques enables the decoder to reduce the power dissipation while keeping the decoding throughput. The simulation results show that the proposed architecture improves the power efficiency up to 52% and 18% compared to that of the decoder based on the overlapped schedule and the rapid convergence schedule without the proposed techniques respectively.

Multiclass fMRI data decoding and visualization using supervised self-organizing maps.

PubMed

Hausfeld, Lars; Valente, Giancarlo; Formisano, Elia

2014-08-01

When multivariate pattern decoding is applied to fMRI studies entailing more than two experimental conditions, a most common approach is to transform the multiclass classification problem into a series of binary problems. Furthermore, for decoding analyses, classification accuracy is often the only outcome reported although the topology of activation patterns in the high-dimensional features space may provide additional insights into underlying brain representations. Here we propose to decode and visualize voxel patterns of fMRI datasets consisting of multiple conditions with a supervised variant of self-organizing maps (SSOMs). Using simulations and real fMRI data, we evaluated the performance of our SSOM-based approach. Specifically, the analysis of simulated fMRI data with varying signal-to-noise and contrast-to-noise ratio suggested that SSOMs perform better than a k-nearest-neighbor classifier for medium and large numbers of features (i.e. 250 to 1000 or more voxels) and similar to support vector machines (SVMs) for small and medium numbers of features (i.e. 100 to 600voxels). However, for a larger number of features (>800voxels), SSOMs performed worse than SVMs. When applied to a challenging 3-class fMRI classification problem with datasets collected to examine the neural representation of three human voices at individual speaker level, the SSOM-based algorithm was able to decode speaker identity from auditory cortical activation patterns. Classification performances were similar between SSOMs and other decoding algorithms; however, the ability to visualize decoding models and underlying data topology of SSOMs promotes a more comprehensive understanding of classification outcomes. We further illustrated this visualization ability of SSOMs with a re-analysis of a dataset examining the representation of visual categories in the ventral visual cortex (Haxby et al., 2001). This analysis showed that SSOMs could retrieve and visualize topography and neighborhood relations of the brain representation of eight visual categories. We conclude that SSOMs are particularly suited for decoding datasets consisting of more than two classes and are optimally combined with approaches that reduce the number of voxels used for classification (e.g. region-of-interest or searchlight approaches). Copyright © 2014. Published by Elsevier Inc.

Decoding Reveals Plasticity in V3A as a Result of Motion Perceptual Learning

PubMed Central

Shibata, Kazuhisa; Chang, Li-Hung; Kim, Dongho; Náñez, José E.; Kamitani, Yukiyasu; Watanabe, Takeo; Sasaki, Yuka

2012-01-01

Visual perceptual learning (VPL) is defined as visual performance improvement after visual experiences. VPL is often highly specific for a visual feature presented during training. Such specificity is observed in behavioral tuning function changes with the highest improvement centered on the trained feature and was originally thought to be evidence for changes in the early visual system associated with VPL. However, results of neurophysiological studies have been highly controversial concerning whether the plasticity underlying VPL occurs within the visual cortex. The controversy may be partially due to the lack of observation of neural tuning function changes in multiple visual areas in association with VPL. Here using human subjects we systematically compared behavioral tuning function changes after global motion detection training with decoded tuning function changes for 8 visual areas using pattern classification analysis on functional magnetic resonance imaging (fMRI) signals. We found that the behavioral tuning function changes were extremely highly correlated to decoded tuning function changes only in V3A, which is known to be highly responsive to global motion with human subjects. We conclude that VPL of a global motion detection task involves plasticity in a specific visual cortical area. PMID:22952849

Spatial domain entertainment audio decompression/compression

NASA Astrophysics Data System (ADS)

Chan, Y. K.; Tam, Ka Him K.

2014-02-01

The ARM7 NEON processor with 128bit SIMD hardware accelerator requires a peak performance of 13.99 Mega Cycles per Second for MP3 stereo entertainment quality decoding. For similar compression bit rate, OGG and AAC is preferred over MP3. The Patent Cooperation Treaty Application dated 28/August/2012 describes an audio decompression scheme producing a sequence of interleaving "min to Max" and "Max to min" rising and falling segments. The number of interior audio samples bound by "min to Max" or "Max to min" can be {0|1|…|N} audio samples. The magnitudes of samples, including the bounding min and Max, are distributed as normalized constants within the 0 and 1 of the bounding magnitudes. The decompressed audio is then a "sequence of static segments" on a frame by frame basis. Some of these frames needed to be post processed to elevate high frequency. The post processing is compression efficiency neutral and the additional decoding complexity is only a small fraction of the overall decoding complexity without the need of extra hardware. Compression efficiency can be speculated as very high as source audio had been decimated and converted to a set of data with only "segment length and corresponding segment magnitude" attributes. The PCT describes how these two attributes are efficiently coded by the PCT innovative coding scheme. The PCT decoding efficiency is obviously very high and decoding latency is basically zero. Both hardware requirement and run time is at least an order of magnitude better than MP3 variants. The side benefit is ultra low power consumption on mobile device. The acid test on how such a simplistic waveform representation can indeed reproduce authentic decompressed quality is benchmarked versus OGG(aoTuv Beta 6.03) by three pair of stereo audio frames and one broadcast like voice audio frame with each frame consisting 2,028 samples at 44,100KHz sampling frequency.

Multi-functional optical signal processing using optical spectrum control circuit

NASA Astrophysics Data System (ADS)

Hayashi, Shuhei; Ikeda, Tatsuhiko; Mizuno, Takayuki; Takahashi, Hiroshi; Tsuda, Hiroyuki

2015-02-01

Processing ultra-fast optical signals without optical/electronic conversion is in demand and time-to-space conversion has been proposed as an effective solution. We have designed and fabricated an arrayed-waveguide grating (AWG) based optical spectrum control circuit (OSCC) using silica planar lightwave circuit (PLC) technology. This device is composed of an AWG, tunable phase shifters and a mirror. The principle of signal processing is to spatially decompose the signal's frequency components by using the AWG. Then, the phase of each frequency component is controlled by the tunable phase shifters. Finally, the light is reflected back to the AWG by the mirror and synthesized. Amplitude of each frequency component can be controlled by distributing the power to high diffraction order light. The spectral controlling range of the OSCC is 100 GHz and its resolution is 1.67 GHz. This paper describes equipping the OSCC with optical coded division multiplex (OCDM) encoder/decoder functionality. The encoding principle is to apply certain phase patterns to the signal's frequency components and intentionally disperse the signal. The decoding principle is also to apply certain phase patterns to the frequency components at the receiving side. If the applied phase pattern compensates the intentional dispersion, the waveform is regenerated, but if the pattern is not appropriate, the waveform remains dispersed. We also propose an arbitrary filter function by exploiting the OSCC's amplitude and phase control attributes. For example, a filtered optical signal transmitted through multiple optical nodes that use the wavelength multiplexer/demultiplexer can be equalized.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1998-01-01

A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and sectionalization of trellises. Chapter 7 discusses trellis decomposition and subtrellises for low-weight codewords. Chapter 8 first presents well known methods for constructing long powerful codes from short component codes or component codes of smaller dimensions, and then provides methods for constructing their trellises which include Shannon and Cartesian product techniques. Chapter 9 deals with convolutional codes, puncturing, zero-tail termination and tail-biting.Chapters 10 through 13 present various trellis-based decoding algorithms, old and new. Chapter 10 first discusses the application of the well known Viterbi decoding algorithm to linear block codes, optimum sectionalization of a code trellis to minimize computation complexity, and design issues for IC (integrated circuit) implementation of a Viterbi decoder. Then it presents a new decoding algorithm for convolutional codes, named Differential Trellis Decoding (DTD) algorithm. Chapter 12 presents a suboptimum reliability-based iterative decoding algorithm with a low-weight trellis search for the most likely codeword. This decoding algorithm provides a good trade-off between error performance and decoding complexity. All the decoding algorithms presented in Chapters 10 through 12 are devised to minimize word error probability. Chapter 13 presents decoding algorithms that minimize bit error probability and provide the corresponding soft (reliability) information at the output of the decoder. Decoding algorithms presented are the MAP (maximum a posteriori probability) decoding algorithm and the Soft-Output Viterbi Algorithm (SOVA) algorithm. Finally, the minimization of bit error probability in trellis-based MLD is discussed.

Gamma-Ray Imaging Probes.

NASA Astrophysics Data System (ADS)

Wild, Walter James

1988-12-01

External nuclear medicine diagnostic imaging of early primary and metastatic lung cancer tumors is difficult due to the poor sensitivity and resolution of existing gamma cameras. Nonimaging counting detectors used for internal tumor detection give ambiguous results because distant background variations are difficult to discriminate from neighboring tumor sites. This suggests that an internal imaging nuclear medicine probe, particularly an esophageal probe, may be advantageously used to detect small tumors because of the ability to discriminate against background variations and the capability to get close to sites neighboring the esophagus. The design, theory of operation, preliminary bench tests, characterization of noise behavior and optimization of such an imaging probe is the central theme of this work. The central concept lies in the representation of the aperture shell by a sequence of binary digits. This, coupled with the mode of operation which is data encoding within an axial slice of space, leads to the fundamental imaging equation in which the coding operation is conveniently described by a circulant matrix operator. The coding/decoding process is a classic coded-aperture problem, and various estimators to achieve decoding are discussed. Some estimators require a priori information about the object (or object class) being imaged; the only unbiased estimator that does not impose this requirement is the simple inverse-matrix operator. The effects of noise on the estimate (or reconstruction) is discussed for general noise models and various codes/decoding operators. The choice of an optimal aperture for detector count times of clinical relevance is examined using a statistical class-separability formalism.

Buffer management for sequential decoding. [block erasure probability reduction

NASA Technical Reports Server (NTRS)

Layland, J. W.

1974-01-01

Sequential decoding has been found to be an efficient means of communicating at low undetected error rates from deep space probes, but erasure or computational overflow remains a significant problem. Erasure of a block occurs when the decoder has not finished decoding that block at the time that it must be output. By drawing upon analogies in computer time sharing, this paper develops a buffer-management strategy which reduces the decoder idle time to a negligible level, and therefore improves the erasure probability of a sequential decoder. For a decoder with a speed advantage of ten and a buffer size of ten blocks, operating at an erasure rate of .01, use of this buffer-management strategy reduces the erasure rate to less than .0001.

Shape-coded silica nanotubes for multiplexed bioassay: rapid and reliable magnetic decoding protocols

PubMed Central

He, Bo; Kim, Sung Kyoung; Son, Sang Jun; Lee, Sang Bok

2010-01-01

Aims The recent development of 1D barcode arrays has proved their capabilities to be applicable to highly multiplexed bioassays. This article introduces two magnetic decoding protocols for suspension arrays of shape-coded silica nanotubes to process multiplexed assays rapidly and easily, which will benefit the minimization and automation of the arrays. Methods In the first protocol, the magnetic nanocrystals are incorporated into the inner voids of barcoded silica nanotubes in order to give the nanotubes magnetic properties. The second protocol is performed by trapping the barcoded silica nanotubes onto streptavidin-modified magnetic beads. Results The rapid and easy decoding process was demonstrated by applying the above two protocols to multiplexed assays, resulting in high selectivity. Furthermore, the magnetic bead-trapped barcode nanotubes provided a great opportunity to exclude the use of dye molecules in multiplexed assays by using barcode nanotubes as signals. Conclusion The rapid and easy manipulation of encoded carriers using magnetic properties could be used to develop promising suspension arrays for portable bioassays. PMID:20025466

A low-cost, scalable, current-sensing digital headstage for high channel count μECoG.

PubMed

Trumpis, Michael; Insanally, Michele; Zou, Jialin; Elsharif, Ashraf; Ghomashchi, Ali; Sertac Artan, N; Froemke, Robert C; Viventi, Jonathan

2017-04-01

High channel count electrode arrays allow for the monitoring of large-scale neural activity at high spatial resolution. Implantable arrays featuring many recording sites require compact, high bandwidth front-end electronics. In the present study, we investigated the use of a small, light weight, and low cost digital current-sensing integrated circuit for acquiring cortical surface signals from a 61-channel micro-electrocorticographic (μECoG) array. We recorded both acute and chronic μECoG signal from rat auditory cortex using our novel digital current-sensing headstage. For direct comparison, separate recordings were made in the same anesthetized preparations using an analog voltage headstage. A model of electrode impedance explained the transformation between current- and voltage-sensed signals, and was used to reconstruct cortical potential. We evaluated the digital headstage using several metrics of the baseline and response signals. The digital current headstage recorded neural signal with similar spatiotemporal statistics and auditory frequency tuning compared to the voltage signal. The signal-to-noise ratio of auditory evoked responses (AERs) was significantly stronger in the current signal. Stimulus decoding based on true and reconstructed voltage signals were not significantly different. Recordings from an implanted system showed AERs that were detectable and decodable for 52 d. The reconstruction filter mitigated the thermal current noise of the electrode impedance and enhanced overall SNR. We developed and validated a novel approach to headstage acquisition that used current-input circuits to independently digitize 61 channels of μECoG measurements of the cortical field. These low-cost circuits, intended to measure photo-currents in digital imaging, not only provided a signal representing the local cortical field with virtually the same sensitivity and specificity as a traditional voltage headstage but also resulted in a small, light headstage that can easily be scaled to record from hundreds of channels.

A low-cost, scalable, current-sensing digital headstage for high channel count μECoG

NASA Astrophysics Data System (ADS)

Trumpis, Michael; Insanally, Michele; Zou, Jialin; Elsharif, Ashraf; Ghomashchi, Ali; Sertac Artan, N.; Froemke, Robert C.; Viventi, Jonathan

2017-04-01

Objective. High channel count electrode arrays allow for the monitoring of large-scale neural activity at high spatial resolution. Implantable arrays featuring many recording sites require compact, high bandwidth front-end electronics. In the present study, we investigated the use of a small, light weight, and low cost digital current-sensing integrated circuit for acquiring cortical surface signals from a 61-channel micro-electrocorticographic (μECoG) array. Approach. We recorded both acute and chronic μECoG signal from rat auditory cortex using our novel digital current-sensing headstage. For direct comparison, separate recordings were made in the same anesthetized preparations using an analog voltage headstage. A model of electrode impedance explained the transformation between current- and voltage-sensed signals, and was used to reconstruct cortical potential. We evaluated the digital headstage using several metrics of the baseline and response signals. Main results. The digital current headstage recorded neural signal with similar spatiotemporal statistics and auditory frequency tuning compared to the voltage signal. The signal-to-noise ratio of auditory evoked responses (AERs) was significantly stronger in the current signal. Stimulus decoding based on true and reconstructed voltage signals were not significantly different. Recordings from an implanted system showed AERs that were detectable and decodable for 52 d. The reconstruction filter mitigated the thermal current noise of the electrode impedance and enhanced overall SNR. Significance. We developed and validated a novel approach to headstage acquisition that used current-input circuits to independently digitize 61 channels of μECoG measurements of the cortical field. These low-cost circuits, intended to measure photo-currents in digital imaging, not only provided a signal representing the local cortical field with virtually the same sensitivity and specificity as a traditional voltage headstage but also resulted in a small, light headstage that can easily be scaled to record from hundreds of channels.

A low-cost, scalable, current-sensing digital headstage for high channel count μECoG

PubMed Central

Trumpis, Michael; Insanally, Michele; Zou, Jialin; Elsharif, Ashraf; Ghomashchi, Ali; Artan, N. Sertac; Froemke, Robert C.; Viventi, Jonathan

2017-01-01

Objective High channel count electrode arrays allow for the monitoring of large-scale neural activity at high spatial resolution. Implantable arrays featuring many recording sites require compact, high bandwidth front-end electronics. In the present study, we investigated the use of a small, light weight, and low cost digital current-sensing integrated circuit for acquiring cortical surface signals from a 61-channel micro-electrocorticographic (μECoG) array. Approach We recorded both acute and chronic μECoG signal from rat auditory cortex using our novel digital current-sensing headstage. For direct comparison, separate recordings were made in the same anesthetized preparations using an analog voltage headstage. A model of electrode impedance explained the transformation between current- and voltage-sensed signals, and was used to reconstruct cortical potential. We evaluated the digital headstage using several metrics of the baseline and response signals. Main results The digital current headstage recorded neural signal with similar spatiotemporal statistics and auditory frequency tuning compared to the voltage signal. The signal-to-noise ratio of auditory evoked responses (AERs) was significantly stronger in the current signal. Stimulus decoding based on true and reconstructed voltage signals were not significantly different. Recordings from an implanted system showed AERs that were detectable and decodable for 52 days. The reconstruction filter mitigated the thermal current noise of the electrode impedance and enhanced overall SNR. Significance We developed and validated a novel approach to headstage acquisition that used current-input circuits to independently digitize 61 channels of μECoG measurements of the cortical field. These low-cost circuits, intended to measure photo-currents in digital imaging, not only provided a signal representing the local cortical field with virtually the same sensitivity and specificity as a traditional voltage headstage but also resulted in a small, light headstage that can easily be scaled to record from hundreds of channels. PMID:28102827

A low-cost, multiplexed μECoG system for high-density recordings in freely moving rodents

NASA Astrophysics Data System (ADS)

Insanally, Michele; Trumpis, Michael; Wang, Charles; Chiang, Chia-Han; Woods, Virginia; Palopoli-Trojani, Kay; Bossi, Silvia; Froemke, Robert C.; Viventi, Jonathan

2016-04-01

Objective. Micro-electrocorticography (μECoG) offers a minimally invasive neural interface with high spatial resolution over large areas of cortex. However, electrode arrays with many contacts that are individually wired to external recording systems are cumbersome and make recordings in freely behaving rodents challenging. We report a novel high-density 60-electrode system for μECoG recording in freely moving rats. Approach. Multiplexed headstages overcome the problem of wiring complexity by combining signals from many electrodes to a smaller number of connections. We have developed a low-cost, multiplexed recording system with 60 contacts at 406 μm spacing. We characterized the quality of the electrode signals using multiple metrics that tracked spatial variation, evoked-response detectability, and decoding value. Performance of the system was validated both in anesthetized animals and freely moving awake animals. Main results. We recorded μECoG signals over the primary auditory cortex, measuring responses to acoustic stimuli across all channels. Single-trial responses had high signal-to-noise ratios (SNR) (up to 25 dB under anesthesia), and were used to rapidly measure network topography within ˜10 s by constructing all single-channel receptive fields in parallel. We characterized evoked potential amplitudes and spatial correlations across the array in the anesthetized and awake animals. Recording quality in awake animals was stable for at least 30 days. Finally, we used these responses to accurately decode auditory stimuli on single trials. Significance. This study introduces (1) a μECoG recording system based on practical hardware design and (2) a rigorous analytical method for characterizing the signal characteristics of μECoG electrode arrays. This methodology can be applied to evaluate the fidelity and lifetime of any μECoG electrode array. Our μECoG-based recording system is accessible and will be useful for studies of perception and decision-making in rodents, particularly over the entire time course of behavioral training and learning.

Classification of different reaching movements from the same limb using EEG

NASA Astrophysics Data System (ADS)

Shiman, Farid; López-Larraz, Eduardo; Sarasola-Sanz, Andrea; Irastorza-Landa, Nerea; Spüler, Martin; Birbaumer, Niels; Ramos-Murguialday, Ander

2017-08-01

Objective. Brain-computer-interfaces (BCIs) have been proposed not only as assistive technologies but also as rehabilitation tools for lost functions. However, due to the stochastic nature, poor spatial resolution and signal to noise ratio from electroencephalography (EEG), multidimensional decoding has been the main obstacle to implement non-invasive BCIs in real-live rehabilitation scenarios. This study explores the classification of several functional reaching movements from the same limb using EEG oscillations in order to create a more versatile BCI for rehabilitation. Approach. Nine healthy participants performed four 3D center-out reaching tasks in four different sessions while wearing a passive robotic exoskeleton at their right upper limb. Kinematics data were acquired from the robotic exoskeleton. Multiclass extensions of Filter Bank Common Spatial Patterns (FBCSP) and a linear discriminant analysis (LDA) classifier were used to classify the EEG activity into four forward reaching movements (from a starting position towards four target positions), a backward movement (from any of the targets to the starting position and rest). Recalibrating the classifier using data from previous or the same session was also investigated and compared. Main results. Average EEG decoding accuracy were significantly above chance with 67%, 62.75%, and 50.3% when decoding three, four and six tasks from the same limb, respectively. Furthermore, classification accuracy could be increased when using data from the beginning of each session as training data to recalibrate the classifier. Significance. Our results demonstrate that classification from several functional movements performed by the same limb is possible with acceptable accuracy using EEG oscillations, especially if data from the same session are used to recalibrate the classifier. Therefore, an ecologically valid decoding could be used to control assistive or rehabilitation mutli-degrees of freedom (DoF) robotic devices using EEG data. These results have important implications towards assistive and rehabilitative neuroprostheses control in paralyzed patients.

A Scalable Architecture of a Structured LDPC Decoder

NASA Technical Reports Server (NTRS)

Lee, Jason Kwok-San; Lee, Benjamin; Thorpe, Jeremy; Andrews, Kenneth; Dolinar, Sam; Hamkins, Jon

2004-01-01

We present a scalable decoding architecture for a certain class of structured LDPC codes. The codes are designed using a small (n,r) protograph that is replicated Z times to produce a decoding graph for a (Z x n, Z x r) code. Using this architecture, we have implemented a decoder for a (4096,2048) LDPC code on a Xilinx Virtex-II 2000 FPGA, and achieved decoding speeds of 31 Mbps with 10 fixed iterations. The implemented message-passing algorithm uses an optimized 3-bit non-uniform quantizer that operates with 0.2dB implementation loss relative to a floating point decoder.

Multiuser signal detection using sequential decoding

NASA Astrophysics Data System (ADS)

Xie, Zhenhua; Rushforth, Craig K.; Short, Robert T.

1990-05-01

The application of sequential decoding to the detection of data transmitted over the additive white Gaussian noise channel by K asynchronous transmitters using direct-sequence spread-spectrum multiple access is considered. A modification of Fano's (1963) sequential-decoding metric, allowing the messages from a given user to be safely decoded if its Eb/N0 exceeds -1.6 dB, is presented. Computer simulation is used to evaluate the performance of a sequential decoder that uses this metric in conjunction with the stack algorithm. In many circumstances, the sequential decoder achieves results comparable to those obtained using the much more complicated optimal receiver.

Complementary Reliability-Based Decodings of Binary Linear Block Codes

NASA Technical Reports Server (NTRS)

Fossorier, Marc P. C.; Lin, Shu

1997-01-01

This correspondence presents a hybrid reliability-based decoding algorithm which combines the reprocessing method based on the most reliable basis and a generalized Chase-type algebraic decoder based on the least reliable positions. It is shown that reprocessing with a simple additional algebraic decoding effort achieves significant coding gain. For long codes, the order of reprocessing required to achieve asymptotic optimum error performance is reduced by approximately 1/3. This significantly reduces the computational complexity, especially for long codes. Also, a more efficient criterion for stopping the decoding process is derived based on the knowledge of the algebraic decoding solution.

Multicore-based 3D-DWT video encoder

NASA Astrophysics Data System (ADS)

Galiano, Vicente; López-Granado, Otoniel; Malumbres, Manuel P.; Migallón, Hector

2013-12-01

Three-dimensional wavelet transform (3D-DWT) encoders are good candidates for applications like professional video editing, video surveillance, multi-spectral satellite imaging, etc. where a frame must be reconstructed as quickly as possible. In this paper, we present a new 3D-DWT video encoder based on a fast run-length coding engine. Furthermore, we present several multicore optimizations to speed-up the 3D-DWT computation. An exhaustive evaluation of the proposed encoder (3D-GOP-RL) has been performed, and we have compared the evaluation results with other video encoders in terms of rate/distortion (R/D), coding/decoding delay, and memory consumption. Results show that the proposed encoder obtains good R/D results for high-resolution video sequences with nearly in-place computation using only the memory needed to store a group of pictures. After applying the multicore optimization strategies over the 3D DWT, the proposed encoder is able to compress a full high-definition video sequence in real-time.

Simultaneous scalp electroencephalography (EEG), electromyography (EMG), and whole-body segmental inertial recording for multi-modal neural decoding.

PubMed

Bulea, Thomas C; Kilicarslan, Atilla; Ozdemir, Recep; Paloski, William H; Contreras-Vidal, Jose L

2013-07-26

Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG.

Local-learning-based neuron selection for grasping gesture prediction in motor brain machine interfaces

NASA Astrophysics Data System (ADS)

Xu, Kai; Wang, Yiwen; Wang, Yueming; Wang, Fang; Hao, Yaoyao; Zhang, Shaomin; Zhang, Qiaosheng; Chen, Weidong; Zheng, Xiaoxiang

2013-04-01

Objective. The high-dimensional neural recordings bring computational challenges to movement decoding in motor brain machine interfaces (mBMI), especially for portable applications. However, not all recorded neural activities relate to the execution of a certain movement task. This paper proposes to use a local-learning-based method to perform neuron selection for the gesture prediction in a reaching and grasping task. Approach. Nonlinear neural activities are decomposed into a set of linear ones in a weighted feature space. A margin is defined to measure the distance between inter-class and intra-class neural patterns. The weights, reflecting the importance of neurons, are obtained by minimizing a margin-based exponential error function. To find the most dominant neurons in the task, 1-norm regularization is introduced to the objective function for sparse weights, where near-zero weights indicate irrelevant neurons. Main results. The signals of only 10 neurons out of 70 selected by the proposed method could achieve over 95% of the full recording's decoding accuracy of gesture predictions, no matter which different decoding methods are used (support vector machine and K-nearest neighbor). The temporal activities of the selected neurons show visually distinguishable patterns associated with various hand states. Compared with other algorithms, the proposed method can better eliminate the irrelevant neurons with near-zero weights and provides the important neuron subset with the best decoding performance in statistics. The weights of important neurons converge usually within 10-20 iterations. In addition, we study the temporal and spatial variation of neuron importance along a period of one and a half months in the same task. A high decoding performance can be maintained by updating the neuron subset. Significance. The proposed algorithm effectively ascertains the neuronal importance without assuming any coding model and provides a high performance with different decoding models. It shows better robustness of identifying the important neurons with noisy signals presented. The low demand of computational resources which, reflected by the fast convergence, indicates the feasibility of the method applied in portable BMI systems. The ascertainment of the important neurons helps to inspect neural patterns visually associated with the movement task. The elimination of irrelevant neurons greatly reduces the computational burden of mBMI systems and maintains the performance with better robustness.

Reaction Decoder Tool (RDT): extracting features from chemical reactions.

PubMed

Rahman, Syed Asad; Torrance, Gilliean; Baldacci, Lorenzo; Martínez Cuesta, Sergio; Fenninger, Franz; Gopal, Nimish; Choudhary, Saket; May, John W; Holliday, Gemma L; Steinbeck, Christoph; Thornton, Janet M

2016-07-01

Extracting chemical features like Atom-Atom Mapping (AAM), Bond Changes (BCs) and Reaction Centres from biochemical reactions helps us understand the chemical composition of enzymatic reactions. Reaction Decoder is a robust command line tool, which performs this task with high accuracy. It supports standard chemical input/output exchange formats i.e. RXN/SMILES, computes AAM, highlights BCs and creates images of the mapped reaction. This aids in the analysis of metabolic pathways and the ability to perform comparative studies of chemical reactions based on these features. This software is implemented in Java, supported on Windows, Linux and Mac OSX, and freely available at https://github.com/asad/ReactionDecoder : asad@ebi.ac.uk or s9asad@gmail.com. © The Author 2016. Published by Oxford University Press.

Maximum likelihood convolutional decoding (MCD) performance due to system losses

NASA Technical Reports Server (NTRS)

Webster, L.

1976-01-01

A model for predicting the computational performance of a maximum likelihood convolutional decoder (MCD) operating in a noisy carrier reference environment is described. This model is used to develop a subroutine that will be utilized by the Telemetry Analysis Program to compute the MCD bit error rate. When this computational model is averaged over noisy reference phase errors using a high-rate interpolation scheme, the results are found to agree quite favorably with experimental measurements.

Decoding sound level in the marmoset primary auditory cortex.

PubMed

Sun, Wensheng; Marongelli, Ellisha N; Watkins, Paul V; Barbour, Dennis L

2017-10-01

Neurons that respond favorably to a particular sound level have been observed throughout the central auditory system, becoming steadily more common at higher processing areas. One theory about the role of these level-tuned or nonmonotonic neurons is the level-invariant encoding of sounds. To investigate this theory, we simulated various subpopulations of neurons by drawing from real primary auditory cortex (A1) neuron responses and surveyed their performance in forming different sound level representations. Pure nonmonotonic subpopulations did not provide the best level-invariant decoding; instead, mixtures of monotonic and nonmonotonic neurons provided the most accurate decoding. For level-fidelity decoding, the inclusion of nonmonotonic neurons slightly improved or did not change decoding accuracy until they constituted a high proportion. These results indicate that nonmonotonic neurons fill an encoding role complementary to, rather than alternate to, monotonic neurons. NEW & NOTEWORTHY Neurons with nonmonotonic rate-level functions are unique to the central auditory system. These level-tuned neurons have been proposed to account for invariant sound perception across sound levels. Through systematic simulations based on real neuron responses, this study shows that neuron populations perform sound encoding optimally when containing both monotonic and nonmonotonic neurons. The results indicate that instead of working independently, nonmonotonic neurons complement the function of monotonic neurons in different sound-encoding contexts. Copyright © 2017 the American Physiological Society.

Simultaneous real-time monitoring of multiple cortical systems.

PubMed

Gupta, Disha; Jeremy Hill, N; Brunner, Peter; Gunduz, Aysegul; Ritaccio, Anthony L; Schalk, Gerwin

2014-10-01

Real-time monitoring of the brain is potentially valuable for performance monitoring, communication, training or rehabilitation. In natural situations, the brain performs a complex mix of various sensory, motor or cognitive functions. Thus, real-time brain monitoring would be most valuable if (a) it could decode information from multiple brain systems simultaneously, and (b) this decoding of each brain system were robust to variations in the activity of other (unrelated) brain systems. Previous studies showed that it is possible to decode some information from different brain systems in retrospect and/or in isolation. In our study, we set out to determine whether it is possible to simultaneously decode important information about a user from different brain systems in real time, and to evaluate the impact of concurrent activity in different brain systems on decoding performance. We study these questions using electrocorticographic signals recorded in humans. We first document procedures for generating stable decoding models given little training data, and then report their use for offline and for real-time decoding from 12 subjects (six for offline parameter optimization, six for online experimentation). The subjects engage in tasks that involve movement intention, movement execution and auditory functions, separately, and then simultaneously. Main Results: Our real-time results demonstrate that our system can identify intention and movement periods in single trials with an accuracy of 80.4% and 86.8%, respectively (where 50% would be expected by chance). Simultaneously, the decoding of the power envelope of an auditory stimulus resulted in an average correlation coefficient of 0.37 between the actual and decoded power envelopes. These decoders were trained separately and executed simultaneously in real time. This study yielded the first demonstration that it is possible to decode simultaneously the functional activity of multiple independent brain systems. Our comparison of univariate and multivariate decoding strategies, and our analysis of the influence of their decoding parameters, provides benchmarks and guidelines for future research on this topic.

Simultaneous Real-Time Monitoring of Multiple Cortical Systems

PubMed Central

Gupta, Disha; Hill, N. Jeremy; Brunner, Peter; Gunduz, Aysegul; Ritaccio, Anthony L.; Schalk, Gerwin

2014-01-01

Objective Real-time monitoring of the brain is potentially valuable for performance monitoring, communication, training or rehabilitation. In natural situations, the brain performs a complex mix of various sensory, motor, or cognitive functions. Thus, real-time brain monitoring would be most valuable if (a) it could decode information from multiple brain systems simultaneously, and (b) this decoding of each brain system were robust to variations in the activity of other (unrelated) brain systems. Previous studies showed that it is possible to decode some information from different brain systems in retrospect and/or in isolation. In our study, we set out to determine whether it is possible to simultaneously decode important information about a user from different brain systems in real time, and to evaluate the impact of concurrent activity in different brain systems on decoding performance. Approach We study these questions using electrocorticographic (ECoG) signals recorded in humans. We first document procedures for generating stable decoding models given little training data, and then report their use for offline and for real-time decoding from 12 subjects (6 for offline parameter optimization, 6 for online experimentation). The subjects engage in tasks that involve movement intention, movement execution and auditory functions, separately, and then simultaneously. Main results Our real-time results demonstrate that our system can identify intention and movement periods in single trials with an accuracy of 80.4% and 86.8%, respectively (where 50% would be expected by chance). Simultaneously, the decoding of the power envelope of an auditory stimulus resulted in an average correlation coefficient of 0.37 between the actual and decoded power envelope. These decoders were trained separately and executed simultaneously in real time. Significance This study yielded the first demonstration that it is possible to decode simultaneously the functional activity of multiple independent brain systems. Our comparison of univariate and multivariate decoding strategies, and our analysis of the influence of their decoding parameters, provides benchmarks and guidelines for future research on this topic. PMID:25080161

The ribosome as an optimal decoder: a lesson in molecular recognition.

PubMed

Savir, Yonatan; Tlusty, Tsvi

2013-04-11

The ribosome is a complex molecular machine that, in order to synthesize proteins, has to decode mRNAs by pairing their codons with matching tRNAs. Decoding is a major determinant of fitness and requires accurate and fast selection of correct tRNAs among many similar competitors. However, it is unclear whether the modern ribosome, and in particular its large conformational changes during decoding, are the outcome of adaptation to its task as a decoder or the result of other constraints. Here, we derive the energy landscape that provides optimal discrimination between competing substrates and thereby optimal tRNA decoding. We show that the measured landscape of the prokaryotic ribosome is sculpted in this way. This model suggests that conformational changes of the ribosome and tRNA during decoding are means to obtain an optimal decoder. Our analysis puts forward a generic mechanism that may be utilized broadly by molecular recognition systems. Copyright © 2013 Elsevier Inc. All rights reserved.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; An Iterative Decoding Algorithm for Linear Block Codes Based on a Low-Weight Trellis Search

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc

1998-01-01

For long linear block codes, maximum likelihood decoding based on full code trellises would be very hard to implement if not impossible. In this case, we may wish to trade error performance for the reduction in decoding complexity. Sub-optimum soft-decision decoding of a linear block code based on a low-weight sub-trellis can be devised to provide an effective trade-off between error performance and decoding complexity. This chapter presents such a suboptimal decoding algorithm for linear block codes. This decoding algorithm is iterative in nature and based on an optimality test. It has the following important features: (1) a simple method to generate a sequence of candidate code-words, one at a time, for test; (2) a sufficient condition for testing a candidate code-word for optimality; and (3) a low-weight sub-trellis search for finding the most likely (ML) code-word.

Enhanced decoding for the Galileo S-band mission

NASA Technical Reports Server (NTRS)

Dolinar, S.; Belongie, M.

1993-01-01

A coding system under consideration for the Galileo S-band low-gain antenna mission is a concatenated system using a variable redundancy Reed-Solomon outer code and a (14,1/4) convolutional inner code. The 8-bit Reed-Solomon symbols are interleaved to depth 8, and the eight 255-symbol codewords in each interleaved block have redundancies 64, 20, 20, 20, 64, 20, 20, and 20, respectively (or equivalently, the codewords have 191, 235, 235, 235, 191, 235, 235, and 235 8-bit information symbols, respectively). This concatenated code is to be decoded by an enhanced decoder that utilizes a maximum likelihood (Viterbi) convolutional decoder; a Reed Solomon decoder capable of processing erasures; an algorithm for declaring erasures in undecoded codewords based on known erroneous symbols in neighboring decodable words; a second Viterbi decoding operation (redecoding) constrained to follow only paths consistent with the known symbols from previously decodable Reed-Solomon codewords; and a second Reed-Solomon decoding operation using the output from the Viterbi redecoder and additional erasure declarations to the extent possible. It is estimated that this code and decoder can achieve a decoded bit error rate of 1 x 10(exp 7) at a concatenated code signal-to-noise ratio of 0.76 dB. By comparison, a threshold of 1.17 dB is required for a baseline coding system consisting of the same (14,1/4) convolutional code, a (255,223) Reed-Solomon code with constant redundancy 32 also interleaved to depth 8, a one-pass Viterbi decoder, and a Reed Solomon decoder incapable of declaring or utilizing erasures. The relative gain of the enhanced system is thus 0.41 dB. It is predicted from analysis based on an assumption of infinite interleaving that the coding gain could be further improved by approximately 0.2 dB if four stages of Viterbi decoding and four levels of Reed-Solomon redundancy are permitted. Confirmation of this effect and specification of the optimum four-level redundancy profile for depth-8 interleaving is currently being done.

LDPC Codes with Minimum Distance Proportional to Block Size

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher; Dolinar, Samuel; Thorpe, Jeremy

2009-01-01

Low-density parity-check (LDPC) codes characterized by minimum Hamming distances proportional to block sizes have been demonstrated. Like the codes mentioned in the immediately preceding article, the present codes are error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels. The previously mentioned codes have low decoding thresholds and reasonably low error floors. However, the minimum Hamming distances of those codes do not grow linearly with code-block sizes. Codes that have this minimum-distance property exhibit very low error floors. Examples of such codes include regular LDPC codes with variable degrees of at least 3. Unfortunately, the decoding thresholds of regular LDPC codes are high. Hence, there is a need for LDPC codes characterized by both low decoding thresholds and, in order to obtain acceptably low error floors, minimum Hamming distances that are proportional to code-block sizes. The present codes were developed to satisfy this need. The minimum Hamming distances of the present codes have been shown, through consideration of ensemble-average weight enumerators, to be proportional to code block sizes. As in the cases of irregular ensembles, the properties of these codes are sensitive to the proportion of degree-2 variable nodes. A code having too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code having too many such nodes tends not to exhibit a minimum distance that is proportional to block size. Results of computational simulations have shown that the decoding thresholds of codes of the present type are lower than those of regular LDPC codes. Included in the simulations were a few examples from a family of codes characterized by rates ranging from low to high and by thresholds that adhere closely to their respective channel capacity thresholds; the simulation results from these examples showed that the codes in question have low error floors as well as low decoding thresholds. As an example, the illustration shows the protograph (which represents the blueprint for overall construction) of one proposed code family for code rates greater than or equal to 1.2. Any size LDPC code can be obtained by copying the protograph structure N times, then permuting the edges. The illustration also provides Field Programmable Gate Array (FPGA) hardware performance simulations for this code family. In addition, the illustration provides minimum signal-to-noise ratios (Eb/No) in decibels (decoding thresholds) to achieve zero error rates as the code block size goes to infinity for various code rates. In comparison with the codes mentioned in the preceding article, these codes have slightly higher decoding thresholds.

Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data.

PubMed

Grootswagers, Tijl; Wardle, Susan G; Carlson, Thomas A

2017-04-01

Multivariate pattern analysis (MVPA) or brain decoding methods have become standard practice in analyzing fMRI data. Although decoding methods have been extensively applied in brain-computer interfaces, these methods have only recently been applied to time series neuroimaging data such as MEG and EEG to address experimental questions in cognitive neuroscience. In a tutorial style review, we describe a broad set of options to inform future time series decoding studies from a cognitive neuroscience perspective. Using example MEG data, we illustrate the effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to "decode" different perceptual stimuli or cognitive states over time from dynamic brain activation patterns. We show that decisions made at both preprocessing (e.g., dimensionality reduction, subsampling, trial averaging) and decoding (e.g., classifier selection, cross-validation design) stages of the analysis can significantly affect the results. In addition to standard decoding, we describe extensions to MVPA for time-varying neuroimaging data including representational similarity analysis, temporal generalization, and the interpretation of classifier weight maps. Finally, we outline important caveats in the design and interpretation of time series decoding experiments.

A Parallel Decoding Algorithm for Short Polar Codes Based on Error Checking and Correcting

PubMed Central

Pan, Xiaofei; Pan, Kegang; Ye, Zhan; Gong, Chao

2014-01-01

We propose a parallel decoding algorithm based on error checking and correcting to improve the performance of the short polar codes. In order to enhance the error-correcting capacity of the decoding algorithm, we first derive the error-checking equations generated on the basis of the frozen nodes, and then we introduce the method to check the errors in the input nodes of the decoder by the solutions of these equations. In order to further correct those checked errors, we adopt the method of modifying the probability messages of the error nodes with constant values according to the maximization principle. Due to the existence of multiple solutions of the error-checking equations, we formulate a CRC-aided optimization problem of finding the optimal solution with three different target functions, so as to improve the accuracy of error checking. Besides, in order to increase the throughput of decoding, we use a parallel method based on the decoding tree to calculate probability messages of all the nodes in the decoder. Numerical results show that the proposed decoding algorithm achieves better performance than that of some existing decoding algorithms with the same code length. PMID:25540813

Decoding Facial Expressions: A New Test with Decoding Norms.

ERIC Educational Resources Information Center

Leathers, Dale G.; Emigh, Ted H.

1980-01-01

Describes the development and testing of a new facial meaning sensitivity test designed to determine how specialized are the meanings that can be decoded from facial expressions. Demonstrates the use of the test to measure a receiver's current level of skill in decoding facial expressions. (JMF)

Tail Biting Trellis Representation of Codes: Decoding and Construction

NASA Technical Reports Server (NTRS)

Shao. Rose Y.; Lin, Shu; Fossorier, Marc

1999-01-01

This paper presents two new iterative algorithms for decoding linear codes based on their tail biting trellises, one is unidirectional and the other is bidirectional. Both algorithms are computationally efficient and achieves virtually optimum error performance with a small number of decoding iterations. They outperform all the previous suboptimal decoding algorithms. The bidirectional algorithm also reduces decoding delay. Also presented in the paper is a method for constructing tail biting trellises for linear block codes.

Reliability of directional information in unsorted spikes and local field potentials recorded in human motor cortex

PubMed Central

Perge, János A.; Zhang, Shaomin; Malik, Wasim Q.; Homer, Mark L.; Cash, Sydney; Friehs, Gerhard; Eskandar, Emad N.; Donoghue, John P.; Hochberg, Leigh R.

2014-01-01

Objective Action potentials and local field potentials (LFPs) recorded in primary motor cortex contain information about the direction of movement. LFPs are assumed to be more robust to signal instabilities than action potentials, which makes LFPs along with action potentials a promising signal source for brain-computer interface applications. Still, relatively little research has directly compared the utility of LFPs to action potentials in decoding movement direction in human motor cortex. Approach We conducted intracortical multielectrode recordings in motor cortex of two persons (T2 and [S3]) as they performed a motor imagery task. We then compared the offline decoding performance of LFPs and spiking extracted from the same data recorded across a one-year period in each participant. Main results We obtained offline prediction accuracy of movement direction and endpoint velocity in multiple LFP bands, with the best performance in the highest (200–400Hz) LFP frequency band, presumably also containing low-pass filtered action potentials. Cross-frequency correlations of preferred directions and directional modulation index showed high similarity of directional information between action potential firing rates (spiking) and high frequency LFPs (70–400Hz), and increasing disparity with lower frequency bands (0–7, 10–40 and 50–65Hz). Spikes predicted the direction of intended movement more accurately than any individual LFP band, however combined decoding of all LFPs was statistically indistinguishable from spike based performance. As the quality of spiking signals (i.e. signal amplitude) and the number of significantly modulated spiking units decreased, the offline decoding performance decreased 3.6[5.65]%/month (for T2 and [S3] respectively). The decrease in the number of significantly modulated LFP signals and their decoding accuracy followed a similar trend (2.4[2.85]%/month, ANCOVA, p=0.27[0.03]). Significance Field potentials provided comparable offline decoding performance to unsorted spikes. Thus, LFPs may provide useful external device control using current human intracortical recording technology. (Clinical trial registration number: NCT00912041) PMID:24921388

Reversible wavelet filter banks with side informationless spatially adaptive low-pass filters

NASA Astrophysics Data System (ADS)

Abhayaratne, Charith

2011-07-01

Wavelet transforms that have an adaptive low-pass filter are useful in applications that require the signal singularities, sharp transitions, and image edges to be left intact in the low-pass signal. In scalable image coding, the spatial resolution scalability is achieved by reconstructing the low-pass signal subband, which corresponds to the desired resolution level, and discarding other high-frequency wavelet subbands. In such applications, it is vital to have low-pass subbands that are not affected by smoothing artifacts associated with low-pass filtering. We present the mathematical framework for achieving 1-D wavelet transforms that have a spatially adaptive low-pass filter (SALP) using the prediction-first lifting scheme. The adaptivity decisions are computed using the wavelet coefficients, and no bookkeeping is required for the perfect reconstruction. Then, 2-D wavelet transforms that have a spatially adaptive low-pass filter are designed by extending the 1-D SALP framework. Because the 2-D polyphase decompositions are used in this case, the 2-D adaptivity decisions are made nonseparable as opposed to the separable 2-D realization using 1-D transforms. We present examples using the 2-D 5/3 wavelet transform and their lossless image coding and scalable decoding performances in terms of quality and resolution scalability. The proposed 2-D-SALP scheme results in better performance compared to the existing adaptive update lifting schemes.

Decoding and Encoding Facial Expressions in Preschool-Age Children.

ERIC Educational Resources Information Center

Zuckerman, Miron; Przewuzman, Sylvia J.

1979-01-01

Preschool-age children drew, decoded, and encoded facial expressions depicting five different emotions. Accuracy of drawing, decoding and encoding each of the five emotions was consistent across the three tasks; decoding ability was correlated with drawing ability among female subjects, but neither of these abilities was correlated with encoding…

Multichannel error correction code decoder

NASA Technical Reports Server (NTRS)

Wagner, Paul K.; Ivancic, William D.

1993-01-01

A brief overview of a processing satellite for a mesh very-small-aperture (VSAT) communications network is provided. The multichannel error correction code (ECC) decoder system, the uplink signal generation and link simulation equipment, and the time-shared decoder are described. The testing is discussed. Applications of the time-shared decoder are recommended.

Using precise word timing information improves decoding accuracy in a multiband-accelerated multimodal reading experiment.

PubMed

Vu, An T; Phillips, Jeffrey S; Kay, Kendrick; Phillips, Matthew E; Johnson, Matthew R; Shinkareva, Svetlana V; Tubridy, Shannon; Millin, Rachel; Grossman, Murray; Gureckis, Todd; Bhattacharyya, Rajan; Yacoub, Essa

2016-01-01

The blood-oxygen-level-dependent (BOLD) signal measured in functional magnetic resonance imaging (fMRI) experiments is generally regarded as sluggish and poorly suited for probing neural function at the rapid timescales involved in sentence comprehension. However, recent studies have shown the value of acquiring data with very short repetition times (TRs), not merely in terms of improvements in contrast to noise ratio (CNR) through averaging, but also in terms of additional fine-grained temporal information. Using multiband-accelerated fMRI, we achieved whole-brain scans at 3-mm resolution with a TR of just 500 ms at both 3T and 7T field strengths. By taking advantage of word timing information, we found that word decoding accuracy across two separate sets of scan sessions improved significantly, with better overall performance at 7T than at 3T. The effect of TR was also investigated; we found that substantial word timing information can be extracted using fast TRs, with diminishing benefits beyond TRs of 1000 ms.

Method and apparatus for ultra-high-sensitivity, incremental and absolute optical encoding

NASA Technical Reports Server (NTRS)

Leviton, Douglas B. (Inventor)

1999-01-01

An absolute optical linear or rotary encoder which encodes the motion of an object (3) with increased resolution and encoding range and decreased sensitivity to damage to the scale includes a scale (5), which moves with the object and is illuminated by a light source (11). The scale carries a pattern (9) which is imaged by a microscope optical system (13) on a CCD array (17) in a camera head (15). The pattern includes both fiducial markings (31) which are identical for each period of the pattern and code areas (33) which include binary codings of numbers identifying the individual periods of the pattern. The image of the pattern formed on the CCD array is analyzed by an image processor (23) to locate the fiducial marking, decode the information encoded in the code area, and thereby determine the position of the object.

Design, fabrication and characterization of Computer Generated Holograms for anti-counterfeiting applications using OAM beams as light decoders.

PubMed

Ruffato, Gianluca; Rossi, Roberto; Massari, Michele; Mafakheri, Erfan; Capaldo, Pietro; Romanato, Filippo

2017-12-21

In this paper, we present the design, fabrication and optical characterization of computer-generated holograms (CGH) encoding information for light beams carrying orbital angular momentum (OAM). Through the use of a numerical code, based on an iterative Fourier transform algorithm, a phase-only diffractive optical element (PO-DOE) specifically designed for OAM illumination has been computed, fabricated and tested. In order to shape the incident beam into a helicoidal phase profile and generate light carrying phase singularities, a method based on transmission through high-order spiral phase plates (SPPs) has been used. The phase pattern of the designed holographic DOEs has been fabricated using high-resolution Electron-Beam Lithography (EBL) over glass substrates coated with a positive photoresist layer (polymethylmethacrylate). To the best of our knowledge, the present study is the first attempt, in a comprehensive work, to design, fabricate and characterize computer-generated holograms encoding information for structured light carrying OAM and phase singularities. These optical devices appear promising as high-security optical elements for anti-counterfeiting applications.

A software simulation study of a (255,223) Reed-Solomon encoder-decoder

NASA Technical Reports Server (NTRS)

Pollara, F.

1985-01-01

A set of software programs which simulates a (255,223) Reed-Solomon encoder/decoder pair is described. The transform decoder algorithm uses a modified Euclid algorithm, and closely follows the pipeline architecture proposed for the hardware decoder. Uncorrectable error patterns are detected by a simple test, and the inverse transform is computed by a finite field FFT. Numerical examples of the decoder operation are given for some test codewords, with and without errors. The use of the software package is briefly described.

Accumulate Repeat Accumulate Coded Modulation

NASA Technical Reports Server (NTRS)

Abbasfar, Aliazam; Divsalar, Dariush; Yao, Kung

2004-01-01

In this paper we propose an innovative coded modulation scheme called 'Accumulate Repeat Accumulate Coded Modulation' (ARA coded modulation). This class of codes can be viewed as serial turbo-like codes, or as a subclass of Low Density Parity Check (LDPC) codes that are combined with high level modulation. Thus at the decoder belief propagation can be used for iterative decoding of ARA coded modulation on a graph, provided a demapper transforms the received in-phase and quadrature samples to reliability of the bits.

The basis of orientation decoding in human primary visual cortex: fine- or coarse-scale biases?

PubMed

Maloney, Ryan T

2015-01-01

Orientation signals in human primary visual cortex (V1) can be reliably decoded from the multivariate pattern of activity as measured with functional magnetic resonance imaging (fMRI). The precise underlying source of these decoded signals (whether by orientation biases at a fine or coarse scale in cortex) remains a matter of some controversy, however. Freeman and colleagues (J Neurosci 33: 19695-19703, 2013) recently showed that the accuracy of decoding of spiral patterns in V1 can be predicted by a voxel's preferred spatial position (the population receptive field) and its coarse orientation preference, suggesting that coarse-scale biases are sufficient for orientation decoding. Whether they are also necessary for decoding remains an open question, and one with implications for the broader interpretation of multivariate decoding results in fMRI studies. Copyright © 2015 the American Physiological Society.

Emotion Decoding and Incidental Processing Fluency as Antecedents of Attitude Certainty.

PubMed

Petrocelli, John V; Whitmire, Melanie B

2017-07-01

Previous research demonstrates that attitude certainty influences the degree to which an attitude changes in response to persuasive appeals. In the current research, decoding emotions from facial expressions and incidental processing fluency, during attitude formation, are examined as antecedents of both attitude certainty and attitude change. In Experiment 1, participants who decoded anger or happiness during attitude formation expressed their greater attitude certainty, and showed more resistance to persuasion than participants who decoded sadness. By manipulating the emotion decoded, the diagnosticity of processing fluency experienced during emotion decoding, and the gaze direction of the social targets, Experiment 2 suggests that the link between emotion decoding and attitude certainty results from incidental processing fluency. Experiment 3 demonstrated that fluency in processing irrelevant stimuli influences attitude certainty, which in turn influences resistance to persuasion. Implications for appraisal-based accounts of attitude formation and attitude change are discussed.

Deep Learning Methods for Improved Decoding of Linear Codes

NASA Astrophysics Data System (ADS)

Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair

2018-02-01

The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.

A Low-Complexity Euclidean Orthogonal LDPC Architecture for Low Power Applications.

PubMed

Revathy, M; Saravanan, R

2015-01-01

Low-density parity-check (LDPC) codes have been implemented in latest digital video broadcasting, broadband wireless access (WiMax), and fourth generation of wireless standards. In this paper, we have proposed a high efficient low-density parity-check code (LDPC) decoder architecture for low power applications. This study also considers the design and analysis of check node and variable node units and Euclidean orthogonal generator in LDPC decoder architecture. The Euclidean orthogonal generator is used to reduce the error rate of the proposed LDPC architecture, which can be incorporated between check and variable node architecture. This proposed decoder design is synthesized on Xilinx 9.2i platform and simulated using Modelsim, which is targeted to 45 nm devices. Synthesis report proves that the proposed architecture greatly reduces the power consumption and hardware utilizations on comparing with different conventional architectures.

Entanglement-assisted quantum quasicyclic low-density parity-check codes

NASA Astrophysics Data System (ADS)

Hsieh, Min-Hsiu; Brun, Todd A.; Devetak, Igor

2009-03-01

We investigate the construction of quantum low-density parity-check (LDPC) codes from classical quasicyclic (QC) LDPC codes with girth greater than or equal to 6. We have shown that the classical codes in the generalized Calderbank-Skor-Steane construction do not need to satisfy the dual-containing property as long as preshared entanglement is available to both sender and receiver. We can use this to avoid the many four cycles which typically arise in dual-containing LDPC codes. The advantage of such quantum codes comes from the use of efficient decoding algorithms such as sum-product algorithm (SPA). It is well known that in the SPA, cycles of length 4 make successive decoding iterations highly correlated and hence limit the decoding performance. We show the principle of constructing quantum QC-LDPC codes which require only small amounts of initial shared entanglement.

Decoding Children's Expressions of Affect.

ERIC Educational Resources Information Center

Feinman, Joel A.; Feldman, Robert S.

Mothers' ability to decode the emotional expressions of their male and female children was compared to the decoding ability of non-mothers. Happiness, sadness, fear and anger were induced in children in situations that varied in terms of spontaneous and role-played encoding modes. It was hypothesized that mothers would be more accurate decoders of…

Decoding Area Studies and Interdisciplinary Majors: Building a Framework for Entry-Level Students

ERIC Educational Resources Information Center

MacPherson, Kristina Ruth

2015-01-01

Decoding disciplinary expertise for novices is increasingly part of the undergraduate curriculum. But how might area studies and other interdisciplinary programs, which require integration of courses from multiple disciplines, decode expertise in a similar fashion? Additionally, as a part of decoding area studies and interdisciplines, how might a…

47 CFR 11.12 - Two-tone Attention Signal encoder and decoder.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 1 2011-10-01 2011-10-01 false Two-tone Attention Signal encoder and decoder... SYSTEM (EAS) General § 11.12 Two-tone Attention Signal encoder and decoder. Existing two-tone Attention Signal encoder and decoder equipment type accepted for use as Emergency Broadcast System equipment under...

47 CFR 11.12 - Two-tone Attention Signal encoder and decoder.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 1 2010-10-01 2010-10-01 false Two-tone Attention Signal encoder and decoder... SYSTEM (EAS) General § 11.12 Two-tone Attention Signal encoder and decoder. Existing two-tone Attention Signal encoder and decoder equipment type accepted for use as Emergency Broadcast System equipment under...

Sequential Syndrome Decoding of Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1984-01-01

The algebraic structure of convolutional codes are reviewed and sequential syndrome decoding is applied to those codes. These concepts are then used to realize by example actual sequential decoding, using the stack algorithm. The Fano metric for use in sequential decoding is modified so that it can be utilized to sequentially find the minimum weight error sequence.

On decoding of multi-level MPSK modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Gupta, Alok Kumar

1990-01-01

The decoding problem of multi-level block modulation codes is investigated. The hardware design of soft-decision Viterbi decoder for some short length 8-PSK block modulation codes is presented. An effective way to reduce the hardware complexity of the decoder by reducing the branch metric and path metric, using a non-uniform floating-point to integer mapping scheme, is proposed and discussed. The simulation results of the design are presented. The multi-stage decoding (MSD) of multi-level modulation codes is also investigated. The cases of soft-decision and hard-decision MSD are considered and their performance are evaluated for several codes of different lengths and different minimum squared Euclidean distances. It is shown that the soft-decision MSD reduces the decoding complexity drastically and it is suboptimum. The hard-decision MSD further simplifies the decoding while still maintaining a reasonable coding gain over the uncoded system, if the component codes are chosen properly. Finally, some basic 3-level 8-PSK modulation codes using BCH codes as component codes are constructed and their coding gains are found for hard decision multistage decoding.

Contributions of phonological awareness, phonological short-term memory, and rapid automated naming, toward decoding ability in students with mild intellectual disability.

PubMed

Soltani, Amanallah; Roslan, Samsilah

2013-03-01

Reading decoding ability is a fundamental skill to acquire word-specific orthographic information necessary for skilled reading. Decoding ability and its underlying phonological processing skills have been heavily investigated typically among developing students. However, the issue has rarely been noticed among students with intellectual disability who commonly suffer from reading decoding problems. This study is aimed at determining the contributions of phonological awareness, phonological short-term memory, and rapid automated naming, as three well known phonological processing skills, to decoding ability among 60 participants with mild intellectual disability of unspecified origin ranging from 15 to 23 years old. The results of the correlation analysis revealed that all three aspects of phonological processing are significantly correlated with decoding ability. Furthermore, a series of hierarchical regression analysis indicated that after controlling the effect of IQ, phonological awareness, and rapid automated naming are two distinct sources of decoding ability, but phonological short-term memory significantly contributes to decoding ability under the realm of phonological awareness. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mapping of MPEG-4 decoding on a flexible architecture platform

NASA Astrophysics Data System (ADS)

van der Tol, Erik B.; Jaspers, Egbert G.

2001-12-01

In the field of consumer electronics, the advent of new features such as Internet, games, video conferencing, and mobile communication has triggered the convergence of television and computers technologies. This requires a generic media-processing platform that enables simultaneous execution of very diverse tasks such as high-throughput stream-oriented data processing and highly data-dependent irregular processing with complex control flows. As a representative application, this paper presents the mapping of a Main Visual profile MPEG-4 for High-Definition (HD) video onto a flexible architecture platform. A stepwise approach is taken, going from the decoder application toward an implementation proposal. First, the application is decomposed into separate tasks with self-contained functionality, clear interfaces, and distinct characteristics. Next, a hardware-software partitioning is derived by analyzing the characteristics of each task such as the amount of inherent parallelism, the throughput requirements, the complexity of control processing, and the reuse potential over different applications and different systems. Finally, a feasible implementation is proposed that includes amongst others a very-long-instruction-word (VLIW) media processor, one or more RISC processors, and some dedicated processors. The mapping study of the MPEG-4 decoder proves the flexibility and extensibility of the media-processing platform. This platform enables an effective HW/SW co-design yielding a high performance density.

An Improved Unscented Kalman Filter Based Decoder for Cortical Brain-Machine Interfaces.

PubMed

Li, Simin; Li, Jie; Li, Zheng

2016-01-01

Brain-machine interfaces (BMIs) seek to connect brains with machines or computers directly, for application in areas such as prosthesis control. For this application, the accuracy of the decoding of movement intentions is crucial. We aim to improve accuracy by designing a better encoding model of primary motor cortical activity during hand movements and combining this with decoder engineering refinements, resulting in a new unscented Kalman filter based decoder, UKF2, which improves upon our previous unscented Kalman filter decoder, UKF1. The new encoding model includes novel acceleration magnitude, position-velocity interaction, and target-cursor-distance features (the decoder does not require target position as input, it is decoded). We add a novel probabilistic velocity threshold to better determine the user's intent to move. We combine these improvements with several other refinements suggested by others in the field. Data from two Rhesus monkeys indicate that the UKF2 generates offline reconstructions of hand movements (mean CC 0.851) significantly more accurately than the UKF1 (0.833) and the popular position-velocity Kalman filter (0.812). The encoding model of the UKF2 could predict the instantaneous firing rate of neurons (mean CC 0.210), given kinematic variables and past spiking, better than the encoding models of these two decoders (UKF1: 0.138, p-v Kalman: 0.098). In closed-loop experiments where each monkey controlled a computer cursor with each decoder in turn, the UKF2 facilitated faster task completion (mean 1.56 s vs. 2.05 s) and higher Fitts's Law bit rate (mean 0.738 bit/s vs. 0.584 bit/s) than the UKF1. These results suggest that the modeling and decoder engineering refinements of the UKF2 improve decoding performance. We believe they can be used to enhance other decoders as well.

An Improved Unscented Kalman Filter Based Decoder for Cortical Brain-Machine Interfaces

PubMed Central

Li, Simin; Li, Jie; Li, Zheng

2016-01-01

Brain-machine interfaces (BMIs) seek to connect brains with machines or computers directly, for application in areas such as prosthesis control. For this application, the accuracy of the decoding of movement intentions is crucial. We aim to improve accuracy by designing a better encoding model of primary motor cortical activity during hand movements and combining this with decoder engineering refinements, resulting in a new unscented Kalman filter based decoder, UKF2, which improves upon our previous unscented Kalman filter decoder, UKF1. The new encoding model includes novel acceleration magnitude, position-velocity interaction, and target-cursor-distance features (the decoder does not require target position as input, it is decoded). We add a novel probabilistic velocity threshold to better determine the user's intent to move. We combine these improvements with several other refinements suggested by others in the field. Data from two Rhesus monkeys indicate that the UKF2 generates offline reconstructions of hand movements (mean CC 0.851) significantly more accurately than the UKF1 (0.833) and the popular position-velocity Kalman filter (0.812). The encoding model of the UKF2 could predict the instantaneous firing rate of neurons (mean CC 0.210), given kinematic variables and past spiking, better than the encoding models of these two decoders (UKF1: 0.138, p-v Kalman: 0.098). In closed-loop experiments where each monkey controlled a computer cursor with each decoder in turn, the UKF2 facilitated faster task completion (mean 1.56 s vs. 2.05 s) and higher Fitts's Law bit rate (mean 0.738 bit/s vs. 0.584 bit/s) than the UKF1. These results suggest that the modeling and decoder engineering refinements of the UKF2 improve decoding performance. We believe they can be used to enhance other decoders as well. PMID:28066170

Portable lensless wide-field microscopy imaging platform based on digital inline holography and multi-frame pixel super-resolution

PubMed Central

Sobieranski, Antonio C; Inci, Fatih; Tekin, H Cumhur; Yuksekkaya, Mehmet; Comunello, Eros; Cobra, Daniel; von Wangenheim, Aldo; Demirci, Utkan

2017-01-01

In this paper, an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame processing. The samples are illuminated by a nearly coherent illumination system, where the hologram shadows are projected into a complementary metal-oxide semiconductor-based imaging sensor. To increase the resolution, a multi-frame pixel resolution approach is employed to produce a single holographic image from multiple frame observations of the scene, with small planar displacements. Displacements are resolved by a hybrid approach: (i) alignment of the LR images by a fast feature-based registration method, and (ii) fine adjustment of the sub-pixel information using a continuous optimization approach designed to find the global optimum solution. Numerical method for phase-retrieval is applied to decode the signal and reconstruct the morphological details of the analyzed sample. The presented approach was evaluated with various biological samples including sperm and platelets, whose dimensions are in the order of a few microns. The obtained results demonstrate a spatial resolution of 1.55 µm on a field-of-view of ≈30 mm2. PMID:29657866

Reed-Solomon decoder

NASA Technical Reports Server (NTRS)

Lahmeyer, Charles R. (Inventor)

1987-01-01

A Reed-Solomon decoder with dedicated hardware for five sequential algorithms was designed with overall pipelining by memory swapping between input, processing and output memories, and internal pipelining through the five algorithms. The code definition used in decoding is specified by a keyword received with each block of data so that a number of different code formats may be decoded by the same hardware.

A study of digital holographic filters generation. Phase 2: Digital data communication system, volume 1

NASA Technical Reports Server (NTRS)

Ingels, F. M.; Mo, C. D.

1978-01-01

An empirical study of the performance of the Viterbi decoders in bursty channels was carried out and an improved algebraic decoder for nonsystematic codes was developed. The hybrid algorithm was simulated for the (2,1), k = 7 code on a computer using 20 channels having various error statistics, ranging from pure random error to pure bursty channels. The hybrid system outperformed both the algebraic and the Viterbi decoders in every case, except the 1% random error channel where the Viterbi decoder had one bit less decoding error.

Large-Constraint-Length, Fast Viterbi Decoder

NASA Technical Reports Server (NTRS)

Collins, O.; Dolinar, S.; Hsu, In-Shek; Pollara, F.; Olson, E.; Statman, J.; Zimmerman, G.

1990-01-01

Scheme for efficient interconnection makes VLSI design feasible. Concept for fast Viterbi decoder provides for processing of convolutional codes of constraint length K up to 15 and rates of 1/2 to 1/6. Fully parallel (but bit-serial) architecture developed for decoder of K = 7 implemented in single dedicated VLSI circuit chip. Contains six major functional blocks. VLSI circuits perform branch metric computations, add-compare-select operations, and then store decisions in traceback memory. Traceback processor reads appropriate memory locations and puts out decoded bits. Used as building block for decoders of larger K.

The highly conserved codon following the slippery sequence supports -1 frameshift efficiency at the HIV-1 frameshift site.

PubMed

Mathew, Suneeth F; Crowe-McAuliffe, Caillan; Graves, Ryan; Cardno, Tony S; McKinney, Cushla; Poole, Elizabeth S; Tate, Warren P

2015-01-01

HIV-1 utilises -1 programmed ribosomal frameshifting to translate structural and enzymatic domains in a defined proportion required for replication. A slippery sequence, U UUU UUA, and a stem-loop are well-defined RNA features modulating -1 frameshifting in HIV-1. The GGG glycine codon immediately following the slippery sequence (the 'intercodon') contributes structurally to the start of the stem-loop but has no defined role in current models of the frameshift mechanism, as slippage is inferred to occur before the intercodon has reached the ribosomal decoding site. This GGG codon is highly conserved in natural isolates of HIV. When the natural intercodon was replaced with a stop codon two different decoding molecules-eRF1 protein or a cognate suppressor tRNA-were able to access and decode the intercodon prior to -1 frameshifting. This implies significant slippage occurs when the intercodon is in the (perhaps distorted) ribosomal A site. We accommodate the influence of the intercodon in a model of frame maintenance versus frameshifting in HIV-1.

Decoding Trajectories from Posterior Parietal Cortex Ensembles

PubMed Central

Mulliken, Grant H.; Musallam, Sam; Andersen, Richard A.

2009-01-01

High-level cognitive signals in the posterior parietal cortex (PPC) have previously been used to decode the intended endpoint of a reach, providing the first evidence that PPC can be used for direct control of a neural prosthesis (Musallam et al., 2004). Here we expand on this work by showing that PPC neural activity can be harnessed to estimate not only the endpoint but also to continuously control the trajectory of an end effector. Specifically, we trained two monkeys to use a joystick to guide a cursor on a computer screen to peripheral target locations while maintaining central ocular fixation. We found that we could accurately reconstruct the trajectory of the cursor using a relatively small ensemble of simultaneously recorded PPC neurons. Using a goal-based Kalman filter that incorporates target information into the state-space, we showed that the decoded estimate of cursor position could be significantly improved. Finally, we tested whether we could decode trajectories during closed-loop brain control sessions, in which the real-time position of the cursor was determined solely by a monkey’s neural activity in PPC. The monkey learned to perform brain control trajectories at 80% success rate(for 8 targets) after just 4–5 sessions. This improvement in behavioral performance was accompanied by a corresponding enhancement in neural tuning properties (i.e., increased tuning depth and coverage of encoding parameter space) as well as an increase in off-line decoding performance of the PPC ensemble. PMID:19036985

Neural decoding of treadmill walking from noninvasive electroencephalographic signals

PubMed Central

Presacco, Alessandro; Goodman, Ronald; Forrester, Larry

2011-01-01

Chronic recordings from ensembles of cortical neurons in primary motor and somatosensory areas in rhesus macaques provide accurate information about bipedal locomotion (Fitzsimmons NA, Lebedev MA, Peikon ID, Nicolelis MA. Front Integr Neurosci 3: 3, 2009). Here we show that the linear and angular kinematics of the ankle, knee, and hip joints during both normal and precision (attentive) human treadmill walking can be inferred from noninvasive scalp electroencephalography (EEG) with decoding accuracies comparable to those from neural decoders based on multiple single-unit activities (SUAs) recorded in nonhuman primates. Six healthy adults were recorded. Participants were asked to walk on a treadmill at their self-selected comfortable speed while receiving visual feedback of their lower limbs (i.e., precision walking), to repeatedly avoid stepping on a strip drawn on the treadmill belt. Angular and linear kinematics of the left and right hip, knee, and ankle joints and EEG were recorded, and neural decoders were designed and optimized with cross-validation procedures. Of note, the optimal set of electrodes of these decoders were also used to accurately infer gait trajectories in a normal walking task that did not require subjects to control and monitor their foot placement. Our results indicate a high involvement of a fronto-posterior cortical network in the control of both precision and normal walking and suggest that EEG signals can be used to study in real time the cortical dynamics of walking and to develop brain-machine interfaces aimed at restoring human gait function. PMID:21768121

Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

NASA Astrophysics Data System (ADS)

Moses, David A.; Mesgarani, Nima; Leonard, Matthew K.; Chang, Edward F.

2016-10-01

Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

A Simple Method to Decode the Complete 18-5.8-28S rRNA Repeated Units of Green Algae by Genome Skimming.

PubMed

Lin, Geng-Ming; Lai, Yu-Heng; Audira, Gilbert; Hsiao, Chung-Der

2017-11-06

Green algae, Chlorella ellipsoidea , Haematococcus pluvialis and Aegagropila linnaei (Phylum Chlorophyta) were simultaneously decoded by a genomic skimming approach within 18-5.8-28S rRNA region. Whole genomic DNAs were isolated from green algae and directly subjected to low coverage genome skimming sequencing. After de novo assembly and mapping, the size of complete 18-5.8-28S rRNA repeated units for three green algae were ranged from 5785 to 6028 bp, which showed high nucleotide diversity (π is around 0.5-0.6) within ITS1 and ITS2 (Internal Transcribed Spacer) regions. Previously, the evolutional diversity of algae has been difficult to decode due to the inability design universal primers that amplify specific marker genes across diverse algal species. In this study, our method provided a rapid and universal approach to decode the 18-5.8-28S rRNA repeat unit in three green algal species. In addition, the completely sequenced 18-5.8-28S rRNA repeated units provided a solid nuclear marker for phylogenetic and evolutionary analysis for green algae for the first time.

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

PubMed Central

Bulea, Thomas C.; Kilicarslan, Atilla; Ozdemir, Recep; Paloski, William H.; Contreras-Vidal, Jose L.

2013-01-01

Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG. PMID:23912203

Decoding static and dynamic arm and hand gestures from the JPL BioSleeve

NASA Astrophysics Data System (ADS)

Wolf, M. T.; Assad, C.; Stoica, A.; You, Kisung; Jethani, H.; Vernacchia, M. T.; Fromm, J.; Iwashita, Y.

This paper presents methods for inferring arm and hand gestures from forearm surface electromyography (EMG) sensors and an inertial measurement unit (IMU). These sensors, together with their electronics, are packaged in an easily donned device, termed the BioSleeve, worn on the forearm. The gestures decoded from BioSleeve signals can provide natural user interface commands to computers and robots, without encumbering the users hands and without problems that hinder camera-based systems. Potential aerospace applications for this technology include gesture-based crew-autonomy interfaces, high degree of freedom robot teleoperation, and astronauts' control of power-assisted gloves during extra-vehicular activity (EVA). We have developed techniques to interpret both static (stationary) and dynamic (time-varying) gestures from the BioSleeve signals, enabling a diverse and adaptable command library. For static gestures, we achieved over 96% accuracy on 17 gestures and nearly 100% accuracy on 11 gestures, based solely on EMG signals. Nine dynamic gestures were decoded with an accuracy of 99%. This combination of wearableEMGand IMU hardware and accurate algorithms for decoding both static and dynamic gestures thus shows promise for natural user interface applications.

Neuromuscular electrical stimulation induced brain patterns to decode motor imagery.

PubMed

Vidaurre, C; Pascual, J; Ramos-Murguialday, A; Lorenz, R; Blankertz, B; Birbaumer, N; Müller, K-R

2013-09-01

Regardless of the paradigm used to implement a brain-computer interface (BCI), all systems suffer from BCI-inefficiency. In the case of patients the inefficiency can be high. Some solutions have been proposed to overcome this problem, however they have not been completely successful yet. EEG from 10 healthy users was recorded during neuromuscular electrical stimulation (NMES) of hands and feet and during motor imagery (MI) of the same limbs. Features and classifiers were computed using part of these data to decode MI. Offline analyses showed that it was possible to decode MI using a classifier based on afferent patterns induced by NMES and even infer a better model than with MI data. Afferent NMES motor patterns can support the calibration of BCI systems and be used to decode MI. This finding might be a new way to train sensorimotor rhythm (SMR) based BCI systems for healthy users having difficulties to attain BCI control. It might also be an alternative to train MI-based BCIs for users who cannot perform real movements but have remaining afferents (ALS, stroke patients). Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Updating National Topographic Data Base Using Change Detection Methods

NASA Astrophysics Data System (ADS)

Keinan, E.; Felus, Y. A.; Tal, Y.; Zilberstien, O.; Elihai, Y.

2016-06-01

The traditional method for updating a topographic database on a national scale is a complex process that requires human resources, time and the development of specialized procedures. In many National Mapping and Cadaster Agencies (NMCA), the updating cycle takes a few years. Today, the reality is dynamic and the changes occur every day, therefore, the users expect that the existing database will portray the current reality. Global mapping projects which are based on community volunteers, such as OSM, update their database every day based on crowdsourcing. In order to fulfil user's requirements for rapid updating, a new methodology that maps major interest areas while preserving associated decoding information, should be developed. Until recently, automated processes did not yield satisfactory results, and a typically process included comparing images from different periods. The success rates in identifying the objects were low, and most were accompanied by a high percentage of false alarms. As a result, the automatic process required significant editorial work that made it uneconomical. In the recent years, the development of technologies in mapping, advancement in image processing algorithms and computer vision, together with the development of digital aerial cameras with NIR band and Very High Resolution satellites, allow the implementation of a cost effective automated process. The automatic process is based on high-resolution Digital Surface Model analysis, Multi Spectral (MS) classification, MS segmentation, object analysis and shape forming algorithms. This article reviews the results of a novel change detection methodology as a first step for updating NTDB in the Survey of Israel.

Characterization of Large-Area SiPM Array for PET Applications

NASA Astrophysics Data System (ADS)

Du, Junwei; Yang, Yongfeng; Bai, Xiaowei; Judenhofer, Martin S.; Berg, Eric; Di, Kun; Buckley, Steve; Jackson, Carl; Cherry, Simon R.

2016-02-01

The performance of an 8 ×8 array of 6.0 ×6.0 mm2 (active area) SiPMs was evaluated for PET applications using crystal arrays with different pitch sizes (3.4, 1.5, 1.35, and 1.2 mm) and custom designed five-channel front-end readout electronics (four channels for position information and one channel for timing information). The total area of this SiPM array is 57.4 ×57.4 mm2, and the pitch size is 7.2 mm. It was fabricated using enhanced blue sensitivity SiPMs (MicroFB-60035-SMT) with peak spectral sensitivity at 420 nm. The performance of the SiPM array was characterized by measuring flood histogram decoding quality, energy resolution, timing resolution and saturation at several bias voltages (from 25.0 to 30.0 V in 0.5 V intervals) and two different temperatures ( 5° C and 20°C). Results show that the best flood histogram was obtained at a bias voltage of 28.0 V and 5°C and an array of polished LSO crystals with a pitch as small as 1.2 mm can be resolved. No saturation was observed up to a bias voltage of 29.5 V during the experiments, due to adequate light sharing between SiPMs. Energy resolution and timing resolution at 5°C ranged from 12.7 ±0.8% to 14.6 ±1.4% and 1.58 ±0.13 ns to 2.50 ±0.44 ns, for crystal array pitch sizes of 3.4 and 1.2 mm, respectively. Superior flood histogram quality, energy resolution and timing resolution were obtained with larger crystal array pitch sizes and at lower temperature. Based on our findings, we conclude that this large-area SiPM array can serve as a suitable photodetector for high-resolution small-animal PET or dedicated human brain PET scanners.

Validity of the two-level model for Viterbi decoder gap-cycle performance

NASA Technical Reports Server (NTRS)

Dolinar, S.; Arnold, S.

1990-01-01

A two-level model has previously been proposed for approximating the performance of a Viterbi decoder which encounters data received with periodically varying signal-to-noise ratio. Such cyclically gapped data is obtained from the Very Large Array (VLA), either operating as a stand-alone system or arrayed with Goldstone. This approximate model predicts that the decoder error rate will vary periodically between two discrete levels with the same period as the gap cycle. It further predicts that the length of the gapped portion of the decoder error cycle for a constraint length K decoder will be about K-1 bits shorter than the actual duration of the gap. The two-level model for Viterbi decoder performance with gapped data is subjected to detailed validation tests. Curves showing the cyclical behavior of the decoder error burst statistics are compared with the simple square-wave cycles predicted by the model. The validity of the model depends on a parameter often considered irrelevant in the analysis of Viterbi decoder performance, the overall scaling of the received signal or the decoder's branch-metrics. Three scaling alternatives are examined: optimum branch-metric scaling and constant branch-metric scaling combined with either constant noise-level scaling or constant signal-level scaling. The simulated decoder error cycle curves roughly verify the accuracy of the two-level model for both the case of optimum branch-metric scaling and the case of constant branch-metric scaling combined with constant noise-level scaling. However, the model is not accurate for the case of constant branch-metric scaling combined with constant signal-level scaling.

Adaptive Distributed Video Coding with Correlation Estimation using Expectation Propagation

PubMed Central

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2013-01-01

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method. PMID:23750314

Decoding continuous three-dimensional hand trajectories from epidural electrocorticographic signals in Japanese macaques

NASA Astrophysics Data System (ADS)

Shimoda, Kentaro; Nagasaka, Yasuo; Chao, Zenas C.; Fujii, Naotaka

2012-06-01

Brain-machine interface (BMI) technology captures brain signals to enable control of prosthetic or communication devices with the goal of assisting patients who have limited or no ability to perform voluntary movements. Decoding of inherent information in brain signals to interpret the user's intention is one of main approaches for developing BMI technology. Subdural electrocorticography (sECoG)-based decoding provides good accuracy, but surgical complications are one of the major concerns for this approach to be applied in BMIs. In contrast, epidural electrocorticography (eECoG) is less invasive, thus it is theoretically more suitable for long-term implementation, although it is unclear whether eECoG signals carry sufficient information for decoding natural movements. We successfully decoded continuous three-dimensional hand trajectories from eECoG signals in Japanese macaques. A steady quantity of information of continuous hand movements could be acquired from the decoding system for at least several months, and a decoding model could be used for ˜10 days without significant degradation in accuracy or recalibration. The correlation coefficients between observed and predicted trajectories were lower than those for sECoG-based decoding experiments we previously reported, owing to a greater degree of chewing artifacts in eECoG-based decoding than is found in sECoG-based decoding. As one of the safest invasive recording methods available, eECoG provides an acceptable level of performance. With the ease of replacement and upgrades, eECoG systems could become the first-choice interface for real-life BMI applications.

Adaptive distributed video coding with correlation estimation using expectation propagation

NASA Astrophysics Data System (ADS)

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-01

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Adaptive Distributed Video Coding with Correlation Estimation using Expectation Propagation.

PubMed

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-15

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Progressive simplification and transmission of building polygons based on triangle meshes

NASA Astrophysics Data System (ADS)

Li, Hongsheng; Wang, Yingjie; Guo, Qingsheng; Han, Jiafu

2010-11-01

Digital earth is a virtual representation of our planet and a data integration platform which aims at harnessing multisource, multi-resolution, multi-format spatial data. This paper introduces a research framework integrating progressive cartographic generalization and transmission of vector data. The progressive cartographic generalization provides multiple resolution data from coarse to fine as key scales and increments between them which is not available in traditional generalization framework. Based on the progressive simplification algorithm, the building polygons are triangulated into meshes and encoded according to the simplification sequence of two basic operations, edge collapse and vertex split. The map data at key scales and encoded increments between them are stored in a multi-resolution file. As the client submits requests to the server, the coarsest map is transmitted first and then the increments. After data decoding and mesh refinement the building polygons with more details will be visualized. Progressive generalization and transmission of building polygons is demonstrated in the paper.

Recent advances in coding theory for near error-free communications

NASA Technical Reports Server (NTRS)

Cheung, K.-M.; Deutsch, L. J.; Dolinar, S. J.; Mceliece, R. J.; Pollara, F.; Shahshahani, M.; Swanson, L.

1991-01-01

Channel and source coding theories are discussed. The following subject areas are covered: large constraint length convolutional codes (the Galileo code); decoder design (the big Viterbi decoder); Voyager's and Galileo's data compression scheme; current research in data compression for images; neural networks for soft decoding; neural networks for source decoding; finite-state codes; and fractals for data compression.

Fast transform decoding of nonsystematic Reed-Solomon codes

NASA Technical Reports Server (NTRS)

Truong, T. K.; Cheung, K.-M.; Reed, I. S.; Shiozaki, A.

1989-01-01

A Reed-Solomon (RS) code is considered to be a special case of a redundant residue polynomial (RRP) code, and a fast transform decoding algorithm to correct both errors and erasures is presented. This decoding scheme is an improvement of the decoding algorithm for the RRP code suggested by Shiozaki and Nishida, and can be realized readily on very large scale integration chips.

The Differential Contributions of Auditory-Verbal and Visuospatial Working Memory on Decoding Skills in Children Who Are Poor Decoders

ERIC Educational Resources Information Center

Squires, Katie Ellen

2013-01-01

This study investigated the differential contribution of auditory-verbal and visuospatial working memory (WM) on decoding skills in second- and fifth-grade children identified with poor decoding. Thirty-two second-grade students and 22 fifth-grade students completed measures that assessed simple and complex auditory-verbal and visuospatial memory,…

Polar Coding with CRC-Aided List Decoding

DTIC Science & Technology

2015-08-01

TECHNICAL REPORT 2087 August 2015 Polar Coding with CRC-Aided List Decoding David Wasserman Approved...list decoding . RESULTS Our simulation results show that polar coding can produce results very similar to the FEC used in the Digital Video...standard. RECOMMENDATIONS In any application for which the DVB-S2 FEC is considered, polar coding with CRC-aided list decod - ing with N = 65536

Decoding position, velocity, or goal: does it matter for brain-machine interfaces?

PubMed

Marathe, A R; Taylor, D M

2011-04-01

Arm end-point position, end-point velocity, and the intended final location or 'goal' of a reach have all been decoded from cortical signals for use in brain-machine interface (BMI) applications. These different aspects of arm movement can be decoded from the brain and used directly to control the position, velocity, or movement goal of a device. However, these decoded parameters can also be remapped to control different aspects of movement, such as using the decoded position of the hand to control the velocity of a device. People easily learn to use the position of a joystick to control the velocity of an object in a videogame. Similarly, in BMI systems, the position, velocity, or goal of a movement could be decoded from the brain and remapped to control some other aspect of device movement. This study evaluates how easily people make transformations between position, velocity, and reach goal in BMI systems. It also evaluates how different amounts of decoding error impact on device control with and without these transformations. Results suggest some remapping options can significantly improve BMI control. This study provides guidance on what remapping options to use when various amounts of decoding error are present.

Encoder-Decoder Optimization for Brain-Computer Interfaces

PubMed Central

Merel, Josh; Pianto, Donald M.; Cunningham, John P.; Paninski, Liam

2015-01-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages. PMID:26029919

Encoder-decoder optimization for brain-computer interfaces.

PubMed

Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam

2015-06-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Decoding position, velocity, or goal: Does it matter for brain-machine interfaces?

NASA Astrophysics Data System (ADS)

Marathe, A. R.; Taylor, D. M.

2011-04-01

Arm end-point position, end-point velocity, and the intended final location or 'goal' of a reach have all been decoded from cortical signals for use in brain-machine interface (BMI) applications. These different aspects of arm movement can be decoded from the brain and used directly to control the position, velocity, or movement goal of a device. However, these decoded parameters can also be remapped to control different aspects of movement, such as using the decoded position of the hand to control the velocity of a device. People easily learn to use the position of a joystick to control the velocity of an object in a videogame. Similarly, in BMI systems, the position, velocity, or goal of a movement could be decoded from the brain and remapped to control some other aspect of device movement. This study evaluates how easily people make transformations between position, velocity, and reach goal in BMI systems. It also evaluates how different amounts of decoding error impact on device control with and without these transformations. Results suggest some remapping options can significantly improve BMI control. This study provides guidance on what remapping options to use when various amounts of decoding error are present.

Improved HDRG decoders for qudit and non-Abelian quantum error correction

NASA Astrophysics Data System (ADS)

Hutter, Adrian; Loss, Daniel; Wootton, James R.

2015-03-01

Hard-decision renormalization group (HDRG) decoders are an important class of decoding algorithms for topological quantum error correction. Due to their versatility, they have been used to decode systems with fractal logical operators, color codes, qudit topological codes, and non-Abelian systems. In this work, we develop a method of performing HDRG decoding which combines strengths of existing decoders and further improves upon them. In particular, we increase the minimal number of errors necessary for a logical error in a system of linear size L from \\Theta ({{L}2/3}) to Ω ({{L}1-ε }) for any ε \\gt 0. We apply our algorithm to decoding D({{{Z}}d}) quantum double models and a non-Abelian anyon model with Fibonacci-like fusion rules, and show that it indeed significantly outperforms previous HDRG decoders. Furthermore, we provide the first study of continuous error correction with imperfect syndrome measurements for the D({{{Z}}d}) quantum double models. The parallelized runtime of our algorithm is poly(log L) for the perfect measurement case. In the continuous case with imperfect syndrome measurements, the averaged runtime is O(1) for Abelian systems, while continuous error correction for non-Abelian anyons stays an open problem.

A soft decoding algorithm and hardware implementation for the visual prosthesis based on high order soft demodulation.

PubMed

Yang, Yuan; Quan, Nannan; Bu, Jingjing; Li, Xueping; Yu, Ningmei

2016-09-26

High order modulation and demodulation technology can solve the frequency requirement between the wireless energy transmission and data communication. In order to achieve reliable wireless data communication based on high order modulation technology for visual prosthesis, this work proposed a Reed-Solomon (RS) error correcting code (ECC) circuit on the basis of differential amplitude and phase shift keying (DAPSK) soft demodulation. Firstly, recognizing the weakness of the traditional DAPSK soft demodulation algorithm based on division that is complex for hardware implementation, an improved phase soft demodulation algorithm for visual prosthesis to reduce the hardware complexity is put forward. Based on this new algorithm, an improved RS soft decoding method is hence proposed. In this new decoding method, the combination of Chase algorithm and hard decoding algorithms is used to achieve soft decoding. In order to meet the requirements of implantable visual prosthesis, the method to calculate reliability of symbol-level based on multiplication of bit reliability is derived, which reduces the testing vectors number of Chase algorithm. The proposed algorithms are verified by MATLAB simulation and FPGA experimental results. During MATLAB simulation, the biological channel attenuation property model is added into the ECC circuit. The data rate is 8 Mbps in the MATLAB simulation and FPGA experiments. MATLAB simulation results show that the improved phase soft demodulation algorithm proposed in this paper saves hardware resources without losing bit error rate (BER) performance. Compared with the traditional demodulation circuit, the coding gain of the ECC circuit has been improved by about 3 dB under the same BER of [Formula: see text]. The FPGA experimental results show that under the condition of data demodulation error with wireless coils 3 cm away, the system can correct it. The greater the distance, the higher the BER. Then we use a bit error rate analyzer to measure BER of the demodulation circuit and the RS ECC circuit with different distance of two coils. And the experimental results show that the RS ECC circuit has about an order of magnitude lower BER than the demodulation circuit when under the same coils distance. Therefore, the RS ECC circuit has more higher reliability of the communication in the system. The improved phase soft demodulation algorithm and soft decoding algorithm proposed in this paper enables data communication that is more reliable than other demodulation system, which also provide a significant reference for further study to the visual prosthesis system.

Motion Direction Biases and Decoding in Human Visual Cortex

PubMed Central

Wang, Helena X.; Merriam, Elisha P.; Freeman, Jeremy

2014-01-01

Functional magnetic resonance imaging (fMRI) studies have relied on multivariate analysis methods to decode visual motion direction from measurements of cortical activity. Above-chance decoding has been commonly used to infer the motion-selective response properties of the underlying neural populations. Moreover, patterns of reliable response biases across voxels that underlie decoding have been interpreted to reflect maps of functional architecture. Using fMRI, we identified a direction-selective response bias in human visual cortex that: (1) predicted motion-decoding accuracy; (2) depended on the shape of the stimulus aperture rather than the absolute direction of motion, such that response amplitudes gradually decreased with distance from the stimulus aperture edge corresponding to motion origin; and 3) was present in V1, V2, V3, but not evident in MT+, explaining the higher motion-decoding accuracies reported previously in early visual cortex. These results demonstrate that fMRI-based motion decoding has little or no dependence on the underlying functional organization of motion selectivity. PMID:25209297

Mathematics is differentially related to reading comprehension and word decoding: Evidence from a genetically-sensitive design

PubMed Central

Harlaar, Nicole; Kovas, Yulia; Dale, Philip S.; Petrill, Stephen A.; Plomin, Robert

2013-01-01

Although evidence suggests that individual differences in reading and mathematics skills are correlated, this relationship has typically only been studied in relation to word decoding or global measures of reading. It is unclear whether mathematics is differentially related to word decoding and reading comprehension. The current study examined these relationships at both a phenotypic and etiological level in a population-based cohort of 5162 twin pairs at age 12. Multivariate genetic analyses of latent phenotypic factors of mathematics, word decoding and reading comprehension revealed substantial genetic and shared environmental correlations among all three domains. However, the phenotypic and genetic correlations between mathematics and reading comprehension were significantly greater than between mathematics and word decoding. Independent of mathematics, there was also evidence for genetic and nonshared environmental links between word decoding and reading comprehension. These findings indicate that word decoding and reading comprehension have partly distinct relationships with mathematics in the middle school years. PMID:24319294

Mathematics is differentially related to reading comprehension and word decoding: Evidence from a genetically-sensitive design.

PubMed

Harlaar, Nicole; Kovas, Yulia; Dale, Philip S; Petrill, Stephen A; Plomin, Robert

2012-08-01

Although evidence suggests that individual differences in reading and mathematics skills are correlated, this relationship has typically only been studied in relation to word decoding or global measures of reading. It is unclear whether mathematics is differentially related to word decoding and reading comprehension. The current study examined these relationships at both a phenotypic and etiological level in a population-based cohort of 5162 twin pairs at age 12. Multivariate genetic analyses of latent phenotypic factors of mathematics, word decoding and reading comprehension revealed substantial genetic and shared environmental correlations among all three domains. However, the phenotypic and genetic correlations between mathematics and reading comprehension were significantly greater than between mathematics and word decoding. Independent of mathematics, there was also evidence for genetic and nonshared environmental links between word decoding and reading comprehension. These findings indicate that word decoding and reading comprehension have partly distinct relationships with mathematics in the middle school years.

Mate choice in the eye and ear of the beholder? Female multimodal sensory configuration influences her preferences.

PubMed

Ronald, Kelly L; Fernández-Juricic, Esteban; Lucas, Jeffrey R

2018-05-16

A common assumption in sexual selection studies is that receivers decode signal information similarly. However, receivers may vary in how they rank signallers if signal perception varies with an individual's sensory configuration. Furthermore, receivers may vary in their weighting of different elements of multimodal signals based on their sensory configuration. This could lead to complex levels of selection on signalling traits. We tested whether multimodal sensory configuration could affect preferences for multimodal signals. We used brown-headed cowbird ( Molothrus ater ) females to examine how auditory sensitivity and auditory filters, which influence auditory spectral and temporal resolution, affect song preferences, and how visual spatial resolution and visual temporal resolution, which influence resolution of a moving visual signal, affect visual display preferences. Our results show that multimodal sensory configuration significantly affects preferences for male displays: females with better auditory temporal resolution preferred songs that were shorter, with lower Wiener entropy, and higher frequency; and females with better visual temporal resolution preferred males with less intense visual displays. Our findings provide new insights into mate-choice decisions and receiver signal processing. Furthermore, our results challenge a long-standing assumption in animal communication which can affect how we address honest signalling, assortative mating and sensory drive. © 2018 The Author(s).

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics.

PubMed

Prins, Noeline W; Sanchez, Justin C; Prasad, Abhishek

2017-06-01

For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-term goal is to create autonomous BMIs that can utilize an evaluative feedback from the brain to update the decoding algorithm and use it intelligently in order to adapt the decoder. In this study, we show how to extract the necessary evaluative feedback from a biologically realistic (synthetic) source, use both the quantity and the quality of the feedback, and how that feedback information can be incorporated into a reinforcement learning (RL) controller architecture to maximize its performance. Motivated by the perception-action-reward cycle (PARC) in the brain which links reward for cognitive decision making and goal-directed behavior, we used a reward-based RL architecture named Actor-Critic RL as the model. Instead of using an error signal towards building an autonomous BMI, we envision to use a reward signal from the nucleus accumbens (NAcc) which plays a key role in the linking of reward to motor behaviors. To deal with the complexity and non-stationarity of biological reward signals, we used a confidence metric which was used to indicate the degree of feedback accuracy. This confidence was added to the Actor's weight update equation in the RL controller architecture. If the confidence was high (>0.2), the BMI decoder used this feedback to update its parameters. However, when the confidence was low, the BMI decoder ignored the feedback and did not update its parameters. The range between high confidence and low confidence was termed as the 'ambiguous' region. When the feedback was within this region, the BMI decoder updated its weight at a lower rate than when fully confident, which was decided by the confidence. We used two biologically realistic models to generate synthetic data for MI (Izhikevich model) and NAcc (Humphries model) to validate proposed controller architecture. In this work, we show how the overall performance of the BMI was improved by using a threshold close to the decision boundary to reject erroneous feedback. Additionally, we show the stability of the system improved when the feedback was used with a threshold. The result of this study is a step towards making BMIs autonomous. While our method is not fully autonomous, the results demonstrate that extensive training times necessary at the beginning of each BMI session can be significantly decreased. In our approach, decoder training time was only limited to 10 trials in the first BMI session. Subsequent sessions used previous session weights to initialize the decoder. We also present a method where the use of a threshold can be applied to any decoder with a feedback signal that is less than perfect so that erroneous feedback can be avoided and the stability of the system can be increased.

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics

NASA Astrophysics Data System (ADS)

Prins, Noeline W.; Sanchez, Justin C.; Prasad, Abhishek

2017-06-01

Objective. For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-term goal is to create autonomous BMIs that can utilize an evaluative feedback from the brain to update the decoding algorithm and use it intelligently in order to adapt the decoder. In this study, we show how to extract the necessary evaluative feedback from a biologically realistic (synthetic) source, use both the quantity and the quality of the feedback, and how that feedback information can be incorporated into a reinforcement learning (RL) controller architecture to maximize its performance. Approach. Motivated by the perception-action-reward cycle (PARC) in the brain which links reward for cognitive decision making and goal-directed behavior, we used a reward-based RL architecture named Actor-Critic RL as the model. Instead of using an error signal towards building an autonomous BMI, we envision to use a reward signal from the nucleus accumbens (NAcc) which plays a key role in the linking of reward to motor behaviors. To deal with the complexity and non-stationarity of biological reward signals, we used a confidence metric which was used to indicate the degree of feedback accuracy. This confidence was added to the Actor’s weight update equation in the RL controller architecture. If the confidence was high (>0.2), the BMI decoder used this feedback to update its parameters. However, when the confidence was low, the BMI decoder ignored the feedback and did not update its parameters. The range between high confidence and low confidence was termed as the ‘ambiguous’ region. When the feedback was within this region, the BMI decoder updated its weight at a lower rate than when fully confident, which was decided by the confidence. We used two biologically realistic models to generate synthetic data for MI (Izhikevich model) and NAcc (Humphries model) to validate proposed controller architecture. Main results. In this work, we show how the overall performance of the BMI was improved by using a threshold close to the decision boundary to reject erroneous feedback. Additionally, we show the stability of the system improved when the feedback was used with a threshold. Significance: The result of this study is a step towards making BMIs autonomous. While our method is not fully autonomous, the results demonstrate that extensive training times necessary at the beginning of each BMI session can be significantly decreased. In our approach, decoder training time was only limited to 10 trials in the first BMI session. Subsequent sessions used previous session weights to initialize the decoder. We also present a method where the use of a threshold can be applied to any decoder with a feedback signal that is less than perfect so that erroneous feedback can be avoided and the stability of the system can be increased.

Soft-output decoding algorithms in iterative decoding of turbo codes

NASA Technical Reports Server (NTRS)

Benedetto, S.; Montorsi, G.; Divsalar, D.; Pollara, F.

1996-01-01

In this article, we present two versions of a simplified maximum a posteriori decoding algorithm. The algorithms work in a sliding window form, like the Viterbi algorithm, and can thus be used to decode continuously transmitted sequences obtained by parallel concatenated codes, without requiring code trellis termination. A heuristic explanation is also given of how to embed the maximum a posteriori algorithms into the iterative decoding of parallel concatenated codes (turbo codes). The performances of the two algorithms are compared on the basis of a powerful rate 1/3 parallel concatenated code. Basic circuits to implement the simplified a posteriori decoding algorithm using lookup tables, and two further approximations (linear and threshold), with a very small penalty, to eliminate the need for lookup tables are proposed.

The Limits of Coding with Joint Constraints on Detected and Undetected Error Rates

NASA Technical Reports Server (NTRS)

Dolinar, Sam; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush

2008-01-01

We develop a remarkably tight upper bound on the performance of a parameterized family of bounded angle maximum-likelihood (BA-ML) incomplete decoders. The new bound for this class of incomplete decoders is calculated from the code's weight enumerator, and is an extension of Poltyrev-type bounds developed for complete ML decoders. This bound can also be applied to bound the average performance of random code ensembles in terms of an ensemble average weight enumerator. We also formulate conditions defining a parameterized family of optimal incomplete decoders, defined to minimize both the total codeword error probability and the undetected error probability for any fixed capability of the decoder to detect errors. We illustrate the gap between optimal and BA-ML incomplete decoding via simulation of a small code.

Modeling vocalization with ECoG cortical activity recorded during vocal production in the macaque monkey.

PubMed

Fukushima, Makoto; Saunders, Richard C; Fujii, Naotaka; Averbeck, Bruno B; Mishkin, Mortimer

2014-01-01

Vocal production is an example of controlled motor behavior with high temporal precision. Previous studies have decoded auditory evoked cortical activity while monkeys listened to vocalization sounds. On the other hand, there have been few attempts at decoding motor cortical activity during vocal production. Here we recorded cortical activity during vocal production in the macaque with a chronically implanted electrocorticographic (ECoG) electrode array. The array detected robust activity in motor cortex during vocal production. We used a nonlinear dynamical model of the vocal organ to reduce the dimensionality of `Coo' calls produced by the monkey. We then used linear regression to evaluate the information in motor cortical activity for this reduced representation of calls. This simple linear model accounted for circa 65% of the variance in the reduced sound representations, supporting the feasibility of using the dynamical model of the vocal organ for decoding motor cortical activity during vocal production.

Reed Solomon codes for error control in byte organized computer memory systems

NASA Technical Reports Server (NTRS)

Lin, S.; Costello, D. J., Jr.

1984-01-01

A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. In LSI and VLSI technology, memories are often organized on a multiple bit (or byte) per chip basis. For example, some 256K-bit DRAM's are organized in 32Kx8 bit-bytes. Byte oriented codes such as Reed Solomon (RS) codes can provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. Some special decoding techniques for extended single-and-double-error-correcting RS codes which are capable of high speed operation are presented. These techniques are designed to find the error locations and the error values directly from the syndrome without having to use the iterative algorithm to find the error locator polynomial.

A Low-Complexity Euclidean Orthogonal LDPC Architecture for Low Power Applications

PubMed Central

Revathy, M.; Saravanan, R.

2015-01-01

Low-density parity-check (LDPC) codes have been implemented in latest digital video broadcasting, broadband wireless access (WiMax), and fourth generation of wireless standards. In this paper, we have proposed a high efficient low-density parity-check code (LDPC) decoder architecture for low power applications. This study also considers the design and analysis of check node and variable node units and Euclidean orthogonal generator in LDPC decoder architecture. The Euclidean orthogonal generator is used to reduce the error rate of the proposed LDPC architecture, which can be incorporated between check and variable node architecture. This proposed decoder design is synthesized on Xilinx 9.2i platform and simulated using Modelsim, which is targeted to 45 nm devices. Synthesis report proves that the proposed architecture greatly reduces the power consumption and hardware utilizations on comparing with different conventional architectures. PMID:26065017

Low-density parity-check codes for volume holographic memory systems.

PubMed

Pishro-Nik, Hossein; Rahnavard, Nazanin; Ha, Jeongseok; Fekri, Faramarz; Adibi, Ali

2003-02-10

We investigate the application of low-density parity-check (LDPC) codes in volume holographic memory (VHM) systems. We show that a carefully designed irregular LDPC code has a very good performance in VHM systems. We optimize high-rate LDPC codes for the nonuniform error pattern in holographic memories to reduce the bit error rate extensively. The prior knowledge of noise distribution is used for designing as well as decoding the LDPC codes. We show that these codes have a superior performance to that of Reed-Solomon (RS) codes and regular LDPC counterparts. Our simulation shows that we can increase the maximum storage capacity of holographic memories by more than 50 percent if we use irregular LDPC codes with soft-decision decoding instead of conventionally employed RS codes with hard-decision decoding. The performance of these LDPC codes is close to the information theoretic capacity.

An integrated approach to improving noisy speech perception

NASA Astrophysics Data System (ADS)

Koval, Serguei; Stolbov, Mikhail; Smirnova, Natalia; Khitrov, Mikhail

2002-05-01

For a number of practical purposes and tasks, experts have to decode speech recordings of very poor quality. A combination of techniques is proposed to improve intelligibility and quality of distorted speech messages and thus facilitate their comprehension. Along with the application of noise cancellation and speech signal enhancement techniques removing and/or reducing various kinds of distortions and interference (primarily unmasking and normalization in time and frequency fields), the approach incorporates optimal listener expert tactics based on selective listening, nonstandard binaural listening, accounting for short-term and long-term human ear adaptation to noisy speech, as well as some methods of speech signal enhancement to support speech decoding during listening. The approach integrating the suggested techniques ensures high-quality ultimate results and has successfully been applied by Speech Technology Center experts and by numerous other users, mainly forensic institutions, to perform noisy speech records decoding for courts, law enforcement and emergency services, accident investigation bodies, etc.

Feedback control policies employed by people using intracortical brain-computer interfaces.

PubMed

Willett, Francis R; Pandarinath, Chethan; Jarosiewicz, Beata; Murphy, Brian A; Memberg, William D; Blabe, Christine H; Saab, Jad; Walter, Benjamin L; Sweet, Jennifer A; Miller, Jonathan P; Henderson, Jaimie M; Shenoy, Krishna V; Simeral, John D; Hochberg, Leigh R; Kirsch, Robert F; Ajiboye, A Bolu

2017-02-01

When using an intracortical BCI (iBCI), users modulate their neural population activity to move an effector towards a target, stop accurately, and correct for movement errors. We call the rules that govern this modulation a 'feedback control policy'. A better understanding of these policies may inform the design of higher-performing neural decoders. We studied how three participants in the BrainGate2 pilot clinical trial used an iBCI to control a cursor in a 2D target acquisition task. Participants used a velocity decoder with exponential smoothing dynamics. Through offline analyses, we characterized the users' feedback control policies by modeling their neural activity as a function of cursor state and target position. We also tested whether users could adapt their policy to different decoder dynamics by varying the gain (speed scaling) and temporal smoothing parameters of the iBCI. We demonstrate that control policy assumptions made in previous studies do not fully describe the policies of our participants. To account for these discrepancies, we propose a new model that captures (1) how the user's neural population activity gradually declines as the cursor approaches the target from afar, then decreases more sharply as the cursor comes into contact with the target, (2) how the user makes constant feedback corrections even when the cursor is on top of the target, and (3) how the user actively accounts for the cursor's current velocity to avoid overshooting the target. Further, we show that users can adapt their control policy to decoder dynamics by attenuating neural modulation when the cursor gain is high and by damping the cursor velocity more strongly when the smoothing dynamics are high. Our control policy model may help to build better decoders, understand how neural activity varies during active iBCI control, and produce better simulations of closed-loop iBCI movements.

Feedback control policies employed by people using intracortical brain-computer interfaces

NASA Astrophysics Data System (ADS)

Willett, Francis R.; Pandarinath, Chethan; Jarosiewicz, Beata; Murphy, Brian A.; Memberg, William D.; Blabe, Christine H.; Saab, Jad; Walter, Benjamin L.; Sweet, Jennifer A.; Miller, Jonathan P.; Henderson, Jaimie M.; Shenoy, Krishna V.; Simeral, John D.; Hochberg, Leigh R.; Kirsch, Robert F.; Bolu Ajiboye, A.

2017-02-01

Objective. When using an intracortical BCI (iBCI), users modulate their neural population activity to move an effector towards a target, stop accurately, and correct for movement errors. We call the rules that govern this modulation a ‘feedback control policy’. A better understanding of these policies may inform the design of higher-performing neural decoders. Approach. We studied how three participants in the BrainGate2 pilot clinical trial used an iBCI to control a cursor in a 2D target acquisition task. Participants used a velocity decoder with exponential smoothing dynamics. Through offline analyses, we characterized the users’ feedback control policies by modeling their neural activity as a function of cursor state and target position. We also tested whether users could adapt their policy to different decoder dynamics by varying the gain (speed scaling) and temporal smoothing parameters of the iBCI. Main results. We demonstrate that control policy assumptions made in previous studies do not fully describe the policies of our participants. To account for these discrepancies, we propose a new model that captures (1) how the user’s neural population activity gradually declines as the cursor approaches the target from afar, then decreases more sharply as the cursor comes into contact with the target, (2) how the user makes constant feedback corrections even when the cursor is on top of the target, and (3) how the user actively accounts for the cursor’s current velocity to avoid overshooting the target. Further, we show that users can adapt their control policy to decoder dynamics by attenuating neural modulation when the cursor gain is high and by damping the cursor velocity more strongly when the smoothing dynamics are high. Significance. Our control policy model may help to build better decoders, understand how neural activity varies during active iBCI control, and produce better simulations of closed-loop iBCI movements.

Numerical and analytical bounds on threshold error rates for hypergraph-product codes

NASA Astrophysics Data System (ADS)

Kovalev, Alexey A.; Prabhakar, Sanjay; Dumer, Ilya; Pryadko, Leonid P.

2018-06-01

We study analytically and numerically decoding properties of finite-rate hypergraph-product quantum low density parity-check codes obtained from random (3,4)-regular Gallager codes, with a simple model of independent X and Z errors. Several nontrivial lower and upper bounds for the decodable region are constructed analytically by analyzing the properties of the homological difference, equal minus the logarithm of the maximum-likelihood decoding probability for a given syndrome. Numerical results include an upper bound for the decodable region from specific heat calculations in associated Ising models and a minimum-weight decoding threshold of approximately 7 % .

A new LDPC decoding scheme for PDM-8QAM BICM coherent optical communication system

NASA Astrophysics Data System (ADS)

Liu, Yi; Zhang, Wen-bo; Xi, Li-xia; Tang, Xian-feng; Zhang, Xiao-guang

2015-11-01

A new log-likelihood ratio (LLR) message estimation method is proposed for polarization-division multiplexing eight quadrature amplitude modulation (PDM-8QAM) bit-interleaved coded modulation (BICM) optical communication system. The formulation of the posterior probability is theoretically analyzed, and the way to reduce the pre-decoding bit error rate ( BER) of the low density parity check (LDPC) decoder for PDM-8QAM constellations is presented. Simulation results show that it outperforms the traditional scheme, i.e., the new post-decoding BER is decreased down to 50% of that of the traditional post-decoding algorithm.

A Systolic VLSI Design of a Pipeline Reed-solomon Decoder

NASA Technical Reports Server (NTRS)

Shao, H. M.; Truong, T. K.; Deutsch, L. J.; Yuen, J. H.; Reed, I. S.

1984-01-01

A pipeline structure of a transform decoder similar to a systolic array was developed to decode Reed-Solomon (RS) codes. An important ingredient of this design is a modified Euclidean algorithm for computing the error locator polynomial. The computation of inverse field elements is completely avoided in this modification of Euclid's algorithm. The new decoder is regular and simple, and naturally suitable for VLSI implementation.

A VLSI design of a pipeline Reed-Solomon decoder

NASA Technical Reports Server (NTRS)

Shao, H. M.; Truong, T. K.; Deutsch, L. J.; Yuen, J. H.; Reed, I. S.

1985-01-01

A pipeline structure of a transform decoder similar to a systolic array was developed to decode Reed-Solomon (RS) codes. An important ingredient of this design is a modified Euclidean algorithm for computing the error locator polynomial. The computation of inverse field elements is completely avoided in this modification of Euclid's algorithm. The new decoder is regular and simple, and naturally suitable for VLSI implementation.

Coding/decoding two-dimensional images with orbital angular momentum of light.

PubMed

Chu, Jiaqi; Li, Xuefeng; Smithwick, Quinn; Chu, Daping

2016-04-01

We investigate encoding and decoding of two-dimensional information using the orbital angular momentum (OAM) of light. Spiral phase plates and phase-only spatial light modulators are used in encoding and decoding of OAM states, respectively. We show that off-axis points and spatial variables encoded with a given OAM state can be recovered through decoding with the corresponding complimentary OAM state.

To sort or not to sort: the impact of spike-sorting on neural decoding performance.

PubMed

Todorova, Sonia; Sadtler, Patrick; Batista, Aaron; Chase, Steven; Ventura, Valérie

2014-10-01

Brain-computer interfaces (BCIs) are a promising technology for restoring motor ability to paralyzed patients. Spiking-based BCIs have successfully been used in clinical trials to control multi-degree-of-freedom robotic devices. Current implementations of these devices require a lengthy spike-sorting step, which is an obstacle to moving this technology from the lab to the clinic. A viable alternative is to avoid spike-sorting, treating all threshold crossings of the voltage waveform on an electrode as coming from one putative neuron. It is not known, however, how much decoding information might be lost by ignoring spike identity. We present a full analysis of the effects of spike-sorting schemes on decoding performance. Specifically, we compare how well two common decoders, the optimal linear estimator and the Kalman filter, reconstruct the arm movements of non-human primates performing reaching tasks, when receiving input from various sorting schemes. The schemes we tested included: using threshold crossings without spike-sorting; expert-sorting discarding the noise; expert-sorting, including the noise as if it were another neuron; and automatic spike-sorting using waveform features. We also decoded from a joint statistical model for the waveforms and tuning curves, which does not involve an explicit spike-sorting step. Discarding the threshold crossings that cannot be assigned to neurons degrades decoding: no spikes should be discarded. Decoding based on spike-sorted units outperforms decoding based on electrodes voltage crossings: spike-sorting is useful. The four waveform based spike-sorting methods tested here yield similar decoding efficiencies: a fast and simple method is competitive. Decoding using the joint waveform and tuning model shows promise but is not consistently superior. Our results indicate that simple automated spike-sorting performs as well as the more computationally or manually intensive methods used here. Even basic spike-sorting adds value to the low-threshold waveform-crossing methods often employed in BCI decoding.

To sort or not to sort: the impact of spike-sorting on neural decoding performance

NASA Astrophysics Data System (ADS)

Todorova, Sonia; Sadtler, Patrick; Batista, Aaron; Chase, Steven; Ventura, Valérie

2014-10-01

Objective. Brain-computer interfaces (BCIs) are a promising technology for restoring motor ability to paralyzed patients. Spiking-based BCIs have successfully been used in clinical trials to control multi-degree-of-freedom robotic devices. Current implementations of these devices require a lengthy spike-sorting step, which is an obstacle to moving this technology from the lab to the clinic. A viable alternative is to avoid spike-sorting, treating all threshold crossings of the voltage waveform on an electrode as coming from one putative neuron. It is not known, however, how much decoding information might be lost by ignoring spike identity. Approach. We present a full analysis of the effects of spike-sorting schemes on decoding performance. Specifically, we compare how well two common decoders, the optimal linear estimator and the Kalman filter, reconstruct the arm movements of non-human primates performing reaching tasks, when receiving input from various sorting schemes. The schemes we tested included: using threshold crossings without spike-sorting; expert-sorting discarding the noise; expert-sorting, including the noise as if it were another neuron; and automatic spike-sorting using waveform features. We also decoded from a joint statistical model for the waveforms and tuning curves, which does not involve an explicit spike-sorting step. Main results. Discarding the threshold crossings that cannot be assigned to neurons degrades decoding: no spikes should be discarded. Decoding based on spike-sorted units outperforms decoding based on electrodes voltage crossings: spike-sorting is useful. The four waveform based spike-sorting methods tested here yield similar decoding efficiencies: a fast and simple method is competitive. Decoding using the joint waveform and tuning model shows promise but is not consistently superior. Significance. Our results indicate that simple automated spike-sorting performs as well as the more computationally or manually intensive methods used here. Even basic spike-sorting adds value to the low-threshold waveform-crossing methods often employed in BCI decoding.

47 CFR 11.33 - EAS Decoder.

Code of Federal Regulations, 2011 CFR

2011-10-01

... time periods expire. (4) Display and logging. A visual message shall be developed from any valid header... input. (8) Decoder Programming. Access to decoder programming shall be protected by a lock or other...

Video Compression

NASA Technical Reports Server (NTRS)

1996-01-01

Optivision developed two PC-compatible boards and associated software under a Goddard Space Flight Center Small Business Innovation Research grant for NASA applications in areas such as telerobotics, telesciences and spaceborne experimentation. From this technology, the company used its own funds to develop commercial products, the OPTIVideo MPEG Encoder and Decoder, which are used for realtime video compression and decompression. They are used in commercial applications including interactive video databases and video transmission. The encoder converts video source material to a compressed digital form that can be stored or transmitted, and the decoder decompresses bit streams to provide high quality playback.

Development of a fault-tolerant microprocessor based computer system for space flight

NASA Technical Reports Server (NTRS)

Montgomery, V. T.

1981-01-01

A methodology for the design of a tightly coupled, highly reliable microprocessor based computer system is described. The concept of triple modular redundancy with sparing is used. The notion of synchronizing by using a single crystal oscillator is examined. The use of decoders to replace voters is also used. The decoders not only isolate the failed module but also allow error identification to be accomplished. Each module is to have its own RAM memory. The necessary circuitry to select a correct memory and the corresponding DMA controller was designed.

On the error probability of general tree and trellis codes with applications to sequential decoding

NASA Technical Reports Server (NTRS)

Johannesson, R.

1973-01-01

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.

Viterbi decoding for satellite and space communication.

NASA Technical Reports Server (NTRS)

Heller, J. A.; Jacobs, I. M.

1971-01-01

Convolutional coding and Viterbi decoding, along with binary phase-shift keyed modulation, is presented as an efficient system for reliable communication on power limited satellite and space channels. Performance results, obtained theoretically and through computer simulation, are given for optimum short constraint length codes for a range of code constraint lengths and code rates. System efficiency is compared for hard receiver quantization and 4 and 8 level soft quantization. The effects on performance of varying of certain parameters relevant to decoder complexity and cost are examined. Quantitative performance degradation due to imperfect carrier phase coherence is evaluated and compared to that of an uncoded system. As an example of decoder performance versus complexity, a recently implemented 2-Mbit/sec constraint length 7 Viterbi decoder is discussed. Finally a comparison is made between Viterbi and sequential decoding in terms of suitability to various system requirements.

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights

PubMed Central

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks. PMID:26973503

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights.

PubMed

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks.

Oriented modulation for watermarking in direct binary search halftone images.

PubMed

Guo, Jing-Ming; Su, Chang-Cheng; Liu, Yun-Fu; Lee, Hua; Lee, Jiann-Der

2012-09-01

In this paper, a halftoning-based watermarking method is presented. This method enables high pixel-depth watermark embedding, while maintaining high image quality. This technique is capable of embedding watermarks with pixel depths up to 3 bits without causing prominent degradation to the image quality. To achieve high image quality, the parallel oriented high-efficient direct binary search (DBS) halftoning is selected to be integrated with the proposed orientation modulation (OM) method. The OM method utilizes different halftone texture orientations to carry different watermark data. In the decoder, the least-mean-square-trained filters are applied for feature extraction from watermarked images in the frequency domain, and the naïve Bayes classifier is used to analyze the extracted features and ultimately to decode the watermark data. Experimental results show that the DBS-based OM encoding method maintains a high degree of image quality and realizes the processing efficiency and robustness to be adapted in printing applications.

All-in-one visual and computer decoding of multiple secrets: translated-flip VC with polynomial-style sharing

NASA Astrophysics Data System (ADS)

Wu, Chia-Hua; Lee, Suiang-Shyan; Lin, Ja-Chen

2017-06-01

This all-in-one hiding method creates two transparencies that have several decoding options: visual decoding with or without translation flipping and computer decoding. In visual decoding, two less-important (or fake) binary secret images S1 and S2 can be revealed. S1 is viewed by the direct stacking of two transparencies. S2 is viewed by flipping one transparency and translating the other to a specified coordinate before stacking. Finally, important/true secret files can be decrypted by a computer using the information extracted from transparencies. The encoding process to hide this information includes the translated-flip visual cryptography, block types, the ways to use polynomial-style sharing, and linear congruential generator. If a thief obtained both transparencies, which are stored in distinct places, he still needs to find the values of keys used in computer decoding to break through after viewing S1 and/or S2 by stacking. However, the thief might just try every other kind of stacking and finally quit finding more secrets; for computer decoding is totally different from stacking decoding. Unlike traditional image hiding that uses images as host media, our method hides fine gray-level images in binary transparencies. Thus, our host media are transparencies. Comparisons and analysis are provided.

Multiscale decoding for reliable brain-machine interface performance over time.

PubMed

Han-Lin Hsieh; Wong, Yan T; Pesaran, Bijan; Shanechi, Maryam M

2017-07-01

Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously use spikes and other recording modalities such as local field potentials (LFP), which are more robust to signal degradation over time. We have developed a multiscale decoder that can simultaneously model the different statistical profiles of multi-scale spike/LFP activity (discrete spikes vs. continuous LFP). This decoder can also run at multiple time-scales (millisecond for spikes vs. tens of milliseconds for LFP). Here, we validate the multiscale decoder for estimating the movement of 7 major upper-arm joint angles in a non-human primate (NHP) during a 3D reach-to-grasp task. The multiscale decoder uses motor cortical spike/LFP recordings as its input. We show that the multiscale decoder can improve decoding accuracy by adding information from LFP to spikes, while running at the fast millisecond time-scale of the spiking activity. Moreover, this improvement is achieved using relatively few LFP channels, demonstrating the robustness of the approach. These results suggest that using multiscale decoders has the potential to improve the reliability and longevity of BMIs.

On the decoding process in ternary error-correcting output codes.

PubMed

Escalera, Sergio; Pujol, Oriol; Radeva, Petia

2010-01-01

A common way to model multiclass classification problems is to design a set of binary classifiers and to combine them. Error-Correcting Output Codes (ECOC) represent a successful framework to deal with these type of problems. Recent works in the ECOC framework showed significant performance improvements by means of new problem-dependent designs based on the ternary ECOC framework. The ternary framework contains a larger set of binary problems because of the use of a "do not care" symbol that allows us to ignore some classes by a given classifier. However, there are no proper studies that analyze the effect of the new symbol at the decoding step. In this paper, we present a taxonomy that embeds all binary and ternary ECOC decoding strategies into four groups. We show that the zero symbol introduces two kinds of biases that require redefinition of the decoding design. A new type of decoding measure is proposed, and two novel decoding strategies are defined. We evaluate the state-of-the-art coding and decoding strategies over a set of UCI Machine Learning Repository data sets and into a real traffic sign categorization problem. The experimental results show that, following the new decoding strategies, the performance of the ECOC design is significantly improved.

Memory-efficient table look-up optimized algorithm for context-based adaptive variable length decoding in H.264/advanced video coding

NASA Astrophysics Data System (ADS)

Wang, Jianhua; Cheng, Lianglun; Wang, Tao; Peng, Xiaodong

2016-03-01

Table look-up operation plays a very important role during the decoding processing of context-based adaptive variable length decoding (CAVLD) in H.264/advanced video coding (AVC). However, frequent table look-up operation can result in big table memory access, and then lead to high table power consumption. Aiming to solve the problem of big table memory access of current methods, and then reduce high power consumption, a memory-efficient table look-up optimized algorithm is presented for CAVLD. The contribution of this paper lies that index search technology is introduced to reduce big memory access for table look-up, and then reduce high table power consumption. Specifically, in our schemes, we use index search technology to reduce memory access by reducing the searching and matching operations for code_word on the basis of taking advantage of the internal relationship among length of zero in code_prefix, value of code_suffix and code_lengh, thus saving the power consumption of table look-up. The experimental results show that our proposed table look-up algorithm based on index search can lower about 60% memory access consumption compared with table look-up by sequential search scheme, and then save much power consumption for CAVLD in H.264/AVC.

Decoding intravesical pressure from local field potentials in rat lumbosacral spinal cord

NASA Astrophysics Data System (ADS)

Im, Changkyun; Park, Hae Yong; Koh, Chin Su; Ryu, Sang Baek; Seo, In Seok; Kim, Yong Jung; Kim, Kyung Hwan; Shin, Hyung-Cheul

2016-10-01

Chronic monitoring of intravesical pressure is required to detect the onset of intravesical hypertension and the progression of a more severe condition. Recent reports demonstrate the bladder state can be monitored from the spiking activity of the dorsal root ganglia or lumbosacral spinal cord. However, one of the most serious challenges for these methods is the difficulty of sustained spike signal acquisition due to the high-electrode-location-sensitivity of spikes or neuro-degeneration. Alternatively, it has been demonstrated that local field potential recordings are less affected by encapsulation reactions or electrode location changes. Here, we hypothesized that local field potential (LFP) from the lumbosacral dorsal horn may provide information concerning the intravesical pressure. LFP and spike activities were simultaneously recorded from the lumbosacral spinal cord of anesthetized rats during bladder filling. The results show that the LFP activities carry significant information about intravesical pressure along with spiking activities. Importantly, the intravesical pressure is decoded from the power in high-frequency bands (83.9-256 Hz) with a substantial performance similar to that of the spike train decoding. These findings demonstrate that high-frequency LFP activity can be an alternative intravesical pressure monitoring signal, which could lead to a proper closed loop system for urinary control.

A model for sequential decoding overflow due to a noisy carrier reference. [communication performance prediction

NASA Technical Reports Server (NTRS)

Layland, J. W.

1974-01-01

An approximate analysis of the effect of a noisy carrier reference on the performance of sequential decoding is presented. The analysis uses previously developed techniques for evaluating noisy reference performance for medium-rate uncoded communications adapted to sequential decoding for data rates of 8 to 2048 bits/s. In estimating the ten to the minus fourth power deletion probability thresholds for Helios, the model agrees with experimental data to within the experimental tolerances. The computational problem involved in sequential decoding, carrier loop effects, the main characteristics of the medium-rate model, modeled decoding performance, and perspectives on future work are discussed.

Performance sustaining intracortical neural prostheses

NASA Astrophysics Data System (ADS)

Nuyujukian, Paul; Kao, Jonathan C.; Fan, Joline M.; Stavisky, Sergey D.; Ryu, Stephen I.; Shenoy, Krishna V.

2014-12-01

Objective. Neural prostheses, or brain-machine interfaces, aim to restore efficient communication and movement ability to those suffering from paralysis. A major challenge these systems face is robust performance, particularly with aging signal sources. The aim in this study was to develop a neural prosthesis that could sustain high performance in spite of signal instability while still minimizing retraining time. Approach. We trained two rhesus macaques implanted with intracortical microelectrode arrays 1-4 years prior to this study to acquire targets with a neurally-controlled cursor. We measured their performance via achieved bitrate (bits per second, bps). This task was repeated over contiguous days to evaluate the sustained performance across time. Main results. We found that in the monkey with a younger (i.e., two year old) implant and better signal quality, a fixed decoder could sustain performance for a month at a rate of 4 bps, the highest achieved communication rate reported to date. This fixed decoder was evaluated across 22 months and experienced a performance decline at a rate of 0.24 bps yr-1. In the monkey with the older (i.e., 3.5 year old) implant and poorer signal quality, a fixed decoder could not sustain performance for more than a few days. Nevertheless, performance in this monkey was maintained for two weeks without requiring additional online retraining time by utilizing prior days’ experimental data. Upon analysis of the changes in channel tuning, we found that this stability appeared partially attributable to the cancelling-out of neural tuning fluctuations when projected to two-dimensional cursor movements. Significance. The findings in this study (1) document the highest-performing communication neural prosthesis in monkeys, (2) confirm and extend prior reports of the stability of fixed decoders, and (3) demonstrate a protocol for system stability under conditions where fixed decoders would otherwise fail. These improvements to decoder stability are important for minimizing training time and should make neural prostheses more practical to use.

Testing interconnected VLSI circuits in the Big Viterbi Decoder

NASA Technical Reports Server (NTRS)

Onyszchuk, I. M.

1991-01-01

The Big Viterbi Decoder (BVD) is a powerful error-correcting hardware device for the Deep Space Network (DSN), in support of the Galileo and Comet Rendezvous Asteroid Flyby (CRAF)/Cassini Missions. Recently, a prototype was completed and run successfully at 400,000 or more decoded bits per second. This prototype is a complex digital system whose core arithmetic unit consists of 256 identical very large scale integration (VLSI) gate-array chips, 16 on each of 16 identical boards which are connected through a 28-layer, printed-circuit backplane using 4416 wires. Special techniques were developed for debugging, testing, and locating faults inside individual chips, on boards, and within the entire decoder. The methods are based upon hierarchical structure in the decoder, and require that chips or boards be wired themselves as Viterbi decoders. The basic procedure consists of sending a small set of known, very noisy channel symbols through a decoder, and matching observables against values computed by a software simulation. Also, tests were devised for finding open and short-circuited wires which connect VLSI chips on the boards and through the backplane.

State-space decoding of primary afferent neuron firing rates

NASA Astrophysics Data System (ADS)

Wagenaar, J. B.; Ventura, V.; Weber, D. J.

2011-02-01

Kinematic state feedback is important for neuroprostheses to generate stable and adaptive movements of an extremity. State information, represented in the firing rates of populations of primary afferent (PA) neurons, can be recorded at the level of the dorsal root ganglia (DRG). Previous work in cats showed the feasibility of using DRG recordings to predict the kinematic state of the hind limb using reverse regression. Although accurate decoding results were attained, reverse regression does not make efficient use of the information embedded in the firing rates of the neural population. In this paper, we present decoding results based on state-space modeling, and show that it is a more principled and more efficient method for decoding the firing rates in an ensemble of PA neurons. In particular, we show that we can extract confounded information from neurons that respond to multiple kinematic parameters, and that including velocity components in the firing rate models significantly increases the accuracy of the decoded trajectory. We show that, on average, state-space decoding is twice as efficient as reverse regression for decoding joint and endpoint kinematics.

Utilizing sensory prediction errors for movement intention decoding: A new methodology

PubMed Central

Nakamura, Keigo; Ando, Hideyuki

2018-01-01

We propose a new methodology for decoding movement intentions of humans. This methodology is motivated by the well-documented ability of the brain to predict sensory outcomes of self-generated and imagined actions using so-called forward models. We propose to subliminally stimulate the sensory modality corresponding to a user’s intended movement, and decode a user’s movement intention from his electroencephalography (EEG), by decoding for prediction errors—whether the sensory prediction corresponding to a user’s intended movement matches the subliminal sensory stimulation we induce. We tested our proposal in a binary wheelchair turning task in which users thought of turning their wheelchair either left or right. We stimulated their vestibular system subliminally, toward either the left or the right direction, using a galvanic vestibular stimulator and show that the decoding for prediction errors from the EEG can radically improve movement intention decoding performance. We observed an 87.2% median single-trial decoding accuracy across tested participants, with zero user training, within 96 ms of the stimulation, and with no additional cognitive load on the users because the stimulation was subliminal. PMID:29750195

Coding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram.

PubMed

Naud, Richard; Gerstner, Wulfram

2012-01-01

The response of a neuron to a time-dependent stimulus, as measured in a Peri-Stimulus-Time-Histogram (PSTH), exhibits an intricate temporal structure that reflects potential temporal coding principles. Here we analyze the encoding and decoding of PSTHs for spiking neurons with arbitrary refractoriness and adaptation. As a modeling framework, we use the spike response model, also known as the generalized linear neuron model. Because of refractoriness, the effect of the most recent spike on the spiking probability a few milliseconds later is very strong. The influence of the last spike needs therefore to be described with high precision, while the rest of the neuronal spiking history merely introduces an average self-inhibition or adaptation that depends on the expected number of past spikes but not on the exact spike timings. Based on these insights, we derive a 'quasi-renewal equation' which is shown to yield an excellent description of the firing rate of adapting neurons. We explore the domain of validity of the quasi-renewal equation and compare it with other rate equations for populations of spiking neurons. The problem of decoding the stimulus from the population response (or PSTH) is addressed analogously. We find that for small levels of activity and weak adaptation, a simple accumulator of the past activity is sufficient to decode the original input, but when refractory effects become large decoding becomes a non-linear function of the past activity. The results presented here can be applied to the mean-field analysis of coupled neuron networks, but also to arbitrary point processes with negative self-interaction.

Alexithymia and the Processing of Emotional Facial Expressions (EFEs): Systematic Review, Unanswered Questions and Further Perspectives

PubMed Central

Grynberg, Delphine; Chang, Betty; Corneille, Olivier; Maurage, Pierre; Vermeulen, Nicolas

2012-01-01

Alexithymia is characterized by difficulties in identifying, differentiating and describing feelings. A high prevalence of alexithymia has often been observed in clinical disorders characterized by low social functioning. This review aims to assess the association between alexithymia and the ability to decode emotional facial expressions (EFEs) within clinical and healthy populations. More precisely, this review has four main objectives: (1) to assess if alexithymia is a better predictor of the ability to decode EFEs than the diagnosis of clinical disorder; (2) to assess the influence of comorbid factors (depression and anxiety disorder) on the ability to decode EFE; (3) to investigate if deficits in decoding EFEs are specific to some levels of processing or task types; (4) to investigate if the deficits are specific to particular EFEs. Twenty four studies (behavioural and neuroimaging) were identified through a computerized literature search of Psycinfo, PubMed, and Web of Science databases from 1990 to 2010. Data on methodology, clinical characteristics, and possible confounds were analyzed. The review revealed that: (1) alexithymia is associated with deficits in labelling EFEs among clinical disorders, (2) the level of depression and anxiety partially account for the decoding deficits, (3) alexithymia is associated with reduced perceptual abilities, and is likely to be associated with impaired semantic representations of emotional concepts, and (4) alexithymia is associated with neither specific EFEs nor a specific valence. These studies are discussed with respect to processes involved in the recognition of EFEs. Future directions for research on emotion perception are also discussed. PMID:22927931

Exploring Differential Effects across Two Decoding Treatments on Item-Level Transfer in Children with Significant Word Reading Difficulties: A New Approach for Testing Intervention Elements

ERIC Educational Resources Information Center

Steacy, Laura M.; Elleman, Amy M.; Lovett, Maureen W.; Compton, Donald L.

2016-01-01

In English, gains in decoding skill do not map directly onto increases in word reading. However, beyond the Self-Teaching Hypothesis, little is known about the transfer of decoding skills to word reading. In this study, we offer a new approach to testing specific decoding elements on transfer to word reading. To illustrate, we modeled word-reading…

Comparison of memory thresholds for planar qudit geometries

NASA Astrophysics Data System (ADS)

Marks, Jacob; Jochym-O'Connor, Tomas; Gheorghiu, Vlad

2017-11-01

We introduce and analyze a new type of decoding algorithm called general color clustering, based on renormalization group methods, to be used in qudit color codes. The performance of this decoder is analyzed under a generalized bit-flip error model, and is used to obtain the first memory threshold estimates for qudit 6-6-6 color codes. The proposed decoder is compared with similar decoding schemes for qudit surface codes as well as the current leading qubit decoders for both sets of codes. We find that, as with surface codes, clustering performs sub-optimally for qubit color codes, giving a threshold of 5.6 % compared to the 8.0 % obtained through surface projection decoding methods. However, the threshold rate increases by up to 112% for large qudit dimensions, plateauing around 11.9 % . All the analysis is performed using QTop, a new open-source software for simulating and visualizing topological quantum error correcting codes.

Error-correction coding for digital communications

NASA Astrophysics Data System (ADS)

Clark, G. C., Jr.; Cain, J. B.

This book is written for the design engineer who must build the coding and decoding equipment and for the communication system engineer who must incorporate this equipment into a system. It is also suitable as a senior-level or first-year graduate text for an introductory one-semester course in coding theory. Fundamental concepts of coding are discussed along with group codes, taking into account basic principles, practical constraints, performance computations, coding bounds, generalized parity check codes, polynomial codes, and important classes of group codes. Other topics explored are related to simple nonalgebraic decoding techniques for group codes, soft decision decoding of block codes, algebraic techniques for multiple error correction, the convolutional code structure and Viterbi decoding, syndrome decoding techniques, and sequential decoding techniques. System applications are also considered, giving attention to concatenated codes, coding for the white Gaussian noise channel, interleaver structures for coded systems, and coding for burst noise channels.

Structural decoding of netrin-4 reveals a regulatory function towards mature basement membranes

PubMed Central

Reuten, Raphael; Patel, Trushar R.; McDougall, Matthew; Rama, Nicolas; Nikodemus, Denise; Gibert, Benjamin; Delcros, Jean-Guy; Prein, Carina; Meier, Markus; Metzger, Stéphanie; Zhou, Zhigang; Kaltenberg, Jennifer; McKee, Karen K.; Bald, Tobias; Tüting, Thomas; Zigrino, Paola; Djonov, Valentin; Bloch, Wilhelm; Clausen-Schaumann, Hauke; Poschl, Ernst; Yurchenco, Peter D.; Ehrbar, Martin; Mehlen, Patrick; Stetefeld, Jörg; Koch, Manuel

2016-01-01

Netrins, a family of laminin-related molecules, have been proposed to act as guidance cues either during nervous system development or the establishment of the vascular system. This was clearly demonstrated for netrin-1 via its interaction with the receptors DCC and UNC5s. However, mainly based on shared homologies with netrin-1, netrin-4 was also proposed to play a role in neuronal outgrowth and developmental/pathological angiogenesis via interactions with netrin-1 receptors. Here, we present the high-resolution structure of netrin-4, which shows unique features in comparison with netrin-1, and show that it does not bind directly to any of the known netrin-1 receptors. We show that netrin-4 disrupts laminin networks and basement membranes (BMs) through high-affinity binding to the laminin γ1 chain. We hypothesize that this laminin-related function is essential for the previously described effects on axon growth promotion and angiogenesis. Our study unveils netrin-4 as a non-enzymatic extracellular matrix protein actively disrupting pre-existing BMs. PMID:27901020

Classification with an edge: Improving semantic image segmentation with boundary detection

NASA Astrophysics Data System (ADS)

Marmanis, D.; Schindler, K.; Wegner, J. D.; Galliani, S.; Datcu, M.; Stilla, U.

2018-01-01

We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art methods rely on DCNNs as their workhorse. A major reason for their success is that deep networks learn to accumulate contextual information over very large receptive fields. However, this success comes at a cost, since the associated loss of effective spatial resolution washes out high-frequency details and leads to blurry object boundaries. Here, we propose to counter this effect by combining semantic segmentation with semantically informed edge detection, thus making class boundaries explicit in the model. First, we construct a comparatively simple, memory-efficient model by adding boundary detection to the SEGNET encoder-decoder architecture. Second, we also include boundary detection in FCN-type models and set up a high-end classifier ensemble. We show that boundary detection significantly improves semantic segmentation with CNNs in an end-to-end training scheme. Our best model achieves >90% overall accuracy on the ISPRS Vaihingen benchmark.

Soft-Decision Decoding of Binary Linear Block Codes Based on an Iterative Search Algorithm

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Moorthy, H. T.

1997-01-01

This correspondence presents a suboptimum soft-decision decoding scheme for binary linear block codes based on an iterative search algorithm. The scheme uses an algebraic decoder to iteratively generate a sequence of candidate codewords one at a time using a set of test error patterns that are constructed based on the reliability information of the received symbols. When a candidate codeword is generated, it is tested based on an optimality condition. If it satisfies the optimality condition, then it is the most likely (ML) codeword and the decoding stops. If it fails the optimality test, a search for the ML codeword is conducted in a region which contains the ML codeword. The search region is determined by the current candidate codeword and the reliability of the received symbols. The search is conducted through a purged trellis diagram for the given code using the Viterbi algorithm. If the search fails to find the ML codeword, a new candidate is generated using a new test error pattern, and the optimality test and search are renewed. The process of testing and search continues until either the MEL codeword is found or all the test error patterns are exhausted and the decoding process is terminated. Numerical results show that the proposed decoding scheme achieves either practically optimal performance or a performance only a fraction of a decibel away from the optimal maximum-likelihood decoding with a significant reduction in decoding complexity compared with the Viterbi decoding based on the full trellis diagram of the codes.

From classic motor imagery to complex movement intention decoding: The noninvasive Graz-BCI approach.

PubMed

Müller-Putz, G R; Schwarz, A; Pereira, J; Ofner, P

2016-01-01

In this chapter, we give an overview of the Graz-BCI research, from the classic motor imagery detection to complex movement intentions decoding. We start by describing the classic motor imagery approach, its application in tetraplegic end users, and the significant improvements achieved using coadaptive brain-computer interfaces (BCIs). These strategies have the drawback of not mirroring the way one plans a movement. To achieve a more natural control-and to reduce the training time-the movements decoded by the BCI need to be closely related to the user's intention. Within this natural control, we focus on the kinematic level, where movement direction and hand position or velocity can be decoded from noninvasive recordings. First, we review movement execution decoding studies, where we describe the decoding algorithms, their performance, and associated features. Second, we describe the major findings in movement imagination decoding, where we emphasize the importance of estimating the sources of the discriminative features. Third, we introduce movement target decoding, which could allow the determination of the target without knowing the exact movement-by-movement details. Aside from the kinematic level, we also address the goal level, which contains relevant information on the upcoming action. Focusing on hand-object interaction and action context dependency, we discuss the possible impact of some recent neurophysiological findings in the future of BCI control. Ideally, the goal and the kinematic decoding would allow an appropriate matching of the BCI to the end users' needs, overcoming the limitations of the classic motor imagery approach. © 2016 Elsevier B.V. All rights reserved.

Taking Attention Away from the Auditory Modality: Context-dependent Effects on Early Sensory Encoding of Speech.

PubMed

Xie, Zilong; Reetzke, Rachel; Chandrasekaran, Bharath

2018-05-24

Increasing visual perceptual load can reduce pre-attentive auditory cortical activity to sounds, a reflection of the limited and shared attentional resources for sensory processing across modalities. Here, we demonstrate that modulating visual perceptual load can impact the early sensory encoding of speech sounds, and that the impact of visual load is highly dependent on the predictability of the incoming speech stream. Participants (n = 20, 9 females) performed a visual search task of high (target similar to distractors) and low (target dissimilar to distractors) perceptual load, while early auditory electrophysiological responses were recorded to native speech sounds. Speech sounds were presented either in a 'repetitive context', or a less predictable 'variable context'. Independent of auditory stimulus context, pre-attentive auditory cortical activity was reduced during high visual load, relative to low visual load. We applied a data-driven machine learning approach to decode speech sounds from the early auditory electrophysiological responses. Decoding performance was found to be poorer under conditions of high (relative to low) visual load, when the incoming acoustic stream was predictable. When the auditory stimulus context was less predictable, decoding performance was substantially greater for the high (relative to low) visual load conditions. Our results provide support for shared attentional resources between visual and auditory modalities that substantially influence the early sensory encoding of speech signals in a context-dependent manner. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Protograph based LDPC codes with minimum distance linearly growing with block size

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher; Dolinar, Sam; Thorpe, Jeremy

2005-01-01

We propose several LDPC code constructions that simultaneously achieve good threshold and error floor performance. Minimum distance is shown to grow linearly with block size (similar to regular codes of variable degree at least 3) by considering ensemble average weight enumerators. Our constructions are based on projected graph, or protograph, structures that support high-speed decoder implementations. As with irregular ensembles, our constructions are sensitive to the proportion of degree-2 variable nodes. A code with too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code with too many such nodes tends to not exhibit a minimum distance that grows linearly in block length. In this paper we also show that precoding can be used to lower the threshold of regular LDPC codes. The decoding thresholds of the proposed codes, which have linearly increasing minimum distance in block size, outperform that of regular LDPC codes. Furthermore, a family of low to high rate codes, with thresholds that adhere closely to their respective channel capacity thresholds, is presented. Simulation results for a few example codes show that the proposed codes have low error floors as well as good threshold SNFt performance.

How Many U.S. High School Students Have a Foreign Language Reading "Disability"? Reading Without Meaning and the Simple View.

PubMed

Sparks, Richard L; Luebbers, Julie

Conventional wisdom suggests that students classified as learning disabled will exhibit difficulties with foreign language (FL) learning, but evidence has not supported a relationship between FL learning problems and learning disabilities. The simple view of reading model posits that reading comprehension is the product of word decoding and language comprehension and that there are good readers and 3 types of poor readers-dyslexic, hyperlexic, and garden variety-who exhibit different profiles of strengths and/or deficits in word decoding and language comprehension. In this study, a random sample of U.S. high school students completing first-, second-, and third-year Spanish courses were administered standardized measures of Spanish word decoding and reading comprehension, compared with monolingual Spanish readers from first to eleventh grades, and classified into reader types according to the simple view of reading. The majority of students fit the hyperlexic profile, and no participants fit the good reader profile until they were compared with first- and second-grade monolingual Spanish readers. Findings call into question the practice of diagnosing an FL "disability" before a student engages in FL study.

Multiformat decoder for a DSP-based IP set-top box

NASA Astrophysics Data System (ADS)

Pescador, F.; Garrido, M. J.; Sanz, C.; Juárez, E.; Samper, D.; Antoniello, R.

2007-05-01

Internet Protocol Set-Top Boxes (IP STBs) based on single-processor architectures have been recently introduced in the market. In this paper, the implementation of an MPEG-4 SP/ASP video decoder for a multi-format IP STB based on a TMS320DM641 DSP is presented. An initial decoder for PC platform was fully tested and ported to the DSP. Using this code an optimization process was started achieving a 90% speedup. This process allows real-time MPEG-4 SP/ASP decoding. The MPEG-4 decoder has been integrated in an IP STB and tested in a real environment using DVD movies and TV channels with excellent results.

Approximate maximum likelihood decoding of block codes

NASA Technical Reports Server (NTRS)

Greenberger, H. J.

1979-01-01

Approximate maximum likelihood decoding algorithms, based upon selecting a small set of candidate code words with the aid of the estimated probability of error of each received symbol, can give performance close to optimum with a reasonable amount of computation. By combining the best features of various algorithms and taking care to perform each step as efficiently as possible, a decoding scheme was developed which can decode codes which have better performance than those presently in use and yet not require an unreasonable amount of computation. The discussion of the details and tradeoffs of presently known efficient optimum and near optimum decoding algorithms leads, naturally, to the one which embodies the best features of all of them.

A MAP-based image interpolation method via Viterbi decoding of Markov chains of interpolation functions.

PubMed

Vedadi, Farhang; Shirani, Shahram

2014-01-01

A new method of image resolution up-conversion (image interpolation) based on maximum a posteriori sequence estimation is proposed. Instead of making a hard decision about the value of each missing pixel, we estimate the missing pixels in groups. At each missing pixel of the high resolution (HR) image, we consider an ensemble of candidate interpolation methods (interpolation functions). The interpolation functions are interpreted as states of a Markov model. In other words, the proposed method undergoes state transitions from one missing pixel position to the next. Accordingly, the interpolation problem is translated to the problem of estimating the optimal sequence of interpolation functions corresponding to the sequence of missing HR pixel positions. We derive a parameter-free probabilistic model for this to-be-estimated sequence of interpolation functions. Then, we solve the estimation problem using a trellis representation and the Viterbi algorithm. Using directional interpolation functions and sequence estimation techniques, we classify the new algorithm as an adaptive directional interpolation using soft-decision estimation techniques. Experimental results show that the proposed algorithm yields images with higher or comparable peak signal-to-noise ratios compared with some benchmark interpolation methods in the literature while being efficient in terms of implementation and complexity considerations.

Visual brain activity patterns classification with simultaneous EEG-fMRI: A multimodal approach.

PubMed

Ahmad, Rana Fayyaz; Malik, Aamir Saeed; Kamel, Nidal; Reza, Faruque; Amin, Hafeez Ullah; Hussain, Muhammad

2017-01-01

Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map the brain activity. For getting a high spatial and temporal resolution of the brain at the same time, simultaneous EEG-fMRI seems to be fruitful. In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes. Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature. The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.

Wide-field lensless fluorescent microscopy using a tapered fiber-optic faceplate on a chip.

PubMed

Coskun, Ahmet F; Sencan, Ikbal; Su, Ting-Wei; Ozcan, Aydogan

2011-09-07

We demonstrate lensless fluorescent microscopy over a large field-of-view of ~60 mm(2) with a spatial resolution of <4 µm. In this on-chip fluorescent imaging modality, the samples are placed on a fiber-optic faceplate that is tapered such that the density of the fiber-optic waveguides on the top facet is >5 fold larger than the bottom one. Placed on this tapered faceplate, the fluorescent samples are pumped from the side through a glass hemisphere interface. After excitation of the samples, the pump light is rejected through total internal reflection that occurs at the bottom facet of the sample substrate. The fluorescent emission from the sample is then collected by the smaller end of the tapered faceplate and is delivered to an opto-electronic sensor-array to be digitally sampled. Using a compressive sampling algorithm, we decode these raw lensfree images to validate the resolution (<4 µm) of this on-chip fluorescent imaging platform using microparticles as well as labeled Giardia muris cysts. This wide-field lensfree fluorescent microscopy platform, being compact and high-throughput, might provide a valuable tool especially for cytometry, rare cell analysis (involving large area microfluidic systems) as well as for microarray imaging applications.

Miniaturization of flight deflection measurement system

NASA Technical Reports Server (NTRS)

Fodale, Robert (Inventor); Hampton, Herbert R. (Inventor)

1990-01-01

A flight deflection measurement system is disclosed including a hybrid microchip of a receiver/decoder. The hybrid microchip decoder is mounted piggy back on the miniaturized receiver and forms an integral unit therewith. The flight deflection measurement system employing the miniaturized receiver/decoder can be used in a wind tunnel. In particular, the miniaturized receiver/decoder can be employed in a spin measurement system due to its small size and can retain already established control surface actuation functions.

Fast and Flexible Successive-Cancellation List Decoders for Polar Codes

NASA Astrophysics Data System (ADS)

Hashemi, Seyyed Ali; Condo, Carlo; Gross, Warren J.

2017-11-01

Polar codes have gained significant amount of attention during the past few years and have been selected as a coding scheme for the next generation of mobile broadband standard. Among decoding schemes, successive-cancellation list (SCL) decoding provides a reasonable trade-off between the error-correction performance and hardware implementation complexity when used to decode polar codes, at the cost of limited throughput. The simplified SCL (SSCL) and its extension SSCL-SPC increase the speed of decoding by removing redundant calculations when encountering particular information and frozen bit patterns (rate one and single parity check codes), while keeping the error-correction performance unaltered. In this paper, we improve SSCL and SSCL-SPC by proving that the list size imposes a specific number of bit estimations required to decode rate one and single parity check codes. Thus, the number of estimations can be limited while guaranteeing exactly the same error-correction performance as if all bits of the code were estimated. We call the new decoding algorithms Fast-SSCL and Fast-SSCL-SPC. Moreover, we show that the number of bit estimations in a practical application can be tuned to achieve desirable speed, while keeping the error-correction performance almost unchanged. Hardware architectures implementing both algorithms are then described and implemented: it is shown that our design can achieve 1.86 Gb/s throughput, higher than the best state-of-the-art decoders.

Low Density Parity Check Codes: Bandwidth Efficient Channel Coding

NASA Technical Reports Server (NTRS)

Fong, Wai; Lin, Shu; Maki, Gary; Yeh, Pen-Shu

2003-01-01

Low Density Parity Check (LDPC) Codes provide near-Shannon Capacity performance for NASA Missions. These codes have high coding rates R=0.82 and 0.875 with moderate code lengths, n=4096 and 8176. Their decoders have inherently parallel structures which allows for high-speed implementation. Two codes based on Euclidean Geometry (EG) were selected for flight ASIC implementation. These codes are cyclic and quasi-cyclic in nature and therefore have a simple encoder structure. This results in power and size benefits. These codes also have a large minimum distance as much as d,,, = 65 giving them powerful error correcting capabilities and error floors less than lo- BER. This paper will present development of the LDPC flight encoder and decoder, its applications and status.

Overview of Decoding across the Disciplines

ERIC Educational Resources Information Center

Boman, Jennifer; Currie, Genevieve; MacDonald, Ron; Miller-Young, Janice; Yeo, Michelle; Zettel, Stephanie

2017-01-01

In this chapter we describe the Decoding the Disciplines Faculty Learning Community at Mount Royal University and how Decoding has been used in new and multidisciplinary ways in the various teaching, curriculum, and research projects that are presented in detail in subsequent chapters.

Maximum likelihood decoding analysis of accumulate-repeat-accumulate codes

NASA Technical Reports Server (NTRS)

Abbasfar, A.; Divsalar, D.; Yao, K.

2004-01-01

In this paper, the performance of the repeat-accumulate codes with (ML) decoding are analyzed and compared to random codes by very tight bounds. Some simple codes are shown that perform very close to Shannon limit with maximum likelihood decoding.

Improved prediction of bimanual movements by a two-staged (effector-then-trajectory) decoder with epidural ECoG in nonhuman primates

NASA Astrophysics Data System (ADS)

Choi, Hoseok; Lee, Jeyeon; Park, Jinsick; Lee, Seho; Ahn, Kyoung-ha; Kim, In Young; Lee, Kyoung-Min; Jang, Dong Pyo

2018-02-01

Objective. In arm movement BCIs (brain-computer interfaces), unimanual research has been much more extensively studied than its bimanual counterpart. However, it is well known that the bimanual brain state is different from the unimanual one. Conventional methodology used in unimanual studies does not take the brain stage into consideration, and therefore appears to be insufficient for decoding bimanual movements. In this paper, we propose the use of a two-staged (effector-then-trajectory) decoder, which combines the classification of movement conditions and uses a hand trajectory predicting algorithm for unimanual and bimanual movements, for application in real-world BCIs. Approach. Two micro-electrode patches (32 channels) were inserted over the dura mater of the left and right hemispheres of two rhesus monkeys, covering the motor related cortex for epidural electrocorticograph (ECoG). Six motion sensors (inertial measurement unit) were used to record the movement signals. The monkeys performed three types of arm movement tasks: left unimanual, right unimanual, bimanual. To decode these movements, we used a two-staged decoder, which combines the effector classifier for four states (left unimanual, right unimanual, bimanual movements, and stationary state) and movement predictor using regression. Main results. Using this approach, we successfully decoded both arm positions using the proposed decoder. The results showed that decoding performance for bimanual movements were improved compared to the conventional method, which does not consider the effector, and the decoding performance was significant and stable over a period of four months. In addition, we also demonstrated the feasibility of epidural ECoG signals, which provided an adequate level of decoding accuracy. Significance. These results provide evidence that brain signals are different depending on the movement conditions or effectors. Thus, the two-staged method could be useful if BCIs are used to generalize for both unimanual and bimanual operations in human applications and in various neuro-prosthetics fields.

Influence of incident angle on the decoding in laser polarization encoding guidance

NASA Astrophysics Data System (ADS)

Zhou, Muchun; Chen, Yanru; Zhao, Qi; Xin, Yu; Wen, Hongyuan

2009-07-01

Dynamic detection of polarization states is very important for laser polarization coding guidance systems. In this paper, a set of dynamic polarization decoding and detection system used in laser polarization coding guidance was designed. Detection process of the normal incident polarized light is analyzed with Jones Matrix; the system can effectively detect changes in polarization. Influence of non-normal incident light on performance of polarization decoding and detection system is studied; analysis showed that changes in incident angle will have a negative impact on measure results, the non-normal incident influence is mainly caused by second-order birefringence and polarization sensitivity effect generated in the phase delay and beam splitter prism. Combined with Fresnel formula, decoding errors of linearly polarized light, elliptically polarized light and circularly polarized light with different incident angles into the detector are calculated respectively, the results show that the decoding errors increase with increase of incident angle. Decoding errors have relations with geometry parameters, material refractive index of wave plate, polarization beam splitting prism. Decoding error can be reduced by using thin low-order wave-plate. Simulation of detection of polarized light with different incident angle confirmed the corresponding conclusions.

Online decoding of object-based attention using real-time fMRI.

PubMed

Niazi, Adnan M; van den Broek, Philip L C; Klanke, Stefan; Barth, Markus; Poel, Mannes; Desain, Peter; van Gerven, Marcel A J

2014-01-01

Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Extracting duration information in a picture category decoding task using hidden Markov Models

NASA Astrophysics Data System (ADS)

Pfeiffer, Tim; Heinze, Nicolai; Frysch, Robert; Deouell, Leon Y.; Schoenfeld, Mircea A.; Knight, Robert T.; Rose, Georg

2016-04-01

Objective. Adapting classifiers for the purpose of brain signal decoding is a major challenge in brain-computer-interface (BCI) research. In a previous study we showed in principle that hidden Markov models (HMM) are a suitable alternative to the well-studied static classifiers. However, since we investigated a rather straightforward task, advantages from modeling of the signal could not be assessed. Approach. Here, we investigate a more complex data set in order to find out to what extent HMMs, as a dynamic classifier, can provide useful additional information. We show for a visual decoding problem that besides category information, HMMs can simultaneously decode picture duration without an additional training required. This decoding is based on a strong correlation that we found between picture duration and the behavior of the Viterbi paths. Main results. Decoding accuracies of up to 80% could be obtained for category and duration decoding with a single classifier trained on category information only. Significance. The extraction of multiple types of information using a single classifier enables the processing of more complex problems, while preserving good training results even on small databases. Therefore, it provides a convenient framework for online real-life BCI utilizations.

Building Bridges from the Decoding Interview to Teaching Practice

ERIC Educational Resources Information Center

Pettit, Jennifer; Rathburn, Melanie; Calvert, Victoria; Lexier, Roberta; Underwood, Margot; Gleeson, Judy; Dean, Yasmin

2017-01-01

This chapter describes a multidisciplinary faculty self-study about reciprocity in service-learning. The study began with each coauthor participating in a Decoding interview. We describe how Decoding combined with collaborative self-study had a positive impact on our teaching practice.