High-Speed, capacitance-based tip clearance sensing

NASA Astrophysics Data System (ADS)

Haase, W. C.; Haase, Z. S.

This paper discusses recent advances in tip clearance measurement systems for turbine engines using capacitive probes. Real time measurements of individual blade pulses are generated using wideband signal processing providing 3 dB bandwidths of typically 5 MHz. Subsequent mixed-signal processing circuitry provide real-time measurements of maximum, minimum, and average clearance with latencies of one blade-to-blade time interval. Both guarded and unguarded probe configurations are possible with the system. Calibration techniques provide high accuracy measurements.

A real-time spike sorting method based on the embedded GPU.

PubMed

Zelan Yang; Kedi Xu; Xiang Tian; Shaomin Zhang; Xiaoxiang Zheng

2017-07-01

Microelectrode arrays with hundreds of channels have been widely used to acquire neuron population signals in neuroscience studies. Online spike sorting is becoming one of the most important challenges for high-throughput neural signal acquisition systems. Graphic processing unit (GPU) with high parallel computing capability might provide an alternative solution for increasing real-time computational demands on spike sorting. This study reported a method of real-time spike sorting through computing unified device architecture (CUDA) which was implemented on an embedded GPU (NVIDIA JETSON Tegra K1, TK1). The sorting approach is based on the principal component analysis (PCA) and K-means. By analyzing the parallelism of each process, the method was further optimized in the thread memory model of GPU. Our results showed that the GPU-based classifier on TK1 is 37.92 times faster than the MATLAB-based classifier on PC while their accuracies were the same with each other. The high-performance computing features of embedded GPU demonstrated in our studies suggested that the embedded GPU provide a promising platform for the real-time neural signal processing.

Overview of the DART project

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

Berry, K.R.; Hansen, F.R.; Napolitano, L.M.

1992-01-01

DART (DSP Arrary for Reconfigurable Tasks) is a parallel architecture of two high-performance SDP (digital signal processing) chips with the flexibility to handle a wide range of real-time applications. Each of the 32-bit floating-point DSP processes in DART is programmable in a high-level languate ( C'' or Ada). We have added extensions to the real-time operating system used by DART in order to support parallel processor. The combination of high-level language programmability, a real-time operating system, and parallel processing support significantly reduces the development cost of application software for signal processing and control applications. We have demonstrated this capability bymore » using DART to reconstruct images in the prototype VIP (Video Imaging Projectile) groundstation.« less

Overview of the DART project

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

Berry, K.R.; Hansen, F.R.; Napolitano, L.M.

1992-01-01

DART (DSP Arrary for Reconfigurable Tasks) is a parallel architecture of two high-performance SDP (digital signal processing) chips with the flexibility to handle a wide range of real-time applications. Each of the 32-bit floating-point DSP processes in DART is programmable in a high-level languate (``C`` or Ada). We have added extensions to the real-time operating system used by DART in order to support parallel processor. The combination of high-level language programmability, a real-time operating system, and parallel processing support significantly reduces the development cost of application software for signal processing and control applications. We have demonstrated this capability by usingmore » DART to reconstruct images in the prototype VIP (Video Imaging Projectile) groundstation.« less

PAU/GNSS-R: Implementation, Performance and First Results of a Real-Time Delay-Doppler Map Reflectometer Using Global Navigation Satellite System Signals

PubMed Central

Marchan-Hernandez, Juan Fernando; Camps, Adriano; Rodriguez-Alvarez, Nereida; Bosch-Lluis, Xavier; Ramos-Perez, Isaac; Valencia, Enric

2008-01-01

Signals from Global Navigation Satellite Systems (GNSS) were originally conceived for position and speed determination, but they can be used as signals of opportunity as well. The reflection process over a given surface modifies the properties of the scattered signal, and therefore, by processing the reflected signal, relevant geophysical data regarding the surface under study (land, sea, ice…) can be retrieved. In essence, a GNSS-R receiver is a multi-channel GNSS receiver that computes the received power from a given satellite at a number of different delay and Doppler bins of the incoming signal. The first approaches to build such a receiver consisted of sampling and storing the scattered signal for later post-processing. However, a real-time approach to the problem is desirable to obtain immediately useful geophysical variables and reduce the amount of data. The use of FPGA technology makes this possible, while at the same time the system can be easily reconfigured. The signal tracking and processing constraints made necessary to fully design several new blocks. The uniqueness of the implemented system described in this work is the capability to compute in real-time Delay-Doppler maps (DDMs) either for four simultaneous satellites or just one, but with a larger number of bins. The first tests have been conducted from a cliff over the sea and demonstrate the successful performance of the instrument to compute DDMs in real-time from the measured reflected GNSS/R signals. The processing of these measurements shall yield quantitative relationships between the sea state (mainly driven by the surface wind and the swell) and the overall DDM shape. The ultimate goal is to use the DDM shape to correct the sea state influence on the L-band brightness temperature to improve the retrieval of the sea surface salinity (SSS). PMID:27879862

Research on photodiode detector-based spatial transient light detection and processing system

NASA Astrophysics Data System (ADS)

Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng

2016-10-01

In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.

Real-Time and Memory Correlation via Acousto-Optic Processing,

DTIC Science & Technology

1978-06-01

acousto - optic technology as an answer to these requirements appears very attractive. Three fundamental signal-processing schemes using the acousto ... optic interaction have been investigated: (i) real-time correlation and convolution, (ii) Fourier and discrete Fourier transformation, and (iii

A customizable system for real-time image processing using the Blackfin DSProcessor and the MicroC/OS-II real-time kernel

NASA Astrophysics Data System (ADS)

Coffey, Stephen; Connell, Joseph

2005-06-01

This paper presents a development platform for real-time image processing based on the ADSP-BF533 Blackfin processor and the MicroC/OS-II real-time operating system (RTOS). MicroC/OS-II is a completely portable, ROMable, pre-emptive, real-time kernel. The Blackfin Digital Signal Processors (DSPs), incorporating the Analog Devices/Intel Micro Signal Architecture (MSA), are a broad family of 16-bit fixed-point products with a dual Multiply Accumulate (MAC) core. In addition, they have a rich instruction set with variable instruction length and both DSP and MCU functionality thus making them ideal for media based applications. Using the MicroC/OS-II for task scheduling and management, the proposed system can capture and process raw RGB data from any standard 8-bit greyscale image sensor in soft real-time and then display the processed result using a simple PC graphical user interface (GUI). Additionally, the GUI allows configuration of the image capture rate and the system and core DSP clock rates thereby allowing connectivity to a selection of image sensors and memory devices. The GUI also allows selection from a set of image processing algorithms based in the embedded operating system.

Signal processing in ultrasound. [for diagnostic medicine

NASA Technical Reports Server (NTRS)

Le Croissette, D. H.; Gammell, P. M.

1978-01-01

Signal is the term used to denote the characteristic in the time or frequency domain of the probing energy of the system. Processing of this signal in diagnostic ultrasound occurs as the signal travels through the ultrasonic and electrical sections of the apparatus. The paper discusses current signal processing methods, postreception processing, display devices, real-time imaging, and quantitative measurements in noninvasive cardiology. The possibility of using deconvolution in a single transducer system is examined, and some future developments using digital techniques are outlined.

Real-Time Visualization of Tissue Ischemia

NASA Technical Reports Server (NTRS)

Bearman, Gregory H. (Inventor); Chrien, Thomas D. (Inventor); Eastwood, Michael L. (Inventor)

2000-01-01

A real-time display of tissue ischemia which comprises three CCD video cameras, each with a narrow bandwidth filter at the correct wavelength is discussed. The cameras simultaneously view an area of tissue suspected of having ischemic areas through beamsplitters. The output from each camera is adjusted to give the correct signal intensity for combining with, the others into an image for display. If necessary a digital signal processor (DSP) can implement algorithms for image enhancement prior to display. Current DSP engines are fast enough to give real-time display. Measurement at three, wavelengths, combined into a real-time Red-Green-Blue (RGB) video display with a digital signal processing (DSP) board to implement image algorithms, provides direct visualization of ischemic areas.

Long-range wind monitoring in real time with optimized coherent lidar

NASA Astrophysics Data System (ADS)

Dolfi-Bouteyre, Agnes; Canat, Guillaume; Lombard, Laurent; Valla, Matthieu; Durécu, Anne; Besson, Claudine

2017-03-01

Two important enabling technologies for pulsed coherent detection wind lidar are the laser and real-time signal processing. In particular, fiber laser is limited in peak power by nonlinear effects, such as stimulated Brillouin scattering (SBS). We report on various technologies that have been developed to mitigate SBS and increase peak power in 1.5-μm fiber lasers, such as special large mode area fiber designs or strain management. Range-resolved wind profiles up to a record range of 16 km within 0.1-s averaging time have been obtained thanks to those high-peak power fiber lasers. At long range, the lidar signal gets much weaker than the noise and special care is required to extract the Doppler peak from the spectral noise. To optimize real-time processing for weak carrier-to-noise ratio signal, we have studied various Doppler mean frequency estimators (MFE) and the influence of data accumulation on outliers occurrence. Five real-time MFEs (maximum, centroid, matched filter, maximum likelihood, and polynomial fit) have been compared in terms of error and processing time using lidar experimental data. MFE errors and data accumulation limits are established using a spectral method.

The software system development for the TAMU real-time fan beam scatterometer data processors

NASA Technical Reports Server (NTRS)

Clark, B. V.; Jean, B. R.

1980-01-01

A software package was designed and written to process in real-time any one quadrature channel pair of radar scatterometer signals form the NASA L- or C-Band radar scatterometer systems. The software was successfully tested in the C-Band processor breadboard hardware using recorded radar and NERDAS (NASA Earth Resources Data Annotation System) signals as the input data sources. The processor development program and the overall processor theory of operation and design are described. The real-time processor software system is documented and the results of the laboratory software tests, and recommendations for the efficient application of the data processing capabilities are presented.

Real-time prediction of hand trajectory by ensembles of cortical neurons in primates

NASA Astrophysics Data System (ADS)

Wessberg, Johan; Stambaugh, Christopher R.; Kralik, Jerald D.; Beck, Pamela D.; Laubach, Mark; Chapin, John K.; Kim, Jung; Biggs, S. James; Srinivasan, Mandayam A.; Nicolelis, Miguel A. L.

2000-11-01

Signals derived from the rat motor cortex can be used for controlling one-dimensional movements of a robot arm. It remains unknown, however, whether real-time processing of cortical signals can be employed to reproduce, in a robotic device, the kind of complex arm movements used by primates to reach objects in space. Here we recorded the simultaneous activity of large populations of neurons, distributed in the premotor, primary motor and posterior parietal cortical areas, as non-human primates performed two distinct motor tasks. Accurate real-time predictions of one- and three-dimensional arm movement trajectories were obtained by applying both linear and nonlinear algorithms to cortical neuronal ensemble activity recorded from each animal. In addition, cortically derived signals were successfully used for real-time control of robotic devices, both locally and through the Internet. These results suggest that long-term control of complex prosthetic robot arm movements can be achieved by simple real-time transformations of neuronal population signals derived from multiple cortical areas in primates.

Defense Applications of Signal Processing

DTIC Science & Technology

1999-08-27

class of multiscale autoregressive moving average (MARMA) processes. These are generalisations of ARMA models in time series analysis , and they contain...including the two theoretical sinusoidal components. Analysis of the amplitude and frequency time series provided some novel insight into the real...communication channels, underwater acoustic signals, radar systems , economic time series and biomedical signals [7]. The alpha stable (aS) distribution has

A Versatile Multichannel Digital Signal Processing Module for Microcalorimeter Arrays

NASA Astrophysics Data System (ADS)

Tan, H.; Collins, J. W.; Walby, M.; Hennig, W.; Warburton, W. K.; Grudberg, P.

2012-06-01

Different techniques have been developed for reading out microcalorimeter sensor arrays: individual outputs for small arrays, and time-division or frequency-division or code-division multiplexing for large arrays. Typically, raw waveform data are first read out from the arrays using one of these techniques and then stored on computer hard drives for offline optimum filtering, leading not only to requirements for large storage space but also limitations on achievable count rate. Thus, a read-out module that is capable of processing microcalorimeter signals in real time will be highly desirable. We have developed multichannel digital signal processing electronics that are capable of on-board, real time processing of microcalorimeter sensor signals from multiplexed or individual pixel arrays. It is a 3U PXI module consisting of a standardized core processor board and a set of daughter boards. Each daughter board is designed to interface a specific type of microcalorimeter array to the core processor. The combination of the standardized core plus this set of easily designed and modified daughter boards results in a versatile data acquisition module that not only can easily expand to future detector systems, but is also low cost. In this paper, we first present the core processor/daughter board architecture, and then report the performance of an 8-channel daughter board, which digitizes individual pixel outputs at 1 MSPS with 16-bit precision. We will also introduce a time-division multiplexing type daughter board, which takes in time-division multiplexing signals through fiber-optic cables and then processes the digital signals to generate energy spectra in real time.

Analysis of real-time vibration data

USGS Publications Warehouse

Safak, E.

2005-01-01

In recent years, a few structures have been instrumented to provide continuous vibration data in real time, recording not only large-amplitude motions generated by extreme loads, but also small-amplitude motions generated by ambient loads. The main objective in continuous recording is to track any changes in structural characteristics, and to detect damage after an extreme event, such as an earthquake or explosion. The Fourier-based spectral analysis methods have been the primary tool to analyze vibration data from structures. In general, such methods do not work well for real-time data, because real-time data are mainly composed of ambient vibrations with very low amplitudes and signal-to-noise ratios. The long duration, linearity, and the stationarity of ambient data, however, allow us to utilize statistical signal processing tools, which can compensate for the adverse effects of low amplitudes and high noise. The analysis of real-time data requires tools and techniques that can be applied in real-time; i.e., data are processed and analyzed while being acquired. This paper presents some of the basic tools and techniques for processing and analyzing real-time vibration data. The topics discussed include utilization of running time windows, tracking mean and mean-square values, filtering, system identification, and damage detection.

Real-Time Neural Signals Decoding onto Off-the-Shelf DSP Processors for Neuroprosthetic Applications.

PubMed

Pani, Danilo; Barabino, Gianluca; Citi, Luca; Meloni, Paolo; Raspopovic, Stanisa; Micera, Silvestro; Raffo, Luigi

2016-09-01

The control of upper limb neuroprostheses through the peripheral nervous system (PNS) can allow restoring motor functions in amputees. At present, the important aspect of the real-time implementation of neural decoding algorithms on embedded systems has been often overlooked, notwithstanding the impact that limited hardware resources have on the efficiency/effectiveness of any given algorithm. Present study is addressing the optimization of a template matching based algorithm for PNS signals decoding that is a milestone for its real-time, full implementation onto a floating-point digital signal processor (DSP). The proposed optimized real-time algorithm achieves up to 96% of correct classification on real PNS signals acquired through LIFE electrodes on animals, and can correctly sort spikes of a synthetic cortical dataset with sufficiently uncorrelated spike morphologies (93% average correct classification) comparably to the results obtained with top spike sorter (94% on average on the same dataset). The power consumption enables more than 24 h processing at the maximum load, and latency model has been derived to enable a fair performance assessment. The final embodiment demonstrates the real-time performance onto a low-power off-the-shelf DSP, opening to experiments exploiting the efferent signals to control a motor neuroprosthesis.

Nonlinear Real-Time Optical Signal Processing.

DTIC Science & Technology

1981-06-30

bandwidth and space-bandwidth products. Real-time homonorphic and loga- rithmic filtering by halftone nonlinear processing has been achieved. A...Page ABSTRACT 1 1. RESEARCH OBJECTIVES AND PROGRESS 3 I-- 1.1 Introduction and Project overview 3 1.2 Halftone Processing 9 1.3 Direct Nonlinear...time homomorphic and logarithmic filtering by halftone nonlinear processing has been achieved. A detailed analysis of degradation due to the finite gamma

[Image processing system of visual prostheses based on digital signal processor DM642].

PubMed

Xie, Chengcheng; Lu, Yanyu; Gu, Yun; Wang, Jing; Chai, Xinyu

2011-09-01

This paper employed a DSP platform to create the real-time and portable image processing system, and introduced a series of commonly used algorithms for visual prostheses. The results of performance evaluation revealed that this platform could afford image processing algorithms to be executed in real time.

Experimental demonstration of real-time adaptively modulated DDO-OFDM systems with a high spectral efficiency up to 5.76bit/s/Hz transmission over SMF links.

PubMed

Chen, Ming; He, Jing; Tang, Jin; Wu, Xian; Chen, Lin

2014-07-28

In this paper, a FPGAs-based real-time adaptively modulated 256/64/16QAM-encoded base-band OFDM transceiver with a high spectral efficiency up to 5.76bit/s/Hz is successfully developed, and experimentally demonstrated in a simple intensity-modulated direct-detection optical communication system. Experimental results show that it is feasible to transmit a raw signal bit rate of 7.19Gbps adaptively modulated real-time optical OFDM signal over 20km and 50km single mode fibers (SMFs). The performance comparison between real-time and off-line digital signal processing is performed, and the results show that there is a negligible power penalty. In addition, to obtain the best transmission performance, direct-current (DC) bias voltage for MZM and launch power into optical fiber links are explored in the real-time optical OFDM systems.

An Open-Source Hardware and Software System for Acquisition and Real-Time Processing of Electrophysiology during High Field MRI

PubMed Central

Purdon, Patrick L.; Millan, Hernan; Fuller, Peter L.; Bonmassar, Giorgio

2008-01-01

Simultaneous recording of electrophysiology and functional magnetic resonance imaging (fMRI) is a technique of growing importance in neuroscience. Rapidly evolving clinical and scientific requirements have created a need for hardware and software that can be customized for specific applications. Hardware may require customization to enable a variety of recording types (e.g., electroencephalogram, local field potentials, or multi-unit activity) while meeting the stringent and costly requirements of MRI safety and compatibility. Real-time signal processing tools are an enabling technology for studies of learning, attention, sleep, epilepsy, neurofeedback, and neuropharmacology, yet real-time signal processing tools are difficult to develop. We describe an open source system for simultaneous electrophysiology and fMRI featuring low-noise (< 0.6 uV p-p input noise), electromagnetic compatibility for MRI (tested up to 7 Tesla), and user-programmable real-time signal processing. The hardware distribution provides the complete specifications required to build an MRI-compatible electrophysiological data acquisition system, including circuit schematics, print circuit board (PCB) layouts, Gerber files for PCB fabrication and robotic assembly, a bill of materials with part numbers, data sheets, and vendor information, and test procedures. The software facilitates rapid implementation of real-time signal processing algorithms. This system has used in human EEG/fMRI studies at 3 and 7 Tesla examining the auditory system, visual system, sleep physiology, and anesthesia, as well as in intracranial electrophysiological studies of the non-human primate visual system during 3 Tesla fMRI, and in human hyperbaric physiology studies at depths of up to 300 feet below sea level. PMID:18761038

An open-source hardware and software system for acquisition and real-time processing of electrophysiology during high field MRI.

PubMed

Purdon, Patrick L; Millan, Hernan; Fuller, Peter L; Bonmassar, Giorgio

2008-11-15

Simultaneous recording of electrophysiology and functional magnetic resonance imaging (fMRI) is a technique of growing importance in neuroscience. Rapidly evolving clinical and scientific requirements have created a need for hardware and software that can be customized for specific applications. Hardware may require customization to enable a variety of recording types (e.g., electroencephalogram, local field potentials, or multi-unit activity) while meeting the stringent and costly requirements of MRI safety and compatibility. Real-time signal processing tools are an enabling technology for studies of learning, attention, sleep, epilepsy, neurofeedback, and neuropharmacology, yet real-time signal processing tools are difficult to develop. We describe an open-source system for simultaneous electrophysiology and fMRI featuring low-noise (<0.6microV p-p input noise), electromagnetic compatibility for MRI (tested up to 7T), and user-programmable real-time signal processing. The hardware distribution provides the complete specifications required to build an MRI-compatible electrophysiological data acquisition system, including circuit schematics, print circuit board (PCB) layouts, Gerber files for PCB fabrication and robotic assembly, a bill of materials with part numbers, data sheets, and vendor information, and test procedures. The software facilitates rapid implementation of real-time signal processing algorithms. This system has been used in human EEG/fMRI studies at 3 and 7T examining the auditory system, visual system, sleep physiology, and anesthesia, as well as in intracranial electrophysiological studies of the non-human primate visual system during 3T fMRI, and in human hyperbaric physiology studies at depths of up to 300 feet below sea level.

Super-Resolution of Multi-Pixel and Sub-Pixel Images for the SDI

DTIC Science & Technology

1993-06-08

where the phase of the transmitted signal is not needed. The Wigner - Ville distribution ( WVD ) of a real signal s(t), associated with the complex...B. Boashash, 0. P. Kenny and H. J. Whitehouse, "Radar imaging using the Wigner - Ville distribution ", in Real-Time Signal Processing, J. P. Letellier...analytic signal z(t), is a time- frequency distribution defined as-’- 00 W(tf) Z (~t + ) t- -)exp(-i2nft) . (45) Note that the WVD is the double Fourier

Nonlinear Real-Time Optical Signal Processing.

DTIC Science & Technology

1984-10-01

I 1.8 IIII III1 1 / U , 0 7 USCIPI Report 1130 E ~C~,OUTfitA N Ivj) UNIVERSITY OF SOUTHERN CALIFORNIA - I FINAL TECHNICAL REPORT April 15, 1981 - June...30, 1984 N NONLINEAR REAL-TIME OPTICAL SIGNAL PROCESSING i E ~ A.A. Sawchuk, Principal Investigator T.C. Strand and A.R. Tanguay. Jr. October 1, 1984...Erter.d) logic system. A computer generated hologram fabricated on an e -beam system serves as a beamsteering interconnection element. A completely

Real-time digital signal processing in multiphoton and time-resolved microscopy

NASA Astrophysics Data System (ADS)

Wilson, Jesse W.; Warren, Warren S.; Fischer, Martin C.

2016-03-01

The use of multiphoton interactions in biological tissue for imaging contrast requires highly sensitive optical measurements. These often involve signal processing and filtering steps between the photodetector and the data acquisition device, such as photon counting and lock-in amplification. These steps can be implemented as real-time digital signal processing (DSP) elements on field-programmable gate array (FPGA) devices, an approach that affords much greater flexibility than commercial photon counting or lock-in devices. We will present progress toward developing two new FPGA-based DSP devices for multiphoton and time-resolved microscopy applications. The first is a high-speed multiharmonic lock-in amplifier for transient absorption microscopy, which is being developed for real-time analysis of the intensity-dependence of melanin, with applications in vivo and ex vivo (noninvasive histopathology of melanoma and pigmented lesions). The second device is a kHz lock-in amplifier running on a low cost (50-200) development platform. It is our hope that these FPGA-based DSP devices will enable new, high-speed, low-cost applications in multiphoton and time-resolved microscopy.

Investigation of optical current transformer signal processing method based on an improved Kalman algorithm

NASA Astrophysics Data System (ADS)

Shen, Yan; Ge, Jin-ming; Zhang, Guo-qing; Yu, Wen-bin; Liu, Rui-tong; Fan, Wei; Yang, Ying-xuan

2018-01-01

This paper explores the problem of signal processing in optical current transformers (OCTs). Based on the noise characteristics of OCTs, such as overlapping signals, noise frequency bands, low signal-to-noise ratios, and difficulties in acquiring statistical features of noise power, an improved standard Kalman filtering algorithm was proposed for direct current (DC) signal processing. The state-space model of the OCT DC measurement system is first established, and then mixed noise can be processed by adding mixed noise into measurement and state parameters. According to the minimum mean squared error criterion, state predictions and update equations of the improved Kalman algorithm could be deduced based on the established model. An improved central difference Kalman filter was proposed for alternating current (AC) signal processing, which improved the sampling strategy and noise processing of colored noise. Real-time estimation and correction of noise were achieved by designing AC and DC noise recursive filters. Experimental results show that the improved signal processing algorithms had a good filtering effect on the AC and DC signals with mixed noise of OCT. Furthermore, the proposed algorithm was able to achieve real-time correction of noise during the OCT filtering process.

Real-time processing of radar return on a parallel computer

NASA Technical Reports Server (NTRS)

Aalfs, David D.

1992-01-01

NASA is working with the FAA to demonstrate the feasibility of pulse Doppler radar as a candidate airborne sensor to detect low altitude windshears. The need to provide the pilot with timely information about possible hazards has motivated a demand for real-time processing of a radar return. Investigated here is parallel processing as a means of accommodating the high data rates required. A PC based parallel computer, called the transputer, is used to investigate issues in real time concurrent processing of radar signals. A transputer network is made up of an array of single instruction stream processors that can be networked in a variety of ways. They are easily reconfigured and software development is largely independent of the particular network topology. The performance of the transputer is evaluated in light of the computational requirements. A number of algorithms have been implemented on the transputers in OCCAM, a language specially designed for parallel processing. These include signal processing algorithms such as the Fast Fourier Transform (FFT), pulse-pair, and autoregressive modelling, as well as routing software to support concurrency. The most computationally intensive task is estimating the spectrum. Two approaches have been taken on this problem, the first and most conventional of which is to use the FFT. By using table look-ups for the basis function and other optimizing techniques, an algorithm has been developed that is sufficient for real time. The other approach is to model the signal as an autoregressive process and estimate the spectrum based on the model coefficients. This technique is attractive because it does not suffer from the spectral leakage problem inherent in the FFT. Benchmark tests indicate that autoregressive modeling is feasible in real time.

A real-time spectrum acquisition system design based on quantum dots-quantum well detector

NASA Astrophysics Data System (ADS)

Zhang, S. H.; Guo, F. M.

2016-01-01

In this paper, we studied the structure characteristics of quantum dots-quantum well photodetector with response wavelength range from 400 nm to 1000 nm. It has the characteristics of high sensitivity, low dark current and the high conductance gain. According to the properties of the quantum dots-quantum well photodetectors, we designed a new type of capacitive transimpedence amplifier (CTIA) readout circuit structure with the advantages of adjustable gain, wide bandwidth and high driving ability. We have implemented the chip packaging between CTIA-CDS structure readout circuit and quantum dots detector and tested the readout response characteristics. According to the timing signals requirements of our readout circuit, we designed a real-time spectral data acquisition system based on FPGA and ARM. Parallel processing mode of programmable devices makes the system has high sensitivity and high transmission rate. In addition, we realized blind pixel compensation and smoothing filter algorithm processing to the real time spectrum data by using C++. Through the fluorescence spectrum measurement of carbon quantum dots and the signal acquisition system and computer software system to realize the collection of the spectrum signal processing and analysis, we verified the excellent characteristics of detector. It meets the design requirements of quantum dot spectrum acquisition system with the characteristics of short integration time, real-time and portability.

Software engineering aspects of real-time programming concepts

NASA Astrophysics Data System (ADS)

Schoitsch, Erwin

1986-08-01

Real-time programming is a discipline of great importance not only in process control, but also in fields like communication, office automation, interactive databases, interactive graphics and operating systems development. General concepts of concurrent programming and constructs for process-synchronization are discussed in detail. Tasking and synchronization concepts, methods of process communication, interrupt and timeout handling in systems based on semaphores, signals, conditional critical regions or on real-time languages like Concurrent PASCAL, MODULA, CHILL and ADA are explained and compared with each other. The second part deals with structuring and modularization of technical processes to build reliable and maintainable real time systems. Software-quality and software engineering aspects are considered throughout the paper.

Signal processing methodologies for an acoustic fetal heart rate monitor

NASA Technical Reports Server (NTRS)

Pretlow, Robert A., III; Stoughton, John W.

1992-01-01

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

"Fast" Is Not "Real-Time": Designing Effective Real-Time AI Systems

NASA Astrophysics Data System (ADS)

O'Reilly, Cindy A.; Cromarty, Andrew S.

1985-04-01

Realistic practical problem domains (such as robotics, process control, and certain kinds of signal processing) stand to benefit greatly from the application of artificial intelligence techniques. These problem domains are of special interest because they are typified by complex dynamic environments in which the ability to select and initiate a proper response to environmental events in real time is a strict prerequisite to effective environmental interaction. Artificial intelligence systems developed to date have been sheltered from this real-time requirement, however, largely by virtue of their use of simplified problem domains or problem representations. The plethora of colloquial and (in general) mutually inconsistent interpretations of the term "real-time" employed by workers in each of these domains further exacerbates the difficul-ties in effectively applying state-of-the-art problem solving tech-niques to time-critical problems. Indeed, the intellectual waters are by now sufficiently muddied that the pursuit of a rigorous treatment of intelligent real-time performance mandates the redevelopment of proper problem perspective on what "real-time" means, starting from first principles. We present a simple but nonetheless formal definition of real-time performance. We then undertake an analysis of both conventional techniques and AI technology with respect to their ability to meet substantive real-time performance criteria. This analysis provides a basis for specification of problem-independent design requirements for systems that would claim real-time performance. Finally, we discuss the application of these design principles to a pragmatic problem in real-time signal understanding.

A real time ECG signal processing application for arrhythmia detection on portable devices

NASA Astrophysics Data System (ADS)

Georganis, A.; Doulgeraki, N.; Asvestas, P.

2017-11-01

Arrhythmia describes the disorders of normal heart rate, which, depending on the case, can even be fatal for a patient with severe history of heart disease. The purpose of this work is to develop an application for heart signal visualization, processing and analysis in Android portable devices e.g. Mobile phones, tablets, etc. The application is able to retrieve the signal initially from a file and at a later stage this signal is processed and analysed within the device so that it can be classified according to the features of the arrhythmia. In the processing and analysing stage, different algorithms are included among them the Moving Average and Pan Tompkins algorithm as well as the use of wavelets, in order to extract features and characteristics. At the final stage, testing is performed by simulating our application in real-time records, using the TCP network protocol for communicating the mobile with a simulated signal source. The classification of ECG beat to be processed is performed by neural networks.

High-resolution correlation

NASA Astrophysics Data System (ADS)

Nelson, D. J.

2007-09-01

In the basic correlation process a sequence of time-lag-indexed correlation coefficients are computed as the inner or dot product of segments of two signals. The time-lag(s) for which the magnitude of the correlation coefficient sequence is maximized is the estimated relative time delay of the two signals. For discrete sampled signals, the delay estimated in this manner is quantized with the same relative accuracy as the clock used in sampling the signals. In addition, the correlation coefficients are real if the input signals are real. There have been many methods proposed to estimate signal delay to more accuracy than the sample interval of the digitizer clock, with some success. These methods include interpolation of the correlation coefficients, estimation of the signal delay from the group delay function, and beam forming techniques, such as the MUSIC algorithm. For spectral estimation, techniques based on phase differentiation have been popular, but these techniques have apparently not been applied to the correlation problem . We propose a phase based delay estimation method (PBDEM) based on the phase of the correlation function that provides a significant improvement of the accuracy of time delay estimation. In the process, the standard correlation function is first calculated. A time lag error function is then calculated from the correlation phase and is used to interpolate the correlation function. The signal delay is shown to be accurately estimated as the zero crossing of the correlation phase near the index of the peak correlation magnitude. This process is nearly as fast as the conventional correlation function on which it is based. For real valued signals, a simple modification is provided, which results in the same correlation accuracy as is obtained for complex valued signals.

Optical information-processing systems and architectures II; Proceedings of the Meeting, San Diego, CA, July 9-13, 1990

NASA Astrophysics Data System (ADS)

Javidi, Bahram

The present conference discusses topics in the fields of neural networks, acoustooptic signal processing, pattern recognition, phase-only processing, nonlinear signal processing, image processing, optical computing, and optical information processing. Attention is given to the optical implementation of an inner-product neural associative memory, optoelectronic associative recall via motionless-head/parallel-readout optical disk, a compact real-time acoustooptic image correlator, a multidimensional synthetic estimation filter, and a light-efficient joint transform optical correlator. Also discussed are a high-resolution spatial light modulator, compact real-time interferometric Fourier-transform processors, a fast decorrelation algorithm for permutation arrays, the optical interconnection of optical modules, and carry-free optical binary adders.

Digital CODEC for real-time processing of broadcast quality video signals at 1.8 bits/pixel

NASA Technical Reports Server (NTRS)

Shalkhauser, Mary JO; Whyte, Wayne A., Jr.

1989-01-01

Advances in very large-scale integration and recent work in the field of bandwidth efficient digital modulation techniques have combined to make digital video processing technically feasible and potentially cost competitive for broadcast quality television transmission. A hardware implementation was developed for a DPCM-based digital television bandwidth compression algorithm which processes standard NTSC composite color television signals and produces broadcast quality video in real time at an average of 1.8 bits/pixel. The data compression algorithm and the hardware implementation of the CODEC are described, and performance results are provided.

Digital CODEC for real-time processing of broadcast quality video signals at 1.8 bits/pixel

NASA Technical Reports Server (NTRS)

Shalkhauser, Mary JO; Whyte, Wayne A.

1991-01-01

Advances in very large scale integration and recent work in the field of bandwidth efficient digital modulation techniques have combined to make digital video processing technically feasible an potentially cost competitive for broadcast quality television transmission. A hardware implementation was developed for DPCM (differential pulse code midulation)-based digital television bandwidth compression algorithm which processes standard NTSC composite color television signals and produces broadcast quality video in real time at an average of 1.8 bits/pixel. The data compression algorithm and the hardware implementation of the codec are described, and performance results are provided.

Independent component analysis algorithm FPGA design to perform real-time blind source separation

NASA Astrophysics Data System (ADS)

Meyer-Baese, Uwe; Odom, Crispin; Botella, Guillermo; Meyer-Baese, Anke

2015-05-01

The conditions that arise in the Cocktail Party Problem prevail across many fields creating a need for of Blind Source Separation. The need for BSS has become prevalent in several fields of work. These fields include array processing, communications, medical signal processing, and speech processing, wireless communication, audio, acoustics and biomedical engineering. The concept of the cocktail party problem and BSS led to the development of Independent Component Analysis (ICA) algorithms. ICA proves useful for applications needing real time signal processing. The goal of this research was to perform an extensive study on ability and efficiency of Independent Component Analysis algorithms to perform blind source separation on mixed signals in software and implementation in hardware with a Field Programmable Gate Array (FPGA). The Algebraic ICA (A-ICA), Fast ICA, and Equivariant Adaptive Separation via Independence (EASI) ICA were examined and compared. The best algorithm required the least complexity and fewest resources while effectively separating mixed sources. The best algorithm was the EASI algorithm. The EASI ICA was implemented on hardware with Field Programmable Gate Arrays (FPGA) to perform and analyze its performance in real time.

Comparison of sEMG-Based Feature Extraction and Motion Classification Methods for Upper-Limb Movement

PubMed Central

Guo, Shuxiang; Pang, Muye; Gao, Baofeng; Hirata, Hideyuki; Ishihara, Hidenori

2015-01-01

The surface electromyography (sEMG) technique is proposed for muscle activation detection and intuitive control of prostheses or robot arms. Motion recognition is widely used to map sEMG signals to the target motions. One of the main factors preventing the implementation of this kind of method for real-time applications is the unsatisfactory motion recognition rate and time consumption. The purpose of this paper is to compare eight combinations of four feature extraction methods (Root Mean Square (RMS), Detrended Fluctuation Analysis (DFA), Weight Peaks (WP), and Muscular Model (MM)) and two classifiers (Neural Networks (NN) and Support Vector Machine (SVM)), for the task of mapping sEMG signals to eight upper-limb motions, to find out the relation between these methods and propose a proper combination to solve this issue. Seven subjects participated in the experiment and six muscles of the upper-limb were selected to record sEMG signals. The experimental results showed that NN classifier obtained the highest recognition accuracy rate (88.7%) during the training process while SVM performed better in real-time experiments (85.9%). For time consumption, SVM took less time than NN during the training process but needed more time for real-time computation. Among the four feature extraction methods, WP had the highest recognition rate for the training process (97.7%) while MM performed the best during real-time tests (94.3%). The combination of MM and NN is recommended for strict real-time applications while a combination of MM and SVM will be more suitable when time consumption is not a key requirement. PMID:25894941

Real Time Phase Noise Meter Based on a Digital Signal Processor

NASA Technical Reports Server (NTRS)

Angrisani, Leopoldo; D'Arco, Mauro; Greenhall, Charles A.; Schiano Lo Morille, Rosario

2006-01-01

A digital signal-processing meter for phase noise measurement on sinusoidal signals is dealt with. It enlists a special hardware architecture, made up of a core digital signal processor connected to a data acquisition board, and takes advantage of a quadrature demodulation-based measurement scheme, already proposed by the authors. Thanks to an efficient measurement process and an optimized implementation of its fundamental stages, the proposed meter succeeds in exploiting all hardware resources in such an effective way as to gain high performance and real-time operation. For input frequencies up to some hundreds of kilohertz, the meter is capable both of updating phase noise power spectrum while seamlessly capturing the analyzed signal into its memory, and granting as good frequency resolution as few units of hertz.

Fast, multi-channel real-time processing of signals with microsecond latency using graphics processing units.

PubMed

Rath, N; Kato, S; Levesque, J P; Mauel, M E; Navratil, G A; Peng, Q

2014-04-01

Fast, digital signal processing (DSP) has many applications. Typical hardware options for performing DSP are field-programmable gate arrays (FPGAs), application-specific integrated DSP chips, or general purpose personal computer systems. This paper presents a novel DSP platform that has been developed for feedback control on the HBT-EP tokamak device. The system runs all signal processing exclusively on a Graphics Processing Unit (GPU) to achieve real-time performance with latencies below 8 μs. Signals are transferred into and out of the GPU using PCI Express peer-to-peer direct-memory-access transfers without involvement of the central processing unit or host memory. Tests were performed on the feedback control system of the HBT-EP tokamak using forty 16-bit floating point inputs and outputs each and a sampling rate of up to 250 kHz. Signals were digitized by a D-TACQ ACQ196 module, processing done on an NVIDIA GTX 580 GPU programmed in CUDA, and analog output was generated by D-TACQ AO32CPCI modules.

Research on control law accelerator of digital signal process chip TMS320F28035 for real-time data acquisition and processing

NASA Astrophysics Data System (ADS)

Zhao, Shuangle; Zhang, Xueyi; Sun, Shengli; Wang, Xudong

2017-08-01

TI C2000 series digital signal process (DSP) chip has been widely used in electrical engineering, measurement and control, communications and other professional fields, DSP TMS320F28035 is one of the most representative of a kind. When using the DSP program, need data acquisition and data processing, and if the use of common mode C or assembly language programming, the program sequence, analogue-to-digital (AD) converter cannot be real-time acquisition, often missing a lot of data. The control low accelerator (CLA) processor can run in parallel with the main central processing unit (CPU), and the frequency is consistent with the main CPU, and has the function of floating point operations. Therefore, the CLA coprocessor is used in the program, and the CLA kernel is responsible for data processing. The main CPU is responsible for the AD conversion. The advantage of this method is to reduce the time of data processing and realize the real-time performance of data acquisition.

Software-safety and software quality assurance in real-time applications Part 2: Real-time structures and languages

NASA Astrophysics Data System (ADS)

Schoitsch, Erwin

1988-07-01

Our society is depending more and more on the reliability of embedded (real-time) computer systems even in every-day life. Considering the complexity of the real world, this might become a severe threat. Real-time programming is a discipline important not only in process control and data acquisition systems, but also in fields like communication, office automation, interactive databases, interactive graphics and operating systems development. General concepts of concurrent programming and constructs for process-synchronization are discussed in detail. Tasking and synchronization concepts, methods of process communication, interrupt- and timeout handling in systems based on semaphores, signals, conditional critical regions or on real-time languages like Concurrent PASCAL, MODULA, CHILL and ADA are explained and compared with each other and with respect to their potential to quality and safety.

Real-time, in situ monitoring of nanoporation using electric field-induced acoustic signal

NASA Astrophysics Data System (ADS)

Zarafshani, Ali; Faiz, Rowzat; Samant, Pratik; Zheng, Bin; Xiang, Liangzhong

2018-02-01

The use of nanoporation in reversible or irreversible electroporation, e.g. cancer ablation, is rapidly growing. This technique uses an ultra-short and intense electric pulse to increase the membrane permeability, allowing non-permeant drugs and genes access to the cytosol via nanopores in the plasma membrane. It is vital to create a real-time in situ monitoring technique to characterize this process and answer the need created by the successful electroporation procedure of cancer treatment. All suggested monitoring techniques for electroporation currently are for pre-and post-stimulation exposure with no real-time monitoring during electric field exposure. This study was aimed at developing an innovative technology for real-time in situ monitoring of electroporation based on the typical cell exposure-induced acoustic emissions. The acoustic signals are the result of the electric field, which itself can be used in realtime to characterize the process of electroporation. We varied electric field distribution by varying the electric pulse from 1μ - 100ns and varying the voltage intensity from 0 - 1.2ܸ݇ to energize two electrodes in a bi-polar set-up. An ultrasound transducer was used for collecting acoustic signals around the subject under test. We determined the relative location of the acoustic signals by varying the position of the electrodes relative to the transducer and varying the electric field distribution between the electrodes to capture a variety of acoustic signals. Therefore, the electric field that is utilized in the nanoporation technique also produces a series of corresponding acoustic signals. This offers a novel imaging technique for the real-time in situ monitoring of electroporation that may directly improve treatment efficiency.

Interferometer with Continuously Varying Path Length Measured in Wavelengths to the Reference Mirror

NASA Technical Reports Server (NTRS)

Ohara, Tetsuo (Inventor)

2016-01-01

An interferometer in which the path length of the reference beam, measured in wavelengths, is continuously changing in sinusoidal fashion and the interference signal created by combining the measurement beam and the reference beam is processed in real time to obtain the physical distance along the measurement beam between the measured surface and a spatial reference frame such as the beam splitter. The processing involves analyzing the Fourier series of the intensity signal at one or more optical detectors in real time and using the time-domain multi-frequency harmonic signals to extract the phase information independently at each pixel position of one or more optical detectors and converting the phase information to distance information.

Real Time Conference 2014 Overview

NASA Astrophysics Data System (ADS)

Nomachi, Masaharu

2015-06-01

This article presents an overview of the 19th Real Time Conference held last May 26-30, 2014, at the Nara Prefectural New Public Hall, Nara, Japan, organized by the Research Center for Nuclear Physics of the Osaka University. The program included many invited talks and oral sessions offering an extensive overview on the following topics: real-time system architectures, intelligent signal processing, fast data transfer links and networks, trigger systems, data acquisition, processing-farms, control, monitoring and test systems, emerging real-time technologies, new standards, real-time safety and security, and some feedback on experiences. In parallel to the oral and poster presentations, industrial exhibits by companies, workshops and short courses also ran through the week.

A demonstration of real-time connected element interferometry for spacecraft navigation

NASA Technical Reports Server (NTRS)

Edwards, C.; Rogstad, D.; Fort, D.; White, L.; Iijima, B.

1992-01-01

Connected element interferometry is a technique of observing a celestial radio source at two spatially separated antennas, and then interfering the received signals to extract the relative phase of the signal at the two antennas. The high precision of the resulting phase delay data type can provide an accurate determination of the angular position of the radio source relative to the baseline vector between the two stations. A connected element interferometer on a 21-km baseline between two antennas at the Deep Space Network's Goldstone, CA tracking complex is developed. Fiber optic links are used to transmit the data at 112 Mbit/sec to a common site for processing. A real-time correlator to process these data in real-time is implemented. The architecture of the system is described, and observational data is presented to characterize the potential performance of such a system. The real-time processing capability offers potential advantages in terms of increased reliability and improved delivery of navigational data for time-critical operations. Angular accuracies of 50-100 nrad are achievable on this baseline.

The goldstone real-time connected element interferometer

NASA Technical Reports Server (NTRS)

Edwards, C., Jr.; Rogstad, D.; Fort, D.; White, L.; Iijima, B.

1992-01-01

Connected element interferometry (CEI) is a technique of observing a celestial radio source at two spatially separated antennas and then interfering the received signals to extract the relative phase of the signal at the two antennas. The high precision of the resulting phase delay data type can provide an accurate determination of the angular position of the radio source relative to the baseline vector between the two stations. This article describes a recently developed connected element interferometer on a 21-km baseline between two antennas at the Deep Space Network's Goldstone, California, tracking complex. Fiber-optic links are used to transmit the data to a common site for processing. The system incorporates a real-time correlator to process these data in real time. The architecture of the system is described, and observational data are presented to characterize the potential performance of such a system. The real-time processing capability offers potential advantages in terms of increased reliability and improved delivery of navigational data for time-critical operations. Angular accuracies of 50-100 nrad are achievable on this baseline.

Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method.

PubMed

Batres-Mendoza, Patricia; Ibarra-Manzano, Mario A; Guerra-Hernandez, Erick I; Almanza-Ojeda, Dora L; Montoro-Sanjose, Carlos R; Romero-Troncoso, Rene J; Rostro-Gonzalez, Horacio

2017-01-01

We present an improvement to the quaternion-based signal analysis (QSA) technique to extract electroencephalography (EEG) signal features with a view to developing real-time applications, particularly in motor imagery (IM) cognitive processes. The proposed methodology (iQSA, improved QSA) extracts features such as the average, variance, homogeneity, and contrast of EEG signals related to motor imagery in a more efficient manner (i.e., by reducing the number of samples needed to classify the signal and improving the classification percentage) compared to the original QSA technique. Specifically, we can sample the signal in variable time periods (from 0.5 s to 3 s, in half-a-second intervals) to determine the relationship between the number of samples and their effectiveness in classifying signals. In addition, to strengthen the classification process a number of boosting-technique-based decision trees were implemented. The results show an 82.30% accuracy rate for 0.5 s samples and 73.16% for 3 s samples. This is a significant improvement compared to the original QSA technique that offered results from 33.31% to 40.82% without sampling window and from 33.44% to 41.07% with sampling window, respectively. We can thus conclude that iQSA is better suited to develop real-time applications.

Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method

PubMed Central

Batres-Mendoza, Patricia; Guerra-Hernandez, Erick I.; Almanza-Ojeda, Dora L.; Montoro-Sanjose, Carlos R.

2017-01-01

We present an improvement to the quaternion-based signal analysis (QSA) technique to extract electroencephalography (EEG) signal features with a view to developing real-time applications, particularly in motor imagery (IM) cognitive processes. The proposed methodology (iQSA, improved QSA) extracts features such as the average, variance, homogeneity, and contrast of EEG signals related to motor imagery in a more efficient manner (i.e., by reducing the number of samples needed to classify the signal and improving the classification percentage) compared to the original QSA technique. Specifically, we can sample the signal in variable time periods (from 0.5 s to 3 s, in half-a-second intervals) to determine the relationship between the number of samples and their effectiveness in classifying signals. In addition, to strengthen the classification process a number of boosting-technique-based decision trees were implemented. The results show an 82.30% accuracy rate for 0.5 s samples and 73.16% for 3 s samples. This is a significant improvement compared to the original QSA technique that offered results from 33.31% to 40.82% without sampling window and from 33.44% to 41.07% with sampling window, respectively. We can thus conclude that iQSA is better suited to develop real-time applications. PMID:29348744

Development of a real time bistatic radar receiver using signals of opportunity

NASA Astrophysics Data System (ADS)

Rainville, Nicholas

Passive bistatic radar remote sensing offers a novel method of monitoring the Earth's surface by observing reflected signals of opportunity. The Global Positioning System (GPS) has been used as a source of signals for these observations and the scattering properties of GPS signals from rough surfaces are well understood. Recent work has extended GPS signal reflection observations and scattering models to include communications signals such as XM radio signals. However the communication signal reflectometry experiments to date have relied on collecting raw, high data-rate signals which are then post-processed after the end of the experiment. This thesis describes the development of a communication signal bistatic radar receiver which computes a real time correlation waveform, which can be used to retrieve measurements of the Earth's surface. The real time bistatic receiver greatly reduces the quantity of data that must be stored to perform the remote sensing measurements, as well as offering immediate feedback. This expands the applications for the receiver to include space and bandwidth limited platforms such as aircraft and satellites. It also makes possible the adjustment of flight plans to the observed conditions. This real time receiver required the development of an FGPA based signal processor, along with the integration of commercial Satellite Digital Audio Radio System (SDARS) components. The resulting device was tested both in a lab environment as well on NOAA WP-3D and NASA WB-57 aircraft.

Real time microcontroller implementation of an adaptive myoelectric filter.

PubMed

Bagwell, P J; Chappell, P H

1995-03-01

This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.

Characterization of a 300-GHz Transmission System for Digital Communications

NASA Astrophysics Data System (ADS)

Hudlička, Martin; Salhi, Mohammed; Kleine-Ostmann, Thomas; Schrader, Thorsten

2017-08-01

The paper presents the characterization of a 300-GHz transmission system for modern digital communications. The quality of the modulated signal at the output of the system (error vector magnitude, EVM) is measured using a vector signal analyzer. A method using a digital real-time oscilloscope and consecutive mathematical processing in a computer is shown for analysis of signals with bandwidths exceeding that of state-of-the-art vector signal analyzers. The uncertainty of EVM measured using the real-time oscilloscope is open to analysis. Behaviour of the 300-GHz transmission system is studied with respect to various modulation schemes and different signal symbol rates.

Deep neural networks to enable real-time multimessenger astrophysics

NASA Astrophysics Data System (ADS)

George, Daniel; Huerta, E. A.

2018-02-01

Gravitational wave astronomy has set in motion a scientific revolution. To further enhance the science reach of this emergent field of research, there is a pressing need to increase the depth and speed of the algorithms used to enable these ground-breaking discoveries. We introduce Deep Filtering—a new scalable machine learning method for end-to-end time-series signal processing. Deep Filtering is based on deep learning with two deep convolutional neural networks, which are designed for classification and regression, to detect gravitational wave signals in highly noisy time-series data streams and also estimate the parameters of their sources in real time. Acknowledging that some of the most sensitive algorithms for the detection of gravitational waves are based on implementations of matched filtering, and that a matched filter is the optimal linear filter in Gaussian noise, the application of Deep Filtering using whitened signals in Gaussian noise is investigated in this foundational article. The results indicate that Deep Filtering outperforms conventional machine learning techniques, achieves similar performance compared to matched filtering, while being several orders of magnitude faster, allowing real-time signal processing with minimal resources. Furthermore, we demonstrate that Deep Filtering can detect and characterize waveform signals emitted from new classes of eccentric or spin-precessing binary black holes, even when trained with data sets of only quasicircular binary black hole waveforms. The results presented in this article, and the recent use of deep neural networks for the identification of optical transients in telescope data, suggests that deep learning can facilitate real-time searches of gravitational wave sources and their electromagnetic and astroparticle counterparts. In the subsequent article, the framework introduced herein is directly applied to identify and characterize gravitational wave events in real LIGO data.

Real-Time GNSS Positioning with JPL's new GIPSYx Software

NASA Astrophysics Data System (ADS)

Bar-Sever, Y. E.

2016-12-01

The JPL Global Differential GPS (GDGPS) System is now producing real-time orbit and clock solutions for GPS, GLONASS, BeiDou, and Galileo. The operations are based on JPL's next generation geodetic analysis and data processing software, GIPSYx (also known at RTGx). We will examine the impact of the nascent GNSS constellations on real-time kinematic positioning for earthquake monitoring, and assess the marginal benefits from each constellation. We will discus the options for signal selection, inter-signal bias modeling, and estimation strategies in the context of real-time point positioning. We will provide a brief overview of the key features and attributes of GIPSYx. Finally we will describe the current natural hazard monitoring services from the GDGPS System.

Realization of guitar audio effects using methods of digital signal processing

NASA Astrophysics Data System (ADS)

Buś, Szymon; Jedrzejewski, Konrad

2015-09-01

The paper is devoted to studies on possibilities of realization of guitar audio effects by means of methods of digital signal processing. As a result of research, some selected audio effects corresponding to the specifics of guitar sound were realized as the real-time system called Digital Guitar Multi-effect. Before implementation in the system, the selected effects were investigated using the dedicated application with a graphical user interface created in Matlab environment. In the second stage, the real-time system based on a microcontroller and an audio codec was designed and realized. The system is designed to perform audio effects on the output signal of an electric guitar.

Station to instrumented aircraft L-band telemetry system and RF signal controller for spacecraft simulations and station calibration

NASA Technical Reports Server (NTRS)

Scaffidi, C. A.; Stocklin, F. J.; Feldman, M. B.

1971-01-01

An L-band telemetry system designed to provide the capability of near-real-time processing of calibration data is described. The system also provides the capability of performing computerized spacecraft simulations, with the aircraft as a data source, and evaluating the network response. The salient characteristics of a telemetry analysis and simulation program (TASP) are discussed, together with the results of TASP testing. The results of the L-band system testing have successfully demonstrated the capability of near-real-time processing of telemetry test data, the control of the ground-received signal to within + or - 0.5 db, and the computer generation of test signals.

Real-time implementations of acoustic signal enhancement techniques for aerial based surveillance and rescue applications

NASA Astrophysics Data System (ADS)

Ramos, Antonio L. L.; Shao, Zhili; Holthe, Aleksander; Sandli, Mathias F.

2017-05-01

The introduction of the System-on-Chip (SoC) technology has brought exciting new opportunities for the development of smart low cost embedded systems spanning a wide range of applications. Currently available SoC devices are capable of performing high speed digital signal processing tasks in software while featuring relatively low development costs and reduced time-to-market. Unmanned aerial vehicles (UAV) are an application example that has shown tremendous potential in an increasing number of scenarios, ranging from leisure to surveillance as well as in search and rescue missions. Video capturing from UAV platforms is a relatively straightforward task that requires almost no preprocessing. However, that does not apply to audio signals, especially in cases where the data is to be used to support real-time decision making. In fact, the enormous amount of acoustic interference from the surroundings, including the noise from the UAVs propellers, becomes a huge problem. This paper discusses a real-time implementation of the NLMS adaptive filtering algorithm applied to enhancing acoustic signals captured from UAV platforms. The model relies on a combination of acoustic sensors and a computational inexpensive algorithm running on a digital signal processor. Given its simplicity, this solution can be incorporated into the main processing system of an UAV using the SoC technology, and run concurrently with other required tasks, such as flight control and communications. Simulations and real-time DSP-based implementations have shown significant signal enhancement results by efficiently mitigating the interference from the noise generated by the UAVs propellers as well as from other external noise sources.

Real time SAR processing

NASA Technical Reports Server (NTRS)

Premkumar, A. B.; Purviance, J. E.

1990-01-01

A simplified model for the SAR imaging problem is presented. The model is based on the geometry of the SAR system. Using this model an expression for the entire phase history of the received SAR signal is formulated. From the phase history, it is shown that the range and the azimuth coordinates for a point target image can be obtained by processing the phase information during the intrapulse and interpulse periods respectively. An architecture for a VLSI implementation for the SAR signal processor is presented which generates images in real time. The architecture uses a small number of chips, a new correlation processor, and an efficient azimuth correlation process.

A computational approach to real-time image processing for serial time-encoded amplified microscopy

NASA Astrophysics Data System (ADS)

Oikawa, Minoru; Hiyama, Daisuke; Hirayama, Ryuji; Hasegawa, Satoki; Endo, Yutaka; Sugie, Takahisa; Tsumura, Norimichi; Kuroshima, Mai; Maki, Masanori; Okada, Genki; Lei, Cheng; Ozeki, Yasuyuki; Goda, Keisuke; Shimobaba, Tomoyoshi

2016-03-01

High-speed imaging is an indispensable technique, particularly for identifying or analyzing fast-moving objects. The serial time-encoded amplified microscopy (STEAM) technique was proposed to enable us to capture images with a frame rate 1,000 times faster than using conventional methods such as CCD (charge-coupled device) cameras. The application of this high-speed STEAM imaging technique to a real-time system, such as flow cytometry for a cell-sorting system, requires successively processing a large number of captured images with high throughput in real time. We are now developing a high-speed flow cytometer system including a STEAM camera. In this paper, we describe our approach to processing these large amounts of image data in real time. We use an analog-to-digital converter that has up to 7.0G samples/s and 8-bit resolution for capturing the output voltage signal that involves grayscale images from the STEAM camera. Therefore the direct data output from the STEAM camera generates 7.0G byte/s continuously. We provided a field-programmable gate array (FPGA) device as a digital signal pre-processor for image reconstruction and finding objects in a microfluidic channel with high data rates in real time. We also utilized graphics processing unit (GPU) devices for accelerating the calculation speed of identification of the reconstructed images. We built our prototype system, which including a STEAM camera, a FPGA device and a GPU device, and evaluated its performance in real-time identification of small particles (beads), as virtual biological cells, owing through a microfluidic channel.

A UWB Radar Signal Processing Platform for Real-Time Human Respiratory Feature Extraction Based on Four-Segment Linear Waveform Model.

PubMed

Hsieh, Chi-Hsuan; Chiu, Yu-Fang; Shen, Yi-Hsiang; Chu, Ta-Shun; Huang, Yuan-Hao

2016-02-01

This paper presents an ultra-wideband (UWB) impulse-radio radar signal processing platform used to analyze human respiratory features. Conventional radar systems used in human detection only analyze human respiration rates or the response of a target. However, additional respiratory signal information is available that has not been explored using radar detection. The authors previously proposed a modified raised cosine waveform (MRCW) respiration model and an iterative correlation search algorithm that could acquire additional respiratory features such as the inspiration and expiration speeds, respiration intensity, and respiration holding ratio. To realize real-time respiratory feature extraction by using the proposed UWB signal processing platform, this paper proposes a new four-segment linear waveform (FSLW) respiration model. This model offers a superior fit to the measured respiration signal compared with the MRCW model and decreases the computational complexity of feature extraction. In addition, an early-terminated iterative correlation search algorithm is presented, substantially decreasing the computational complexity and yielding negligible performance degradation. These extracted features can be considered the compressed signals used to decrease the amount of data storage required for use in long-term medical monitoring systems and can also be used in clinical diagnosis. The proposed respiratory feature extraction algorithm was designed and implemented using the proposed UWB radar signal processing platform including a radar front-end chip and an FPGA chip. The proposed radar system can detect human respiration rates at 0.1 to 1 Hz and facilitates the real-time analysis of the respiratory features of each respiration period.

Real Time Data Acquisition and Online Signal Processing for Magnetoencephalography

NASA Astrophysics Data System (ADS)

Rongen, H.; Hadamschek, V.; Schiek, M.

2006-06-01

To establish improved therapies for patients suffering from severe neurological and psychiatric diseases, a demand controlled and desynchronizing brain-pacemaker has been developed with techniques from statistical physics and nonlinear dynamics. To optimize the novel therapeutic approach, brain activity is investigated with a Magnetoencephalography (MEG) system prior to surgery. For this, a real time data acquisition system for a 148 channel MEG and online signal processing for artifact rejection, filtering, cross trial phase resetting analysis and three-dimensional (3-D) reconstruction of the cerebral current sources was developed. The developed PCI bus hardware is based on a FPGA and DSP design, using the benefits from both architectures. The reconstruction and visualization of the 3-D volume data is done by the PC which hosts the real time DAQ and pre-processing board. The framework of the MEG-online system is introduced and the architecture of the real time DAQ board and online reconstruction is described. In addition we show first results with the MEG-Online system for the investigation of dynamic brain activities in relation to external visual stimulation, based on test data sets.

Rapid update of discrete Fourier transform for real-time signal processing

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.; Kakad, Yogendra P.

2001-10-01

In many identification and target recognition applications, the incoming signal will have properties that render it amenable to analysis or processing in the Fourier domain. In such applications, however, it is usually essential that the identification or target recognition be performed in real time. An important constraint upon real-time processing in the Fourier domain is the time taken to perform the Discrete Fourier Transform (DFT). Ideally, a new Fourier transform should be obtained after the arrival of every new data point. However, the Fast Fourier Transform (FFT) algorithm requires on the order of N log2 N operations, where N is the length of the transform, and this usually makes calculation of the transform for every new data point computationally prohibitive. In this paper, we develop an algorithm to update the existing DFT to represent the new data series that results when a new signal point is received. Updating the DFT in this way uses less computational order by a factor of log2 N. The algorithm can be modified to work in the presence of data window functions. This is a considerable advantage, because windowing is often necessary to reduce edge effects that occur because the implicit periodicity of the Fourier transform is not exhibited by the real-world signal. Versions are developed in this paper for use with the boxcar window, the split triangular, Hanning, Hamming, and Blackman windows. Generalization of these results to 2D is also presented.

Real-time Fourier transformation of lightwave spectra and application in optical reflectometry.

PubMed

Malacarne, Antonio; Park, Yongwoo; Li, Ming; LaRochelle, Sophie; Azaña, José

2015-12-14

We propose and experimentally demonstrate a fiber-optics scheme for real-time analog Fourier transform (FT) of a lightwave energy spectrum, such that the output signal maps the FT of the spectrum of interest along the time axis. This scheme avoids the need for analog-to-digital conversion and subsequent digital signal post-processing of the photo-detected spectrum, thus being capable of providing the desired FT processing directly in the optical domain at megahertz update rates. The proposed concept is particularly attractive for applications requiring FT analysis of optical spectra, such as in many optical Fourier-domain reflectrometry (OFDR), interferometry, spectroscopy and sensing systems. Examples are reported to illustrate the use of the method for real-time OFDR, where the target axial-line profile is directly observed in a single-shot oscilloscope trace, similarly to a time-of-flight measurement, but with a resolution and depth of range dictated by the underlying interferometry scheme.

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

Lovell, Jack, E-mail: jack.lovell@durham.ac.uk; Culham Centre for Fusion Energy, Culham Science Centre, Abingdon, Oxon OX14 3DB; Naylor, Graham

A new resistive bolometer system has been developed for MAST-Upgrade. It will measure radiated power in the new Super-X divertor, with millisecond time resolution, along 16 vertical and 16 horizontal lines of sight. The system uses a Xilinx Zynq-7000 series Field-Programmable Gate Array (FPGA) in the D-TACQ ACQ2106 carrier to perform real time data acquisition and signal processing. The FPGA enables AC-synchronous detection using high performance digital filtering to achieve a high signal-to-noise ratio and will be able to output processed data in real time with millisecond latency. The system has been installed on 8 previously unused channels of themore » JET vertical bolometer system. Initial results suggest good agreement with data from existing vertical channels but with higher bandwidth and signal-to-noise ratio.« less

Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay

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

Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.

2008-11-06

This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use,more » a filtering algorithm based on linear approximations of the real observations is proposed.« less

Generation of optical OFDM signals using 21.4 GS/s real time digital signal processing.

PubMed

Benlachtar, Yannis; Watts, Philip M; Bouziane, Rachid; Milder, Peter; Rangaraj, Deepak; Cartolano, Anthony; Koutsoyannis, Robert; Hoe, James C; Püschel, Markus; Glick, Madeleine; Killey, Robert I

2009-09-28

We demonstrate a field programmable gate array (FPGA) based optical orthogonal frequency division multiplexing (OFDM) transmitter implementing real time digital signal processing at a sample rate of 21.4 GS/s. The QPSK-OFDM signal is generated using an 8 bit, 128 point inverse fast Fourier transform (IFFT) core, performing one transform per clock cycle at a clock speed of 167.2 MHz and can be deployed with either a direct-detection or a coherent receiver. The hardware design and the main digital signal processing functions are described, and we show that the main performance limitation is due to the low (4-bit) resolution of the digital-to-analog converter (DAC) and the 8-bit resolution of the IFFT core used. We analyze the back-to-back performance of the transmitter generating an 8.36 Gb/s optical single sideband (SSB) OFDM signal using digital up-conversion, suitable for direct-detection. Additionally, we use the device to transmit 8.36 Gb/s SSB OFDM signals over 200 km of uncompensated standard single mode fiber achieving an overall BER<10(-3).

A multi-band spectral subtraction-based algorithm for real-time noise cancellation applied to gunshot acoustics

NASA Astrophysics Data System (ADS)

Ramos, António L. L.; Holm, Sverre; Gudvangen, Sigmund; Otterlei, Ragnvald

2013-06-01

Acoustical sniper positioning is based on the detection and direction-of-arrival estimation of the shockwave and the muzzle blast acoustical signals. In real-life situations, the detection and direction-of-arrival estimation processes is usually performed under the influence of background noise sources, e.g., vehicles noise, and might result in non-negligible inaccuracies than can affect the system performance and reliability negatively, specially when detecting the muzzle sound under long range distance and absorbing terrains. This paper introduces a multi-band spectral subtraction based algorithm for real-time noise reduction, applied to gunshot acoustical signals. The ballistic shockwave and the muzzle blast signals exhibit distinct frequency contents that are affected differently by additive noise. In most real situations, the noise component is colored and a multi-band spectral subtraction approach for noise reduction contributes to reducing the presence of artifacts in denoised signals. The proposed algorithm is tested using a dataset generated by combining signals from real gunshots and real vehicle noise. The noise component was generated using a steel tracked military tank running on asphalt and includes, therefore, the sound from the vehicle engine, which varies slightly in frequency over time according to the engine's rpm, and the sound from the steel tracks as the vehicle moves.

Real-time optical signal processors employing optical feedback: amplitude and phase control.

PubMed

Gallagher, N C

1976-04-01

The development of real-time coherent optical signal processors has increased the appeal of optical computing techniques in signal processing applications. A major limitation of these real-time systems is the. fact that the optical processing material is generally of a phase-only type. The result is that the spatial filters synthesized with these systems must be either phase-only filters or amplitude-only filters. The main concern of this paper is the application of optical feedback techniques to obtain simultaneous and independent amplitude and phase control of the light passing through the system. It is shown that optical feedback techniques may be employed with phase-only spatial filters to obtain this amplitude and phase control. The feedback system with phase-only filters is compared with other feedback systems that employ combinations of phase-only and amplitude-only filters; it is found that the phase-only system is substantially more flexible than the other two systems investigated.

Fast contactless vibrating structure characterization using real time field programmable gate array-based digital signal processing: demonstrations with a passive wireless acoustic delay line probe and vision.

PubMed

Goavec-Mérou, G; Chrétien, N; Friedt, J-M; Sandoz, P; Martin, G; Lenczner, M; Ballandras, S

2014-01-01

Vibrating mechanical structure characterization is demonstrated using contactless techniques best suited for mobile and rotating equipments. Fast measurement rates are achieved using Field Programmable Gate Array (FPGA) devices as real-time digital signal processors. Two kinds of algorithms are implemented on FPGA and experimentally validated in the case of the vibrating tuning fork. A first application concerns in-plane displacement detection by vision with sampling rates above 10 kHz, thus reaching frequency ranges above the audio range. A second demonstration concerns pulsed-RADAR cooperative target phase detection and is applied to radiofrequency acoustic transducers used as passive wireless strain gauges. In this case, the 250 ksamples/s refresh rate achieved is only limited by the acoustic sensor design but not by the detection bandwidth. These realizations illustrate the efficiency, interest, and potentialities of FPGA-based real-time digital signal processing for the contactless interrogation of passive embedded probes with high refresh rates.

Real-time monitoring and massive inversion of source parameters of very long period seismic signals: An application to Stromboli Volcano, Italy

USGS Publications Warehouse

Auger, E.; D'Auria, L.; Martini, M.; Chouet, B.; Dawson, P.

2006-01-01

We present a comprehensive processing tool for the real-time analysis of the source mechanism of very long period (VLP) seismic data based on waveform inversions performed in the frequency domain for a point source. A search for the source providing the best-fitting solution is conducted over a three-dimensional grid of assumed source locations, in which the Green's functions associated with each point source are calculated by finite differences using the reciprocal relation between source and receiver. Tests performed on 62 nodes of a Linux cluster indicate that the waveform inversion and search for the best-fitting signal over 100,000 point sources require roughly 30 s of processing time for a 2-min-long record. The procedure is applied to post-processing of a data archive and to continuous automatic inversion of real-time data at Stromboli, providing insights into different modes of degassing at this volcano. Copyright 2006 by the American Geophysical Union.

An accuracy aware low power wireless EEG unit with information content based adaptive data compression.

PubMed

Tolbert, Jeremy R; Kabali, Pratik; Brar, Simeranjit; Mukhopadhyay, Saibal

2009-01-01

We present a digital system for adaptive data compression for low power wireless transmission of Electroencephalography (EEG) data. The proposed system acts as a base-band processor between the EEG analog-to-digital front-end and RF transceiver. It performs a real-time accuracy energy trade-off for multi-channel EEG signal transmission by controlling the volume of transmitted data. We propose a multi-core digital signal processor for on-chip processing of EEG signals, to detect signal information of each channel and perform real-time adaptive compression. Our analysis shows that the proposed approach can provide significant savings in transmitter power with minimal impact on the overall signal accuracy.

The VLBA correlator: Real-time in the distributed era

NASA Technical Reports Server (NTRS)

Wells, D. C.

1992-01-01

The correlator is the signal processing engine of the Very Long Baseline Array (VLBA). Radio signals are recorded on special wideband (128 Mb/s) digital recorders at the 10 telescopes, with sampling times controlled by hydrogen maser clocks. The magnetic tapes are shipped to the Array Operations Center in Socorro, New Mexico, where they are played back simultaneously into the correlator. Real-time software and firmware controls the playback drives to achieve synchronization, compute models of the wavefront delay, control the numerous modules of the correlator, and record FITS files of the fringe visibilities at the back-end of the correlator. In addition to the more than 3000 custom VLSI chips which handle the massive data flow of the signal processing, the correlator contains a total of more than 100 programmable computers, 8-, 16- and 32-bit CPUs. Code is downloaded into front-end CPU's dependent on operating mode. Low-level code is assembly language, high-level code is C running under a RT OS. We use VxWorks on Motorola MVME147 CPU's. Code development is on a complex of SPARC workstations connected to the RT CPU's by Ethernet. The overall management of the correlation process is dependent on a database management system. We use Ingres running on a Sparcstation-2. We transfer logging information from the database of the VLBA Monitor and Control System to our database using Ingres/NET. Job scripts are computed and are transferred to the real-time computers using NFS, and correlation job execution logs and status flow back by the route. Operator status and control displays use windows on workstations, interfaced to the real-time processes by network protocols. The extensive network protocol support provided by VxWorks is invaluable. The VLBA Correlator's dependence on network protocols is an example of the radical transformation of the real-time world over the past five years. Real-time is becoming more like conventional computing. Paradoxically, 'conventional' computing is also adopting practices from the real-time world: semaphores, shared memory, light-weight threads, and concurrency. This appears to be a convergence of thinking.

A digital signal processing system for coherent laser radar

NASA Technical Reports Server (NTRS)

Hampton, Diana M.; Jones, William D.; Rothermel, Jeffry

1991-01-01

A data processing system for use with continuous-wave lidar is described in terms of its configuration and performance during the second survey mission of NASA'a Global Backscatter Experiment. The system is designed to estimate a complete lidar spectrum in real time, record the data from two lidars, and monitor variables related to the lidar operating environment. The PC-based system includes a transient capture board, a digital-signal processing (DSP) board, and a low-speed data-acquisition board. Both unprocessed and processed lidar spectrum data are monitored in real time, and the results are compared to those of a previous non-DSP-based system. Because the DSP-based system is digital it is slower than the surface-acoustic-wave signal processor and collects 2500 spectra/s. However, the DSP-based system provides complete data sets at two wavelengths from the continuous-wave lidars.

Low cost MATLAB-based pulse oximeter for deployment in research and development applications.

PubMed

Shokouhian, M; Morling, R C S; Kale, I

2013-01-01

Problems such as motion artifact and effects of ambient lights have forced developers to design different signal processing techniques and algorithms to increase the reliability and accuracy of the conventional pulse oximeter device. To evaluate the robustness of these techniques, they are applied either to recorded data or are implemented on chip to be applied to real-time data. Recorded data is the most common method of evaluating however it is not as reliable as real-time measurements. On the other hand, hardware implementation can be both expensive and time consuming. This paper presents a low cost MATLAB-based pulse oximeter that can be used for rapid evaluation of newly developed signal processing techniques and algorithms. Flexibility to apply different signal processing techniques, providing both processed and unprocessed data along with low implementation cost are the important features of this design which makes it ideal for research and development purposes, as well as commercial, hospital and healthcare application.

Microcomputer-Based Digital Signal Processing Laboratory Experiments.

ERIC Educational Resources Information Center

Tinari, Jr., Rocco; Rao, S. Sathyanarayan

1985-01-01

Describes a system (Apple II microcomputer interfaced to flexible, custom-designed digital hardware) which can provide: (1) Fast Fourier Transform (FFT) computation on real-time data with a video display of spectrum; (2) frequency synthesis experiments using the inverse FFT; and (3) real-time digital filtering experiments. (JN)

Study on a Real-Time BEAM System for Diagnosis Assistance Based on a System on Chips Design

PubMed Central

Sung, Wen-Tsai; Chen, Jui-Ho; Chang, Kung-Wei

2013-01-01

As an innovative as well as an interdisciplinary research project, this study performed an analysis of brain signals so as to establish BrainIC as an auxiliary tool for physician diagnosis. Cognition behavior sciences, embedded technology, system on chips (SOC) design and physiological signal processing are integrated in this work. Moreover, a chip is built for real-time electroencephalography (EEG) processing purposes and a Brain Electrical Activity Mapping (BEAM) system, and a knowledge database is constructed to diagnose psychosis and body challenges in learning various behaviors and signals antithesis by a fuzzy inference engine. This work is completed with a medical support system developed for the mentally disabled or the elderly abled. PMID:23681095

Real-time biscuit tile image segmentation method based on edge detection.

PubMed

Matić, Tomislav; Aleksi, Ivan; Hocenski, Željko; Kraus, Dieter

2018-05-01

In this paper we propose a novel real-time Biscuit Tile Segmentation (BTS) method for images from ceramic tile production line. BTS method is based on signal change detection and contour tracing with a main goal of separating tile pixels from background in images captured on the production line. Usually, human operators are visually inspecting and classifying produced ceramic tiles. Computer vision and image processing techniques can automate visual inspection process if they fulfill real-time requirements. Important step in this process is a real-time tile pixels segmentation. BTS method is implemented for parallel execution on a GPU device to satisfy the real-time constraints of tile production line. BTS method outperforms 2D threshold-based methods, 1D edge detection methods and contour-based methods. Proposed BTS method is in use in the biscuit tile production line. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Real-time Enhancement, Registration, and Fusion for a Multi-Sensor Enhanced Vision System

NASA Technical Reports Server (NTRS)

Hines, Glenn D.; Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2006-01-01

Over the last few years NASA Langley Research Center (LaRC) has been developing an Enhanced Vision System (EVS) to aid pilots while flying in poor visibility conditions. The EVS captures imagery using two infrared video cameras. The cameras are placed in an enclosure that is mounted and flown forward-looking underneath the NASA LaRC ARIES 757 aircraft. The data streams from the cameras are processed in real-time and displayed on monitors on-board the aircraft. With proper processing the camera system can provide better-than- human-observed imagery particularly during poor visibility conditions. However, to obtain this goal requires several different stages of processing including enhancement, registration, and fusion, and specialized processing hardware for real-time performance. We are using a real-time implementation of the Retinex algorithm for image enhancement, affine transformations for registration, and weighted sums to perform fusion. All of the algorithms are executed on a single TI DM642 digital signal processor (DSP) clocked at 720 MHz. The image processing components were added to the EVS system, tested, and demonstrated during flight tests in August and September of 2005. In this paper we briefly discuss the EVS image processing hardware and algorithms. We then discuss implementation issues and show examples of the results obtained during flight tests. Keywords: enhanced vision system, image enhancement, retinex, digital signal processing, sensor fusion

SSME propellant path leak detection real-time

NASA Technical Reports Server (NTRS)

Crawford, R. A.; Smith, L. M.

1994-01-01

Included are four documents that outline the technical aspects of the research performed on NASA Grant NAG8-140: 'A System for Sequential Step Detection with Application to Video Image Processing'; 'Leak Detection from the SSME Using Sequential Image Processing'; 'Digital Image Processor Specifications for Real-Time SSME Leak Detection'; and 'A Color Change Detection System for Video Signals with Applications to Spectral Analysis of Rocket Engine Plumes'.

Developing infrared array controller with software real time operating system

NASA Astrophysics Data System (ADS)

Sako, Shigeyuki; Miyata, Takashi; Nakamura, Tomohiko; Motohara, Kentaro; Uchimoto, Yuka Katsuno; Onaka, Takashi; Kataza, Hirokazu

2008-07-01

Real-time capabilities are required for a controller of a large format array to reduce a dead-time attributed by readout and data transfer. The real-time processing has been achieved by dedicated processors including DSP, CPLD, and FPGA devices. However, the dedicated processors have problems with memory resources, inflexibility, and high cost. Meanwhile, a recent PC has sufficient resources of CPUs and memories to control the infrared array and to process a large amount of frame data in real-time. In this study, we have developed an infrared array controller with a software real-time operating system (RTOS) instead of the dedicated processors. A Linux PC equipped with a RTAI extension and a dual-core CPU is used as a main computer, and one of the CPU cores is allocated to the real-time processing. A digital I/O board with DMA functions is used for an I/O interface. The signal-processing cores are integrated in the OS kernel as a real-time driver module, which is composed of two virtual devices of the clock processor and the frame processor tasks. The array controller with the RTOS realizes complicated operations easily, flexibly, and at a low cost.

FPGA-based real-time swept-source OCT systems for B-scan live-streaming or volumetric imaging

NASA Astrophysics Data System (ADS)

Bandi, Vinzenz; Goette, Josef; Jacomet, Marcel; von Niederhäusern, Tim; Bachmann, Adrian H.; Duelk, Marcus

2013-03-01

We have developed a Swept-Source Optical Coherence Tomography (Ss-OCT) system with high-speed, real-time signal processing on a commercially available Data-Acquisition (DAQ) board with a Field-Programmable Gate Array (FPGA). The Ss-OCT system simultaneously acquires OCT and k-clock reference signals at 500MS/s. From the k-clock signal of each A-scan we extract a remap vector for the k-space linearization of the OCT signal. The linear but oversampled interpolation is followed by a 2048-point FFT, additional auxiliary computations, and a data transfer to a host computer for real-time, live-streaming of B-scan or volumetric C-scan OCT visualization. We achieve a 100 kHz A-scan rate by parallelization of our hardware algorithms, which run on standard and affordable, commercially available DAQ boards. Our main development tool for signal analysis as well as for hardware synthesis is MATLAB® with add-on toolboxes and 3rd-party tools.

Real-time nondestructive monitoring of the gas tungsten arc welding (GTAW) process by combined airborne acoustic emission and non-contact ultrasonics

NASA Astrophysics Data System (ADS)

Zhang, Lu; Basantes-Defaz, Alexandra-Del-Carmen; Abbasi, Zeynab; Yuhas, Donald; Ozevin, Didem; Indacochea, Ernesto

2018-03-01

Welding is a key manufacturing process for many industries and may introduce defects into the welded parts causing significant negative impacts, potentially ruining high-cost pieces. Therefore, a real-time process monitoring method is important to implement for avoiding producing a low-quality weld. Due to high surface temperature and possible contamination of surface by contact transducers, the welding process should be monitored via non-contact transducers. In this paper, airborne acoustic emission (AE) transducers tuned at 60 kHz and non-contact ultrasonic testing (UT) transducers tuned at 500 kHz are implemented for real time weld monitoring. AE is a passive nondestructive evaluation method that listens for the process noise, and provides information about the uniformity of manufacturing process. UT provides more quantitative information about weld defects. One of the most common weld defects as burn-through is investigated. The influences of weld defects on AE signatures (time-driven data) and UT signals (received signal energy, change in peak frequency) are presented. The level of burn-through damage is defined by using single method or combine AE/UT methods.

Parallel optimization of signal detection in active magnetospheric signal injection experiments

NASA Astrophysics Data System (ADS)

Gowanlock, Michael; Li, Justin D.; Rude, Cody M.; Pankratius, Victor

2018-05-01

Signal detection and extraction requires substantial manual parameter tuning at different stages in the processing pipeline. Time-series data depends on domain-specific signal properties, necessitating unique parameter selection for a given problem. The large potential search space makes this parameter selection process time-consuming and subject to variability. We introduce a technique to search and prune such parameter search spaces in parallel and select parameters for time series filters using breadth- and depth-first search strategies to increase the likelihood of detecting signals of interest in the field of magnetospheric physics. We focus on studying geomagnetic activity in the extremely and very low frequency ranges (ELF/VLF) using ELF/VLF transmissions from Siple Station, Antarctica, received at Québec, Canada. Our technique successfully detects amplified transmissions and achieves substantial speedup performance gains as compared to an exhaustive parameter search. We present examples where our algorithmic approach reduces the search from hundreds of seconds down to less than 1 s, with a ranked signal detection in the top 99th percentile, thus making it valuable for real-time monitoring. We also present empirical performance models quantifying the trade-off between the quality of signal recovered and the algorithm response time required for signal extraction. In the future, improved signal extraction in scenarios like the Siple experiment will enable better real-time diagnostics of conditions of the Earth's magnetosphere for monitoring space weather activity.

Parallel implementation of all-digital timing recovery for high-speed and real-time optical coherent receivers.

PubMed

Zhou, Xian; Chen, Xue

2011-05-09

The digital coherent receivers combine coherent detection with digital signal processing (DSP) to compensate for transmission impairments, and therefore are a promising candidate for future high-speed optical transmission system. However, the maximum symbol rate supported by such real-time receivers is limited by the processing rate of hardware. In order to cope with this difficulty, the parallel processing algorithms is imperative. In this paper, we propose a novel parallel digital timing recovery loop (PDTRL) based on our previous work. Furthermore, for increasing the dynamic dispersion tolerance range of receivers, we embed a parallel adaptive equalizer in the PDTRL. This parallel joint scheme (PJS) can be used to complete synchronization, equalization and polarization de-multiplexing simultaneously. Finally, we demonstrate that PDTRL and PJS allow the hardware to process 112 Gbit/s POLMUX-DQPSK signal at the hundreds MHz range. © 2011 Optical Society of America

Smartphone Cortex Controlled Real-Time Image Processing and Reprocessing for Concentration Independent LED Induced Fluorescence Detection in Capillary Electrophoresis.

PubMed

Szarka, Mate; Guttman, Andras

2017-10-17

We present the application of a smartphone anatomy based technology in the field of liquid phase bioseparations, particularly in capillary electrophoresis. A simple capillary electrophoresis system was built with LED induced fluorescence detection and a credit card sized minicomputer to prove the concept of real time fluorescent imaging (zone adjustable time-lapse fluorescence image processor) and separation controller. The system was evaluated by analyzing under- and overloaded aminopyrenetrisulfonate (APTS)-labeled oligosaccharide samples. The open source software based image processing tool allowed undistorted signal modulation (reprocessing) if the signal was inappropriate for the actual detection system settings (too low or too high). The novel smart detection tool for fluorescently labeled biomolecules greatly expands dynamic range and enables retrospective correction for injections with unsuitable signal levels without the necessity to repeat the analysis.

An FPGA-based bolometer for the MAST-U Super-X divertor.

PubMed

Lovell, Jack; Naylor, Graham; Field, Anthony; Drewelow, Peter; Sharples, Ray

2016-11-01

A new resistive bolometer system has been developed for MAST-Upgrade. It will measure radiated power in the new Super-X divertor, with millisecond time resolution, along 16 vertical and 16 horizontal lines of sight. The system uses a Xilinx Zynq-7000 series Field-Programmable Gate Array (FPGA) in the D-TACQ ACQ2106 carrier to perform real time data acquisition and signal processing. The FPGA enables AC-synchronous detection using high performance digital filtering to achieve a high signal-to-noise ratio and will be able to output processed data in real time with millisecond latency. The system has been installed on 8 previously unused channels of the JET vertical bolometer system. Initial results suggest good agreement with data from existing vertical channels but with higher bandwidth and signal-to-noise ratio.

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.

Air-Flow-Driven Triboelectric Nanogenerators for Self-Powered Real-Time Respiratory Monitoring.

PubMed

Wang, Meng; Zhang, Jiahao; Tang, Yingjie; Li, Jun; Zhang, Baosen; Liang, Erjun; Mao, Yanchao; Wang, Xudong

2018-06-04

Respiration is one of the most important vital signs of humans, and respiratory monitoring plays an important role in physical health management. A low-cost and convenient real-time respiratory monitoring system is extremely desirable. In this work, we demonstrated an air-flow-driven triboelectric nanogenerator (TENG) for self-powered real-time respiratory monitoring by converting mechanical energy of human respiration into electric output signals. The operation of the TENG was based on the air-flow-driven vibration of a flexible nanostructured polytetrafluoroethylene (n-PTFE) thin film in an acrylic tube. This TENG can generate distinct real-time electric signals when exposed to the air flow from different breath behaviors. It was also found that the accumulative charge transferred in breath sensing corresponds well to the total volume of air exchanged during the respiration process. Based on this TENG device, an intelligent wireless respiratory monitoring and alert system was further developed, which used the TENG signal to directly trigger a wireless alarm or dial a cell phone to provide timely alerts in response to breath behavior changes. This research offers a promising solution for developing self-powered real-time respiratory monitoring devices.

The mathematical theory of signal processing and compression-designs

NASA Astrophysics Data System (ADS)

Feria, Erlan H.

2006-05-01

The mathematical theory of signal processing, named processor coding, will be shown to inherently arise as the computational time dual of Shannon's mathematical theory of communication which is also known as source coding. Source coding is concerned with signal source memory space compression while processor coding deals with signal processor computational time compression. Their combination is named compression-designs and referred as Conde in short. A compelling and pedagogically appealing diagram will be discussed highlighting Conde's remarkable successful application to real-world knowledge-aided (KA) airborne moving target indicator (AMTI) radar.

Data Telemetry and Acquisition System for Acoustic Signal Processing Investigations.

DTIC Science & Technology

1996-02-20

were VME- based computer systems operating under the VxWorks real - time operating system . Each system shared a common hardware and software... real - time operating system . It interfaces to the Berg PCM Decommutator board, which searches for the embedded synchronization word in the data and re...software were built on top of this architecture. The multi-tasking, message queue and memory management facilities of the VxWorks real - time operating system are

Smart surgical tool

NASA Astrophysics Data System (ADS)

Huang, Huan; Yang, Lih-Mei; Bai, Shuang; Liu, Jian

2015-02-01

A laser-induced breakdown spectroscopy (LIBS) guided smart surgical tool using a femtosecond fiber laser is developed. This system provides real-time material identification by processing and analyzing the peak intensity and ratio of atomic emissions of LIBS signals. Algorithms to identify emissions of different tissues and metals are developed and implemented into the real-time control system. This system provides a powerful smart surgical tool for precise robotic microsurgery applications with real-time feedback and control.

Real-time processing of ASL signs: Delayed first language acquisition affects organization of the mental lexicon

PubMed Central

Lieberman, Amy M.; Borovsky, Arielle; Hatrak, Marla; Mayberry, Rachel I.

2014-01-01

Sign language comprehension requires visual attention to the linguistic signal and visual attention to referents in the surrounding world, whereas these processes are divided between the auditory and visual modalities for spoken language comprehension. Additionally, the age-onset of first language acquisition and the quality and quantity of linguistic input and for deaf individuals is highly heterogeneous, which is rarely the case for hearing learners of spoken languages. Little is known about how these modality and developmental factors affect real-time lexical processing. In this study, we ask how these factors impact real-time recognition of American Sign Language (ASL) signs using a novel adaptation of the visual world paradigm in deaf adults who learned sign from birth (Experiment 1), and in deaf individuals who were late-learners of ASL (Experiment 2). Results revealed that although both groups of signers demonstrated rapid, incremental processing of ASL signs, only native-signers demonstrated early and robust activation of sub-lexical features of signs during real-time recognition. Our findings suggest that the organization of the mental lexicon into units of both form and meaning is a product of infant language learning and not the sensory and motor modality through which the linguistic signal is sent and received. PMID:25528091

SPROC: A multiple-processor DSP IC

NASA Technical Reports Server (NTRS)

Davis, R.

1991-01-01

A large, single-chip, multiple-processor, digital signal processing (DSP) integrated circuit (IC) fabricated in HP-Cmos34 is presented. The innovative architecture is best suited for analog and real-time systems characterized by both parallel signal data flows and concurrent logic processing. The IC is supported by a powerful development system that transforms graphical signal flow graphs into production-ready systems in minutes. Automatic compiler partitioning of tasks among four on-chip processors gives the IC the signal processing power of several conventional DSP chips.

Evaluating Acoustic Emission Signals as an in situ process monitoring technique for Selective Laser Melting (SLM)

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

Fisher, Karl A.; Candy, Jim V.; Guss, Gabe

2016-10-14

In situ real-time monitoring of the Selective Laser Melting (SLM) process has significant implications for the AM community. The ability to adjust the SLM process parameters during a build (in real-time) can save time, money and eliminate expensive material waste. Having a feedback loop in the process would allow the system to potentially ‘fix’ problem regions before a next powder layer is added. In this study we have investigated acoustic emission (AE) phenomena generated during the SLM process, and evaluated the results in terms of a single process parameter, of an in situ process monitoring technique.

A Real-Time Data Acquisition and Processing Framework Based on FlexRIO FPGA and ITER Fast Plant System Controller

NASA Astrophysics Data System (ADS)

Yang, C.; Zheng, W.; Zhang, M.; Yuan, T.; Zhuang, G.; Pan, Y.

2016-06-01

Measurement and control of the plasma in real-time are critical for advanced Tokamak operation. It requires high speed real-time data acquisition and processing. ITER has designed the Fast Plant System Controllers (FPSC) for these purposes. At J-TEXT Tokamak, a real-time data acquisition and processing framework has been designed and implemented using standard ITER FPSC technologies. The main hardware components of this framework are an Industrial Personal Computer (IPC) with a real-time system and FlexRIO devices based on FPGA. With FlexRIO devices, data can be processed by FPGA in real-time before they are passed to the CPU. The software elements are based on a real-time framework which runs under Red Hat Enterprise Linux MRG-R and uses Experimental Physics and Industrial Control System (EPICS) for monitoring and configuring. That makes the framework accord with ITER FPSC standard technology. With this framework, any kind of data acquisition and processing FlexRIO FPGA program can be configured with a FPSC. An application using the framework has been implemented for the polarimeter-interferometer diagnostic system on J-TEXT. The application is able to extract phase-shift information from the intermediate frequency signal produced by the polarimeter-interferometer diagnostic system and calculate plasma density profile in real-time. Different algorithms implementations on the FlexRIO FPGA are compared in the paper.

Track Detection in Railway Sidings Based on MEMS Gyroscope Sensors

PubMed Central

Broquetas, Antoni; Comerón, Adolf; Gelonch, Antoni; Fuertes, Josep M.; Castro, J. Antonio; Felip, Damià; López, Miguel A.; Pulido, José A.

2012-01-01

The paper presents a two-step technique for real-time track detection in single-track railway sidings using low-cost MEMS gyroscopes. The objective is to reliably know the path the train has taken in a switch, diverted or main road, immediately after the train head leaves the switch. The signal delivered by the gyroscope is first processed by an adaptive low-pass filter that rejects noise and converts the temporal turn rate data in degree/second units into spatial turn rate data in degree/meter. The conversion is based on the travelled distance taken from odometer data. The filter is implemented to achieve a speed-dependent cut-off frequency to maximize the signal-to-noise ratio. Although direct comparison of the filtered turn rate signal with a predetermined threshold is possible, the paper shows that better detection performance can be achieved by processing the turn rate signal with a filter matched to the rail switch curvature parameters. Implementation aspects of the track detector have been optimized for real-time operation. The detector has been tested with both simulated data and real data acquired in railway campaigns. PMID:23443376

[3D-TV health assessment system by the multi-modal physiological signals].

PubMed

Li, Zhongqiang; Xing, Lidong; Qian, Zhiyu; Wang, Xiao; Yu, Defei; Liu, Baoyu; Jin, Shuai

2014-03-01

In order to meet the requirements of the multi-physiological signal measurement of the 3D-TV health assessment, try to find the suitable biological acquisition chips and design the hardware system which can detect different physiological signals in real time. The systems mainly uses ARM11/S3C6410 microcontroller to control the EEG/EOG acquisition chip RHA2116 and the ECG acquisition chip ADS1298, and then the microcontroller transfer the data collected by the chips to the PC software by the USB port which can display and save the experimental data in real time, then use the Matlab software for further processing of the data, finally make a final health assessment. In the meantime, for the different varieties in the different brain regions of watching 3D-TV, developed the special brain electrode placement and the experimental data processing methods, then effectively disposed the multi-signal data in the multilevel.

Satellite on-board real-time SAR processor prototype

NASA Astrophysics Data System (ADS)

Bergeron, Alain; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Marchese, Linda; Bourqui, Pascal; Desnoyers, Nicholas; Legros, Mathieu; Guillot, Ludovic; Mercier, Luc; Châteauneuf, François

2017-11-01

A Compact Real-Time Optronic SAR Processor has been successfully developed and tested up to a Technology Readiness Level of 4 (TRL4), the breadboard validation in a laboratory environment. SAR, or Synthetic Aperture Radar, is an active system allowing day and night imaging independent of the cloud coverage of the planet. The SAR raw data is a set of complex data for range and azimuth, which cannot be compressed. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Originally the first SAR images were optically processed. The optical Fourier processor architecture provides inherent parallel computing capabilities allowing real-time SAR data processing and thus the ability for compression and strongly reduced communication bandwidth requirements for the satellite. SAR signal return data are in general complex data. Both amplitude and phase must be combined optically in the SAR processor for each range and azimuth pixel. Amplitude and phase are generated by dedicated spatial light modulators and superimposed by an optical relay set-up. The spatial light modulators display the full complex raw data information over a two-dimensional format, one for the azimuth and one for the range. Since the entire signal history is displayed at once, the processor operates in parallel yielding real-time performances, i.e. without resulting bottleneck. Processing of both azimuth and range information is performed in a single pass. This paper focuses on the onboard capabilities of the compact optical SAR processor prototype that allows in-orbit processing of SAR images. Examples of processed ENVISAT ASAR images are presented. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and size are reviewed.

Computational problems and signal processing in SETI

NASA Technical Reports Server (NTRS)

Deans, Stanley R.; Cullers, D. K.; Stauduhar, Richard

1991-01-01

The Search for Extraterrestrial Intelligence (SETI), currently being planned at NASA, will require that an enormous amount of data (on the order of 10 exp 11 distinct signal paths for a typical observation) be analyzed in real time by special-purpose hardware. Even though the SETI system design is not based on maximum entropy and Bayesian methods (partly due to the real-time processing constraint), it is expected that enough data will be saved to be able to apply these and other methods off line where computational complexity is not an overriding issue. Interesting computational problems that relate directly to the system design for processing such an enormous amount of data have emerged. Some of these problems are discussed, along with the current status on their solution.

Development of inferential sensors for real-time quality control of water-level data for the Everglades Depth Estimation Network

USGS Publications Warehouse

Daamen, Ruby C.; Edwin A. Roehl, Jr.; Conrads, Paul

2010-01-01

A technology often used for industrial applications is “inferential sensor.” Rather than installing a redundant sensor to measure a process, such as an additional waterlevel gage, an inferential sensor, or virtual sensor, is developed that estimates the processes measured by the physical sensor. The advantage of an inferential sensor is that it provides a redundant signal to the sensor in the field but without exposure to environmental threats. In the event that a gage does malfunction, the inferential sensor provides an estimate for the period of missing data. The inferential sensor also can be used in the quality assurance and quality control of the data. Inferential sensors for gages in the EDEN network are currently (2010) under development. The inferential sensors will be automated so that the real-time EDEN data will continuously be compared to the inferential sensor signal and digital reports of the status of the real-time data will be sent periodically to the appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.

A low-cost biomedical signal transceiver based on a Bluetooth wireless system.

PubMed

Fazel-Rezai, Reza; Pauls, Mark; Slawinski, David

2007-01-01

Most current wireless biomedical signal transceivers use range-limiting communication. This work presents a low-cost biomedical signal transceiver that uses Bluetooth wireless technology. The design is implemented in a modular form to be adaptable to different types of biomedical signals. The signal front end obtains and processes incoming signals, which are then transmitted via a microcontroller and wireless module. Near real-time receive software in LabVIEW was developed to demonstrate the system capability. The completed transmitter prototype successfully transmits ECG signals, and is able to simultaneously send multiple signals. The sampling rate of the transmitter is fast enough to send up to thirteen ECG signals simultaneously, with an error rate below 0.1% for transmission exceeding 65 meters. A low-cost wireless biomedical transceiver has many applications, such as real-time monitoring of patients with a known condition in non-clinical settings.

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

PubMed Central

Huang, Chih-Sheng; Yang, Wen-Yu; Chuang, Chun-Hsiang; Wang, Yu-Kai

2018-01-01

Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research. PMID:29599950

Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data

USGS Publications Warehouse

Petkewich, Matthew D.; Daamen, Ruby C.; Roehl, Edwin A.; Conrads, Paul

2016-09-29

The Everglades Depth Estimation Network (EDEN), with over 240 real-time gaging stations, provides hydrologic data for freshwater and tidal areas of the Everglades. These data are used to generate daily water-level and water-depth maps of the Everglades that are used to assess biotic responses to hydrologic change resulting from the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The generation of EDEN daily water-level and water-depth maps is dependent on high quality real-time data from water-level stations. Real-time data are automatically checked for outliers by assigning minimum and maximum thresholds for each station. Small errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the stations. Correcting these small errors in the data often is time consuming and water-level data may not be finalized for several months. To provide daily water-level and water-depth maps on a near real-time basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous water-level data.The Automated Data Assurance and Management (ADAM) software uses inferential sensor technology often used in industrial applications. Rather than installing a redundant sensor to measure a process, such as an additional water-level station, inferential sensors, or virtual sensors, were developed for each station that make accurate estimates of the process measured by the hard sensor (water-level gaging station). The inferential sensors in the ADAM software are empirical models that use inputs from one or more proximal stations. The advantage of ADAM is that it provides a redundant signal to the sensor in the field without the environmental threats associated with field conditions at stations (flood or hurricane, for example). In the event that a station does malfunction, ADAM provides an accurate estimate for the period of missing data. The ADAM software also is used in the quality assurance and quality control of the data. The virtual signals are compared to the real-time data, and if the difference between the two signals exceeds a certain tolerance, corrective action to the data and (or) the gaging station can be taken. The ADAM software is automated so that, each morning, the real-time EDEN data are compared to the inferential sensor signals and digital reports highlighting potential erroneous real-time data are generated for appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.

Real-time detection of laser-GaAs interaction process

NASA Astrophysics Data System (ADS)

Jia, Zhichao; Li, Zewen; Lv, Xueming; Ni, Xiaowu

2017-05-01

A real-time method based on laser scattering technology was used to detect the interaction process of GaAs with a 1080 nm laser. The detector collected the scattered laser beam from the GaAs wafer. The main scattering sources were back surface at first, later turn into front surface and vapor, so scattering signal contained much information of the interaction process. The surface morphologies of GaAs with different irradiation times were observed using an optical microscope to confirm occurrence of various phenomena. The proposed method is shown to be effective for the real-time detection of GaAs. By choosing a proper wavelength, the scattering technology can be promoted in detection of thicker GaAs wafer or other materials.

Real-Time On-Board Processing Validation of MSPI Ground Camera Images

NASA Technical Reports Server (NTRS)

Pingree, Paula J.; Werne, Thomas A.; Bekker, Dmitriy L.

2010-01-01

The Earth Sciences Decadal Survey identifies a multiangle, multispectral, high-accuracy polarization imager as one requirement for the Aerosol-Cloud-Ecosystem (ACE) mission. JPL has been developing a Multiangle SpectroPolarimetric Imager (MSPI) as a candidate to fill this need. A key technology development needed for MSPI is on-board signal processing to calculate polarimetry data as imaged by each of the 9 cameras forming the instrument. With funding from NASA's Advanced Information Systems Technology (AIST) Program, JPL is solving the real-time data processing requirements to demonstrate, for the first time, how signal data at 95 Mbytes/sec over 16-channels for each of the 9 multiangle cameras in the spaceborne instrument can be reduced on-board to 0.45 Mbytes/sec. This will produce the intensity and polarization data needed to characterize aerosol and cloud microphysical properties. Using the Xilinx Virtex-5 FPGA including PowerPC440 processors we have implemented a least squares fitting algorithm that extracts intensity and polarimetric parameters in real-time, thereby substantially reducing the image data volume for spacecraft downlink without loss of science information.

A real-time GNSS-R system based on software-defined radio and graphics processing units

NASA Astrophysics Data System (ADS)

Hobiger, Thomas; Amagai, Jun; Aida, Masanori; Narita, Hideki

2012-04-01

Reflected signals of the Global Navigation Satellite System (GNSS) from the sea or land surface can be utilized to deduce and monitor physical and geophysical parameters of the reflecting area. Unlike most other remote sensing techniques, GNSS-Reflectometry (GNSS-R) operates as a passive radar that takes advantage from the increasing number of navigation satellites that broadcast their L-band signals. Thereby, most of the GNSS-R receiver architectures are based on dedicated hardware solutions. Software-defined radio (SDR) technology has advanced in the recent years and enabled signal processing in real-time, which makes it an ideal candidate for the realization of a flexible GNSS-R system. Additionally, modern commodity graphic cards, which offer massive parallel computing performances, allow to handle the whole signal processing chain without interfering with the PC's CPU. Thus, this paper describes a GNSS-R system which has been developed on the principles of software-defined radio supported by General Purpose Graphics Processing Units (GPGPUs), and presents results from initial field tests which confirm the anticipated capability of the system.

A polyphase filter for many-core architectures

NASA Astrophysics Data System (ADS)

Adámek, K.; Novotný, J.; Armour, W.

2016-07-01

In this article we discuss our implementation of a polyphase filter for real-time data processing in radio astronomy. The polyphase filter is a standard tool in digital signal processing and as such a well established algorithm. We describe in detail our implementation of the polyphase filter algorithm and its behaviour on three generations of NVIDIA GPU cards (Fermi, Kepler, Maxwell), on the Intel Xeon CPU and Xeon Phi (Knights Corner) platforms. All of our implementations aim to exploit the potential for data reuse that the algorithm offers. Our GPU implementations explore two different methods for achieving this, the first makes use of L1/Texture cache, the second uses shared memory. We discuss the usability of each of our implementations along with their behaviours. We measure performance in execution time, which is a critical factor for real-time systems, we also present results in terms of bandwidth (GB/s), compute (GFLOP/s/s) and type conversions (GTc/s). We include a presentation of our results in terms of the sample rate which can be processed in real-time by a chosen platform, which more intuitively describes the expected performance in a signal processing setting. Our findings show that, for the GPUs considered, the performance of our polyphase filter when using lower precision input data is limited by type conversions rather than device bandwidth. We compare these results to an implementation on the Xeon Phi. We show that our Xeon Phi implementation has a performance that is 1.5 × to 1.92 × greater than our CPU implementation, however is not insufficient to compete with the performance of GPUs. We conclude with a comparison of our best performing code to two other implementations of the polyphase filter, showing that our implementation is faster in nearly all cases. This work forms part of the Astro-Accelerate project, a many-core accelerated real-time data processing library for digital signal processing of time-domain radio astronomy data.

Real-time holographic surveillance system

DOEpatents

Collins, H. Dale; McMakin, Douglas L.; Hall, Thomas E.; Gribble, R. Parks

1995-01-01

A holographic surveillance system including means for generating electromagnetic waves; means for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; means for receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; means for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and means for displaying the processed information to determine nature of the target. The means for processing the electrical signals includes means for converting analog signals to digital signals followed by a computer means to apply a backward wave algorithm.

Massively Parallel Signal Processing using the Graphics Processing Unit for Real-Time Brain-Computer Interface Feature Extraction.

PubMed

Wilson, J Adam; Williams, Justin C

2009-01-01

The clock speeds of modern computer processors have nearly plateaued in the past 5 years. Consequently, neural prosthetic systems that rely on processing large quantities of data in a short period of time face a bottleneck, in that it may not be possible to process all of the data recorded from an electrode array with high channel counts and bandwidth, such as electrocorticographic grids or other implantable systems. Therefore, in this study a method of using the processing capabilities of a graphics card [graphics processing unit (GPU)] was developed for real-time neural signal processing of a brain-computer interface (BCI). The NVIDIA CUDA system was used to offload processing to the GPU, which is capable of running many operations in parallel, potentially greatly increasing the speed of existing algorithms. The BCI system records many channels of data, which are processed and translated into a control signal, such as the movement of a computer cursor. This signal processing chain involves computing a matrix-matrix multiplication (i.e., a spatial filter), followed by calculating the power spectral density on every channel using an auto-regressive method, and finally classifying appropriate features for control. In this study, the first two computationally intensive steps were implemented on the GPU, and the speed was compared to both the current implementation and a central processing unit-based implementation that uses multi-threading. Significant performance gains were obtained with GPU processing: the current implementation processed 1000 channels of 250 ms in 933 ms, while the new GPU method took only 27 ms, an improvement of nearly 35 times.

Efficient block processing of long duration biotelemetric brain data for health care monitoring

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

Soumya, I.; Zia Ur Rahman, M., E-mail: mdzr-5@ieee.org; Rama Koti Reddy, D. V.

In real time clinical environment, the brain signals which doctor need to analyze are usually very long. Such a scenario can be made simple by partitioning the input signal into several blocks and applying signal conditioning. This paper presents various block based adaptive filter structures for obtaining high resolution electroencephalogram (EEG) signals, which estimate the deterministic components of the EEG signal by removing noise. To process these long duration signals, we propose Time domain Block Least Mean Square (TDBLMS) algorithm for brain signal enhancement. In order to improve filtering capability, we introduce normalization in the weight update recursion of TDBLMS,more » which results TD-B-normalized-least mean square (LMS). To increase accuracy and resolution in the proposed noise cancelers, we implement the time domain cancelers in frequency domain which results frequency domain TDBLMS and FD-B-Normalized-LMS. Finally, we have applied these algorithms on real EEG signals obtained from human using Emotive Epoc EEG recorder and compared their performance with the conventional LMS algorithm. The results show that the performance of the block based algorithms is superior to the LMS counter-parts in terms of signal to noise ratio, convergence rate, excess mean square error, misadjustment, and coherence.« less

Variable threshold method for ECG R-peak detection.

PubMed

Kew, Hsein-Ping; Jeong, Do-Un

2011-10-01

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

Implementation and optimization of ultrasound signal processing algorithms on mobile GPU

NASA Astrophysics Data System (ADS)

Kong, Woo Kyu; Lee, Wooyoul; Kim, Kyu Cheol; Yoo, Yangmo; Song, Tai-Kyong

2014-03-01

A general-purpose graphics processing unit (GPGPU) has been used for improving computing power in medical ultrasound imaging systems. Recently, a mobile GPU becomes powerful to deal with 3D games and videos at high frame rates on Full HD or HD resolution displays. This paper proposes the method to implement ultrasound signal processing on a mobile GPU available in the high-end smartphone (Galaxy S4, Samsung Electronics, Seoul, Korea) with programmable shaders on the OpenGL ES 2.0 platform. To maximize the performance of the mobile GPU, the optimization of shader design and load sharing between vertex and fragment shader was performed. The beamformed data were captured from a tissue mimicking phantom (Model 539 Multipurpose Phantom, ATS Laboratories, Inc., Bridgeport, CT, USA) by using a commercial ultrasound imaging system equipped with a research package (Ultrasonix Touch, Ultrasonix, Richmond, BC, Canada). The real-time performance is evaluated by frame rates while varying the range of signal processing blocks. The implementation method of ultrasound signal processing on OpenGL ES 2.0 was verified by analyzing PSNR with MATLAB gold standard that has the same signal path. CNR was also analyzed to verify the method. From the evaluations, the proposed mobile GPU-based processing method has no significant difference with the processing using MATLAB (i.e., PSNR<52.51 dB). The comparable results of CNR were obtained from both processing methods (i.e., 11.31). From the mobile GPU implementation, the frame rates of 57.6 Hz were achieved. The total execution time was 17.4 ms that was faster than the acquisition time (i.e., 34.4 ms). These results indicate that the mobile GPU-based processing method can support real-time ultrasound B-mode processing on the smartphone.

A FPGA-based Fast Converging Digital Adaptive Filter for Real-time RFI Mitigation on Ground Based Radio Telescopes

NASA Astrophysics Data System (ADS)

Finger, R.; Curotto, F.; Fuentes, R.; Duan, R.; Bronfman, L.; Li, D.

2018-02-01

Radio Frequency Interference (RFI) is a growing concern in the radio astronomy community. Single-dish telescopes are particularly susceptible to RFI. Several methods have been developed to cope with RF-polluted environments, based on flagging, excision, and real-time blanking, among others. All these methods produce some degree of data loss or require assumptions to be made on the astronomical signal. We report the development of a real-time, digital adaptive filter implemented on a Field Programmable Gate Array (FPGA) capable of processing 4096 spectral channels in a 1 GHz of instantaneous bandwidth. The filter is able to cancel a broad range of interference signals and quickly adapt to changes on the RFI source, minimizing the data loss without any assumption on the astronomical or interfering signal properties. The speed of convergence (for a decrease to a 1%) was measured to be 208.1 μs for a broadband noise-like RFI signal and 125.5 μs for a multiple-carrier RFI signal recorded at the FAST radio telescope.

Real-time micro-vibration multi-spot synchronous measurement within a region based on heterodyne interference

NASA Astrophysics Data System (ADS)

Lan, Ma; Xiao, Wen; Chen, Zonghui; Hao, Hongliang; Pan, Feng

2018-01-01

Real-time micro-vibration measurement is widely used in engineering applications. It is very difficult for traditional optical detection methods to achieve real-time need in a relatively high frequency and multi-spot synchronous measurement of a region at the same time,especially at the nanoscale. Based on the method of heterodyne interference, an experimental system of real-time measurement of micro - vibration is constructed to satisfy the demand in engineering applications. The vibration response signal is measured by combing optical heterodyne interferometry and a high-speed CMOS-DVR image acquisition system. Then, by extracting and processing multiple pixels at the same time, four digital demodulation technique are implemented to simultaneously acquire the vibrating velocity of the target from the recorded sequences of images. Different kinds of demodulation algorithms are analyzed and the results show that these four demodulation algorithms are suitable for different interference signals. Both autocorrelation algorithm and cross-correlation algorithm meet the needs of real-time measurements. The autocorrelation algorithm demodulates the frequency more accurately, while the cross-correlation algorithm is more accurate in solving the amplitude.

Multi-Dimensional Signal Processing Research Program

DTIC Science & Technology

1981-09-30

applications to real-time image processing and analysis. A specific long-range application is the automated processing of aerial reconnaissance imagery...Non-supervised image segmentation is a potentially im- portant operation in the automated processing of aerial reconnaissance pho- tographs since it

Optical mapping system with real-time control capability.

PubMed

Iravanian, Shahriar; Christini, David J

2007-10-01

Real-time, closed-loop intervention is an emerging experiment-control method that promises to provide invaluable new insight into cardiac electrophysiology. One example is the investigation of closed-loop feedback control of cardiac activity (e.g., alternans) as a possible method of preventing arrhythmia onset. To date, such methods have been investigated only in vitro using microelectrode systems, which are hindered by poor spatial resolution and are not well suited for atrial or ventricular tissue preparations. We have developed a system that uses optical mapping techniques and an electrical stimulator as the sensory and effector arms, respectively, of a closed-loop, real-time control system. The system consists of a 2,048 x 1 pixel line-scan charge-coupled device camera that records optical signals from the tissue. Custom-image processing and control software, which is implemented on top of a hard real-time operation system (RTAI Linux), process the data and make control decisions with a deterministic delay of <1 ms. The system is tested in two ways: 1) it is used to control, in real time, simulated optical signals of electrical alternans; and 2) it uses precisely timed, feedback-controlled initiation of antitachycardia pacing to terminate reentrant arrhythmias in an arterially perfused swine right ventricle stained with voltage-sensitive fluorescent dye 4{beta-[2-(di-n-butylamino)-6-napathy]vinyl}pyridinium (di-4-ANEPPS). Thus real-time control of cardiac activity using optical mapping techniques is feasible. Such a system is attractive because it offers greater measurement resolution than the electrode-based systems with which real-time control has been used previously.

Real-time spatio-temporal coherence estimation for autonomous mode identification and invariance tracking

NASA Technical Reports Server (NTRS)

Park, Han G. (Inventor); Zak, Michail (Inventor); James, Mark L. (Inventor); Mackey, Ryan M. E. (Inventor)

2003-01-01

A general method of anomaly detection from time-correlated sensor data is disclosed. Multiple time-correlated signals are received. Their cross-signal behavior is compared against a fixed library of invariants. The library is constructed during a training process, which is itself data-driven using the same time-correlated signals. The method is applicable to a broad class of problems and is designed to respond to any departure from normal operation, including faults or events that lie outside the training envelope.

Real time pressure signal system for a rotary engine

NASA Technical Reports Server (NTRS)

Rice, W. J. (Inventor)

1984-01-01

A real-time IMEP signal which is a composite of those produced in any one chamber of a three-lobed rotary engine is developed by processing the signals of four transducers positioned in a Wankel engine housing such that the rotor overlaps two of the transducers for a brief period during each cycle. During the overlap period of any two transducers, their output is compared and sampled for 10 microseconds per 0.18 degree of rotation by a sampling switch and capacitive circuit. When the switch is closed, the instantaneous difference between the value of the transducer signals is provided while with the switch open the average difference is produced. This combined signal, along with the original signal of the second transducer, is fed through a multiplexer to a pressure output terminal. Timing circuits, controlled by a crank angle encoder on the engine, determine which compared transducer signals are applied to the output terminal and when, as well as the open and closed periods of the switches.

Development of a Real Time Sparse Non-Negative Matrix Factorization Module for Cochlear Implants by Using xPC Target

PubMed Central

Hu, Hongmei; Krasoulis, Agamemnon; Lutman, Mark; Bleeck, Stefan

2013-01-01

Cochlear implants (CIS) require efficient speech processing to maximize information transmission to the brain, especially in noise. A novel CI processing strategy was proposed in our previous studies, in which sparsity-constrained non-negative matrix factorization (NMF) was applied to the envelope matrix in order to improve the CI performance in noisy environments. It showed that the algorithm needs to be adaptive, rather than fixed, in order to adjust to acoustical conditions and individual characteristics. Here, we explore the benefit of a system that allows the user to adjust the signal processing in real time according to their individual listening needs and their individual hearing capabilities. In this system, which is based on MATLAB®, SIMULINK® and the xPC Target™ environment, the input/outupt (I/O) boards are interfaced between the SIMULINK blocks and the CI stimulation system, such that the output can be controlled successfully in the manner of a hardware-in-the-loop (HIL) simulation, hence offering a convenient way to implement a real time signal processing module that does not require any low level language. The sparsity constrained parameter of the algorithm was adapted online subjectively during an experiment with normal-hearing subjects and noise vocoded speech simulation. Results show that subjects chose different parameter values according to their own intelligibility preferences, indicating that adaptive real time algorithms are beneficial to fully explore subjective preferences. We conclude that the adaptive real time systems are beneficial for the experimental design, and such systems allow one to conduct psychophysical experiments with high ecological validity. PMID:24129021

Development of a real time sparse non-negative matrix factorization module for cochlear implants by using xPC target.

PubMed

Hu, Hongmei; Krasoulis, Agamemnon; Lutman, Mark; Bleeck, Stefan

2013-10-14

Cochlear implants (CIs) require efficient speech processing to maximize information transmission to the brain, especially in noise. A novel CI processing strategy was proposed in our previous studies, in which sparsity-constrained non-negative matrix factorization (NMF) was applied to the envelope matrix in order to improve the CI performance in noisy environments. It showed that the algorithm needs to be adaptive, rather than fixed, in order to adjust to acoustical conditions and individual characteristics. Here, we explore the benefit of a system that allows the user to adjust the signal processing in real time according to their individual listening needs and their individual hearing capabilities. In this system, which is based on MATLAB®, SIMULINK® and the xPC Target™ environment, the input/outupt (I/O) boards are interfaced between the SIMULINK blocks and the CI stimulation system, such that the output can be controlled successfully in the manner of a hardware-in-the-loop (HIL) simulation, hence offering a convenient way to implement a real time signal processing module that does not require any low level language. The sparsity constrained parameter of the algorithm was adapted online subjectively during an experiment with normal-hearing subjects and noise vocoded speech simulation. Results show that subjects chose different parameter values according to their own intelligibility preferences, indicating that adaptive real time algorithms are beneficial to fully explore subjective preferences. We conclude that the adaptive real time systems are beneficial for the experimental design, and such systems allow one to conduct psychophysical experiments with high ecological validity.

Neuromimetic Sound Representation for Percept Detection and Manipulation

NASA Astrophysics Data System (ADS)

Zotkin, Dmitry N.; Chi, Taishih; Shamma, Shihab A.; Duraiswami, Ramani

2005-12-01

The acoustic wave received at the ears is processed by the human auditory system to separate different sounds along the intensity, pitch, and timbre dimensions. Conventional Fourier-based signal processing, while endowed with fast algorithms, is unable to easily represent a signal along these attributes. In this paper, we discuss the creation of maximally separable sounds in auditory user interfaces and use a recently proposed cortical sound representation, which performs a biomimetic decomposition of an acoustic signal, to represent and manipulate sound for this purpose. We briefly overview algorithms for obtaining, manipulating, and inverting a cortical representation of a sound and describe algorithms for manipulating signal pitch and timbre separately. The algorithms are also used to create sound of an instrument between a "guitar" and a "trumpet." Excellent sound quality can be achieved if processing time is not a concern, and intelligible signals can be reconstructed in reasonable processing time (about ten seconds of computational time for a one-second signal sampled at [InlineEquation not available: see fulltext.]). Work on bringing the algorithms into the real-time processing domain is ongoing.

Real-time operation without a real-time operating system for instrument control and data acquisition

NASA Astrophysics Data System (ADS)

Klein, Randolf; Poglitsch, Albrecht; Fumi, Fabio; Geis, Norbert; Hamidouche, Murad; Hoenle, Rainer; Looney, Leslie; Raab, Walfried; Viehhauser, Werner

2004-09-01

We are building the Field-Imaging Far-Infrared Line Spectrometer (FIFI LS) for the US-German airborne observatory SOFIA. The detector read-out system is driven by a clock signal at a certain frequency. This signal has to be provided and all other sub-systems have to work synchronously to this clock. The data generated by the instrument has to be received by a computer in a timely manner. Usually these requirements are met with a real-time operating system (RTOS). In this presentation we want to show how we meet these demands differently avoiding the stiffness of an RTOS. Digital I/O-cards with a large buffer separate the asynchronous working computers and the synchronous working instrument. The advantage is that the data processing computers do not need to process the data in real-time. It is sufficient that the computer can process the incoming data stream on average. But since the data is read-in synchronously, problems of relating commands and responses (data) have to be solved: The data is arriving at a fixed rate. The receiving I/O-card buffers the data in its buffer until the computer can access it. To relate the data to commands sent previously, the data is tagged by counters in the read-out electronics. These counters count the system's heartbeat and signals derived from that. The heartbeat and control signals synchronous with the heartbeat are sent by an I/O-card working as pattern generator. Its buffer gets continously programmed with a pattern which is clocked out on the control lines. A counter in the I/O-card keeps track of the amount of pattern words clocked out. By reading this counter, the computer knows the state of the instrument or knows the meaning of the data that will arrive with a certain time-tag.

NASA Pioneer: Venus reverse playback telemetry program TR 78-2

NASA Technical Reports Server (NTRS)

Modestino, J. W.; Daut, D. G.; Vickers, A. L.; Matis, K. R.

1978-01-01

During the entry of the Pioneer Venus Atmospheric Probes into the Venus atmosphere, there were several events (RF blackout and data rate changes) which caused the ground receiving equipment to lose lock on the signal. This caused periods of data loss immediately following each one of these disturbing events which lasted until all the ground receiving units (receiver, subcarrier demodulator, symbol synchronizer, and sequential decoder) acquired lock once more. A scheme to recover these data by off-line data processing was implemented. This scheme consisted of receiving the S band signals from the probes with an open loop reciever (requiring no lock up on the signal) in parallel with the closed loop receivers of the real time receiving equipment, down converting the signals to baseband, and recording them on an analog recorder. The off-line processing consisted of playing the analog recording in the reverse direction (starting with the end of the tape) up, converting the signal to S-band, feeding the signal into the "real time" receiving system and recording on digital tape, the soft decisions from the symbol synchronizer.

Advanced Engine Health Management Applications of the SSME Real-Time Vibration Monitoring System

NASA Technical Reports Server (NTRS)

Fiorucci, Tony R.; Lakin, David R., II; Reynolds, Tracy D.; Turner, James E. (Technical Monitor)

2000-01-01

The Real Time Vibration Monitoring System (RTVMS) is a 32-channel high speed vibration data acquisition and processing system developed at Marshall Space Flight Center (MSFC). It Delivers sample rates as high as 51,200 samples/second per channel and performs Fast Fourier Transform (FFT) processing via on-board digital signal processing (DSP) chips in a real-time format. Advanced engine health assessment is achieved by utilizing the vibration spectra to provide accurate sensor validation and enhanced engine vibration redlines. Discrete spectral signatures (such as synchronous) that are indicators of imminent failure can be assessed and utilized to mitigate catastrophic engine failures- a first in rocket engine health assessment. This paper is presented in viewgraph form.

Event-driven processing for hardware-efficient neural spike sorting

NASA Astrophysics Data System (ADS)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

Real-time digital signal recovery for a multi-pole low-pass transfer function system.

PubMed

Lee, Jhinhwan

2017-08-01

In order to solve the problems of waveform distortion and signal delay by many physical and electrical systems with multi-pole linear low-pass transfer characteristics, a simple digital-signal-processing (DSP)-based method of real-time recovery of the original source waveform from the distorted output waveform is proposed. A mathematical analysis on the convolution kernel representation of the single-pole low-pass transfer function shows that the original source waveform can be accurately recovered in real time using a particular moving average algorithm applied on the input stream of the distorted waveform, which can also significantly reduce the overall delay time constant. This method is generalized for multi-pole low-pass systems and has noise characteristics of the inverse of the low-pass filter characteristics. This method can be applied to most sensors and amplifiers operating close to their frequency response limits to improve the overall performance of data acquisition systems and digital feedback control systems.

Real-time system for imaging and object detection with a multistatic GPR array

DOEpatents

Paglieroni, David W; Beer, N Reginald; Bond, Steven W; Top, Philip L; Chambers, David H; Mast, Jeffrey E; Donetti, John G; Mason, Blake C; Jones, Steven M

2014-10-07

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Laser pulse coded signal frequency measuring device based on DSP and CPLD

NASA Astrophysics Data System (ADS)

Zhang, Hai-bo; Cao, Li-hua; Geng, Ai-hui; Li, Yan; Guo, Ru-hai; Wang, Ting-feng

2011-06-01

Laser pulse code is an anti-jamming measures used in semi-active laser guided weapons. On account of the laser-guided signals adopting pulse coding mode and the weak signal processing, it need complex calculations in the frequency measurement process according to the laser pulse code signal time correlation to meet the request in optoelectronic countermeasures in semi-active laser guided weapons. To ensure accurately completing frequency measurement in a short time, it needed to carry out self-related process with the pulse arrival time series composed of pulse arrival time, calculate the signal repetition period, and then identify the letter type to achieve signal decoding from determining the time value, number and rank number in a signal cycle by Using CPLD and DSP for signal processing chip, designing a laser-guided signal frequency measurement in the pulse frequency measurement device, improving the signal processing capability through the appropriate software algorithms. In this article, we introduced the principle of frequency measurement of the device, described the hardware components of the device, the system works and software, analyzed the impact of some system factors on the accuracy of the measurement. The experimental results indicated that this system improve the accuracy of the measurement under the premise of volume, real-time, anti-interference, low power of the laser pulse frequency measuring device. The practicality of the design, reliability has been demonstrated from the experimental point of view.

Real-time holographic surveillance system

DOEpatents

Collins, H.D.; McMakin, D.L.; Hall, T.E.; Gribble, R.P.

1995-10-03

A holographic surveillance system is disclosed including means for generating electromagnetic waves; means for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; means for receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; means for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and means for displaying the processed information to determine nature of the target. The means for processing the electrical signals includes means for converting analog signals to digital signals followed by a computer means to apply a backward wave algorithm. 21 figs.

Real-Time Data Display

NASA Technical Reports Server (NTRS)

Pedings, Marc

2007-01-01

RT-Display is a MATLAB-based data acquisition environment designed to use a variety of commercial off-the-shelf (COTS) hardware to digitize analog signals to a standard data format usable by other post-acquisition data analysis tools. This software presents the acquired data in real time using a variety of signal-processing algorithms. The acquired data is stored in a standard Operator Interactive Signal Processing Software (OISPS) data-formatted file. RT-Display is primarily configured to use the Agilent VXI (or equivalent) data acquisition boards used in such systems as MIDDAS (Multi-channel Integrated Dynamic Data Acquisition System). The software is generalized and deployable in almost any testing environment, without limitations or proprietary configuration for a specific test program or project. With the Agilent hardware configured and in place, users can start the program and, in one step, immediately begin digitizing multiple channels of data. Once the acquisition is completed, data is converted into a common binary format that also can be translated to specific formats used by external analysis software, such as OISPS and PC-Signal (product of AI Signal Research Inc.). RT-Display at the time of this reporting was certified on Agilent hardware capable of acquisition up to 196,608 samples per second. Data signals are presented to the user on-screen simultaneously for 16 channels. Each channel can be viewed individually, with a maximum capability of 160 signal channels (depending on hardware configuration). Current signal presentations include: time data, fast Fourier transforms (FFT), and power spectral density plots (PSD). Additional processing algorithms can be easily incorporated into this environment.

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery

PubMed Central

Qi, Baogui; Zhuang, Yin; Chen, He; Chen, Liang

2018-01-01

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited. PMID:29693585

New technique for real-time distortion-invariant multiobject recognition and classification

NASA Astrophysics Data System (ADS)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery.

PubMed

Qi, Baogui; Shi, Hao; Zhuang, Yin; Chen, He; Chen, Liang

2018-04-25

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited.

An FPGA-based High Speed Parallel Signal Processing System for Adaptive Optics Testbed

NASA Astrophysics Data System (ADS)

Kim, H.; Choi, Y.; Yang, Y.

In this paper a state-of-the-art FPGA (Field Programmable Gate Array) based high speed parallel signal processing system (SPS) for adaptive optics (AO) testbed with 1 kHz wavefront error (WFE) correction frequency is reported. The AO system consists of Shack-Hartmann sensor (SHS) and deformable mirror (DM), tip-tilt sensor (TTS), tip-tilt mirror (TTM) and an FPGA-based high performance SPS to correct wavefront aberrations. The SHS is composed of 400 subapertures and the DM 277 actuators with Fried geometry, requiring high speed parallel computing capability SPS. In this study, the target WFE correction speed is 1 kHz; therefore, it requires massive parallel computing capabilities as well as strict hard real time constraints on measurements from sensors, matrix computation latency for correction algorithms, and output of control signals for actuators. In order to meet them, an FPGA based real-time SPS with parallel computing capabilities is proposed. In particular, the SPS is made up of a National Instrument's (NI's) real time computer and five FPGA boards based on state-of-the-art Xilinx Kintex 7 FPGA. Programming is done with NI's LabView environment, providing flexibility when applying different algorithms for WFE correction. It also facilitates faster programming and debugging environment as compared to conventional ones. One of the five FPGA's is assigned to measure TTS and calculate control signals for TTM, while the rest four are used to receive SHS signal, calculate slops for each subaperture and correction signal for DM. With this parallel processing capabilities of the SPS the overall closed-loop WFE correction speed of 1 kHz has been achieved. System requirements, architecture and implementation issues are described; furthermore, experimental results are also given.

Investigation of FPGA-Based Real-Time Adaptive Digital Pulse Shaping for High-Count-Rate Applications

NASA Astrophysics Data System (ADS)

Saxena, Shefali; Hawari, Ayman I.

2017-07-01

Digital signal processing techniques have been widely used in radiation spectrometry to provide improved stability and performance with compact physical size over the traditional analog signal processing. In this paper, field-programmable gate array (FPGA)-based adaptive digital pulse shaping techniques are investigated for real-time signal processing. National Instruments (NI) NI 5761 14-bit, 250-MS/s adaptor module is used for digitizing high-purity germanium (HPGe) detector's preamplifier pulses. Digital pulse processing algorithms are implemented on the NI PXIe-7975R reconfigurable FPGA (Kintex-7) using the LabVIEW FPGA module. Based on the time separation between successive input pulses, the adaptive shaping algorithm selects the optimum shaping parameters (rise time and flattop time of trapezoid-shaping filter) for each incoming signal. A digital Sallen-Key low-pass filter is implemented to enhance signal-to-noise ratio and reduce baseline drifting in trapezoid shaping. A recursive trapezoid-shaping filter algorithm is employed for pole-zero compensation of exponentially decayed (with two-decay constants) preamplifier pulses of an HPGe detector. It allows extraction of pulse height information at the beginning of each pulse, thereby reducing the pulse pileup and increasing throughput. The algorithms for RC-CR2 timing filter, baseline restoration, pile-up rejection, and pulse height determination are digitally implemented for radiation spectroscopy. Traditionally, at high-count-rate conditions, a shorter shaping time is preferred to achieve high throughput, which deteriorates energy resolution. In this paper, experimental results are presented for varying count-rate and pulse shaping conditions. Using adaptive shaping, increased throughput is accepted while preserving the energy resolution observed using the longer shaping times.

Real-time EEG-based detection of fatigue driving danger for accident prediction.

PubMed

Wang, Hong; Zhang, Chi; Shi, Tianwei; Wang, Fuwang; Ma, Shujun

2015-03-01

This paper proposes a real-time electroencephalogram (EEG)-based detection method of the potential danger during fatigue driving. To determine driver fatigue in real time, wavelet entropy with a sliding window and pulse coupled neural network (PCNN) were used to process the EEG signals in the visual area (the main information input route). To detect the fatigue danger, the neural mechanism of driver fatigue was analyzed. The functional brain networks were employed to track the fatigue impact on processing capacity of brain. The results show the overall functional connectivity of the subjects is weakened after long time driving tasks. The regularity is summarized as the fatigue convergence phenomenon. Based on the fatigue convergence phenomenon, we combined both the input and global synchronizations of brain together to calculate the residual amount of the information processing capacity of brain to obtain the dangerous points in real time. Finally, the danger detection system of the driver fatigue based on the neural mechanism was validated using accident EEG. The time distributions of the output danger points of the system have a good agreement with those of the real accident points.

IoGET: Internet of Geophysical and Environmental Things

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

Mudunuru, Maruti Kumar

The objective of this project is to provide novel and fast reduced-order models for onboard computation at sensor nodes for real-time analysis. The approach will require that LANL perform high-fidelity numerical simulations, construct simple reduced-order models (ROMs) using machine learning and signal processing algorithms, and use real-time data analysis for ROMs and compressive sensing at sensor nodes.

Real-Time, Polyphase-FFT, 640-MHz Spectrum Analyzer

NASA Technical Reports Server (NTRS)

Zimmerman, George A.; Garyantes, Michael F.; Grimm, Michael J.; Charny, Bentsian; Brown, Randy D.; Wilck, Helmut C.

1994-01-01

Real-time polyphase-fast-Fourier-transform, polyphase-FFT, spectrum analyzer designed to aid in detection of multigigahertz radio signals in two 320-MHz-wide polarization channels. Spectrum analyzer divides total spectrum of 640 MHz into 33,554,432 frequency channels of about 20 Hz each. Size and cost of polyphase-coefficient memory substantially reduced and much of processing loss of windowed FFTs eliminated.

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

NASA Astrophysics Data System (ADS)

Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis

2016-09-01

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology's potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces.

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

PubMed Central

Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis

2016-01-01

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology's potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces. PMID:27666698

A CAMAC based real-time noise analysis system for nuclear reactors

NASA Astrophysics Data System (ADS)

Ciftcioglu, Özer

1987-05-01

A CAMAC based real-time noise analysis system was designed for the TRIGA MARK II nuclear reactor at the Institute for Nuclear Energy, Istanbul. The input analog signals obtained from the radiation detectors are introduced to the system through CAMAC interface. The signals converted into digital form are processed by a PDP-11 computer. The fast data processing based on auto/cross power spectral density computations is carried out by means of assembly written FFT algorithms in real-time and the spectra obtained are displayed on a CAMAC driven display system as an additional monitoring device. The system has the advantage of being software programmable and controlled by a CAMAC system so that it is operated under program control for reactor surveillance, anomaly detection and diagnosis. The system can also be used for the identification of nonstationary operational characteristics of the reactor in long term by comparing the noise power spectra with the corresponding reference noise patterns prepared in advance.

Real-time GMAW quality classification using an artificial neural network with airborne acoustic signals as inputs

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

Matteson, A.; Morris, R.; Tate, R.

1993-12-31

The acoustic signal produced by the gas metal arc welding (GMAW) arc contains information about the behavior of the arc column, the molten pool and droplet transfer. It is possible to detect some defect producing conditions from the acoustic signal from the GMAW arc. An intelligent sensor, called the Weld Acoustic Monitor (WAM) has been developed to take advantage of this acoustic information in order to provide real-time quality assessment information for process control. The WAM makes use of an Artificial Neural Network (ANN) to classify the characteristic arc acoustic signals of acceptable and unacceptable welds. The ANN used inmore » the Weld Acoustic Monitor developed its own set of rules for this classification problem by learning a data base of known GMAW acoustic signals.« less

EARLINET: potential operationality of a research network

NASA Astrophysics Data System (ADS)

Sicard, M.; D'Amico, G.; Comerón, A.; Mona, L.; Alados-Arboledas, L.; Amodeo, A.; Baars, H.; Belegante, L.; Binietoglou, I.; Bravo-Aranda, J. A.; Fernández, A. J.; Fréville, P.; García-Vizcaíno, D.; Giunta, A.; Granados-Muñoz, M. J.; Guerrero-Rascado, J. L.; Hadjimitsis, D.; Haefele, A.; Hervo, M.; Iarlori, M.; Kokkalis, P.; Lange, D.; Mamouri, R. E.; Mattis, I.; Molero, F.; Montoux, N.; Muñoz, A.; Muñoz Porcar, C.; Navas-Guzmán, F.; Nicolae, D.; Nisantzi, A.; Papagiannopoulos, N.; Papayannis, A.; Pereira, S.; Preißler, J.; Pujadas, M.; Rizi, V.; Rocadenbosch, F.; Sellegri, K.; Simeonov, V.; Tsaknakis, G.; Wagner, F.; Pappalardo, G.

2015-07-01

In the framework of ACTRIS summer 2012 measurement campaign (8 June-17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. Eleven lidar stations participated to the exercise which started on 9 July 2012 at 06:00 UT and ended 72 h later on 12 July at 06:00 UT. For the first time the Single-Calculus Chain (SCC), the common calculus chain developed within EARLINET for the automatic evaluation of lidar data from raw signals up to the final products, was used. All stations sent in real time measurements of 1 h of duration to the SCC server in a predefined netcdf file format. The pre-processing of the data was performed in real time by the SCC while the optical processing was performed in near-real time after the exercise ended. 98 and 84 % of the files sent to SCC were successfully pre-processed and processed, respectively. Those percentages are quite large taking into account that no cloud screening was performed on lidar data. The paper shows time series of continuous and homogeneously obtained products retrieved at different levels of the SCC: range-square corrected signals (pre-processing) and daytime backscatter and nighttime extinction coefficient profiles (optical processing), as well as combined plots of all direct and derived optical products. The derived products include backscatter- and extinction-related Ångström exponents, lidar ratios and color ratios. The combined plots reveal extremely valuable for aerosol classification. The efforts made to define the measurements protocol and to configure properly the SCC pave the way for applying this protocol for specific applications such as the monitoring of special events, atmospheric modelling, climate research and calibration/validation activities of spaceborne observations.

Non-stationary least-squares complex decomposition for microseismic noise attenuation

NASA Astrophysics Data System (ADS)

Chen, Yangkang

2018-06-01

Microseismic data processing and imaging are crucial for subsurface real-time monitoring during hydraulic fracturing process. Unlike the active-source seismic events or large-scale earthquake events, the microseismic event is usually of very small magnitude, which makes its detection challenging. The biggest trouble of microseismic data is the low signal-to-noise ratio issue. Because of the small energy difference between effective microseismic signal and ambient noise, the effective signals are usually buried in strong random noise. I propose a useful microseismic denoising algorithm that is based on decomposing a microseismic trace into an ensemble of components using least-squares inversion. Based on the predictive property of useful microseismic event along the time direction, the random noise can be filtered out via least-squares fitting of multiple damping exponential components. The method is flexible and almost automated since the only parameter needed to be defined is a decomposition number. I use some synthetic and real data examples to demonstrate the potential of the algorithm in processing complicated microseismic data sets.

Low-complexity camera digital signal imaging for video document projection system

NASA Astrophysics Data System (ADS)

Hsia, Shih-Chang; Tsai, Po-Shien

2011-04-01

We present high-performance and low-complexity algorithms for real-time camera imaging applications. The main functions of the proposed camera digital signal processing (DSP) involve color interpolation, white balance, adaptive binary processing, auto gain control, and edge and color enhancement for video projection systems. A series of simulations demonstrate that the proposed method can achieve good image quality while keeping computation cost and memory requirements low. On the basis of the proposed algorithms, the cost-effective hardware core is developed using Verilog HDL. The prototype chip has been verified with one low-cost programmable device. The real-time camera system can achieve 1270 × 792 resolution with the combination of extra components and can demonstrate each DSP function.

Knowledge-based tracking algorithm

NASA Astrophysics Data System (ADS)

Corbeil, Allan F.; Hawkins, Linda J.; Gilgallon, Paul F.

1990-10-01

This paper describes the Knowledge-Based Tracking (KBT) algorithm for which a real-time flight test demonstration was recently conducted at Rome Air Development Center (RADC). In KBT processing, the radar signal in each resolution cell is thresholded at a lower than normal setting to detect low RCS targets. This lower threshold produces a larger than normal false alarm rate. Therefore, additional signal processing including spectral filtering, CFAR and knowledge-based acceptance testing are performed to eliminate some of the false alarms. TSC's knowledge-based Track-Before-Detect (TBD) algorithm is then applied to the data from each azimuth sector to detect target tracks. In this algorithm, tentative track templates are formed for each threshold crossing and knowledge-based association rules are applied to the range, Doppler, and azimuth measurements from successive scans. Lastly, an M-association out of N-scan rule is used to declare a detection. This scan-to-scan integration enhances the probability of target detection while maintaining an acceptably low output false alarm rate. For a real-time demonstration of the KBT algorithm, the L-band radar in the Surveillance Laboratory (SL) at RADC was used to illuminate a small Cessna 310 test aircraft. The received radar signal wa digitized and processed by a ST-100 Array Processor and VAX computer network in the lab. The ST-100 performed all of the radar signal processing functions, including Moving Target Indicator (MTI) pulse cancelling, FFT Doppler filtering, and CFAR detection. The VAX computers performed the remaining range-Doppler clustering, beamsplitting and TBD processing functions. The KBT algorithm provided a 9.5 dB improvement relative to single scan performance with a nominal real time delay of less than one second between illumination and display.

A real time dynamic data acquisition and processing system for velocity, density, and total temperature fluctuation measurements

NASA Technical Reports Server (NTRS)

Clukey, Steven J.

1991-01-01

The real time Dynamic Data Acquisition and Processing System (DDAPS) is described which provides the capability for the simultaneous measurement of velocity, density, and total temperature fluctuations. The system of hardware and software is described in context of the wind tunnel environment. The DDAPS replaces both a recording mechanism and a separate data processing system. DDAPS receives input from hot wire anemometers. Amplifiers and filters condition the signals with computer controlled modules. The analog signals are simultaneously digitized and digitally recorded on disk. Automatic acquisition collects necessary calibration and environment data. Hot wire sensitivities are generated and applied to the hot wire data to compute fluctuations. The presentation of the raw and processed data is accomplished on demand. The interface to DDAPS is described along with the internal mechanisms of DDAPS. A summary of operations relevant to the use of the DDAPS is also provided.

Timeseries Signal Processing for Enhancing Mobile Surveys: Learning from Field Studies

NASA Astrophysics Data System (ADS)

Risk, D. A.; Lavoie, M.; Marshall, A. D.; Baillie, J.; Atherton, E. E.; Laybolt, W. D.

2015-12-01

Vehicle-based surveys using laser and other analyzers are now commonplace in research and industry. In many cases when these studies target biologically-relevant gases like methane and carbon dioxide, the minimum detection limits are often coarse (ppm) relative to the analyzer's capabilities (ppb), because of the inherent variability in the ambient background concentrations across the landscape that creates noise and uncertainty. This variation arises from localized biological sinks and sources, but also atmospheric turbulence, air pooling, and other factors. Computational processing routines are widely used in many fields to increase resolution of a target signal in temporally dense data, and offer promise for enhancing mobile surveying techniques. Signal processing routines can both help identify anomalies at very low levels, or can be used inversely to remove localized industrially-emitted anomalies from ecological data. This presentation integrates learnings from various studies in which simple signal processing routines were used successfully to isolate different temporally-varying components of 1 Hz timeseries measured with laser- and UV fluorescence-based analyzers. As illustrative datasets, we present results from industrial fugitive emission studies from across Canada's western provinces and other locations, and also an ecological study that aimed to model near-surface concentration variability across different biomes within eastern Canada. In these cases, signal processing algorithms contributed significantly to the clarity of both industrial, and ecological processes. In some instances, signal processing was too computationally intensive for real-time in-vehicle processing, but we identified workarounds for analyzer-embedded software that contributed to an improvement in real-time resolution of small anomalies. Signal processing is a natural accompaniment to these datasets, and many avenues are open to researchers who wish to enhance existing, and future datasets.

Signal processing techniques for damage detection with piezoelectric wafer active sensors and embedded ultrasonic structural radar

NASA Astrophysics Data System (ADS)

Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor

2004-07-01

Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.

Sensory System for Implementing a Human—Computer Interface Based on Electrooculography

PubMed Central

Barea, Rafael; Boquete, Luciano; Rodriguez-Ascariz, Jose Manuel; Ortega, Sergio; López, Elena

2011-01-01

This paper describes a sensory system for implementing a human–computer interface based on electrooculography. An acquisition system captures electrooculograms and transmits them via the ZigBee protocol. The data acquired are analysed in real time using a microcontroller-based platform running the Linux operating system. The continuous wavelet transform and neural network are used to process and analyse the signals to obtain highly reliable results in real time. To enhance system usability, the graphical interface is projected onto special eyewear, which is also used to position the signal-capturing electrodes. PMID:22346579

Robot Control Through Brain Computer Interface For Patterns Generation

NASA Astrophysics Data System (ADS)

Belluomo, P.; Bucolo, M.; Fortuna, L.; Frasca, M.

2011-09-01

A Brain Computer Interface (BCI) system processes and translates neuronal signals, that mainly comes from EEG instruments, into commands for controlling electronic devices. This system can allow people with motor disabilities to control external devices through the real-time modulation of their brain waves. In this context an EEG-based BCI system that allows creative luminous artistic representations is here presented. The system that has been designed and realized in our laboratory interfaces the BCI2000 platform performing real-time analysis of EEG signals with a couple of moving luminescent twin robots. Experiments are also presented.

Ultrasound contrast agent imaging: Real-time imaging of the superharmonics

NASA Astrophysics Data System (ADS)

Peruzzini, D.; Viti, J.; Tortoli, P.; Verweij, M. D.; de Jong, N.; Vos, H. J.

2015-10-01

Currently, in medical ultrasound contrast agent (UCA) imaging the second harmonic scattering of the microbubbles is regularly used. This scattering is in competition with the signal that is caused by nonlinear wave propagation in tissue. It was reported that UCA imaging based on the third or higher harmonics, i.e. "superharmonic" imaging, shows better contrast. However, the superharmonic scattering has a lower signal level compared to e.g. second harmonic signals. This study investigates the contrast-to-tissue ratio (CTR) and signal to noise ratio (SNR) of superharmonic UCA scattering in a tissue/vessel mimicking phantom using a real-time clinical scanner. Numerical simulations were performed to estimate the level of harmonics generated by the microbubbles. Data were acquired with a custom built dual-frequency cardiac phased array probe. Fundamental real-time images were produced while beam formed radiofrequency (RF) data was stored for further offline processing. The phantom consisted of a cavity filled with UCA surrounded by tissue mimicking material. The acoustic pressure in the cavity of the phantom was 110 kPa (MI = 0.11) ensuring non-destructivity of UCA. After processing of the acquired data from the phantom, the UCA-filled cavity could be clearly observed in the images, while tissue signals were suppressed at or below the noise floor. The measured CTR values were 36 dB, >38 dB, and >32 dB, for the second, third, and fourth harmonic respectively, which were in agreement with those reported earlier for preliminary contrast superharmonic imaging. The single frame SNR values (in which `signal' denotes the signal level from the UCA area) were 23 dB, 18 dB, and 11 dB, respectively. This indicates that noise, and not the tissue signal, is the limiting factor for the UCA detection when using the superharmonics in nondestructive mode.

Real-Time Algebraic Derivative Estimations Using a Novel Low-Cost Architecture Based on Reconfigurable Logic

PubMed Central

Morales, Rafael; Rincón, Fernando; Gazzano, Julio Dondo; López, Juan Carlos

2014-01-01

Time derivative estimation of signals plays a very important role in several fields, such as signal processing and control engineering, just to name a few of them. For that purpose, a non-asymptotic algebraic procedure for the approximate estimation of the system states is used in this work. The method is based on results from differential algebra and furnishes some general formulae for the time derivatives of a measurable signal in which two algebraic derivative estimators run simultaneously, but in an overlapping fashion. The algebraic derivative algorithm presented in this paper is computed online and in real-time, offering high robustness properties with regard to corrupting noises, versatility and ease of implementation. Besides, in this work, we introduce a novel architecture to accelerate this algebraic derivative estimator using reconfigurable logic. The core of the algorithm is implemented in an FPGA, improving the speed of the system and achieving real-time performance. Finally, this work proposes a low-cost platform for the integration of hardware in the loop in MATLAB. PMID:24859033

Robust real-time extraction of respiratory signals from PET list-mode data

NASA Astrophysics Data System (ADS)

Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-06-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware.

Virtual Proprioception for eccentric training.

PubMed

LeMoyne, Robert; Mastroianni, Timothy

2017-07-01

Wireless inertial sensors enable quantified feedback, which can be applied to evaluate the efficacy of therapy and rehabilitation. In particular eccentric training promotes a beneficial rehabilitation and strength training strategy. Virtual Proprioception for eccentric training applies real-time feedback from a wireless gyroscope platform enabled through a software application for a smartphone. Virtual Proprioception for eccentric training is applied to the eccentric phase of a biceps brachii strength training and contrasted to a biceps brachii strength training scenario without feedback. During the operation of Virtual Proprioception for eccentric training the intent is to not exceed a prescribed gyroscope signal threshold based on the real-time presentation of the gyroscope signal, in order to promote the eccentric aspect of the strength training endeavor. The experimental trial data is transmitted wireless through connectivity to the Internet as an email attachment for remote post-processing. A feature set is derived from the gyroscope signal for machine learning classification of the two scenarios of Virtual Proprioception real-time feedback for eccentric training and eccentric training without feedback. Considerable classification accuracy is achieved through the application of a multilayer perceptron neural network for distinguishing between the Virtual Proprioception real-time feedback for eccentric training and eccentric training without feedback.

Scalable Multiprocessor for High-Speed Computing in Space

NASA Technical Reports Server (NTRS)

Lux, James; Lang, Minh; Nishimoto, Kouji; Clark, Douglas; Stosic, Dorothy; Bachmann, Alex; Wilkinson, William; Steffke, Richard

2004-01-01

A report discusses the continuing development of a scalable multiprocessor computing system for hard real-time applications aboard a spacecraft. "Hard realtime applications" signifies applications, like real-time radar signal processing, in which the data to be processed are generated at "hundreds" of pulses per second, each pulse "requiring" millions of arithmetic operations. In these applications, the digital processors must be tightly integrated with analog instrumentation (e.g., radar equipment), and data input/output must be synchronized with analog instrumentation, controlled to within fractions of a microsecond. The scalable multiprocessor is a cluster of identical commercial-off-the-shelf generic DSP (digital-signal-processing) computers plus generic interface circuits, including analog-to-digital converters, all controlled by software. The processors are computers interconnected by high-speed serial links. Performance can be increased by adding hardware modules and correspondingly modifying the software. Work is distributed among the processors in a parallel or pipeline fashion by means of a flexible master/slave control and timing scheme. Each processor operates under its own local clock; synchronization is achieved by broadcasting master time signals to all the processors, which compute offsets between the master clock and their local clocks.

Sensor-based atomic layer deposition for rapid process learning and enhanced manufacturability

NASA Astrophysics Data System (ADS)

Lei, Wei

In the search for sensor based atomic layer deposition (ALD) process to accelerate process learning and enhance manufacturability, we have explored new reactor designs and applied in-situ process sensing to W and HfO 2 ALD processes. A novel wafer scale ALD reactor, which features fast gas switching, good process sensing compatibility and significant similarity to the real manufacturing environment, is constructed. The reactor has a unique movable reactor cap design that allows two possible operation modes: (1) steady-state flow with alternating gas species; or (2) fill-and-pump-out cycling of each gas, accelerating the pump-out by lifting the cap to employ the large chamber volume as ballast. Downstream quadrupole mass spectrometry (QMS) sampling is applied for in-situ process sensing of tungsten ALD process. The QMS reveals essential surface reaction dynamics through real-time signals associated with byproduct generation as well as precursor introduction and depletion for each ALD half cycle, which are then used for process learning and optimization. More subtle interactions such as imperfect surface saturation and reactant dose interaction are also directly observed by QMS, indicating that ALD process is more complicated than the suggested layer-by-layer growth. By integrating in real-time the byproduct QMS signals over each exposure and plotting it against process cycle number, the deposition kinetics on the wafer is directly measured. For continuous ALD runs, the total integrated byproduct QMS signal in each ALD run is also linear to ALD film thickness, and therefore can be used for ALD film thickness metrology. The in-situ process sensing is also applied to HfO2 ALD process that is carried out in a furnace type ALD reactor. Precursor dose end-point control is applied to precisely control the precursor dose in each half cycle. Multiple process sensors, including quartz crystal microbalance (QCM) and QMS are used to provide real time process information. The sensing results confirm the proposed surface reaction path and once again reveal the complexity of ALD processes. The impact of this work includes: (1) It explores new ALD reactor designs which enable the implementation of in-situ process sensors for rapid process learning and enhanced manufacturability; (2) It demonstrates in the first time that in-situ QMS can reveal detailed process dynamics and film growth kinetics in wafer-scale ALD process, and thus can be used for ALD film thickness metrology. (3) Based on results from two different processes carried out in two different reactors, it is clear that ALD is a more complicated process than normally believed or advertised, but real-time observation of the operational chemistries in ALD by in-situ sensors provides critical insight to the process and the basis for more effective process control for ALD applications.

Missile signal processing common computer architecture for rapid technology upgrade

NASA Astrophysics Data System (ADS)

Rabinkin, Daniel V.; Rutledge, Edward; Monticciolo, Paul

2004-10-01

Interceptor missiles process IR images to locate an intended target and guide the interceptor towards it. Signal processing requirements have increased as the sensor bandwidth increases and interceptors operate against more sophisticated targets. A typical interceptor signal processing chain is comprised of two parts. Front-end video processing operates on all pixels of the image and performs such operations as non-uniformity correction (NUC), image stabilization, frame integration and detection. Back-end target processing, which tracks and classifies targets detected in the image, performs such algorithms as Kalman tracking, spectral feature extraction and target discrimination. In the past, video processing was implemented using ASIC components or FPGAs because computation requirements exceeded the throughput of general-purpose processors. Target processing was performed using hybrid architectures that included ASICs, DSPs and general-purpose processors. The resulting systems tended to be function-specific, and required custom software development. They were developed using non-integrated toolsets and test equipment was developed along with the processor platform. The lifespan of a system utilizing the signal processing platform often spans decades, while the specialized nature of processor hardware and software makes it difficult and costly to upgrade. As a result, the signal processing systems often run on outdated technology, algorithms are difficult to update, and system effectiveness is impaired by the inability to rapidly respond to new threats. A new design approach is made possible three developments; Moore's Law - driven improvement in computational throughput; a newly introduced vector computing capability in general purpose processors; and a modern set of open interface software standards. Today's multiprocessor commercial-off-the-shelf (COTS) platforms have sufficient throughput to support interceptor signal processing requirements. This application may be programmed under existing real-time operating systems using parallel processing software libraries, resulting in highly portable code that can be rapidly migrated to new platforms as processor technology evolves. Use of standardized development tools and 3rd party software upgrades are enabled as well as rapid upgrade of processing components as improved algorithms are developed. The resulting weapon system will have a superior processing capability over a custom approach at the time of deployment as a result of a shorter development cycles and use of newer technology. The signal processing computer may be upgraded over the lifecycle of the weapon system, and can migrate between weapon system variants enabled by modification simplicity. This paper presents a reference design using the new approach that utilizes an Altivec PowerPC parallel COTS platform. It uses a VxWorks-based real-time operating system (RTOS), and application code developed using an efficient parallel vector library (PVL). A quantification of computing requirements and demonstration of interceptor algorithm operating on this real-time platform are provided.

On Design and Implementation of Neural-Machine Interface for Artificial Legs

PubMed Central

Zhang, Xiaorong; Liu, Yuhong; Zhang, Fan; Ren, Jin; Sun, Yan (Lindsay); Yang, Qing

2011-01-01

The quality of life of leg amputees can be improved dramatically by using a cyber physical system (CPS) that controls artificial legs based on neural signals representing amputees’ intended movements. The key to the CPS is the neural-machine interface (NMI) that senses electromyographic (EMG) signals to make control decisions. This paper presents a design and implementation of a novel NMI using an embedded computer system to collect neural signals from a physical system - a leg amputee, provide adequate computational capability to interpret such signals, and make decisions to identify user’s intent for prostheses control in real time. A new deciphering algorithm, composed of an EMG pattern classifier and a post-processing scheme, was developed to identify the user’s intended lower limb movements. To deal with environmental uncertainty, a trust management mechanism was designed to handle unexpected sensor failures and signal disturbances. Integrating the neural deciphering algorithm with the trust management mechanism resulted in a highly accurate and reliable software system for neural control of artificial legs. The software was then embedded in a newly designed hardware platform based on an embedded microcontroller and a graphic processing unit (GPU) to form a complete NMI for real time testing. Real time experiments on a leg amputee subject and an able-bodied subject have been carried out to test the control accuracy of the new NMI. Our extensive experiments have shown promising results on both subjects, paving the way for clinical feasibility of neural controlled artificial legs. PMID:22389637

Passive (Micro-) Seismic Event Detection by Identifying Embedded "Event" Anomalies Within Statistically Describable Background Noise

NASA Astrophysics Data System (ADS)

Baziw, Erick; Verbeek, Gerald

2012-12-01

Among engineers there is considerable interest in the real-time identification of "events" within time series data with a low signal to noise ratio. This is especially true for acoustic emission analysis, which is utilized to assess the integrity and safety of many structures and is also applied in the field of passive seismic monitoring (PSM). Here an array of seismic receivers are used to acquire acoustic signals to monitor locations where seismic activity is expected: underground excavations, deep open pits and quarries, reservoirs into which fluids are injected or from which fluids are produced, permeable subsurface formations, or sites of large underground explosions. The most important element of PSM is event detection: the monitoring of seismic acoustic emissions is a continuous, real-time process which typically runs 24 h a day, 7 days a week, and therefore a PSM system with poor event detection can easily acquire terabytes of useless data as it does not identify crucial acoustic events. This paper outlines a new algorithm developed for this application, the so-called SEED™ (Signal Enhancement and Event Detection) algorithm. The SEED™ algorithm uses real-time Bayesian recursive estimation digital filtering techniques for PSM signal enhancement and event detection.

Real-time high-velocity resolution color Doppler OCT

NASA Astrophysics Data System (ADS)

Westphal, Volker; Yazdanfar, Siavash; Rollins, Andrew M.; Izatt, Joseph A.

2001-05-01

Color Doppler optical coherence tomography (CDOCT), also called Optical Doppler Tomography) is a noninvasive optical imaging technique, which allows for micron-scale physiological flow mapping simultaneous with morphological OCT imaging. Current systems for real-time endoscopic optical coherence tomography (EOCT) would be enhanced by the capability to visualize sub-surface blood flow for applications in early cancer diagnosis and the management of bleeding ulcers. Unfortunately, previous implementations of CDOCT have either been sufficiently computationally expensive (employing Fourier or Hilbert transform techniques) to rule out real-time imaging of flow, or have been restricted to imaging of excessively high flow velocities when used in real time. We have developed a novel Doppler OCT signal-processing strategy capable of imaging physiological flow rates in real time. This strategy employs cross-correlation processing of sequential A-scans in an EOCT image, as opposed to autocorrelation processing as described previously. To measure Doppler shifts in the kHz range using this technique, it was necessary to stabilize the EOCT interferometer center frequency, eliminate parasitic phase noise, and to construct a digital cross correlation unit able to correlate signals of megahertz bandwidth by a fixed lag of up to a few ms. The performance of the color Doppler OCT system was demonstrated in a flow phantom, demonstrating a minimum detectable flow velocity of ~0.8 mm/s at a data acquisition rate of 8 images/second (with 480 A-scans/image) using a handheld probe. Dynamic flow as well as using it freehanded was shown. Flow was also detectable in a phantom in combination with a clinical usable endoscopic probe.

Tracking radar advanced signal processing and computing for Kwajalein Atoll (KA) application

NASA Astrophysics Data System (ADS)

Cottrill, Stanley D.

1992-11-01

Two means are examined whereby the operations of KMR during mission execution may be improved through the introduction of advanced signal processing techniques. In the first approach, the addition of real time coherent signal processing technology to the FPQ-19 radar is considered. In the second approach, the incorporation of the MMW radar, with its very fine range precision, to the MMS system is considered. The former appears very attractive and a Phase 2 SBIR has been proposed. The latter does not appear promising enough to warrant further development.

Eliminating Bias In Acousto-Optical Spectrum Analysis

NASA Technical Reports Server (NTRS)

Ansari, Homayoon; Lesh, James R.

1992-01-01

Scheme for digital processing of video signals in acousto-optical spectrum analyzer provides real-time correction for signal-dependent spectral bias. Spectrum analyzer described in "Two-Dimensional Acousto-Optical Spectrum Analyzer" (NPO-18092), related apparatus described in "Three-Dimensional Acousto-Optical Spectrum Analyzer" (NPO-18122). Essence of correction is to average over digitized outputs of pixels in each CCD row and to subtract this from the digitized output of each pixel in row. Signal processed electro-optically with reference-function signals to form two-dimensional spectral image in CCD camera.

Ultra-high throughput real-time instruments for capturing fast signals and rare events

NASA Astrophysics Data System (ADS)

Buckley, Brandon Walter

Wide-band signals play important roles in the most exciting areas of science, engineering, and medicine. To keep up with the demands of exploding internet traffic, modern data centers and communication networks are employing increasingly faster data rates. Wide-band techniques such as pulsed radar jamming and spread spectrum frequency hopping are used on the battlefield to wrestle control of the electromagnetic spectrum. Neurons communicate with each other using transient action potentials that last for only milliseconds at a time. And in the search for rare cells, biologists flow large populations of cells single file down microfluidic channels, interrogating them one-by-one, tens of thousands of times per second. Studying and enabling such high-speed phenomena pose enormous technical challenges. For one, parasitic capacitance inherent in analog electrical components limits their response time. Additionally, converting these fast analog signals to the digital domain requires enormous sampling speeds, which can lead to significant jitter and distortion. State-of-the-art imaging technologies, essential for studying biological dynamics and cells in flow, are limited in speed and sensitivity by finite charge transfer and read rates, and by the small numbers of photo-electrons accumulated in short integration times. And finally, ultra-high throughput real-time digital processing is required at the backend to analyze the streaming data. In this thesis, I discuss my work in developing real-time instruments, employing ultrafast optical techniques, which overcome some of these obstacles. In particular, I use broadband dispersive optics to slow down fast signals to speeds accessible to high-bit depth digitizers and signal processors. I also apply telecommunication multiplexing techniques to boost the speeds of confocal fluorescence microscopy. The photonic time stretcher (TiSER) uses dispersive Fourier transformation to slow down analog signals before digitization and processing. The act of time-stretching effectively boosts the performance of the back-end electronics and digital signal processors. The slowed down signals reach the back-end electronics with reduced bandwidth, and are therefore less affected by high-frequency roll-off and distortion. Time-stretching also increases the effective sampling rate of analog-to-digital converters and reduces aperture jitter, thereby improving resolution. Finally, the instantaneous throughputs of digital signal processors are enhanced by the stretch factor to otherwise unattainable speeds. Leveraging these unique capabilities, TiSER becomes the ideal tool for capturing high-speed signals and characterizing rare phenomena. For this thesis, I have developed techniques to improve the spectral efficiency, bandwidth, and resolution of TiSER using polarization multiplexing, all-optical modulation, and coherent dispersive Fourier transformation. To reduce the latency and improve the data handling capacity, I have also designed and implemented a real-time digital signal processing electronic backend, achieving 1.5 tera-bit per second instantaneous processing throughput. Finally, I will present results from experiments highlighting TiSER's impact in real-world applications. Confocal fluorescence microscopy is the most widely used method for unveiling the molecular composition of biological specimens. However, the weak optical emission of fluorescent probes and the tradeoff between imaging speed and sensitivity is problematic for acquiring blur-free images of fast phenomena and cells flowing at high speed. Here I introduce a new fluorescence imaging modality, which leverages techniques from wireless communication to reach record pixel and frame rates. Termed Fluorescence Imaging using Radio-frequency tagged Emission (FIRE), this new imaging modality is capable of resolving never before seen dynamics in living cells - such as action potentials in neurons and metabolic waves in astrocytes - as well as performing high-content image assays of cells and particles in high-speed flow.

Stream computing for biomedical signal processing: A QRS complex detection case-study.

PubMed

Murphy, B M; O'Driscoll, C; Boylan, G B; Lightbody, G; Marnane, W P

2015-01-01

Recent developments in "Big Data" have brought significant gains in the ability to process large amounts of data on commodity server hardware. Stream computing is a relatively new paradigm in this area, addressing the need to process data in real time with very low latency. While this approach has been developed for dealing with large scale data from the world of business, security and finance, there is a natural overlap with clinical needs for physiological signal processing. In this work we present a case study of streams processing applied to a typical physiological signal processing problem: QRS detection from ECG data.

Optical signal processing of spatially distributed sensor data in smart structures

NASA Technical Reports Server (NTRS)

Bennett, K. D.; Claus, R. O.; Murphy, K. A.; Goette, A. M.

1989-01-01

Smart structures which contain dense two- or three-dimensional arrays of attached or embedded sensor elements inherently require signal multiplexing and processing capabilities to permit good spatial data resolution as well as the adequately short calculation times demanded by real time active feedback actuator drive circuitry. This paper reports the implementation of an in-line optical signal processor and its application in a structural sensing system which incorporates multiple discrete optical fiber sensor elements. The signal processor consists of an array of optical fiber couplers having tailored s-parameters and arranged to allow gray code amplitude scaling of sensor inputs. The use of this signal processor in systems designed to indicate the location of distributed strain and damage in composite materials, as well as to quantitatively characterize that damage, is described. Extension of similar signal processing methods to more complicated smart materials and structures applications are discussed.

Design of an FMCW radar baseband signal processing system for automotive application.

PubMed

Lin, Jau-Jr; Li, Yuan-Ping; Hsu, Wei-Chiang; Lee, Ta-Sung

2016-01-01

For a typical FMCW automotive radar system, a new design of baseband signal processing architecture and algorithms is proposed to overcome the ghost targets and overlapping problems in the multi-target detection scenario. To satisfy the short measurement time constraint without increasing the RF front-end loading, a three-segment waveform with different slopes is utilized. By introducing a new pairing mechanism and a spatial filter design algorithm, the proposed detection architecture not only provides high accuracy and reliability, but also requires low pairing time and computational loading. This proposed baseband signal processing architecture and algorithms balance the performance and complexity, and are suitable to be implemented in a real automotive radar system. Field measurement results demonstrate that the proposed automotive radar signal processing system can perform well in a realistic application scenario.

Development of MATLAB software to control data acquisition from a multichannel systems multi-electrode array.

PubMed

Messier, Erik

2016-08-01

A Multichannel Systems (MCS) microelectrode array data acquisition (DAQ) unit is used to collect multichannel electrograms (EGM) from a Langendorff perfused rabbit heart system to study sudden cardiac death (SCD). MCS provides software through which data being processed by the DAQ unit can be displayed and saved, but this software's combined utility with MATLAB is not very effective. MCSs software stores recorded EGM data in a MathCad (MCD) format, which is then converted to a text file format. These text files are very large, and it is therefore very time consuming to import the EGM data into MATLAB for real-time analysis. Therefore, customized MATLAB software was developed to control the acquisition of data from the MCS DAQ unit, and provide specific laboratory accommodations for this study of SCD. The developed DAQ unit control software will be able to accurately: provide real time display of EGM signals; record and save EGM signals in MATLAB in a desired format; and produce real time analysis of the EGM signals; all through an intuitive GUI.

Multiunit Activity-Based Real-Time Limb-State Estimation from Dorsal Root Ganglion Recordings

PubMed Central

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

2017-01-01

Proprioceptive afferent activities could be useful for providing sensory feedback signals for closed-loop control during functional electrical stimulation (FES). However, most previous studies have used the single-unit activity of individual neurons to extract sensory information from proprioceptive afferents. This study proposes a new decoding method to estimate ankle and knee joint angles using multiunit activity data. Proprioceptive afferent signals were recorded from a dorsal root ganglion with a single-shank microelectrode during passive movements of the ankle and knee joints, and joint angles were measured as kinematic data. The mean absolute value (MAV) was extracted from the multiunit activity data, and a dynamically driven recurrent neural network (DDRNN) was used to estimate ankle and knee joint angles. The multiunit activity-based MAV feature was sufficiently informative to estimate limb states, and the DDRNN showed a better decoding performance than conventional linear estimators. In addition, processing time delay satisfied real-time constraints. These results demonstrated that the proposed method could be applicable for providing real-time sensory feedback signals in closed-loop FES systems. PMID:28276474

Integration of digital signal processing technologies with pulsed electron paramagnetic resonance imaging

PubMed Central

Pursley, Randall H.; Salem, Ghadi; Devasahayam, Nallathamby; Subramanian, Sankaran; Koscielniak, Janusz; Krishna, Murali C.; Pohida, Thomas J.

2006-01-01

The integration of modern data acquisition and digital signal processing (DSP) technologies with Fourier transform electron paramagnetic resonance (FT-EPR) imaging at radiofrequencies (RF) is described. The FT-EPR system operates at a Larmor frequency (Lf) of 300 MHz to facilitate in vivo studies. This relatively low frequency Lf, in conjunction with our ~10 MHz signal bandwidth, enables the use of direct free induction decay time-locked subsampling (TLSS). This particular technique provides advantages by eliminating the traditional analog intermediate frequency downconversion stage along with the corresponding noise sources. TLSS also results in manageable sample rates that facilitate the design of DSP-based data acquisition and image processing platforms. More specifically, we utilize a high-speed field programmable gate array (FPGA) and a DSP processor to perform advanced real-time signal and image processing. The migration to a DSP-based configuration offers the benefits of improved EPR system performance, as well as increased adaptability to various EPR system configurations (i.e., software configurable systems instead of hardware reconfigurations). The required modifications to the FT-EPR system design are described, with focus on the addition of DSP technologies including the application-specific hardware, software, and firmware developed for the FPGA and DSP processor. The first results of using real-time DSP technologies in conjunction with direct detection bandpass sampling to implement EPR imaging at RF frequencies are presented. PMID:16243552

Real-time windowing in imaging radar using FPGA technique

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; Escamilla-Hernandez, Enrique

2005-02-01

The imaging radar uses the high frequency electromagnetic waves reflected from different objects for estimating of its parameters. Pulse compression is a standard signal processing technique used to minimize the peak transmission power and to maximize SNR, and to get a better resolution. Usually the pulse compression can be achieved using a matched filter. The level of the side-lobes in the imaging radar can be reduced using the special weighting function processing. There are very known different weighting functions: Hamming, Hanning, Blackman, Chebyshev, Blackman-Harris, Kaiser-Bessel, etc., widely used in the signal processing applications. Field Programmable Gate Arrays (FPGAs) offers great benefits like instantaneous implementation, dynamic reconfiguration, design, and field programmability. This reconfiguration makes FPGAs a better solution over custom-made integrated circuits. This work aims at demonstrating a reasonably flexible implementation of FM-linear signal and pulse compression using Matlab, Simulink, and System Generator. Employing FPGA and mentioned software we have proposed the pulse compression design on FPGA using classical and novel windows technique to reduce the side-lobes level. This permits increasing the detection ability of the small or nearly placed targets in imaging radar. The advantage of FPGA that can do parallelism in real time processing permits to realize the proposed algorithms. The paper also presents the experimental results of proposed windowing procedure in the marine radar with such the parameters: signal is linear FM (Chirp); frequency deviation DF is 9.375MHz; the pulse width T is 3.2μs taps number in the matched filter is 800 taps; sampling frequency 253.125*106 MHz. It has been realized the reducing of side-lobes levels in real time permitting better resolution of the small targets.

A software framework for real-time multi-modal detection of microsleeps.

PubMed

Knopp, Simon J; Bones, Philip J; Weddell, Stephen J; Jones, Richard D

2017-09-01

A software framework is described which was designed to process EEG, video of one eye, and head movement in real time, towards achieving early detection of microsleeps for prevention of fatal accidents, particularly in transport sectors. The framework is based around a pipeline structure with user-replaceable signal processing modules. This structure can encapsulate a wide variety of feature extraction and classification techniques and can be applied to detecting a variety of aspects of cognitive state. Users of the framework can implement signal processing plugins in C++ or Python. The framework also provides a graphical user interface and the ability to save and load data to and from arbitrary file formats. Two small studies are reported which demonstrate the capabilities of the framework in typical applications: monitoring eye closure and detecting simulated microsleeps. While specifically designed for microsleep detection/prediction, the software framework can be just as appropriately applied to (i) other measures of cognitive state and (ii) development of biomedical instruments for multi-modal real-time physiological monitoring and event detection in intensive care, anaesthesiology, cardiology, neurosurgery, etc. The software framework has been made freely available for researchers to use and modify under an open source licence.

Real-time Graphics Processing Unit Based Fourier Domain Optical Coherence Tomography and Surgical Applications

NASA Astrophysics Data System (ADS)

Zhang, Kang

2011-12-01

In this dissertation, real-time Fourier domain optical coherence tomography (FD-OCT) capable of multi-dimensional micrometer-resolution imaging targeted specifically for microsurgical intervention applications was developed and studied. As a part of this work several ultra-high speed real-time FD-OCT imaging and sensing systems were proposed and developed. A real-time 4D (3D+time) OCT system platform using the graphics processing unit (GPU) to accelerate OCT signal processing, the imaging reconstruction, visualization, and volume rendering was developed. Several GPU based algorithms such as non-uniform fast Fourier transform (NUFFT), numerical dispersion compensation, and multi-GPU implementation were developed to improve the impulse response, SNR roll-off and stability of the system. Full-range complex-conjugate-free FD-OCT was also implemented on the GPU architecture to achieve doubled image range and improved SNR. These technologies overcome the imaging reconstruction and visualization bottlenecks widely exist in current ultra-high speed FD-OCT systems and open the way to interventional OCT imaging for applications in guided microsurgery. A hand-held common-path optical coherence tomography (CP-OCT) distance-sensor based microsurgical tool was developed and validated. Through real-time signal processing, edge detection and feed-back control, the tool was shown to be capable of track target surface and compensate motion. The micro-incision test using a phantom was performed using a CP-OCT-sensor integrated hand-held tool, which showed an incision error less than +/-5 microns, comparing to >100 microns error by free-hand incision. The CP-OCT distance sensor has also been utilized to enhance the accuracy and safety of optical nerve stimulation. Finally, several experiments were conducted to validate the system for surgical applications. One of them involved 4D OCT guided micro-manipulation using a phantom. Multiple volume renderings of one 3D data set were performed with different view angles to allow accurate monitoring of the micro-manipulation, and the user to clearly monitor tool-to-target spatial relation in real-time. The system was also validated by imaging multiple biological samples, such as human fingerprint, human cadaver head and small animals. Compared to conventional surgical microscopes, GPU-based real-time FD-OCT can provide the surgeons with a real-time comprehensive spatial view of the microsurgical region and accurate depth perception.

Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring

PubMed Central

Pappachan, Bobby K; Caesarendra, Wahyu; Tjahjowidodo, Tegoeh; Wijaya, Tomi

2017-01-01

Process monitoring using indirect methods relies on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling rate is often used in real-time monitoring applications to increase the chances of capturing and understanding all possible events related to the process. Advanced signal processing methods are used to further decipher meaningful information from the acquired data. In this research work, power spectrum density (PSD) of sensor data acquired at sampling rates between 40–51.2 kHz was calculated and the corelation between PSD and completed number of cycles/passes is presented. Here, the progress in number of cycles/passes is the event this research work intends to classify and the algorithm used to compute PSD is Welch’s estimate method. A comparison between Welch’s estimate method and statistical methods is also discussed. A clear co-relation was observed using Welch’s estimate to classify the number of cycles/passes. The paper also succeeds in classifying vibration signal generated by the spindle from the vibration signal acquired during finishing process. PMID:28556809

Optical sensor for real-time weld defect detection

NASA Astrophysics Data System (ADS)

Ancona, Antonio; Maggipinto, Tommaso; Spagnolo, Vincenzo; Ferrara, Michele; Lugara, Pietro M.

2002-04-01

In this work we present an innovative optical sensor for on- line and non-intrusive welding process monitoring. It is based on the spectroscopic analysis of the optical VIS emission of the welding plasma plume generated in the laser- metal interaction zone. Plasma electron temperature has been measured for different chemical species composing the plume. Temperature signal evolution has been recorded and analyzed during several CO2-laser welding processes, under variable operating conditions. We have developed a suitable software able to real time detect a wide range of weld defects like crater formation, lack of fusion, excessive penetration, seam oxidation. The same spectroscopic approach has been applied for electric arc welding process monitoring. We assembled our optical sensor in a torch for manual Gas Tungsten Arc Welding procedures and tested the prototype in a manufacturing industry production line. Even in this case we found a clear correlation between the signal behavior and the welded joint quality.

A Binaural CI Research Platform for Oticon Medical SP/XP Implants Enabling ITD/ILD and Variable Rate Processing

PubMed Central

Adiloğlu, K.; Herzke, T.

2015-01-01

We present the first portable, binaural, real-time research platform compatible with Oticon Medical SP and XP generation cochlear implants. The platform consists of (a) a pair of behind-the-ear devices, each containing front and rear calibrated microphones, (b) a four-channel USB analog-to-digital converter, (c) real-time PC-based sound processing software called the Master Hearing Aid, and (d) USB-connected hardware and output coils capable of driving two implants simultaneously. The platform is capable of processing signals from the four microphones simultaneously and producing synchronized binaural cochlear implant outputs that drive two (bilaterally implanted) SP or XP implants. Both audio signal preprocessing algorithms (such as binaural beamforming) and novel binaural stimulation strategies (within the implant limitations) can be programmed by researchers. When the whole research platform is combined with Oticon Medical SP implants, interaural electrode timing can be controlled on individual electrodes to within ±1 µs and interaural electrode energy differences can be controlled to within ±2%. Hence, this new platform is particularly well suited to performing experiments related to interaural time differences in combination with interaural level differences in real-time. The platform also supports instantaneously variable stimulation rates and thereby enables investigations such as the effect of changing the stimulation rate on pitch perception. Because the processing can be changed on the fly, researchers can use this platform to study perceptual changes resulting from different processing strategies acutely. PMID:26721923

A Binaural CI Research Platform for Oticon Medical SP/XP Implants Enabling ITD/ILD and Variable Rate Processing.

PubMed

Backus, B; Adiloğlu, K; Herzke, T

2015-12-30

We present the first portable, binaural, real-time research platform compatible with Oticon Medical SP and XP generation cochlear implants. The platform consists of (a) a pair of behind-the-ear devices, each containing front and rear calibrated microphones, (b) a four-channel USB analog-to-digital converter, (c) real-time PC-based sound processing software called the Master Hearing Aid, and (d) USB-connected hardware and output coils capable of driving two implants simultaneously. The platform is capable of processing signals from the four microphones simultaneously and producing synchronized binaural cochlear implant outputs that drive two (bilaterally implanted) SP or XP implants. Both audio signal preprocessing algorithms (such as binaural beamforming) and novel binaural stimulation strategies (within the implant limitations) can be programmed by researchers. When the whole research platform is combined with Oticon Medical SP implants, interaural electrode timing can be controlled on individual electrodes to within ±1 µs and interaural electrode energy differences can be controlled to within ±2%. Hence, this new platform is particularly well suited to performing experiments related to interaural time differences in combination with interaural level differences in real-time. The platform also supports instantaneously variable stimulation rates and thereby enables investigations such as the effect of changing the stimulation rate on pitch perception. Because the processing can be changed on the fly, researchers can use this platform to study perceptual changes resulting from different processing strategies acutely. © The Author(s) 2015.

Generation of real-time global ionospheric map based on the global GNSS stations with only a sparse distribution

NASA Astrophysics Data System (ADS)

Li, Zishen; Wang, Ningbo; Li, Min; Zhou, Kai; Yuan, Yunbin; Yuan, Hong

2017-04-01

The Earth's ionosphere is part of the atmosphere stretching from an altitude of about 50 km to more than 1000 km. When the Global Navigation Satellite System (GNSS) signal emitted from a satellite travels through the ionosphere before reaches a receiver on or near the Earth surface, the GNSS signal is significantly delayed by the ionosphere and this delay bas been considered as one of the major errors in the GNSS measurement. The real-time global ionospheric map calculated from the real-time data obtained by global stations is an essential method for mitigating the ionospheric delay for real-time positioning. The generation of an accurate global ionospheric map generally depends on the global stations with dense distribution; however, the number of global stations that can produce the real-time data is very limited at present, which results that the generation of global ionospheric map with a high accuracy is very different when only using the current stations with real-time data. In view of this, a new approach is proposed for calculating the real-time global ionospheric map only based on the current stations with real-time data. This new approach is developed on the basis of the post-processing and the one-day predicted global ionospheric map from our research group. The performance of the proposed approach is tested by the current global stations with the real-time data and the test results are also compared with the IGS-released final global ionospheric map products.

Real Time Implementation of an LPC Algorithm. Speech Signal Processing Research at CHI

DTIC Science & Technology

1975-05-01

SIGNAL PROCESSING HARDWARE 2-1 2.1 INTRODUCTION 2-1 2.2 TWO- CHANNEL AUDIO SIGNAL SYSTEM 2-2 2.3 MULTI- CHANNEL AUDIO SIGNAL SYSTEM 2-5 2.3.1... Channel Audio Signal System 2-30 I ii kv^i^ünt«.jfc*. ji .„* ,:-v*. ’.ii. *.. ...... — ■ -,,.,-c-» —ipponp ■^ TOHaBWgBpwiBWgPlpaiPWgW v.«.wN...Messages .... 1-55 1-13. Lost or Out of Order Message 1-56 2-1. Block Diagram of Two- Channel Audio Signal System . . 2-3 2-2. Block Diagram of Audio

Robust real-time extraction of respiratory signals from PET list-mode data.

PubMed

Salomon, Andre; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-05-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions' detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting ("binning") of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signalsdirectly from the acquired PET data simplifies the clinical workflow as it avoids to handle additional signal measurement equipment. We introduce a new data-driven method "Combined Local Motion Detection" (CLMD). It uses the Time-of-Flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using 7 measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware. © 2018 Institute of Physics and Engineering in Medicine.

High-resolution (>5 800 time-bandwidth product) shear mode TeO2 deflector

NASA Astrophysics Data System (ADS)

Soos, Jolanta I.; Caviris, Nicholas P.; Phuvan, Sonlinh

1992-12-01

Acousto-optic deflectors play an important role in optical signal processing systems due to their real time processing capabilities, as well as their conversion capabilities of a function of time to a function of space and time. In this work Brimrose investigated the design and fabrication of state-of-the-art, very large time-bandwidth acousto-optic devices from TeO2 single crystals.

Investigation of signal processing algorithms for an embedded microcontroller-based wearable pulse oximeter.

PubMed

Johnston, W S; Mendelson, Y

2006-01-01

Despite steady progress in the miniaturization of pulse oximeters over the years, significant challenges remain since advanced signal processing must be implemented efficiently in real-time by a relatively small size wearable device. The goal of this study was to investigate several potential digital signal processing algorithms for computing arterial oxygen saturation (SpO(2)) and heart rate (HR) in a battery-operated wearable reflectance pulse oximeter that is being developed in our laboratory for use by medics and first responders in the field. We found that a differential measurement approach, combined with a low-pass filter (LPF), yielded the most suitable signal processing technique for estimating SpO(2), while a signal derivative approach produced the most accurate HR measurements.

Real-time MST radar signal processing using a microcomputer running under FORTH

NASA Technical Reports Server (NTRS)

Bowhill, S. A.

1983-01-01

Data on power, correlation time, and velocity were obtained at the Urbana radar using microcomputer and a single floppy disk drive. This system includes the following features: (1) measurement of the real and imaginary components of the received signal at 20 altitudes spaced by 1.5 km; (2) coherent integration of these components over a 1/8-s time period; (3) continuous real time display of the height profiles of the two coherently integrated components; (4) real time calculation of the 1 minute averages of the power and autocovariance function up to 6 lags; (5) output of these data to floppy disk once every 2 minutes; (6) display of the 1 minute power profiles while the data are stored to the disk; (7) visual prompting for the operator to change disks when required at the end of each hour of data; and (8) continuous audible indication of the status of the interrupt service routine. Accomplishments were enabled by two developments: the use of a new correlation algorithm and the use of the FORTH language to manage the various low level and high level procedures involved.

Low-complexity image processing for real-time detection of neonatal clonic seizures.

PubMed

Ntonfo, Guy Mathurin Kouamou; Ferrari, Gianluigi; Raheli, Riccardo; Pisani, Francesco

2012-05-01

In this paper, we consider a novel low-complexity real-time image-processing-based approach to the detection of neonatal clonic seizures. Our approach is based on the extraction, from a video of a newborn, of an average luminance signal representative of the body movements. Since clonic seizures are characterized by periodic movements of parts of the body (e.g., the limbs), by evaluating the periodicity of the extracted average luminance signal it is possible to detect the presence of a clonic seizure. The periodicity is investigated, through a hybrid autocorrelation-Yin estimation technique, on a per-window basis, where a time window is defined as a sequence of consecutive video frames. While processing is first carried out on a single window basis, we extend our approach to interlaced windows. The performance of the proposed detection algorithm is investigated, in terms of sensitivity and specificity, through receiver operating characteristic curves, considering video recordings of newborns affected by neonatal seizures.

Noise suppression methods for robust speech processing

NASA Astrophysics Data System (ADS)

Boll, S. F.; Ravindra, H.; Randall, G.; Armantrout, R.; Power, R.

1980-05-01

Robust speech processing in practical operating environments requires effective environmental and processor noise suppression. This report describes the technical findings and accomplishments during this reporting period for the research program funded to develop real time, compressed speech analysis synthesis algorithms whose performance in invariant under signal contamination. Fulfillment of this requirement is necessary to insure reliable secure compressed speech transmission within realistic military command and control environments. Overall contributions resulting from this research program include the understanding of how environmental noise degrades narrow band, coded speech, development of appropriate real time noise suppression algorithms, and development of speech parameter identification methods that consider signal contamination as a fundamental element in the estimation process. This report describes the current research and results in the areas of noise suppression using the dual input adaptive noise cancellation using the short time Fourier transform algorithms, articulation rate change techniques, and a description of an experiment which demonstrated that the spectral subtraction noise suppression algorithm can improve the intelligibility of 2400 bps, LPC 10 coded, helicopter speech by 10.6 point.

A digital wireless system for closed-loop inhibition of nociceptive signals

NASA Astrophysics Data System (ADS)

Zuo, Chao; Yang, Xiaofei; Wang, Yang; Hagains, Christopher E.; Li, Ai-Ling; Peng, Yuan B.; Chiao, J.-C.

2012-10-01

Neurostimulation of the spinal cord or brain has been used to inhibit nociceptive signals in pain management applications. Nevertheless, most of the current neurostimulation models are based on open-loop system designs. There is a lack of closed-loop systems for neurostimulation in research with small freely-moving animals and in future clinical applications. Based on our previously developed analog wireless system for closed-loop neurostimulation, a digital wireless system with real-time feedback between recorder and stimulator modules has been developed to achieve multi-channel communication. The wireless system includes a wearable recording module, a wearable stimulation module and a transceiver connected to a computer for real-time and off-line data processing, display and storage. To validate our system, wide dynamic range neurons in the spinal cord dorsal horn have been recorded from anesthetized rats in response to graded mechanical stimuli (brush, pressure and pinch) applied in the hind paw. The identified nociceptive signals were used to automatically trigger electrical stimulation at the periaqueductal gray in real time to inhibit their own activities by the closed-loop design. Our digital wireless closed-loop system has provided a simplified and efficient method for further study of pain processing in freely-moving animals and potential clinical application in patients. Groups 1, 2 and 3 contributed equally to this project.

Acoustic sensor for real-time control for the inductive heating process

DOEpatents

Kelley, John Bruce; Lu, Wei-Yang; Zutavern, Fred J.

2003-09-30

Disclosed is a system and method for providing closed-loop control of the heating of a workpiece by an induction heating machine, including generating an acoustic wave in the workpiece with a pulsed laser; optically measuring displacements of the surface of the workpiece in response to the acoustic wave; calculating a sub-surface material property by analyzing the measured surface displacements; creating an error signal by comparing an attribute of the calculated sub-surface material properties with a desired attribute; and reducing the error signal below an acceptable limit by adjusting, in real-time, as often as necessary, the operation of the inductive heating machine.

Automatic pattern identification of rock moisture based on the Staff-RF model

NASA Astrophysics Data System (ADS)

Zheng, Wei; Tao, Kai; Jiang, Wei

2018-04-01

Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.

Feasibility study of microprocessor systems suitable for use in developing a real-time for the 4.75 GHz scatterometer

NASA Technical Reports Server (NTRS)

1977-01-01

A class of signal processors suitable for the reduction of radar scatterometer data in real time was developed. The systems were applied to the reduction of single polarized 13.3 GHz scatterometer data and provided a real time output of radar scattering coefficient as a function of incident angle. It was proposed that a system for processing of C band radar data be constructed to support scatterometer system currently under development. The establishment of a feasible design approach to the development of this processor system utilizing microprocessor technology was emphasized.

Adaptation of vestibular signals for self-motion perception

PubMed Central

St George, Rebecca J; Day, Brian L; Fitzpatrick, Richard C

2011-01-01

A fundamental concern of the brain is to establish the spatial relationship between self and the world to allow purposeful action. Response adaptation to unvarying sensory stimuli is a common feature of neural processing, both peripherally and centrally. For the semicircular canals, peripheral adaptation of the canal-cupula system to constant angular-velocity stimuli dominates the picture and masks central adaptation. Here we ask whether galvanic vestibular stimulation circumvents peripheral adaptation and, if so, does it reveal central adaptive processes. Transmastoidal bipolar galvanic stimulation and platform rotation (20 deg s−1) were applied separately and held constant for 2 min while perceived rotation was measured by verbal report. During real rotation, the perception of turn decayed from the onset of constant velocity with a mean time constant of 15.8 s. During galvanic-evoked virtual rotation, the perception of rotation initially rose but then declined towards zero over a period of ∼100 s. For both stimuli, oppositely directed perceptions of similar amplitude were reported when stimulation ceased indicating signal adaptation at some level. From these data the time constants of three independent processes were estimated: (i) the peripheral canal-cupula adaptation with time constant 7.3 s, (ii) the central ‘velocity-storage’ process that extends the afferent signal with time constant 7.7 s, and (iii) a long-term adaptation with time constant 75.9 s. The first two agree with previous data based on constant-velocity stimuli. The third component decayed with the profile of a real constant angular acceleration stimulus, showing that the galvanic stimulus signal bypasses the peripheral transformation so that the brainstem sees the galvanic signal as angular acceleration. An adaptive process involving both peripheral and central processes is indicated. Signals evoked by most natural movements will decay peripherally before adaptation can exert an appreciable effect, making a specific vestibular behavioural role unlikely. This adaptation appears to be a general property of the internal coding of self-motion that receives information from multiple sensory sources and filters out the unvarying components regardless of their origin. In this instance of a pure vestibular sensation, it defines the afferent signal that represents the stationary or zero-rotation state. PMID:20937715

Far-field photostable optical nanoscopy (PHOTON) for real-time super-resolution single-molecular imaging of signaling pathways of single live cells

NASA Astrophysics Data System (ADS)

Huang, Tao; Browning, Lauren M.; Xu, Xiao-Hong Nancy

2012-04-01

Cellular signaling pathways play crucial roles in cellular functions and design of effective therapies. Unfortunately, study of cellular signaling pathways remains formidably challenging because sophisticated cascades are involved, and a few molecules are sufficient to trigger signaling responses of a single cell. Here we report the development of far-field photostable-optical-nanoscopy (PHOTON) with photostable single-molecule-nanoparticle-optical-biosensors (SMNOBS) for mapping dynamic cascades of apoptotic signaling pathways of single live cells in real-time at single-molecule (SM) and nanometer (nm) resolutions. We have quantitatively imaged single ligand molecules (tumor necrosis factor α, TNFα) and their binding kinetics with their receptors (TNFR1) on single live cells; tracked formation and internalization of their clusters and their initiation of intracellular signaling pathways in real-time; and studied apoptotic signaling dynamics and mechanisms of single live cells with sufficient temporal and spatial resolutions. This study provides new insights into complex real-time dynamic cascades and molecular mechanisms of apoptotic signaling pathways of single live cells. PHOTON provides superior imaging and sensing capabilities and SMNOBS offer unrivaled biocompatibility and photostability, which enable probing of signaling pathways of single live cells in real-time at SM and nm resolutions.Cellular signaling pathways play crucial roles in cellular functions and design of effective therapies. Unfortunately, study of cellular signaling pathways remains formidably challenging because sophisticated cascades are involved, and a few molecules are sufficient to trigger signaling responses of a single cell. Here we report the development of far-field photostable-optical-nanoscopy (PHOTON) with photostable single-molecule-nanoparticle-optical-biosensors (SMNOBS) for mapping dynamic cascades of apoptotic signaling pathways of single live cells in real-time at single-molecule (SM) and nanometer (nm) resolutions. We have quantitatively imaged single ligand molecules (tumor necrosis factor α, TNFα) and their binding kinetics with their receptors (TNFR1) on single live cells; tracked formation and internalization of their clusters and their initiation of intracellular signaling pathways in real-time; and studied apoptotic signaling dynamics and mechanisms of single live cells with sufficient temporal and spatial resolutions. This study provides new insights into complex real-time dynamic cascades and molecular mechanisms of apoptotic signaling pathways of single live cells. PHOTON provides superior imaging and sensing capabilities and SMNOBS offer unrivaled biocompatibility and photostability, which enable probing of signaling pathways of single live cells in real-time at SM and nm resolutions. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr11739h

Femtosecond Carrier Processes in Compound Semiconductors and Real Time Signal Processing

DTIC Science & Technology

1993-03-10

Blocks in Real Schur Form" ................... 179 5. "The Periodic Schur Decomposition. Algorithms and A p p lication s...existence of short period superlattices (confined LO GaAs and AlAs vibrations) on all samples produced with this method. The degret of deposition zone...small amount of zone intermixing occurs in the spatially separated growth mode (see 1 Figure 1b), the short period superlattices have graded interfaces

Digital Audio Signal Processing and Nde: AN Unlikely but Valuable Partnership

NASA Astrophysics Data System (ADS)

Gaydecki, Patrick

2008-02-01

In the Digital Signal Processing (DSP) group, within the School of Electrical and Electronic Engineering at The University of Manchester, research is conducted into two seemingly distinct and disparate subjects: instrumentation for nondestructive evaluation, and DSP systems & algorithms for digital audio. We have often found that many of the hardware systems and algorithms employed to recover, extract or enhance audio signals may also be applied to signals provided by ultrasonic or magnetic NDE instruments. Furthermore, modern DSP hardware is so fast (typically performing hundreds of millions of operations per second), that much of the processing and signal reconstruction may be performed in real time. Here, we describe some of the hardware systems we have developed, together with algorithms that can be implemented both in real time and offline. A next generation system has now been designed, which incorporates a processor operating at 0.55 Giga MMACS, six input and eight output analogue channels, digital input/output in the form of S/PDIF, a JTAG and a USB interface. The software allows the user, with no knowledge of filter theory or programming, to design and run standard or arbitrary FIR, IIR and adaptive filters. Using audio as a vehicle, we can demonstrate the remarkable properties of modern reconstruction algorithms when used in conjunction with such hardware; applications in NDE include signal enhancement and recovery in acoustic, ultrasonic, magnetic and eddy current modalities.

Noninvasive Diagnosis of Coronary Artery Disease Using 12-Lead High-Frequency Electrocardiograms

NASA Technical Reports Server (NTRS)

Schlegel, Todd T.; Arenare, Brian

2006-01-01

A noninvasive, sensitive method of diagnosing certain pathological conditions of the human heart involves computational processing of digitized electrocardiographic (ECG) signals acquired from a patient at all 12 conventional ECG electrode positions. In the processing, attention is focused on low-amplitude, high-frequency components of those portions of the ECG signals known in the art as QRS complexes. The unique contribution of this method lies in the utilization of signal features and combinations of signal features from various combinations of electrode positions, not reported previously, that have been found to be helpful in diagnosing coronary artery disease and such related pathological conditions as myocardial ischemia, myocardial infarction, and congestive heart failure. The electronic hardware and software used to acquire the QRS complexes and perform some preliminary analyses of their high-frequency components were summarized in Real-Time, High-Frequency QRS Electrocardiograph (MSC- 23154), NASA Tech Briefs, Vol. 27, No. 7 (July 2003), pp. 26-28. To recapitulate, signals from standard electrocardiograph electrodes are preamplified, then digitized at a sampling rate of 1,000 Hz, then analyzed by the software that detects R waves and QRS complexes and analyzes them from several perspectives. The software includes provisions for averaging signals over multiple beats and for special-purpose nonrecursive digital filters with specific low- and high-frequency cutoffs. These filters, applied to the averaged signal, effect a band-pass operation in the frequency range from 150 to 250 Hz. The output of the bandpass filter is the desired high-frequency QRS signal. Further processing is then performed in real time to obtain the beat-to-beat root mean square (RMS) voltage amplitude of the filtered signal, certain variations of the RMS voltage, and such standard measures as the heart rate and R-R interval at any given time. A key signal feature analyzed in the present method is the presence versus the absence of reduced-amplitude zones (RAZs). In terms that must be simplified for the sake of brevity, an RAZ comprises several cycles of a high-frequency QRS signal during which the amplitude of the high-frequency oscillation in a portion of the signal is abnormally low (see figure). A given signal sample exhibiting an interval of reduced amplitude may or may not be classified as an RAZ, depending on quantitative criteria regarding peaks and troughs within the reduced-amplitude portion of the high-frequency QRS signal. This analysis is performed in all 12 leads in real time.

Ultrafast chirped optical waveform recorder using a time microscope

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

Bennett, Corey Vincent

2015-04-21

A new technique for capturing both the amplitude and phase of an optical waveform is presented. This technique can capture signals with many THz of bandwidths in a single shot (e.g., temporal resolution of about 44 fs), or be operated repetitively at a high rate. That is, each temporal window (or frame) is captured single shot, in real time, but the process may be run repeatedly or single-shot. By also including a variety of possible demultiplexing techniques, this process is scalable to recoding continuous signals.

Mathematical Sciences Division 1992 Programs

DTIC Science & Technology

1992-10-01

statistical theory that underlies modern signal analysis . There is a strong emphasis on stochastic processes and time series , particularly those which...include optimal resource planning and real- time scheduling of stochastic shop-floor processes. Scheduling systems will be developed that can adapt to...make forecasts for the length-of-service time series . Protocol analysis of these sessions will be used to idenify relevant contextual features and to

Implementation of a portable device for real-time ECG signal analysis.

PubMed

Jeon, Taegyun; Kim, Byoungho; Jeon, Moongu; Lee, Byung-Geun

2014-12-10

Cardiac disease is one of the main causes of catastrophic mortality. Therefore, detecting the symptoms of cardiac disease as early as possible is important for increasing the patient's survival. In this study, a compact and effective architecture for detecting atrial fibrillation (AFib) and myocardial ischemia is proposed. We developed a portable device using this architecture, which allows real-time electrocardiogram (ECG) signal acquisition and analysis for cardiac diseases. A noisy ECG signal was preprocessed by an analog front-end consisting of analog filters and amplifiers before it was converted into digital data. The analog front-end was minimized to reduce the size of the device and power consumption by implementing some of its functions with digital filters realized in software. With the ECG data, we detected QRS complexes based on wavelet analysis and feature extraction for morphological shape and regularity using an ARM processor. A classifier for cardiac disease was constructed based on features extracted from a training dataset using support vector machines. The classifier then categorized the ECG data into normal beats, AFib, and myocardial ischemia. A portable ECG device was implemented, and successfully acquired and processed ECG signals. The performance of this device was also verified by comparing the processed ECG data with high-quality ECG data from a public cardiac database. Because of reduced computational complexity, the ARM processor was able to process up to a thousand samples per second, and this allowed real-time acquisition and diagnosis of heart disease. Experimental results for detection of heart disease showed that the device classified AFib and ischemia with a sensitivity of 95.1% and a specificity of 95.9%. Current home care and telemedicine systems have a separate device and diagnostic service system, which results in additional time and cost. Our proposed portable ECG device provides captured ECG data and suspected waveform to identify sporadic and chronic events of heart diseases. This device has been built and evaluated for high quality of signals, low computational complexity, and accurate detection.

Digital seismo-acoustic signal processing aboard a wireless sensor platform

NASA Astrophysics Data System (ADS)

Marcillo, O.; Johnson, J. B.; Lorincz, K.; Werner-Allen, G.; Welsh, M.

2006-12-01

We are developing a low power, low-cost wireless sensor array to conduct real-time signal processing of earthquakes at active volcanoes. The sensor array, which integrates data from both seismic and acoustic sensors, is based on Moteiv TMote Sky wireless sensor nodes (www.moteiv.com). The nodes feature a Texas Instruments MSP430 microcontroller, 48 Kbytes of program memory, 10 Kbytes of static RAM, 1 Mbyte of external flash memory, and a 2.4-GHz Chipcon CC2420 IEEE 802.15.4 radio. The TMote Sky is programmed in TinyOS. Basic signal processing occurs on an array of three peripheral sensor nodes. These nodes are tied into a dedicated GPS receiver node, which is focused on time synchronization, and a central communications node, which handles data integration and additional processing. The sensor nodes incorporate dual 12-bit digitizers sampling a seismic sensor and a pressure transducer at 100 samples per second. The wireless capabilities of the system allow flexible array geometry, with a maximum aperture of 200m. We have already developed the digital signal processing routines on board the Moteiv Tmote sensor nodes. The developed routines accomplish Real-time Seismic-Amplitude Measurement (RSAM), Seismic Spectral- Amplitude Measurement (SSAM), and a user-configured Short Term Averaging / Long Term Averaging (STA LTA ratio), which is used to calculate first arrivals. The processed data from individual nodes are transmitted back to a central node, where additional processing may be performed. Such processing will include back azimuth determination and other wave field analyses. Future on-board signal processing will focus on event characterization utilizing pattern recognition and spectral characterization. The processed data is intended as low bandwidth information which can be transmitted periodically and at low cost through satellite telemetry to a web server. The processing is limited by the computational capabilities (RAM, ROM) of the nodes. Nevertheless, we envision this product to be a useful tool for assessing the state of unrest at remote volcanoes.

Method of detecting system function by measuring frequency response

DOEpatents

Morrison, John L.; Morrison, William H.

2008-07-01

Real time battery impedance spectrum is acquired using one time record, Compensated Synchronous Detection (CSD). This parallel method enables battery diagnostics. The excitation current to a test battery is a sum of equal amplitude sin waves of a few frequencies spread over range of interest. The time profile of this signal has duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known, synchronous detection processes the time record and each component, both magnitude and phase, is obtained. For compensation, the components, except the one of interest, are reassembled in the time domain. The resulting signal is subtracted from the original signal and the component of interest is synchronously detected. This process is repeated for each component.

Method of Detecting System Function by Measuring Frequency Response

NASA Technical Reports Server (NTRS)

Morrison, John L. (Inventor); Morrison, William H. (Inventor)

2008-01-01

Real time battery impedance spectrum is acquired using one time record, Compensated Synchronous Detection (CSD). This parallel method enables battery diagnostics. The excitation current to a test battery is a sum of equal amplitude sin waves of a few frequencies spread over range of interest. The time profile of this signal has duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known, synchronous detection processes the time record and each component, both magnitude and phase, is obtained. For compensation, the components, except the one of interest, are reassembled in the time domain. The resulting signal is subtracted from the original signal and the component of interest is synchronously detected. This process is repeated for each component.

A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

PubMed Central

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S.; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities. PMID:22164116

A real-time capable software-defined receiver using GPU for adaptive anti-jam GPS sensors.

PubMed

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities.

FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation

PubMed Central

Millan-Almaraz, Jesus Roberto; de Jesus Romero-Troncoso, Rene; Guevara-Gonzalez, Ramon Gerardo; Contreras-Medina, Luis Miguel; Carrillo-Serrano, Roberto Valentin; Osornio-Rios, Roque Alfredo; Duarte-Galvan, Carlos; Rios-Alcaraz, Miguel Angel; Torres-Pacheco, Irineo

2010-01-01

Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities. PMID:22163656

Automated recognition of helium speech. Phase I: Investigation of microprocessor based analysis/synthesis system

NASA Astrophysics Data System (ADS)

Jelinek, H. J.

1986-01-01

This is the Final Report of Electronic Design Associates on its Phase I SBIR project. The purpose of this project is to develop a method for correcting helium speech, as experienced in diver-surface communication. The goal of the Phase I study was to design, prototype, and evaluate a real time helium speech corrector system based upon digital signal processing techniques. The general approach was to develop hardware (an IBM PC board) to digitize helium speech and software (a LAMBDA computer based simulation) to translate the speech. As planned in the study proposal, this initial prototype may now be used to assess expected performance from a self contained real time system which uses an identical algorithm. The Final Report details the work carried out to produce the prototype system. Four major project tasks were: a signal processing scheme for converting helium speech to normal sounding speech was generated. The signal processing scheme was simulated on a general purpose (LAMDA) computer. Actual helium speech was supplied to the simulation and the converted speech was generated. An IBM-PC based 14 bit data Input/Output board was designed and built. A bibliography of references on speech processing was generated.

Automated eddy current analysis of materials

NASA Technical Reports Server (NTRS)

Workman, Gary L.

1990-01-01

This research effort focused on the use of eddy current techniques for characterizing flaws in graphite-based filament-wound cylindrical structures. A major emphasis was on incorporating artificial intelligence techniques into the signal analysis portion of the inspection process. Developing an eddy current scanning system using a commercial robot for inspecting graphite structures (and others) has been a goal in the overall concept and is essential for the final implementation for expert system interpretation. Manual scans, as performed in the preliminary work here, do not provide sufficiently reproducible eddy current signatures to be easily built into a real time expert system. The expert systems approach to eddy current signal analysis requires that a suitable knowledge base exist in which correct decisions as to the nature of the flaw can be performed. In eddy current or any other expert systems used to analyze signals in real time in a production environment, it is important to simplify computational procedures as much as possible. For that reason, we have chosen to use the measured resistance and reactance values for the preliminary aspects of this work. A simple computation, such as phase angle of the signal, is certainly within the real time processing capability of the computer system. In the work described here, there is a balance between physical measurements and finite element calculations of those measurements. The goal is to evolve into the most cost effective procedures for maintaining the correctness of the knowledge base.

Noise-assisted data processing with empirical mode decomposition in biomedical signals.

PubMed

Karagiannis, Alexandros; Constantinou, Philip

2011-01-01

In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.

ARPA surveillance technology for detection of targets hidden in foliage

NASA Astrophysics Data System (ADS)

Hoff, Lawrence E.; Stotts, Larry B.

1994-02-01

The processing of large quantities of synthetic aperture radar data in real time is a complex problem. Even the image formation process taxes today's most advanced computers. The use of complex algorithms with multiple channels adds another dimension to the computational problem. Advanced Research Projects Agency (ARPA) is currently planning on using the Paragon parallel processor for this task. The Paragon is small enough to allow its use in a sensor aircraft. Candidate algorithms will be implemented on the Paragon for evaluation for real time processing. In this paper ARPA technology developments for detecting targets hidden in foliage are reviewed and examples of signal processing techniques on field collected data are presented.

Impact of the Test Device on the Behavior of the Acoustic Emission Signals: Contribution of the Numerical Modeling to Signal Processing

NASA Astrophysics Data System (ADS)

Issiaka Traore, Oumar; Cristini, Paul; Favretto-Cristini, Nathalie; Pantera, Laurent; Viguier-Pla, Sylvie

2018-01-01

In a context of nuclear safety experiment monitoring with the non destructive testing method of acoustic emission, we study the impact of the test device on the interpretation of the recorded physical signals by using spectral finite element modeling. The numerical results are validated by comparison with real acoustic emission data obtained from previous experiments. The results show that several parameters can have significant impacts on acoustic wave propagation and then on the interpretation of the physical signals. The potential position of the source mechanism, the positions of the receivers and the nature of the coolant fluid have to be taken into account in the definition a pre-processing strategy of the real acoustic emission signals. In order to show the relevance of such an approach, we use the results to propose an optimization of the positions of the acoustic emission sensors in order to reduce the estimation bias of the time-delay and then improve the localization of the source mechanisms.

Development of IR imaging system simulator

NASA Astrophysics Data System (ADS)

Xiang, Xinglang; He, Guojing; Dong, Weike; Dong, Lu

2017-02-01

To overcome the disadvantages of the tradition semi-physical simulation and injection simulation equipment in the performance evaluation of the infrared imaging system (IRIS), a low-cost and reconfigurable IRIS simulator, which can simulate the realistic physical process of infrared imaging, is proposed to test and evaluate the performance of the IRIS. According to the theoretical simulation framework and the theoretical models of the IRIS, the architecture of the IRIS simulator is constructed. The 3D scenes are generated and the infrared atmospheric transmission effects are simulated using OGRE technology in real-time on the computer. The physical effects of the IRIS are classified as the signal response characteristic, modulation transfer characteristic and noise characteristic, and they are simulated on the single-board signal processing platform based on the core processor FPGA in real-time using high-speed parallel computation method.

Time-frequency representation of a highly nonstationary signal via the modified Wigner distribution

NASA Technical Reports Server (NTRS)

Zoladz, T. F.; Jones, J. H.; Jong, J.

1992-01-01

A new signal analysis technique called the modified Wigner distribution (MWD) is presented. The new signal processing tool has been very successful in determining time frequency representations of highly non-stationary multicomponent signals in both simulations and trials involving actual Space Shuttle Main Engine (SSME) high frequency data. The MWD departs from the classic Wigner distribution (WD) in that it effectively eliminates the cross coupling among positive frequency components in a multiple component signal. This attribute of the MWD, which prevents the generation of 'phantom' spectral peaks, will undoubtedly increase the utility of the WD for real world signal analysis applications which more often than not involve multicomponent signals.

Smart signal processing for an evolving electric grid

NASA Astrophysics Data System (ADS)

Silva, Leandro Rodrigues Manso; Duque, Calos Augusto; Ribeiro, Paulo F.

2015-12-01

Electric grids are interconnected complex systems consisting of generation, transmission, distribution, and active loads, recently called prosumers as they produce and consume electric energy. Additionally, these encompass a vast array of equipment such as machines, power transformers, capacitor banks, power electronic devices, motors, etc. that are continuously evolving in their demand characteristics. Given these conditions, signal processing is becoming an essential assessment tool to enable the engineer and researcher to understand, plan, design, and operate the complex and smart electronic grid of the future. This paper focuses on recent developments associated with signal processing applied to power system analysis in terms of characterization and diagnostics. The following techniques are reviewed and their characteristics and applications discussed: active power system monitoring, sparse representation of power system signal, real-time resampling, and time-frequency (i.e., wavelets) applied to power fluctuations.

Phased-array ultrasonic surface contour mapping system and method for solids hoppers and the like

DOEpatents

Fasching, George E.; Smith, Jr., Nelson S.

1994-01-01

A real time ultrasonic surface contour mapping system is provided including a digitally controlled phased-array of transmitter/receiver (T/R) elements located in a fixed position above the surface to be mapped. The surface is divided into a predetermined number of pixels which are separately scanned by an arrangement of T/R elements by applying phase delayed signals thereto that produce ultrasonic tone bursts from each T/R that arrive at a point X in phase and at the same time relative to the leading edge of the tone burst pulse so that the acoustic energies from each T/R combine in a reinforcing manner at point X. The signals produced by the reception of the echo signals reflected from point X back to the T/Rs are also delayed appropriately so that they add in phase at the input of a signal combiner. This combined signal is then processed to determine the range to the point X using density-corrected sound velocity values. An autofocusing signal is developed from the computed average range for a complete scan of the surface pixels. A surface contour map is generated in real time form the range signals on a video monitor.

The X-33 range Operations Control Center

NASA Technical Reports Server (NTRS)

Shy, Karla S.; Norman, Cynthia L.

1998-01-01

This paper describes the capabilities and features of the X-33 Range Operations Center at NASA Dryden Flight Research Center. All the unprocessed data will be collected and transmitted over fiber optic lines to the Lockheed Operations Control Center for real-time flight monitoring of the X-33 vehicle. By using the existing capabilities of the Western Aeronautical Test Range, the Range Operations Center will provide the ability to monitor all down-range tracking sites for the Extended Test Range systems. In addition to radar tracking and aircraft telemetry data, the Telemetry and Radar Acquisition and Processing System is being enhanced to acquire vehicle command data, differential Global Positioning System corrections and telemetry receiver signal level status. The Telemetry and Radar Acquisition Processing System provides the flexibility to satisfy all X-33 data processing requirements quickly and efficiently. Additionally, the Telemetry and Radar Acquisition Processing System will run a real-time link margin analysis program. The results of this model will be compared in real-time with actual flight data. The hardware and software concepts presented in this paper describe a method of merging all types of data into a common database for real-time display in the Range Operations Center in support of the X-33 program. All types of data will be processed for real-time analysis and display of the range system status to ensure public safety.

Nonlinear Real-Time Optical Signal Processing.

DTIC Science & Technology

1988-07-01

Principal Investigator B. K. Jenkins Signal and Image Processing Institute University of Southern California Mail Code 0272 Los Angeles, California...ADDRESS (09% SteW. Mnd ZIP Code ) 10. SOURC OF FUNONG NUMBERS Bldg. 410, Bolling AFB PROGAM CT TASK WORK UNIT Washington, D.C. 20332 EEETP.aso o 11...TAB Unmnnncced Justification By Distribution/ I O’ Availablility Codes I - ’_ ji and/or 2 I Summary During the period 1 July 1987 - 30 June 1988, the

Algorithm for removing scalp signals from functional near-infrared spectroscopy signals in real time using multidistance optodes.

PubMed

Kiguchi, Masashi; Funane, Tsukasa

2014-11-01

A real-time algorithm for removing scalp-blood signals from functional near-infrared spectroscopy signals is proposed. Scalp and deep signals have different dependencies on the source-detector distance. These signals were separated using this characteristic. The algorithm was validated through an experiment using a dynamic phantom in which shallow and deep absorptions were independently changed. The algorithm for measurement of oxygenated and deoxygenated hemoglobins using two wavelengths was explicitly obtained. This algorithm is potentially useful for real-time systems, e.g., brain-computer interfaces and neuro-feedback systems.

Research on human physiological parameters intelligent clothing based on distributed Fiber Bragg Grating

NASA Astrophysics Data System (ADS)

Miao, Changyun; Shi, Boya; Li, Hongqiang

2008-12-01

A human physiological parameters intelligent clothing is researched with FBG sensor technology. In this paper, the principles and methods of measuring human physiological parameters including body temperature and heart rate in intelligent clothing with distributed FBG are studied, the mathematical models of human physiological parameters measurement are built; the processing method of body temperature and heart rate detection signals is presented; human physiological parameters detection module is designed, the interference signals are filtered out, and the measurement accuracy is improved; the integration of the intelligent clothing is given. The intelligent clothing can implement real-time measurement, processing, storage and output of body temperature and heart rate. It has accurate measurement, portability, low cost, real-time monitoring, and other advantages. The intelligent clothing can realize the non-contact monitoring between doctors and patients, timely find the diseases such as cancer and infectious diseases, and make patients get timely treatment. It has great significance and value for ensuring the health of the elders and the children with language dysfunction.

Integrating Clarus data in traffic signal system operation : a survivable real-time weather-responsive system.

DOT National Transportation Integrated Search

2011-07-11

This report presents a prototype of a secure, dependable, real-time weather-responsive traffic signal system. The prototype executes two tasks: 1) accesses weather information that provides near real-time atmospheric and pavement surface condition ob...

Rapid and reliable diagnostic method to detect Zika virus by real-time fluorescence reverse transcription loop-mediated isothermal amplification.

PubMed

Guo, Xu-Guang; Zhou, Yong-Zhuo; Li, Qin; Wang, Wei; Wen, Jin-Zhou; Zheng, Lei; Wang, Qian

2018-04-18

To detect Zika virus more rapidly and accurately, we developed a novel method that utilized a real-time fluorescence reverse transcription loop-mediated isothermal amplification (LAMP) technique. The NS5 gene was amplified by a set of six specific primers that recognized six distinct sequences. The amplification process, including 60 min of thermostatic reaction with Bst DNA polymerase following real-time fluorescence reverse transcriptase using genomic Zika virus standard strain (MR766), was conducted through fluorescent signaling. Among the six pairs of primers that we designate here, NS5 was the most efficient with a high sensitivity of up to 3.3 ng/μl and reproducible specificity on eight pathogen samples that were used as negative controls. The real-time fluorescence reverse transcription LAMP detection process can be completed within 35 min. Our study demonstrated that real-time fluorescence reverse transcription LAMP could be highly beneficial and convenient clinical application to detect Zika virus due to its high specificity and stability.

Real time analysis with the upgraded LHCb trigger in Run III

NASA Astrophysics Data System (ADS)

Szumlak, Tomasz

2017-10-01

The current LHCb trigger system consists of a hardware level, which reduces the LHC bunch-crossing rate of 40 MHz to 1.1 MHz, a rate at which the entire detector is read out. A second level, implemented in a farm of around 20k parallel processing CPUs, the event rate is reduced to around 12.5 kHz. The LHCb experiment plans a major upgrade of the detector and DAQ system in the LHC long shutdown II (2018-2019). In this upgrade, a purely software based trigger system is being developed and it will have to process the full 30 MHz of bunch crossings with inelastic collisions. LHCb will also receive a factor of 5 increase in the instantaneous luminosity, which further contributes to the challenge of reconstructing and selecting events in real time with the CPU farm. We discuss the plans and progress towards achieving efficient reconstruction and selection with a 30 MHz throughput. Another challenge is to exploit the increased signal rate that results from removing the 1.1 MHz readout bottleneck, combined with the higher instantaneous luminosity. Many charm hadron signals can be recorded at up to 50 times higher rate. LHCb is implementing a new paradigm in the form of real time data analysis, in which abundant signals are recorded in a reduced event format that can be fed directly to the physics analyses. These data do not need any further offline event reconstruction, which allows a larger fraction of the grid computing resources to be devoted to Monte Carlo productions. We discuss how this real-time analysis model is absolutely critical to the LHCb upgrade, and how it will evolve during Run-II.

Data Acquisition and Processing System for Airborne Wind Profiling with a Pulsed, 2-Micron, Coherent-Detection, Doppler Lidar System

NASA Technical Reports Server (NTRS)

Beyon, J. Y.; Koch, G. J.; Kavaya, M. J.

2010-01-01

A data acquisition and signal processing system is being developed for a 2-micron airborne wind profiling coherent Doppler lidar system. This lidar, called the Doppler Aerosol Wind Lidar (DAWN), is based on a Ho:Tm:LuLiF laser transmitter and 15-cm diameter telescope. It is being packaged for flights onboard the NASA DC-8, with the first flights in the summer of 2010 in support of the NASA Genesis and Rapid Intensification Processes (GRIP) campaign for the study of hurricanes. The data acquisition and processing system is housed in a compact PCI chassis and consists of four components such as a digitizer, a digital signal processing (DSP) module, a video controller, and a serial port controller. The data acquisition and processing software (DAPS) is also being developed to control the system including real-time data analysis and display. The system detects an external 10 Hz trigger pulse and initiates the data acquisition and processing process, and displays selected wind profile parameters such as Doppler shift, power distribution, wind directions and velocities. Doppler shift created by aircraft motion is measured by an inertial navigation/GPS sensor and fed to the signal processing system for real-time removal of aircraft effects from wind measurements. A general overview of the system and the DAPS as well as the coherent Doppler lidar system is presented in this paper.

Multimodal neuroelectric interface development

NASA Technical Reports Server (NTRS)

Trejo, Leonard J.; Wheeler, Kevin R.; Jorgensen, Charles C.; Rosipal, Roman; Clanton, Sam T.; Matthews, Bryan; Hibbs, Andrew D.; Matthews, Robert; Krupka, Michael

2003-01-01

We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body.

Near real-time adverse drug reaction surveillance within population-based health networks: methodology considerations for data accrual.

PubMed

Avery, Taliser R; Kulldorff, Martin; Vilk, Yury; Li, Lingling; Cheetham, T Craig; Dublin, Sascha; Davis, Robert L; Liu, Liyan; Herrinton, Lisa; Brown, Jeffrey S

2013-05-01

This study describes practical considerations for implementation of near real-time medical product safety surveillance in a distributed health data network. We conducted pilot active safety surveillance comparing generic divalproex sodium to historical branded product at four health plans from April to October 2009. Outcomes reported are all-cause emergency room visits and fractures. One retrospective data extract was completed (January 2002-June 2008), followed by seven prospective monthly extracts (January 2008-November 2009). To evaluate delays in claims processing, we used three analytic approaches: near real-time sequential analysis, sequential analysis with 1.5 month delay, and nonsequential (using final retrospective data). Sequential analyses used the maximized sequential probability ratio test. Procedural and logistical barriers to active surveillance were documented. We identified 6586 new users of generic divalproex sodium and 43,960 new users of the branded product. Quality control methods identified 16 extract errors, which were corrected. Near real-time extracts captured 87.5% of emergency room visits and 50.0% of fractures, which improved to 98.3% and 68.7% respectively with 1.5 month delay. We did not identify signals for either outcome regardless of extract timeframe, and slight differences in the test statistic and relative risk estimates were found. Near real-time sequential safety surveillance is feasible, but several barriers warrant attention. Data quality review of each data extract was necessary. Although signal detection was not affected by delay in analysis, when using a historical control group differential accrual between exposure and outcomes may theoretically bias near real-time risk estimates towards the null, causing failure to detect a signal. Copyright © 2013 John Wiley & Sons, Ltd.

An Intelligent Computer-Based System for Sign Language Tutoring

ERIC Educational Resources Information Center

Ritchings, Tim; Khadragi, Ahmed; Saeb, Magdy

2012-01-01

A computer-based system for sign language tutoring has been developed using a low-cost data glove and a software application that processes the movement signals for signs in real-time and uses Pattern Matching techniques to decide if a trainee has closely replicated a teacher's recorded movements. The data glove provides 17 movement signals from…

Real-time lexical comprehension in young children learning American Sign Language.

PubMed

MacDonald, Kyle; LaMarr, Todd; Corina, David; Marchman, Virginia A; Fernald, Anne

2018-04-16

When children interpret spoken language in real time, linguistic information drives rapid shifts in visual attention to objects in the visual world. This language-vision interaction can provide insights into children's developing efficiency in language comprehension. But how does language influence visual attention when the linguistic signal and the visual world are both processed via the visual channel? Here, we measured eye movements during real-time comprehension of a visual-manual language, American Sign Language (ASL), by 29 native ASL-learning children (16-53 mos, 16 deaf, 13 hearing) and 16 fluent deaf adult signers. All signers showed evidence of rapid, incremental language comprehension, tending to initiate an eye movement before sign offset. Deaf and hearing ASL-learners showed similar gaze patterns, suggesting that the in-the-moment dynamics of eye movements during ASL processing are shaped by the constraints of processing a visual language in real time and not by differential access to auditory information in day-to-day life. Finally, variation in children's ASL processing was positively correlated with age and vocabulary size. Thus, despite competition for attention within a single modality, the timing and accuracy of visual fixations during ASL comprehension reflect information processing skills that are important for language acquisition regardless of language modality. © 2018 John Wiley & Sons Ltd.

The GPU implementation of micro - Doppler period estimation

NASA Astrophysics Data System (ADS)

Yang, Liyuan; Wang, Junling; Bi, Ran

2018-03-01

Aiming at the problem that the computational complexity and the deficiency of real-time of the wideband radar echo signal, a program is designed to improve the performance of real-time extraction of micro-motion feature in this paper based on the CPU-GPU heterogeneous parallel structure. Firstly, we discuss the principle of the micro-Doppler effect generated by the rolling of the scattering points on the orbiting satellite, analyses how to use Kalman filter to compensate the translational motion of tumbling satellite and how to use the joint time-frequency analysis and inverse Radon transform to extract the micro-motion features from the echo after compensation. Secondly, the advantages of GPU in terms of real-time processing and the working principle of CPU-GPU heterogeneous parallelism are analysed, and a program flow based on GPU to extract the micro-motion feature from the radar echo signal of rolling satellite is designed. At the end of the article the results of extraction are given to verify the correctness of the program and algorithm.

Real-time Enhancement, Registration, and Fusion for an Enhanced Vision System

NASA Technical Reports Server (NTRS)

Hines, Glenn D.; Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2006-01-01

Over the last few years NASA Langley Research Center (LaRC) has been developing an Enhanced Vision System (EVS) to aid pilots while flying in poor visibility conditions. The EVS captures imagery using two infrared video cameras. The cameras are placed in an enclosure that is mounted and flown forward-looking underneath the NASA LaRC ARIES 757 aircraft. The data streams from the cameras are processed in real-time and displayed on monitors on-board the aircraft. With proper processing the camera system can provide better-than-human-observed imagery particularly during poor visibility conditions. However, to obtain this goal requires several different stages of processing including enhancement, registration, and fusion, and specialized processing hardware for real-time performance. We are using a real-time implementation of the Retinex algorithm for image enhancement, affine transformations for registration, and weighted sums to perform fusion. All of the algorithms are executed on a single TI DM642 digital signal processor (DSP) clocked at 720 MHz. The image processing components were added to the EVS system, tested, and demonstrated during flight tests in August and September of 2005. In this paper we briefly discuss the EVS image processing hardware and algorithms. We then discuss implementation issues and show examples of the results obtained during flight tests.

Exploring Listeners' Real-Time Reactions to Regional Accents

ERIC Educational Resources Information Center

Watson, Kevin; Clark, Lynn

2015-01-01

Evaluative reactions to language stimuli are presumably dynamic events, constantly changing through time as the signal unfolds, yet the tools we usually use to capture these reactions provide us with only a snapshot of this process by recording reactions at a single point in time. This paper outlines and evaluates a new methodology which employs…

Identification and classification of failure modes in laminated composites by using a multivariate statistical analysis of wavelet coefficients

NASA Astrophysics Data System (ADS)

Baccar, D.; Söffker, D.

2017-11-01

Acoustic Emission (AE) is a suitable method to monitor the health of composite structures in real-time. However, AE-based failure mode identification and classification are still complex to apply due to the fact that AE waves are generally released simultaneously from all AE-emitting damage sources. Hence, the use of advanced signal processing techniques in combination with pattern recognition approaches is required. In this paper, AE signals generated from laminated carbon fiber reinforced polymer (CFRP) subjected to indentation test are examined and analyzed. A new pattern recognition approach involving a number of processing steps able to be implemented in real-time is developed. Unlike common classification approaches, here only CWT coefficients are extracted as relevant features. Firstly, Continuous Wavelet Transform (CWT) is applied to the AE signals. Furthermore, dimensionality reduction process using Principal Component Analysis (PCA) is carried out on the coefficient matrices. The PCA-based feature distribution is analyzed using Kernel Density Estimation (KDE) allowing the determination of a specific pattern for each fault-specific AE signal. Moreover, waveform and frequency content of AE signals are in depth examined and compared with fundamental assumptions reported in this field. A correlation between the identified patterns and failure modes is achieved. The introduced method improves the damage classification and can be used as a non-destructive evaluation tool.

Design of a dataway processor for a parallel image signal processing system

NASA Astrophysics Data System (ADS)

Nomura, Mitsuru; Fujii, Tetsuro; Ono, Sadayasu

1995-04-01

Recently, demands for high-speed signal processing have been increasing especially in the field of image data compression, computer graphics, and medical imaging. To achieve sufficient power for real-time image processing, we have been developing parallel signal-processing systems. This paper describes a communication processor called 'dataway processor' designed for a new scalable parallel signal-processing system. The processor has six high-speed communication links (Dataways), a data-packet routing controller, a RISC CORE, and a DMA controller. Each communication link operates at 8-bit parallel in a full duplex mode at 50 MHz. Moreover, data routing, DMA, and CORE operations are processed in parallel. Therefore, sufficient throughput is available for high-speed digital video signals. The processor is designed in a top- down fashion using a CAD system called 'PARTHENON.' The hardware is fabricated using 0.5-micrometers CMOS technology, and its hardware is about 200 K gates.

Brain-computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms.

PubMed

McFarland, Dennis J; Krusienski, Dean J; Wolpaw, Jonathan R

2006-01-01

The Wadsworth brain-computer interface (BCI), based on mu and beta sensorimotor rhythms, uses one- and two-dimensional cursor movement tasks and relies on user training. This is a real-time closed-loop system. Signal processing consists of channel selection, spatial filtering, and spectral analysis. Feature translation uses a regression approach and normalization. Adaptation occurs at several points in this process on the basis of different criteria and methods. It can use either feedforward (e.g., estimating the signal mean for normalization) or feedback control (e.g., estimating feature weights for the prediction equation). We view this process as the interaction between a dynamic user and a dynamic system that coadapt over time. Understanding the dynamics of this interaction and optimizing its performance represent a major challenge for BCI research.

Enhancement tuning and control for high dynamic range images in multi-scale locally adaptive contrast enhancement algorithms

NASA Astrophysics Data System (ADS)

Cvetkovic, Sascha D.; Schirris, Johan; de With, Peter H. N.

2009-01-01

For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.

Digital signal processing algorithms for automatic voice recognition

NASA Technical Reports Server (NTRS)

Botros, Nazeih M.

1987-01-01

The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.

Prototype real-time baseband signal combiner. [deep space network

NASA Technical Reports Server (NTRS)

Howard, L. D.

1980-01-01

The design and performance of a prototype real-time baseband signal combiner, used to enhance the received Voyager 2 spacecraft signals during the Jupiter flyby, is described. Hardware delay paths, operating programs, and firmware are discussed.

Real-time video signal processing by generalized DDA and control memories: three-dimensional rotation and mapping

NASA Astrophysics Data System (ADS)

Hama, Hiromitsu; Yamashita, Kazumi

1991-11-01

A new method for video signal processing is described in this paper. The purpose is real-time image transformations at low cost, low power, and small size hardware. This is impossible without special hardware. Here generalized digital differential analyzer (DDA) and control memory (CM) play a very important role. Then indentation, which is called jaggy, is caused on the boundary of a background and a foreground accompanied with the processing. Jaggy does not occur inside the transformed image because of adopting linear interpretation. But it does occur inherently on the boundary of the background and the transformed images. It causes deterioration of image quality, and must be avoided. There are two well-know ways to improve image quality, blurring and supersampling. The former does not have much effect, and the latter has the much higher cost of computing. As a means of settling such a trouble, a method is proposed, which searches for positions that may arise jaggy and smooths such points. Computer simulations based on the real data from VTR, one scene of a movie, are presented to demonstrate our proposed scheme using DDA and CMs and to confirm the effectiveness on various transformations.

Real-time diagnostics for a reusable rocket engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Merrill, W.; Duyar, A.

1992-01-01

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

RTSPM: real-time Linux control software for scanning probe microscopy.

PubMed

Chandrasekhar, V; Mehta, M M

2013-01-01

Real time computer control is an essential feature of scanning probe microscopes, which have become important tools for the characterization and investigation of nanometer scale samples. Most commercial (and some open-source) scanning probe data acquisition software uses digital signal processors to handle the real time data processing and control, which adds to the expense and complexity of the control software. We describe here scan control software that uses a single computer and a data acquisition card to acquire scan data. The computer runs an open-source real time Linux kernel, which permits fast acquisition and control while maintaining a responsive graphical user interface. Images from a simulated tuning-fork based microscope as well as a standard topographical sample are also presented, showing some of the capabilities of the software.

Miniaturized and Wireless Optical Neurotransmitter Sensor for Real-Time Monitoring of Dopamine in the Brain

PubMed Central

Kim, Min H.; Yoon, Hargsoon; Choi, Sang H.; Zhao, Fei; Kim, Jongsung; Song, Kyo D.; Lee, Uhn

2016-01-01

Real-time monitoring of extracellular neurotransmitter concentration offers great benefits for diagnosis and treatment of neurological disorders and diseases. This paper presents the study design and results of a miniaturized and wireless optical neurotransmitter sensor (MWONS) for real-time monitoring of brain dopamine concentration. MWONS is based on fluorescent sensing principles and comprises a microspectrometer unit, a microcontroller for data acquisition, and a Bluetooth wireless network for real-time monitoring. MWONS has a custom-designed application software that controls the operation parameters for excitation light sources, data acquisition, and signal processing. MWONS successfully demonstrated a measurement capability with a limit of detection down to a 100 nanomole dopamine concentration, and high selectivity to ascorbic acid (90:1) and uric acid (36:1). PMID:27834927

Miniaturized and Wireless Optical Neurotransmitter Sensor for Real-Time Monitoring of Dopamine in the Brain.

PubMed

Kim, Min H; Yoon, Hargsoon; Choi, Sang H; Zhao, Fei; Kim, Jongsung; Song, Kyo D; Lee, Uhn

2016-11-10

Real-time monitoring of extracellular neurotransmitter concentration offers great benefits for diagnosis and treatment of neurological disorders and diseases. This paper presents the study design and results of a miniaturized and wireless optical neurotransmitter sensor (MWONS) for real-time monitoring of brain dopamine concentration. MWONS is based on fluorescent sensing principles and comprises a microspectrometer unit, a microcontroller for data acquisition, and a Bluetooth wireless network for real-time monitoring. MWONS has a custom-designed application software that controls the operation parameters for excitation light sources, data acquisition, and signal processing. MWONS successfully demonstrated a measurement capability with a limit of detection down to a 100 nanomole dopamine concentration, and high selectivity to ascorbic acid (90:1) and uric acid (36:1).

Brain-computer interface analysis of a dynamic visuo-motor task.

PubMed

Logar, Vito; Belič, Aleš

2011-01-01

The area of brain-computer interfaces (BCIs) represents one of the more interesting fields in neurophysiological research, since it investigates the development of the machines that perform different transformations of the brain's "thoughts" to certain pre-defined actions. Experimental studies have reported some successful implementations of BCIs; however, much of the field still remains unexplored. According to some recent reports the phase coding of informational content is an important mechanism in the brain's function and cognition, and has the potential to explain various mechanisms of the brain's data transfer, but it has yet to be scrutinized in the context of brain-computer interface. Therefore, if the mechanism of phase coding is plausible, one should be able to extract the phase-coded content, carried by brain signals, using appropriate signal-processing methods. In our previous studies we have shown that by using a phase-demodulation-based signal-processing approach it is possible to decode some relevant information on the current motor action in the brain from electroencephalographic (EEG) data. In this paper the authors would like to present a continuation of their previous work on the brain-information-decoding analysis of visuo-motor (VM) tasks. The present study shows that EEG data measured during more complex, dynamic visuo-motor (dVM) tasks carries enough information about the currently performed motor action to be successfully extracted by using the appropriate signal-processing and identification methods. The aim of this paper is therefore to present a mathematical model, which by means of the EEG measurements as its inputs predicts the course of the wrist movements as applied by each subject during the task in simulated or real time (BCI analysis). However, several modifications to the existing methodology are needed to achieve optimal decoding results and a real-time, data-processing ability. The information extracted from the EEG could, therefore, be further used for the development of a closed-loop, non-invasive, brain-computer interface. For the case of this study two types of measurements were performed, i.e., the electroencephalographic (EEG) signals and the wrist movements were measured simultaneously, during the subject's performance of a dynamic visuo-motor task. Wrist-movement predictions were computed by using the EEG data-processing methodology of double brain-rhythm filtering, double phase demodulation and double principal component analyses (PCA), each with a separate set of parameters. For the movement-prediction model a fuzzy inference system was used. The results have shown that the EEG signals measured during the dVM tasks carry enough information about the subjects' wrist movements for them to be successfully decoded using the presented methodology. Reasonably high values of the correlation coefficients suggest that the validation of the proposed approach is satisfactory. Moreover, since the causality of the rhythm filtering and the PCA transformation has been achieved, we have shown that these methods can also be used in a real-time, brain-computer interface. The study revealed that using non-causal, optimized methods yields better prediction results in comparison with the causal, non-optimized methodology; however, taking into account that the causality of these methods allows real-time processing, the minor decrease in prediction quality is acceptable. The study suggests that the methodology that was proposed in our previous studies is also valid for identifying the EEG-coded content during dVM tasks, albeit with various modifications, which allow better prediction results and real-time data processing. The results have shown that wrist movements can be predicted in simulated or real time; however, the results of the non-causal, optimized methodology (simulated) are slightly better. Nevertheless, the study has revealed that these methods should be suitable for use in the development of a non-invasive, brain-computer interface. Copyright © 2010 Elsevier B.V. All rights reserved.

Design and Implementation of a Video-Zoom Driven Digital Audio-Zoom System for Portable Digital Imaging Devices

NASA Astrophysics Data System (ADS)

Park, Nam In; Kim, Seon Man; Kim, Hong Kook; Kim, Ji Woon; Kim, Myeong Bo; Yun, Su Won

In this paper, we propose a video-zoom driven audio-zoom algorithm in order to provide audio zooming effects in accordance with the degree of video-zoom. The proposed algorithm is designed based on a super-directive beamformer operating with a 4-channel microphone system, in conjunction with a soft masking process that considers the phase differences between microphones. Thus, the audio-zoom processed signal is obtained by multiplying an audio gain derived from a video-zoom level by the masked signal. After all, a real-time audio-zoom system is implemented on an ARM-CORETEX-A8 having a clock speed of 600 MHz after different levels of optimization are performed such as algorithmic level, C-code, and memory optimizations. To evaluate the complexity of the proposed real-time audio-zoom system, test data whose length is 21.3 seconds long is sampled at 48 kHz. As a result, it is shown from the experiments that the processing time for the proposed audio-zoom system occupies 14.6% or less of the ARM clock cycles. It is also shown from the experimental results performed in a semi-anechoic chamber that the signal with the front direction can be amplified by approximately 10 dB compared to the other directions.

ROADNET: A Real-time Data Aware System for Earth, Oceanographic, and Environmental Applications

NASA Astrophysics Data System (ADS)

Vernon, F.; Hansen, T.; Lindquist, K.; Ludascher, B.; Orcutt, J.; Rajasekar, A.

2003-12-01

The Real-time Observatories, Application, and Data management Network (ROADNet) Program aims to develop an integrated, seamless, and transparent environmental information network that will deliver geophysical, oceanographic, hydrological, ecological, and physical data to a variety of users in real-time. ROADNet is a multidisciplinary, multinational partnership of researchers, policymakers, natural resource managers, educators, and students who aim to use the data to advance our understanding and management of coastal, ocean, riparian, and terrestrial Earth systems in Southern California, Mexico, and well off shore. To date, project activity and funding have focused on the design and deployment of network linkages and on the exploratory development of the real-time data management system. We are currently adapting powerful "Data Grid" technologies to the unique challenges associated with the management and manipulation of real-time data. Current "Grid" projects deal with static data files, and significant technical innovation is required to address fundamental problems of real-time data processing, integration, and distribution. The technologies developed through this research will create a system that dynamically adapt downstream processing, cataloging, and data access interfaces when sensors are added or removed from the system; provide for real-time processing and monitoring of data streams--detecting events, and triggering computations, sensor and logger modifications, and other actions; integrate heterogeneous data from multiple (signal) domains; and provide for large-scale archival and querying of "consolidated" data. The software tools which must be developed do not exist, although limited prototype systems are available. This research has implications for the success of large-scale NSF initiatives in the Earth sciences (EarthScope), ocean sciences (OOI- Ocean Observatories Initiative), biological sciences (NEON - National Ecological Observatory Network) and civil engineering (NEES - Network for Earthquake Engineering Simulation). Each of these large scale initiatives aims to collect real-time data from thousands of sensors, and each will require new technologies to process, manage, and communicate real-time multidisciplinary environmental data on regional, national, and global scales.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

PubMed

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force.

Digital codec for real-time processing of broadcast quality video signals at 1.8 bits/pixel

NASA Technical Reports Server (NTRS)

Shalkhauser, Mary JO; Whyte, Wayne A., Jr.

1989-01-01

The authors present the hardware implementation of a digital television bandwidth compression algorithm which processes standard NTSC (National Television Systems Committee) composite color television signals and produces broadcast-quality video in real time at an average of 1.8 b/pixel. The sampling rate used with this algorithm results in 768 samples over the active portion of each video line by 512 active video lines per video frame. The algorithm is based on differential pulse code modulation (DPCM), but additionally utilizes a nonadaptive predictor, nonuniform quantizer, and multilevel Huffman coder to reduce the data rate substantially below that achievable with straight DPCM. The nonadaptive predictor and multilevel Huffman coder combine to set this technique apart from prior-art DPCM encoding algorithms. The authors describe the data compression algorithm and the hardware implementation of the codec and provide performance results.

An in vitro test bench reproducing coronary blood flow signals.

PubMed

Chodzyński, Kamil Jerzy; Boudjeltia, Karim Zouaoui; Lalmand, Jacques; Aminian, Adel; Vanhamme, Luc; de Sousa, Daniel Ribeiro; Gremmo, Simone; Bricteux, Laurent; Renotte, Christine; Courbebaisse, Guy; Coussement, Grégory

2015-08-07

It is a known fact that blood flow pattern and more specifically the pulsatile time variation of shear stress on the vascular wall play a key role in atherogenesis. The paper presents the conception, the building and the control of a new in vitro test bench that mimics the pulsatile flows behavior based on in vivo measurements. An in vitro cardiovascular simulator is alimented with in vivo constraints upstream and provided with further post-processing analysis downstream in order to mimic the pulsatile in vivo blood flow quantities. This real-time controlled system is designed to perform real pulsatile in vivo blood flow signals to study endothelial cells' behavior under near physiological environment. The system is based on an internal model controller and a proportional-integral controller that controls a linear motor with customized piston pump, two proportional-integral controllers that control the mean flow rate and temperature of the medium. This configuration enables to mimic any resulting blood flow rate patterns between 40 and 700 ml/min. In order to feed the system with reliable periodic flow quantities in vivo measurements were performed. Data from five patients (1 female, 4 males; ages 44-63) were filtered and post-processed using the Newtonian Womersley's solution. These resulting flow signals were compared with 2D axisymmetric, numerical simulation using a Carreau non-Newtonian model to validate the approximation of a Newtonian behavior. This in vitro test bench reproduces the measured flow rate time evolution and the complexity of in vivo hemodynamic signals within the accuracy of the relative error below 5%. This post-processing method is compatible with any real complex in vivo signal and demonstrates the heterogeneity of pulsatile patterns in coronary arteries among of different patients. The comparison between analytical and numerical solution demonstrate the fair quality of the Newtonian Womersley's approximation. Therefore, Womersley's solution was used to calculate input flow rate for the in vitro test bench.

A Real-Time System for Lane Detection Based on FPGA and DSP

NASA Astrophysics Data System (ADS)

Xiao, Jing; Li, Shutao; Sun, Bin

2016-12-01

This paper presents a real-time lane detection system including edge detection and improved Hough Transform based lane detection algorithm and its hardware implementation with field programmable gate array (FPGA) and digital signal processor (DSP). Firstly, gradient amplitude and direction information are combined to extract lane edge information. Then, the information is used to determine the region of interest. Finally, the lanes are extracted by using improved Hough Transform. The image processing module of the system consists of FPGA and DSP. Particularly, the algorithms implemented in FPGA are working in pipeline and processing in parallel so that the system can run in real-time. In addition, DSP realizes lane line extraction and display function with an improved Hough Transform. The experimental results show that the proposed system is able to detect lanes under different road situations efficiently and effectively.

Real-time speckle reduction in optical coherence tomography using the dual window method.

PubMed

Zhao, Yang; Chu, Kengyeh K; Eldridge, Will J; Jelly, Evan T; Crose, Michael; Wax, Adam

2018-02-01

Speckle is an intrinsic noise of interferometric signals which reduces contrast and degrades the quality of optical coherence tomography (OCT) images. Here, we present a frequency compounding speckle reduction technique using the dual window (DW) method. Using the DW method, speckle noise is reduced without the need to acquire multiple frames. A ~25% improvement in the contrast-to-noise ratio (CNR) was achieved using the DW speckle reduction method with only minimal loss (~17%) in axial resolution. We also demonstrate that real-time speckle reduction can be achieved at a B-scan rate of ~21 frames per second using a graphic processing unit (GPU). The DW speckle reduction technique can work on any existing OCT instrument without further system modification or extra components. This makes it applicable both in real-time imaging systems and during post-processing.

Ultrasound contrast agent imaging: Real-time imaging of the superharmonics

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

Peruzzini, D.; Viti, J.; Erasmus MC, ’s-Gravendijkwal 230, Faculty Building, Ee 2302, 3015 CE Rotterdam

2015-10-28

Currently, in medical ultrasound contrast agent (UCA) imaging the second harmonic scattering of the microbubbles is regularly used. This scattering is in competition with the signal that is caused by nonlinear wave propagation in tissue. It was reported that UCA imaging based on the third or higher harmonics, i.e. “superharmonic” imaging, shows better contrast. However, the superharmonic scattering has a lower signal level compared to e.g. second harmonic signals. This study investigates the contrast-to-tissue ratio (CTR) and signal to noise ratio (SNR) of superharmonic UCA scattering in a tissue/vessel mimicking phantom using a real-time clinical scanner. Numerical simulations were performedmore » to estimate the level of harmonics generated by the microbubbles. Data were acquired with a custom built dual-frequency cardiac phased array probe. Fundamental real-time images were produced while beam formed radiofrequency (RF) data was stored for further offline processing. The phantom consisted of a cavity filled with UCA surrounded by tissue mimicking material. The acoustic pressure in the cavity of the phantom was 110 kPa (MI = 0.11) ensuring non-destructivity of UCA. After processing of the acquired data from the phantom, the UCA-filled cavity could be clearly observed in the images, while tissue signals were suppressed at or below the noise floor. The measured CTR values were 36 dB, >38 dB, and >32 dB, for the second, third, and fourth harmonic respectively, which were in agreement with those reported earlier for preliminary contrast superharmonic imaging. The single frame SNR values (in which ‘signal’ denotes the signal level from the UCA area) were 23 dB, 18 dB, and 11 dB, respectively. This indicates that noise, and not the tissue signal, is the limiting factor for the UCA detection when using the superharmonics in nondestructive mode.« less

SIG. Signal Processing, Analysis, & Display

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

Hernandez, J.; Lager, D.; Azevedo, S.

1992-01-22

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG; a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time and frequency-domain signals includingmore » operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments, commenting lines, defining commands, and automatic execution for each item in a `repeat` sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

SIG. Signal Processing, Analysis, & Display

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

Hernandez, J.; Lager, D.; Azevedo, S.

1992-01-22

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time-and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time and frequency-domain signals includingmore » operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments, commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

A real-time device for converting Doppler ultrasound audio signals into fluid flow velocity

PubMed Central

Hogeman, Cynthia S.; Koch, Dennis W.; Krishnan, Anandi; Momen, Afsana; Leuenberger, Urs A.

2010-01-01

A Doppler signal converter has been developed to facilitate cardiovascular and exercise physiology research. This device directly converts audio signals from a clinical Doppler ultrasound imaging system into a real-time analog signal that accurately represents blood flow velocity and is easily recorded by any standard data acquisition system. This real-time flow velocity signal, when simultaneously recorded with other physiological signals of interest, permits the observation of transient flow response to experimental interventions in a manner not possible when using standard Doppler imaging devices. This converted flow velocity signal also permits a more robust and less subjective analysis of data in a fraction of the time required by previous analytic methods. This signal converter provides this capability inexpensively and requires no modification of either the imaging or data acquisition system. PMID:20173048

A real-time stress classification system based on arousal analysis of the nervous system by an F-state machine.

PubMed

Martinez, R; Irigoyen, E; Arruti, A; Martin, J I; Muguerza, J

2017-09-01

Detection and labelling of an increment in the human stress level is a contribution focused principally on improving the quality of life of people. This work is aimed to develop a biophysical real-time stress identification and classification system, analysing two noninvasive signals, the galvanic skin response and the heart rate variability. An experimental procedure was designed and configured in order to elicit a stressful situation that is similar to those found in real cases. A total of 166 subjects participated in this experimental stage. The set of registered signals of each subject was considered as one experiment. A preliminary qualitative analysis of the signals collected was made, based on previous counselling received from neurophysiologists and psychologists. This study revealed a relationship between changes in the temporal signals and the induced stress states in each subject. To identify and classify such states, a subsequent quantitative analysis was performed in order to determine specific numerical information related to the above mentioned relationship. This second analysis gives the particular details to design the finally proposed classification algorithm, based on a Finite State Machine. The proposed system is able to classify the detected stress stages at three levels: low, medium, and high. Furthermore, the system identifies persistent stress situations or momentary alerts, depending on the subject's arousal. The system reaches an F 1 score of 0.984 in the case of high level, an F 1 score of 0.970 for medium level, and an F 1 score of 0.943 for low level. The resulting system is able to detect and classify different stress stages only based on two non invasive signals. These signals can be collected in people during their monitoring and be processed in a real-time sense, as the system can be previously preconfigured. Therefore, it could easily be implemented in a wearable prototype that could be worn by end users without feeling to be monitored. Besides, due to its low computational, the computation of the signals slopes is easy to do and its deployment in real-time applications is feasible. Copyright © 2017 Elsevier B.V. All rights reserved.

A new proof of the generalized Hamiltonian–Real calculus

PubMed Central

Gao, Hua; Mandic, Danilo P.

2016-01-01

The recently introduced generalized Hamiltonian–Real (GHR) calculus comprises, for the first time, the product and chain rules that makes it a powerful tool for quaternion-based optimization and adaptive signal processing. In this paper, we introduce novel dual relationships between the GHR calculus and multivariate real calculus, in order to provide a new, simpler proof of the GHR derivative rules. This further reinforces the theoretical foundation of the GHR calculus and provides a convenient methodology for generic extensions of real- and complex-valued learning algorithms to the quaternion domain.

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Design of signal reception and processing system of embedded ultrasonic endoscope

NASA Astrophysics Data System (ADS)

Li, Ming; Yu, Feng; Zhang, Ruiqiang; Li, Yan; Chen, Xiaodong; Yu, Daoyin

2009-11-01

Embedded Ultrasonic Endoscope, based on embedded microprocessor and embedded real-time operating system, sends a micro ultrasonic probe into coelom through the biopsy channel of the Electronic Endoscope to get the fault histology features of digestive organs by rotary scanning, and acquires the pictures of the alimentary canal mucosal surface. At the same time, ultrasonic signals are processed by signal reception and processing system, forming images of the full histology of the digestive organs. Signal Reception and Processing System is an important component of Embedded Ultrasonic Endoscope. However, the traditional design, using multi-level amplifiers and special digital processing circuits to implement signal reception and processing, is no longer satisfying the standards of high-performance, miniaturization and low power requirements that embedded system requires, and as a result of the high noise that multi-level amplifier brought, the extraction of small signal becomes hard. Therefore, this paper presents a method of signal reception and processing based on double variable gain amplifier and FPGA, increasing the flexibility and dynamic range of the Signal Reception and Processing System, improving system noise level, and reducing power consumption. Finally, we set up the embedded experiment system, using a transducer with the center frequency of 8MHz to scan membrane samples, and display the image of ultrasonic echo reflected by each layer of membrane, with a frame rate of 5Hz, verifying the correctness of the system.

Real-time plasma control based on the ISTTOK tomography diagnostica)

NASA Astrophysics Data System (ADS)

Carvalho, P. J.; Carvalho, B. B.; Neto, A.; Coelho, R.; Fernandes, H.; Sousa, J.; Varandas, C.; Chávez-Alarcón, E.; Herrera-Velázquez, J. J. E.

2008-10-01

The presently available processing power in generic processing units (GPUs) combined with state-of-the-art programmable logic devices benefits the implementation of complex, real-time driven, data processing algorithms for plasma diagnostics. A tomographic reconstruction diagnostic has been developed for the ISTTOK tokamak, based on three linear pinhole cameras each with ten lines of sight. The plasma emissivity in a poloidal cross section is computed locally on a submillisecond time scale, using a Fourier-Bessel algorithm, allowing the use of the output signals for active plasma position control. The data acquisition and reconstruction (DAR) system is based on ATCA technology and consists of one acquisition board with integrated field programmable gate array (FPGA) capabilities and a dual-core Pentium module running real-time application interface (RTAI) Linux. In this paper, the DAR real-time firmware/software implementation is presented, based on (i) front-end digital processing in the FPGA; (ii) a device driver specially developed for the board which enables streaming data acquisition to the host GPU; and (iii) a fast reconstruction algorithm running in Linux RTAI. This system behaves as a module of the central ISTTOK control and data acquisition system (FIRESIGNAL). Preliminary results of the above experimental setup are presented and a performance benchmarking against the magnetic coil diagnostic is shown.

Bulgarian National Digital Seismological Network

NASA Astrophysics Data System (ADS)

Dimitrova, L.; Solakov, D.; Nikolova, S.; Stoyanov, S.; Simeonova, S.; Zimakov, L. G.; Khaikin, L.

2011-12-01

The Bulgarian National Digital Seismological Network (BNDSN) consists of a National Data Center (NDC), 13 stations equipped with RefTek High Resolution Broadband Seismic Recorders - model DAS 130-01/3, 1 station equipped with Quanterra 680 and broadband sensors and accelerometers. Real-time data transfer from seismic stations to NDC is realized via Virtual Private Network of the Bulgarian Telecommunication Company. The communication interruptions don't cause any data loss at the NDC. The data are backed up in the field station recorder's 4Mb RAM memory and are retransmitted to the NDC immediately after the communication link is re-established. The recorders are equipped with 2 compact flash disks able to save more than 1 month long data. The data from the flash disks can be downloaded remotely using FTP. The data acquisition and processing hardware redundancy at the NDC is achieved by two clustered SUN servers and two Blade Workstations. To secure the acquisition, processing and data storage processes a three layer local network is designed at the NDC. Real-time data acquisition is performed using REFTEK's full duplex error-correction protocol RTPD. Data from the Quanterra recorder and foreign stations are fed into RTPD in real-time via SeisComP/SeedLink protocol. Using SeisComP/SeedLink software the NDC transfers real-time data to INGV-Roma, NEIC-USA, ORFEUS Data Center. Regional real-time data exchange with Romania, Macedonia, Serbia and Greece is established at the NDC also. Data processing is performed by the Seismic Network Data Processor (SNDP) software package running on the both Servers. SNDP includes subsystems: Real-time subsystem (RTS_SNDP) - for signal detection; evaluation of the signal parameters; phase identification and association; source estimation; Seismic analysis subsystem (SAS_SNDP) - for interactive data processing; Early warning subsystem (EWS_SNDP) - based on the first arrived P-phases. The signal detection process is performed by traditional STA/LTA detection algorithm. The filter parameters of the detectors are defined on the base of previously evaluated ambient noise at the seismic stations. Some extra modules for network command/control, state-of-health network monitoring and data archiving are running as well in the National Data Center. Three types of archives are produced in the NDC - two continuous - miniSEED format and RefTek PASSCAL format; and one event oriented in CSS3.0 scheme format. Modern digital equipment and broad-band seismometers installed at Bulgarian seismic stations, careful selection of the software packages for automatic and interactive data processing in the data center proved to be suitable choice for the purposes of BNDSN and NDC: ? to ensure reliable automatic localization of the seismic events and rapid notification of the governmental authorities in case of felt earthquakes on the territory of Bulgaria; ? to provide a modern basis for seismological studies in Bulgaria.

Agent-based real-time signal coordination in congested networks.

DOT National Transportation Integrated Search

2014-01-01

This study is the continuation of a previous NEXTRANS study on agent-based reinforcement : learning methods for signal coordination in congested networks. In the previous study, the : formulation of a real-time agent-based traffic signal control in o...

Real-time monitoring of drowsiness through wireless nanosensor systems

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Varadan, Vijay K.

2016-04-01

Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Generally, the bio potential signals - ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper reviews the design aspects of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person's condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the textile based nanosensors mounted on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through ZigBee communication. This system is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the fatigue level. This approach of using a wireless, real time, dry sensor on a flexible substrate mitigates obtrusiveness that is expected from a wearable system. We have previously presented the results of the aforementioned wearable systems. This paper aims to extend our work conceptually through a review of engineering and medical techniques involved in wearable systems to detect drowsiness.

High-speed real-time OFDM transmission based on FPGA

NASA Astrophysics Data System (ADS)

Xiao, Xin; Li, Fan; Yu, Jianjun

2016-02-01

In this paper, we review our recent research progresses on real-time orthogonal frequency division multiplexing (OFDM) transmission based on FPGA. We successfully demonstrated four-channel wavelength-division multiplexing (WDM) 256.51Gb/s 16-ary quadrature amplitude modulation (16QAM)-OFDM signal transmission system for short-reach optical amplifier free inter-connection with real-time reception. Four optical carriers are modulated by four different 16QAM-OFDM signals via 10G-class direct modulation lasers (DMLs). We achieved highest capacity real-time reception optical OFDM signal transmission over 2.4-km SMF with the bit-error ratio (BER) under soft-decision forward error correction (SD-FEC) limitation of 2.4×10-2. In order to achieve higher spectrum efficiency (SE), we demonstrate 4-channel high level QAM-OFDM transmission over 20-km SMF-28 with real-time reception. 58.72-Gb/s 256QAM-OFDM and 56.4-Gb/s 128QAM-OFDM signal transmission within 25-GHz grid is achieved with the BER under 2.4×10-2 and real-time reception.

Signal Processing, Analysis, & Display

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

Lager, Darrell; Azevado, Stephen

1986-06-01

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time- and frequency-domain signalsmore » including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments,commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

SIG. Signal Processing, Analysis, & Display

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

Hernandez, J.; Lager, D.; Azevedo, S.

1992-01-22

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time- and frequency-domain signalsmore » including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments,commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

Deep Learning for real-time gravitational wave detection and parameter estimation: Results with Advanced LIGO data

NASA Astrophysics Data System (ADS)

George, Daniel; Huerta, E. A.

2018-03-01

The recent Nobel-prize-winning detections of gravitational waves from merging black holes and the subsequent detection of the collision of two neutron stars in coincidence with electromagnetic observations have inaugurated a new era of multimessenger astrophysics. To enhance the scope of this emergent field of science, we pioneered the use of deep learning with convolutional neural networks, that take time-series inputs, for rapid detection and characterization of gravitational wave signals. This approach, Deep Filtering, was initially demonstrated using simulated LIGO noise. In this article, we present the extension of Deep Filtering using real data from LIGO, for both detection and parameter estimation of gravitational waves from binary black hole mergers using continuous data streams from multiple LIGO detectors. We demonstrate for the first time that machine learning can detect and estimate the true parameters of real events observed by LIGO. Our results show that Deep Filtering achieves similar sensitivities and lower errors compared to matched-filtering while being far more computationally efficient and more resilient to glitches, allowing real-time processing of weak time-series signals in non-stationary non-Gaussian noise with minimal resources, and also enables the detection of new classes of gravitational wave sources that may go unnoticed with existing detection algorithms. This unified framework for data analysis is ideally suited to enable coincident detection campaigns of gravitational waves and their multimessenger counterparts in real-time.

Real-time wideband cylindrical holographic surveillance system

DOEpatents

Sheen, David M.; McMakin, Douglas L.; Hall, Thomas E.; Severtsen, Ronald H.

1999-01-01

A wideband holographic cylindrical surveillance system including a transceiver for generating a plurality of electromagnetic waves; antenna for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; the transceiver also receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; a computer for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and a display for displaying the processed information to determine nature of the target. The computer has instructions to apply Fast Fourier Transforms and obtain a three dimensional cylindrical image.

Real-time wideband holographic surveillance system

DOEpatents

Sheen, David M.; Collins, H. Dale; Hall, Thomas E.; McMakin, Douglas L.; Gribble, R. Parks; Severtsen, Ronald H.; Prince, James M.; Reid, Larry D.

1996-01-01

A wideband holographic surveillance system including a transceiver for generating a plurality of electromagnetic waves; antenna for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; the transceiver also receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; a computer for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and a display for displaying the processed information to determine nature of the target. The computer has instructions to apply a three dimensional backward wave algorithm.

Real-time wideband holographic surveillance system

DOEpatents

Sheen, D.M.; Collins, H.D.; Hall, T.E.; McMakin, D.L.; Gribble, R.P.; Severtsen, R.H.; Prince, J.M.; Reid, L.D.

1996-09-17

A wideband holographic surveillance system including a transceiver for generating a plurality of electromagnetic waves; antenna for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; the transceiver also receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; a computer for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and a display for displaying the processed information to determine nature of the target. The computer has instructions to apply a three dimensional backward wave algorithm. 28 figs.

Real-time detection and data acquisition system for the left ventricular outline. Ph.D. Thesis - Stanford Univ.

NASA Technical Reports Server (NTRS)

Reiber, J. H. C.

1976-01-01

To automate the data acquisition procedure, a real-time contour detection and data acquisition system for the left ventricular outline was developed using video techniques. The X-ray image of the contrast-filled left ventricle is stored for subsequent processing on film (cineangiogram), video tape or disc. The cineangiogram is converted into video format using a television camera. The video signal from either the TV camera, video tape or disc is the input signal to the system. The contour detection is based on a dynamic thresholding technique. Since the left ventricular outline is a smooth continuous function, for each contour side a narrow expectation window is defined in which the next borderpoint will be detected. A computer interface was designed and built for the online acquisition of the coordinates using a PDP-12 computer. The advantage of this system over other available systems is its potential for online, real-time acquisition of the left ventricular size and shape during angiocardiography.

Real-time automatic inspection under adverse conditions

NASA Astrophysics Data System (ADS)

Carvalho, Fernando D.; Correia, Fernando C.; Freitas, Jose C. A.; Rodrigues, Fernando C.

1991-03-01

This paper presents the results of a R&D Program supported by a grant from the Ministry of Defense, devoted to the development of an inteffigent camera for surveillance in the open air. The effects of shadows, clouds and winds were problems to be solved without generating false alarm events. The system is based on a video CCD camera which generates a video CCIR signal. The signal is then processed in modular hardware which detects the changes in the scene and processes the image, in order to enhance the intruder image and path. Windows may be defined over the image in order to increase the information obtained about the intruder and a first approach to the classification of the type of intruder may be achieved. The paper describes the hardware used in the system, as well as the software, used for the installation of the camera and the software developed for the microprocessor which is responsible for the generation of the alarm signals. The paper also presents some results of surveillance tasks in the open air executed by the system with real time performance.

Seismic tremor signals from Bárðarbunga, Grímsvötn and other glacier covered volcanoes in Iceland's Vatnajökull ice cap

NASA Astrophysics Data System (ADS)

Vogfjörd, Kristin S.; Eibl, Eva; Bean, Chris; Roberts, Matthew; Ófeigsson, Benedikt; Jóhannesson, Tómas

2016-04-01

Many of Iceland's most active volcanoes, like Grímsvötn and Bárðarbunga are located under glaciers giving rise to a range of volcanic hazards having both local and cross-border effects on humans, infrastructures and aviation. Volcanic eruptions under ice can lead to explosive hydromagmatic volcanism and generate small to catastrophic subglacial floods that may take hours to days to emerge from the glacier edge. Unrest in subglacial hydrothermal systems and the draining of subglacial meltwater can also lead to flood hazards. These processes and magma-ice interactions in general, generate seismic tremor signals that are commonly observed on seismic systems during volcanic unrest and/or eruptions. The tremor signals exhibit certain characteristics in frequency content, amplitude and behavior with time, but their characteristics overlap. Ability to discriminate between the different processes in real-time or near-real time can support early eruption and flood warnings and help mitigate their detrimental effects. One of the goals set forth in the FUTUREVOLC volcano supersite project was in fact to understand and discriminate between the different types of seismic tremor recorded at subglacial volcanoes. In that pursuit, the seismic network was expanded into the Vatnajökull glacier with four permanent stations on rock and in the ice, in addition to three seismic arrays installed at the ice margin, to enable location and possible tracking of the tremor sources. To track subglacial floods with better resolution three GPS receivers were also installed on the ice, one in an ice cauldron above the Skaftárkatlar geothermal melting area and two down glacier, above the track of the expected subglacial flood. During FUTUREVOLC this infrastructure has recorded all the types of process expected: Magmatic dyke intrusion and propagation from Bárðarbunga, subaerial fissure eruption of that magma at Holuhraun, two subglacial floods, one small and one large, draining from the Skaftárkatlar area, a small flood from Grímsvötn and a small hydrothermal explosion at Kverkfjöll volcano. During the Bárðarbunga dyke propagation under the ice several sequences of tremor were observed, some particularly energetic. Examination of these signals in relation to the advancing dyke intrusion shows that they occurred when the migrating seismicity moved through the areas that later developed cauldrons on the ice surface, indicating increased melting at the bedrock-ice interface and possible magma-ice interaction. The subglacial flood from the Eastern Skaftár cauldron geothermal area, generated a strong tremor signal as well as small ice quakes recorded on near-by stations. Continuous real-time transmission of the GPS signal from inside the cauldron enabled near-real time processing and webcasting of the subsiding cauldron and thus early warning of the oncoming flood and its expected size. The signals recorded above the subglacial track also showed the glacier uplifting and advancing as the flood peak passed underneath. These observations allowed joint interpretation of the seismic single stations and array signals with the GPS signals. Results from the different processes will be presented and explained.

Linewidth-tolerant real-time 40-Gbit/s 16-QAM self-homodyne detection using a pilot carrier and ISI suppression based on electronic digital processing.

PubMed

Nakamura, Moriya; Kamio, Yukiyoshi; Miyazaki, Tetsuya

2010-01-01

We experimentally demonstrate linewidth-tolerant real-time 40-Gbit/s(10-Gsymbol/s) 16-quadrature amplitude modulation. We achieved bit-error rates of <10(-9) using an external-cavity laser diode with a linewidth of 200 kHz and <10(-7) using a distributed-feedback laser diode with a linewidth of 30 MHz, thanks to the phase-noise canceling capability provided by self-homodyne detection using a pilot carrier. Pre-equalization based on digital signal processing was employed to suppress intersymbol interference caused by the limited-frequency bandwidth of electrical components.

Real time emotion aware applications: a case study employing emotion evocative pictures and neuro-physiological sensing enhanced by Graphic Processor Units.

PubMed

Konstantinidis, Evdokimos I; Frantzidis, Christos A; Pappas, Costas; Bamidis, Panagiotis D

2012-07-01

In this paper the feasibility of adopting Graphic Processor Units towards real-time emotion aware computing is investigated for boosting the time consuming computations employed in such applications. The proposed methodology was employed in analysis of encephalographic and electrodermal data gathered when participants passively viewed emotional evocative stimuli. The GPU effectiveness when processing electroencephalographic and electrodermal recordings is demonstrated by comparing the execution time of chaos/complexity analysis through nonlinear dynamics (multi-channel correlation dimension/D2) and signal processing algorithms (computation of skin conductance level/SCL) into various popular programming environments. Apart from the beneficial role of parallel programming, the adoption of special design techniques regarding memory management may further enhance the time minimization which approximates a factor of 30 in comparison with ANSI C language (single-core sequential execution). Therefore, the use of GPU parallel capabilities offers a reliable and robust solution for real-time sensing the user's affective state. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Real-time controller for foot-drop correction by using surface electromyography sensor.

PubMed

Al Mashhadany, Yousif I; Abd Rahim, Nasrudin

2013-04-01

Foot drop is a disease caused mainly by muscle paralysis, which incapacitates the nerves generating the impulses that control feet in a heel strike. The incapacity may stem from lesions that affect the brain, the spinal cord, or peripheral nerves. The foot becomes dorsiflexed, affecting normal walking. A design and analysis of a controller for such legs is the subject of this article. Surface electromyography electrodes are connected to the skin surface of the human muscle and work on the mechanics of human muscle contraction. The design uses real surface electromyography signals for estimation of the joint angles. Various-speed flexions and extensions of the leg were analyzed. The two phases of the design began with surface electromyography of real human leg electromyography signal, which was subsequently filtered, amplified, and normalized to the maximum amplitude. Parameters extracted from the surface electromyography signal were then used to train an artificial neural network for prediction of the joint angle. The artificial neural network design included various-speed identification of the electromyography signal and estimation of the angles of the knee and ankle joints by a recognition process that depended on the parameters of the real surface electromyography signal measured through real movements. The second phase used artificial neural network estimation of the control signal, for calculation of the electromyography signal to be stimulated for the leg muscle to move the ankle joint. Satisfactory simulation (MATLAB/Simulink version 2012a) and implementation results verified the design feasibility.

A Real-Time Image Acquisition And Processing System For A RISC-Based Microcomputer

NASA Astrophysics Data System (ADS)

Luckman, Adrian J.; Allinson, Nigel M.

1989-03-01

A low cost image acquisition and processing system has been developed for the Acorn Archimedes microcomputer. Using a Reduced Instruction Set Computer (RISC) architecture, the ARM (Acorn Risc Machine) processor provides instruction speeds suitable for image processing applications. The associated improvement in data transfer rate has allowed real-time video image acquisition without the need for frame-store memory external to the microcomputer. The system is comprised of real-time video digitising hardware which interfaces directly to the Archimedes memory, and software to provide an integrated image acquisition and processing environment. The hardware can digitise a video signal at up to 640 samples per video line with programmable parameters such as sampling rate and gain. Software support includes a work environment for image capture and processing with pixel, neighbourhood and global operators. A friendly user interface is provided with the help of the Archimedes Operating System WIMP (Windows, Icons, Mouse and Pointer) Manager. Windows provide a convenient way of handling images on the screen and program control is directed mostly by pop-up menus.

Real-time speckle variance swept-source optical coherence tomography using a graphics processing unit.

PubMed

Lee, Kenneth K C; Mariampillai, Adrian; Yu, Joe X Z; Cadotte, David W; Wilson, Brian C; Standish, Beau A; Yang, Victor X D

2012-07-01

Advances in swept source laser technology continues to increase the imaging speed of swept-source optical coherence tomography (SS-OCT) systems. These fast imaging speeds are ideal for microvascular detection schemes, such as speckle variance (SV), where interframe motion can cause severe imaging artifacts and loss of vascular contrast. However, full utilization of the laser scan speed has been hindered by the computationally intensive signal processing required by SS-OCT and SV calculations. Using a commercial graphics processing unit that has been optimized for parallel data processing, we report a complete high-speed SS-OCT platform capable of real-time data acquisition, processing, display, and saving at 108,000 lines per second. Subpixel image registration of structural images was performed in real-time prior to SV calculations in order to reduce decorrelation from stationary structures induced by the bulk tissue motion. The viability of the system was successfully demonstrated in a high bulk tissue motion scenario of human fingernail root imaging where SV images (512 × 512 pixels, n = 4) were displayed at 54 frames per second.

Real-time separation of multineuron recordings with a DSP32C signal processor.

PubMed

Gädicke, R; Albus, K

1995-04-01

We have developed a hardware and software package for real-time discrimination of multiple-unit activities recorded simultaneously from multiple microelectrodes using a VME-Bus system. Compared with other systems cited in literature or commercially available, our system has the following advantages. (1) Each electrode is served by its own preprocessor (DSP32C); (2) On-line spike discrimination is performed independently for each electrode. (3) The VME-bus allows processing of data received from 16 electrodes. The digitized (62.5 kHz) spike form is itself used as the model spike; the algorithm allows for comparing and sorting complete wave forms in real time into 8 different models per electrode.

[Microinjection Monitoring System Design Applied to MRI Scanning].

PubMed

Xu, Yongfeng

2017-09-30

A microinjection monitoring system applied to the MRI scanning was introduced. The micro camera probe was used to stretch into the main magnet for real-time video injection monitoring of injection tube terminal. The programming based on LabVIEW was created to analysis and process the real-time video information. The feedback signal was used for intelligent controlling of the modified injection pump. The real-time monitoring system can make the best use of injection under the condition that the injection device was away from the sample which inside the magnetic room and unvisible. 9.4 T MRI scanning experiment showed that the system in ultra-high field can work stability and doesn't affect the MRI scans.

Cardiac Care Assistance using Self Configured Sensor Network—a Remote Patient Monitoring System

NASA Astrophysics Data System (ADS)

Sarma Dhulipala, V. R.; Kanagachidambaresan, G. R.

2014-04-01

Pervasive health care systems are used to monitor patients remotely without disturbing the normal day-to-day activities in real-time. Wearable physiological sensors required to monitor various significant ecological parameters of the patients are connected to Body Central Unit (BCU). Body Sensor Network (BSN) updates data in real-time and are designed to transmit alerts against abnormalities which enables quick response by medical units in case of an emergency. BSN helps monitoring patient without any need for attention to the subject. BSN helps in reducing the stress and strain caused by hospital environment. In this paper, mathematical models for heartbeat signal, electro cardio graph (ECG) signal and pulse rate are introduced. These signals are compared and their RMS difference-fast Fourier transforms (PRD-FFT) are processed. In the context of cardiac arrest, alert messages of these parameters and first aid for post-surgical operations has been suggested.

BPSK Demodulation Using Digital Signal Processing

NASA Technical Reports Server (NTRS)

Garcia, Thomas R.

1996-01-01

A digital communications signal is a sinusoidal waveform that is modified by a binary (digital) information signal. The sinusoidal waveform is called the carrier. The carrier may be modified in amplitude, frequency, phase, or a combination of these. In this project a binary phase shift keyed (BPSK) signal is the communication signal. In a BPSK signal the phase of the carrier is set to one of two states, 180 degrees apart, by a binary (i.e., 1 or 0) information signal. A digital signal is a sampled version of a "real world" time continuous signal. The digital signal is generated by sampling the continuous signal at discrete points in time. The rate at which the signal is sampled is called the sampling rate (f(s)). The device that performs this operation is called an analog-to-digital (A/D) converter or a digitizer. The digital signal is composed of the sequence of individual values of the sampled BPSK signal. Digital signal processing (DSP) is the modification of the digital signal by mathematical operations. A device that performs this processing is called a digital signal processor. After processing, the digital signal may then be converted back to an analog signal using a digital-to-analog (D/A) converter. The goal of this project is to develop a system that will recover the digital information from a BPSK signal using DSP techniques. The project is broken down into the following steps: (1) Development of the algorithms required to demodulate the BPSK signal; (2) Simulation of the system; and (3) Implementation a BPSK receiver using digital signal processing hardware.

APNEA list mode data acquisition and real-time event processing

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

Hogle, R.A.; Miller, P.; Bramblett, R.L.

1997-11-01

The LMSC Active Passive Neutron Examinations and Assay (APNEA) Data Logger is a VME-based data acquisition system using commercial-off-the-shelf hardware with the application-specific software. It receives TTL inputs from eighty-eight {sup 3}He detector tubes and eight timing signals. Two data sets are generated concurrently for each acquisition session: (1) List Mode recording of all detector and timing signals, timestamped to 3 microsecond resolution; (2) Event Accumulations generated in real-time by counting events into short (tens of microseconds) and long (seconds) time bins following repetitive triggers. List Mode data sets can be post-processed to: (1) determine the optimum time bins formore » TRU assay of waste drums, (2) analyze a given data set in several ways to match different assay requirements and conditions and (3) confirm assay results by examining details of the raw data. Data Logger events are processed and timestamped by an array of 15 TMS320C40 DSPs and delivered to an embedded controller (PowerPC604) for interim disk storage. Three acquisition modes, corresponding to different trigger sources are provided. A standard network interface to a remote host system (Windows NT or SunOS) provides for system control, status, and transfer of previously acquired data. 6 figs.« less

Real-time inspection by submarine images

NASA Astrophysics Data System (ADS)

Tascini, Guido; Zingaretti, Primo; Conte, Giuseppe

1996-10-01

A real-time application of computer vision concerning tracking and inspection of a submarine pipeline is described. The objective is to develop automatic procedures for supporting human operators in the real-time analysis of images acquired by means of cameras mounted on underwater remotely operated vehicles (ROV) Implementation of such procedures gives rise to a human-machine system for underwater pipeline inspection that can automatically detect and signal the presence of the pipe, of its structural or accessory elements, and of dangerous or alien objects in its neighborhood. The possibility of modifying the image acquisition rate in the simulations performed on video- recorded images is used to prove that the system performs all necessary processing with an acceptable robustness working in real-time up to a speed of about 2.5 kn, widely greater than that the actual ROVs and the security features allow.

[Design of the psychology tester based on ZigBee technology].

PubMed

Zhong, Tianping; Tang, Liming

2012-09-01

To design a psychological state tester based on ZigBee wireless technology. Through analog circuit preprocessing, the heartbeat collected by the pulse sensor will be transformed into digital signal from analog signal, and then can be processed and displayed after transported to the personal computer through the Zigbee wireless communicate units. The data will be retrieval and playback for the measurement of psychology. The experiments show that the device is able to acquire the pulse wave of the human body in real-time, at the same time, through the ZigBee wireless network, it can accomplish real-time, secure and reliable communications, and it also can be used in the research of testing the mental state of the individual. Through the application of the ZigBee communicate technology; the psychology tester can collect the pulse signal to reflect the individual's mental state in different conditions. So it will be applicable to a wide range of psychology measurement and other areas.

Real-time image dehazing using local adaptive neighborhoods and dark-channel-prior

NASA Astrophysics Data System (ADS)

Valderrama, Jesus A.; Díaz-Ramírez, Víctor H.; Kober, Vitaly; Hernandez, Enrique

2015-09-01

A real-time algorithm for single image dehazing is presented. The algorithm is based on calculation of local neighborhoods of a hazed image inside a moving window. The local neighborhoods are constructed by computing rank-order statistics. Next the dark-channel-prior approach is applied to the local neighborhoods to estimate the transmission function of the scene. By using the suggested approach there is no need for applying a refining algorithm to the estimated transmission such as the soft matting algorithm. To achieve high-rate signal processing the proposed algorithm is implemented exploiting massive parallelism on a graphics processing unit (GPU). Computer simulation results are carried out to test the performance of the proposed algorithm in terms of dehazing efficiency and speed of processing. These tests are performed using several synthetic and real images. The obtained results are analyzed and compared with those obtained with existing dehazing algorithms.

Dynamic Singularity Spectrum Distribution of Sea Clutter

NASA Astrophysics Data System (ADS)

Xiong, Gang; Yu, Wenxian; Zhang, Shuning

2015-12-01

The fractal and multifractal theory have provided new approaches for radar signal processing and target-detecting under the background of ocean. However, the related research mainly focuses on fractal dimension or multifractal spectrum (MFS) of sea clutter. In this paper, a new dynamic singularity analysis method of sea clutter using MFS distribution is developed, based on moving detrending analysis (DMA-MFSD). Theoretically, we introduce the time information by using cyclic auto-correlation of sea clutter. For transient correlation series, the instantaneous singularity spectrum based on multifractal detrending moving analysis (MF-DMA) algorithm is calculated, and the dynamic singularity spectrum distribution of sea clutter is acquired. In addition, we analyze the time-varying singularity exponent ranges and maximum position function in DMA-MFSD of sea clutter. For the real sea clutter data, we analyze the dynamic singularity spectrum distribution of real sea clutter in level III sea state, and conclude that the radar sea clutter has the non-stationary and time-varying scale characteristic and represents the time-varying singularity spectrum distribution based on the proposed DMA-MFSD method. The DMA-MFSD will also provide reference for nonlinear dynamics and multifractal signal processing.

Improved Air Combat Awareness; with AESA and Next-Generation Signal Processing

DTIC Science & Technology

2002-09-01

competence network Building techniques Software development environment Communication Computer architecture Modeling Real-time programming Radar...memory access, skewed load and store, 3.2 GB/s BW • Performance: 400 MFLOPS Runtime environment Custom runtime routines Driver routines Hardware

Time-frequency domain SNR estimation and its application in seismic data processing

NASA Astrophysics Data System (ADS)

Zhao, Yan; Liu, Yang; Li, Xuxuan; Jiang, Nansen

2014-08-01

Based on an approach estimating frequency domain signal-to-noise ratio (FSNR), we propose a method to evaluate time-frequency domain signal-to-noise ratio (TFSNR). This method adopts short-time Fourier transform (STFT) to estimate instantaneous power spectrum of signal and noise, and thus uses their ratio to compute TFSNR. Unlike FSNR describing the variation of SNR with frequency only, TFSNR depicts the variation of SNR with time and frequency, and thus better handles non-stationary seismic data. By considering TFSNR, we develop methods to improve the effects of inverse Q filtering and high frequency noise attenuation in seismic data processing. Inverse Q filtering considering TFSNR can better solve the problem of amplitude amplification of noise. The high frequency noise attenuation method considering TFSNR, different from other de-noising methods, distinguishes and suppresses noise using an explicit criterion. Examples of synthetic and real seismic data illustrate the correctness and effectiveness of the proposed methods.

Real-time synchronization of wireless sensor network by 1-PPS signal

NASA Astrophysics Data System (ADS)

Giammarini, Marco; Pieralisi, Marco; Isidori, Daniela; Concettoni, Enrico; Cristalli, Cristina; Fioravanti, Matteo

2015-05-01

The use of wireless sensor networks with different nodes is desirable in a smart environment, because the network setting up and installation on preexisting structures can be done without a fixed cabled infrastructure. The flexibility of the monitoring system is fundamental where the use of a considerable quantity of cables could compromise the normal exercise, could affect the quality of acquired signal and finally increase the cost of the materials and installation. The network is composed of several intelligent "nodes", which acquires data from different kind of sensors, and then store or transmit them to a central elaboration unit. The synchronization of data acquisition is the core of the real-time wireless sensor network (WSN). In this paper, we present a comparison between different methods proposed by literature for the real-time acquisition in a WSN and finally we present our solution based on 1-Pulse-Per-Second (1-PPS) signal generated by GPS systems. The sensor node developed is a small-embedded system based on ARM microcontroller that manages the acquisition, the timing and the post-processing of the data. The communications between the sensors and the master based on IEEE 802.15.4 protocol and managed by dedicated software. Finally, we present the preliminary results obtained on a 3 floor building simulator with the wireless sensors system developed.

DSP Implementation of the Retinex Image Enhancement Algorithm

NASA Technical Reports Server (NTRS)

Hines, Glenn; Rahman, Zia-Ur; Jobson, Daniel; Woodell, Glenn

2004-01-01

The Retinex is a general-purpose image enhancement algorithm that is used to produce good visual representations of scenes. It performs a non-linear spatial/spectral transform that synthesizes strong local contrast enhancement and color constancy. A real-time, video frame rate implementation of the Retinex is required to meet the needs of various potential users. Retinex processing contains a relatively large number of complex computations, thus to achieve real-time performance using current technologies requires specialized hardware and software. In this paper we discuss the design and development of a digital signal processor (DSP) implementation of the Retinex. The target processor is a Texas Instruments TMS320C6711 floating point DSP. NTSC video is captured using a dedicated frame-grabber card, Retinex processed, and displayed on a standard monitor. We discuss the optimizations used to achieve real-time performance of the Retinex and also describe our future plans on using alternative architectures.

Real-time speckle reduction in optical coherence tomography using the dual window method

PubMed Central

Zhao, Yang; Chu, Kengyeh K.; Eldridge, Will J.; Jelly, Evan T.; Crose, Michael; Wax, Adam

2018-01-01

Speckle is an intrinsic noise of interferometric signals which reduces contrast and degrades the quality of optical coherence tomography (OCT) images. Here, we present a frequency compounding speckle reduction technique using the dual window (DW) method. Using the DW method, speckle noise is reduced without the need to acquire multiple frames. A ~25% improvement in the contrast-to-noise ratio (CNR) was achieved using the DW speckle reduction method with only minimal loss (~17%) in axial resolution. We also demonstrate that real-time speckle reduction can be achieved at a B-scan rate of ~21 frames per second using a graphic processing unit (GPU). The DW speckle reduction technique can work on any existing OCT instrument without further system modification or extra components. This makes it applicable both in real-time imaging systems and during post-processing. PMID:29552398

On protecting the planet against cosmic attack: Ultrafast real-time estimate of the asteroid's radial velocity

NASA Astrophysics Data System (ADS)

Zakharchenko, V. D.; Kovalenko, I. G.

2014-05-01

A new method for the line-of-sight velocity estimation of a high-speed near-Earth object (asteroid, meteorite) is suggested. The method is based on the use of fractional, one-half order derivative of a Doppler signal. The algorithm suggested is much simpler and more economical than the classical one, and it appears preferable for use in orbital weapon systems of threat response. Application of fractional differentiation to quick evaluation of mean frequency location of the reflected Doppler signal is justified. The method allows an assessment of the mean frequency in the time domain without spectral analysis. An algorithm structure for the real-time estimation is presented. The velocity resolution estimates are made for typical asteroids in the X-band. It is shown that the wait time can be shortened by orders of magnitude compared with similar value in the case of a standard spectral processing.

Gauss-Seidel Iterative Method as a Real-Time Pile-Up Solver of Scintillation Pulses

NASA Astrophysics Data System (ADS)

Novak, Roman; Vencelj, Matja¿

2009-12-01

The pile-up rejection in nuclear spectroscopy has been confronted recently by several pile-up correction schemes that compensate for distortions of the signal and subsequent energy spectra artifacts as the counting rate increases. We study here a real-time capability of the event-by-event correction method, which at the core translates to solving many sets of linear equations. Tight time limits and constrained front-end electronics resources make well-known direct solvers inappropriate. We propose a novel approach based on the Gauss-Seidel iterative method, which turns out to be a stable and cost-efficient solution to improve spectroscopic resolution in the front-end electronics. We show the method convergence properties for a class of matrices that emerge in calorimetric processing of scintillation detector signals and demonstrate the ability of the method to support the relevant resolutions. The sole iteration-based error component can be brought below the sliding window induced errors in a reasonable number of iteration steps, thus allowing real-time operation. An area-efficient hardware implementation is proposed that fully utilizes the method's inherent parallelism.

Television animation store: Recording pictures on a parallel transfer magnetic disc

NASA Astrophysics Data System (ADS)

Durey, A. J.

1984-12-01

The recording and replaying of digital video signals using a computer-type magnetic disc-drive as part of an electronic rostrum camera animation system is described. The system was developed to enable picture sequences to be generated directly as television signals, instead of using cine film. The characteristics of the disc-drive are described together with data processing, error protection and signal synchronization systems, which enable digital television YUV component signals, sampled at 12 MHz, 4 MHz and 4 MHz respectively, to be recorded and replayed in real time.

SU-F-J-54: Towards Real-Time Volumetric Imaging Using the Treatment Beam and KV Beam

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

Chen, M; Rozario, T; Liu, A

Purpose: Existing real-time imaging uses dual (orthogonal) kV beam fluoroscopies and may result in significant amount of extra radiation to patients, especially for prolonged treatment cases. In addition, kV projections only provide 2D information, which is insufficient for in vivo dose reconstruction. We propose real-time volumetric imaging using prior knowledge of pre-treatment 4D images and real-time 2D transit data of treatment beam and kV beam. Methods: The pre-treatment multi-snapshot volumetric images are used to simulate 2D projections of both the treatment beam and kV beam, respectively, for each treatment field defined by the control point. During radiation delivery, the transitmore » signals acquired by the electronic portal image device (EPID) are processed for every projection and compared with pre-calculation by cross-correlation for phase matching and thus 3D snapshot identification or real-time volumetric imaging. The data processing involves taking logarithmic ratios of EPID signals with respect to the air scan to reduce modeling uncertainties in head scatter fluence and EPID response. Simulated 2D projections are also used to pre-calculate confidence levels in phase matching. Treatment beam projections that have a low confidence level either in pre-calculation or real-time acquisition will trigger kV beams so that complementary information can be exploited. In case both the treatment beam and kV beam return low confidence in phase matching, a predicted phase based on linear regression will be generated. Results: Simulation studies indicated treatment beams provide sufficient confidence in phase matching for most cases. At times of low confidence from treatment beams, kV imaging provides sufficient confidence in phase matching due to its complementary configuration. Conclusion: The proposed real-time volumetric imaging utilizes the treatment beam and triggers kV beams for complementary information when the treatment beam along does not provide sufficient confidence for phase matching. This strategy minimizes the use of extra radiation to patients. This project is partially supported by a Varian MRA grant.« less

Signal processing for order 10 PM accuracy displacement metrology in real-world scientific applications

NASA Astrophysics Data System (ADS)

Halverson, Peter G.; Loya, Frank M.

2017-11-01

Projects such as the Space Interferometry Mission (SIM) [1] and Terrestrial Planet Finder (TPF) [2] rely heavily on sub-nanometer accuracy metrology systems to define their optical paths and geometries. The James Web Space Telescope (JWST) is using this metrology in a cryogenic dilatometer for characterizing material properties (thermal expansion, creep) of optical materials. For all these projects, a key issue has been the reliability and stability of the electronics that convert displacement metrology signals into real-time distance determinations. A particular concern is the behavior of the electronics in situations where laser heterodyne signals are weak or noisy and subject to abrupt Doppler shifts due to vibrations or the slewing of motorized optics. A second concern is the long-term (hours to days) stability of the distance measurements under conditions of drifting laser power and ambient temperature. This paper describes heterodyne displacement metrology gauge signal processing methods that achieve satisfactory robustness against low signal strength and spurious signals, and good long-term stability. We have a proven displacement-measuring approach that is useful not only to space-optical projects at JPL, but also to the wider field of distance measurements.

Real-time data compression of broadcast video signals

NASA Technical Reports Server (NTRS)

Shalkauser, Mary Jo W. (Inventor); Whyte, Wayne A., Jr. (Inventor); Barnes, Scott P. (Inventor)

1991-01-01

A non-adaptive predictor, a nonuniform quantizer, and a multi-level Huffman coder are incorporated into a differential pulse code modulation system for coding and decoding broadcast video signals in real time.

The Vector, Signal, and Image Processing Library (VSIPL): an Open Standard for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Kepner, J. V.; Janka, R. S.; Lebak, J.; Richards, M. A.

1999-12-01

The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float, complex, ...) and layouts (vectors, matrices and tensors) and is ideal for astronomical data processing. The VSIPL API is intended to serve as an open, vendor-neutral, industry standard interface. The object-based VSIPL API abstracts the memory architecture of the underlying machine by using the concept of memory blocks and views. Early experiments with VSIPL code conversions have been carried out by the High Performance Computing Program team at the UCSD. Commercially, several major vendors of signal processors are actively developing implementations. VSIPL has also been explicitly required as part of a recent Rome Labs teraflop procurement. This poster presents the VSIPL API, its functionality and the status of various implementations.

A Real-Time Cardiac Arrhythmia Classification System with Wearable Sensor Networks

PubMed Central

Hu, Sheng; Wei, Hongxing; Chen, Youdong; Tan, Jindong

2012-01-01

Long term continuous monitoring of electrocardiogram (ECG) in a free living environment provides valuable information for prevention on the heart attack and other high risk diseases. This paper presents the design of a real-time wearable ECG monitoring system with associated cardiac arrhythmia classification algorithms. One of the striking advantages is that ECG analog front-end and on-node digital processing are designed to remove most of the noise and bias. In addition, the wearable sensor node is able to monitor the patient's ECG and motion signal in an unobstructive way. To realize the real-time medical analysis, the ECG is digitalized and transmitted to a smart phone via Bluetooth. On the smart phone, the ECG waveform is visualized and a novel layered hidden Markov model is seamlessly integrated to classify multiple cardiac arrhythmias in real time. Experimental results demonstrate that the clean and reliable ECG waveform can be captured in multiple stressed conditions and the real-time classification on cardiac arrhythmia is competent to other workbenches. PMID:23112746

Real-Time Processing of ASL Signs: Delayed First Language Acquisition Affects Organization of the Mental Lexicon

ERIC Educational Resources Information Center

Lieberman, Amy M.; Borovsky, Arielle; Hatrak, Marla; Mayberry, Rachel I.

2015-01-01

Sign language comprehension requires visual attention to the linguistic signal and visual attention to referents in the surrounding world, whereas these processes are divided between the auditory and visual modalities for spoken language comprehension. Additionally, the age-onset of first language acquisition and the quality and quantity of…

Sampling Operations on Big Data

DTIC Science & Technology

2015-11-29

gories. These include edge sampling methods where edges are selected by a predetermined criteria; snowball sampling methods where algorithms start... Sampling Operations on Big Data Vijay Gadepally, Taylor Herr, Luke Johnson, Lauren Milechin, Maja Milosavljevic, Benjamin A. Miller Lincoln...process and disseminate information for discovery and exploration under real-time constraints. Common signal processing operations such as sampling and

Real-Time Speech/Music Classification With a Hierarchical Oblique Decision Tree

DTIC Science & Technology

2008-04-01

REAL-TIME SPEECH/ MUSIC CLASSIFICATION WITH A HIERARCHICAL OBLIQUE DECISION TREE Jun Wang, Qiong Wu, Haojiang Deng, Qin Yan Institute of Acoustics...time speech/ music classification with a hierarchical oblique decision tree. A set of discrimination features in frequency domain are selected...handle signals without discrimination and can not work properly in the existence of multimedia signals. This paper proposes a real-time speech/ music

Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification.

PubMed

Lee, Dongha; Jang, Changwon; Park, Hae-Jeong

2015-03-01

Signal drift in functional magnetic resonance imaging (fMRI) is an unavoidable artifact that limits classification performance in multi-voxel pattern analysis of fMRI. As conventional methods to reduce signal drift, global demeaning or proportional scaling disregards regional variations of drift, whereas voxel-wise univariate detrending is too sensitive to noisy fluctuations. To overcome these drawbacks, we propose a multivariate real-time detrending method for multiclass classification that involves spatial demeaning at each scan and the recursive detrending of drifts in the classifier outputs driven by a multiclass linear support vector machine. Experiments using binary and multiclass data showed that the linear trend estimation of the classifier output drift for each class (a weighted sum of drifts in the class-specific voxels) was more robust against voxel-wise artifacts that lead to inconsistent spatial patterns and the effect of online processing than voxel-wise detrending. The classification performance of the proposed method was significantly better, especially for multiclass data, than that of voxel-wise linear detrending, global demeaning, and classifier output detrending without demeaning. We concluded that the multivariate approach using classifier output detrending of fMRI signals with spatial demeaning preserves spatial patterns, is less sensitive than conventional methods to sample size, and increases classification performance, which is a useful feature for real-time fMRI classification. Copyright © 2014 Elsevier Inc. All rights reserved.

Conversion-Integration of MSFC Nonlinear Signal Diagnostic Analysis Algorithms for Realtime Execution of MSFC's MPP Prototype System

NASA Technical Reports Server (NTRS)

Jong, Jen-Yi

1996-01-01

NASA's advanced propulsion system Small Scale Magnetic Disturbances/Advanced Technology Development (SSME/ATD) has been undergoing extensive flight certification and developmental testing, which involves large numbers of health monitoring measurements. To enhance engine safety and reliability, detailed analysis and evaluation of the measurement signals are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce the risk of catastrophic system failures and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. During the development of SSME, ASRI participated in the research and development of several advanced non- linear signal diagnostic methods for health monitoring and failure prediction in turbomachinery components. However, due to the intensive computational requirement associated with such advanced analysis tasks, current SSME dynamic data analysis and diagnostic evaluation is performed off-line following flight or ground test with a typical diagnostic turnaround time of one to two days. The objective of MSFC's MPP Prototype System is to eliminate such 'diagnostic lag time' by achieving signal processing and analysis in real-time. Such an on-line diagnostic system can provide sufficient lead time to initiate corrective action and also to enable efficient scheduling of inspection, maintenance and repair activities. The major objective of this project was to convert and implement a number of advanced nonlinear diagnostic DSP algorithms in a format consistent with that required for integration into the Vanderbilt Multigraph Architecture (MGA) Model Based Programming environment. This effort will allow the real-time execution of these algorithms using the MSFC MPP Prototype System. ASRI has completed the software conversion and integration of a sequence of nonlinear signal analysis techniques specified in the SOW for real-time execution on MSFC's MPP Prototype. This report documents and summarizes the results of the contract tasks; provides the complete computer source code; including all FORTRAN/C Utilities; and all other utilities/supporting software libraries that are required for operation.

Time-Frequency Distribution Analyses of Ku-Band Radar Doppler Echo Signals

NASA Astrophysics Data System (ADS)

Bujaković, Dimitrije; Andrić, Milenko; Bondžulić, Boban; Mitrović, Srđan; Simić, Slobodan

2015-03-01

Real radar echo signals of a pedestrian, vehicle and group of helicopters are analyzed in order to maximize signal energy around central Doppler frequency in time-frequency plane. An optimization, preserving this concentration, is suggested based on three well-known concentration measures. Various window functions and time-frequency distributions were optimization inputs. Conducted experiments on an analytic and three real signals have shown that energy concentration significantly depends on used time-frequency distribution and window function, for all three used criteria.

Signal processing for ION mobility spectrometers

NASA Technical Reports Server (NTRS)

Taylor, S.; Hinton, M.; Turner, R.

1995-01-01

Signal processing techniques for systems based upon Ion Mobility Spectrometry will be discussed in the light of 10 years of experience in the design of real-time IMS. Among the topics to be covered are compensation techniques for variations in the number density of the gas - the use of an internal standard (a reference peak) or pressure and temperature sensors. Sources of noise and methods for noise reduction will be discussed together with resolution limitations and the ability of deconvolution techniques to improve resolving power. The use of neural networks (either by themselves or as a component part of a processing system) will be reviewed.

Plasma plume oscillations monitoring during laser welding of stainless steel by discrete wavelet transform application.

PubMed

Sibillano, Teresa; Ancona, Antonio; Rizzi, Domenico; Lupo, Valentina; Tricarico, Luigi; Lugarà, Pietro Mario

2010-01-01

The plasma optical radiation emitted during CO2 laser welding of stainless steel samples has been detected with a Si-PIN photodiode and analyzed under different process conditions. The discrete wavelet transform (DWT) has been used to decompose the optical signal into various discrete series of sequences over different frequency bands. The results show that changes of the process settings may yield different signal features in the range of frequencies between 200 Hz and 30 kHz. Potential applications of this method to monitor in real time the laser welding processes are also discussed.

Frequency accurate coherent electro-optic dual-comb spectroscopy in real-time.

PubMed

Martín-Mateos, Pedro; Jerez, Borja; Largo-Izquierdo, Pedro; Acedo, Pablo

2018-04-16

Electro-optic dual-comb spectrometers have proved to be a promising technology for sensitive, high-resolution and rapid spectral measurements. Electro-optic combs possess very attractive features like simplicity, reliability, bright optical teeth, and typically moderate but quickly tunable optical spans. Furthermore, in a dual-comb arrangement, narrowband electro-optic combs are generated with a level of mutual coherence that is sufficiently high to enable optical multiheterodyning without inter-comb stabilization or signal processing systems. However, this valuable tool still presents several limitations; for instance, on most systems, absolute frequency accuracy and long-term stability cannot be guaranteed; likewise, interferometer-induced phase noise restricts coherence time and limits the attainable signal-to-noise ratio. In this paper, we address these drawbacks and demonstrate a cost-efficient absolute electro-optic dual-comb instrument based on a frequency stabilization mechanism and a novel adaptive interferogram acquisition approach devised for electro-optic dual-combs capable of operating in real-time. The spectrometer, completely built from commercial components, provides sub-ppm frequency uncertainties and enables a signal-to-noise ratio of 10000 (intensity noise) in 30 seconds of integration time.

Distributed processing for features improvement in real-time portable medical devices.

PubMed

Mercado, Erwin John Saavedra

2008-01-01

Portable biomedical devices are being developed and incorporated in daily life. Nevertheless, their standalone capacity is diminished due to the lack of processing power required to face such duties as for example, signal artifacts robustness in EKG monitor devices. The following paper presents a multiprocessor architecture made from simple microcontrollers to provide an increase in processing performance, power consumption efficiency and lower cost.

On the extraction of directional sea-wave spectra from synthetic- aperture radar-signal arrays without matched filtering.

USGS Publications Warehouse

Wildey, R.L.

1980-01-01

An economical method of digitally extracting sea-wave spectra from synthetic-aperture radar-signal records, which can be performed routinely in real or near-real time with the reception of telemetry from Seasat satellites, would be of value to a variety of scientific disciplines. This paper explores techniques for such data extraction and concludes that the mere fact that the desired result is devoid of phase information does not, of itself, lead to a simplification in data processing because of the nature of the modulation performed on the radar pulse by the backscattering surface. -from Author

Bi-Fi: an embedded sensor/system architecture for REMOTE biological monitoring.

PubMed

Farshchi, Shahin; Pesterev, Aleksey; Nuyujukian, Paul H; Mody, Istvan; Judy, Jack W

2007-11-01

Wireless-enabled processor modules intended for communicating low-frequency phenomena (i.e., temperature, humidity, and ambient light) have been enabled to acquire and transmit multiple biological signals in real time, which has been achieved by using computationally efficient data acquisition, filtering, and compression algorithms, and interfacing the modules with biological interface hardware. The sensor modules can acquire and transmit raw biological signals at a rate of 32 kb/s, which is near the hardware limit of the modules. Furthermore, onboard signal processing enables one channel, sampled at a rate of 4000 samples/s at 12-bit resolution, to be compressed via adaptive differential-pulse-code modulation (ADPCM) and transmitted in real time. In addition, the sensors can be configured to filter and transmit individual time-referenced "spike" waveforms, or to transmit the spike height and width for alleviating network traffic and increasing battery life. The system is capable of acquiring eight channels of analog signals as well as data via an asynchronous serial connection. A back-end server archives the biological data received via networked gateway sensors, and hosts them to a client application that enables users to browse recorded data. The system also acquires, filters, and transmits oxygen saturation and pulse rate via a commercial-off-the-shelf interface board. The system architecture can be configured for performing real-time nonobtrusive biological monitoring of humans or rodents. This paper demonstrates that low-power, computational, and bandwidth-constrained wireless-enabled platforms can indeed be leveraged for wireless biosignal monitoring.

Real-time wideband cylindrical holographic surveillance system

DOEpatents

Sheen, D.M.; McMakin, D.L.; Hall, T.E.; Severtsen, R.H.

1999-01-12

A wideband holographic cylindrical surveillance system is disclosed including a transceiver for generating a plurality of electromagnetic waves; antenna for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; the transceiver also receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; a computer for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and a display for displaying the processed information to determine nature of the target. The computer has instructions to apply Fast Fourier Transforms and obtain a three dimensional cylindrical image. 13 figs.

Correlator data analysis for the array feed compensation system

NASA Technical Reports Server (NTRS)

Iijima, B.; Fort, D.; Vilnrotter, V.

1994-01-01

The real-time array feed compensation system is currently being evaluated at DSS 13. This system recovers signal-to-noise ratio (SNR) loss due to mechanical antenna deformations by using an array of seven Ka-band (33.7-GHz) horns to collect the defocused signal fields. The received signals are downconverted and digitized, in-phase and quadrature samples are generated, and combining weights are applied before the samples are recombined. It is shown that when optimum combining weights are employed, the SNR of the combined signal approaches the sum of the channel SNR's. The optimum combining weights are estimated directly from the signals in each channel by the Real-Time Block 2 (RTB2) correlator; since it was designed for very-long-baseline interferometer (VLBI) applications, it can process broadband signals as well as tones to extract the required weight estimates. The estimation algorithms for the optimum combining weights are described for tones and broadband sources. Data recorded in correlator output files can also be used off-line to estimate combiner performance by estimating the SNR in each channel, which was done for data taken during a Jupiter track at DSS 13.

Optical fiber sensor technique for strain measurement

DOEpatents

Butler, Michael A.; Ginley, David S.

1989-01-01

Laser light from a common source is split and conveyed through two similar optical fibers and emitted at their respective ends to form an interference pattern, one of the optical fibers having a portion thereof subjected to a strain. Changes in the strain cause changes in the optical path length of the strain fiber, and generate corresponding changes in the interference pattern. The interference pattern is received and transduced into signals representative of fringe shifts corresponding to changes in the strain experienced by the strained one of the optical fibers. These signals are then processed to evaluate strain as a function of time, typical examples of the application of the apparatus including electrodeposition of a metallic film on a conductive surface provided on the outside of the optical fiber being strained, so that strains generated in the optical fiber during the course of the electrodeposition are measurable as a function of time. In one aspect of the invention, signals relating to the fringe shift are stored for subsequent processing and analysis, whereas in another aspect of the invention the signals are processed for real-time display of the strain changes under study.

Seismpol_ a visual-basic computer program for interactive and automatic earthquake waveform analysis

NASA Astrophysics Data System (ADS)

Patanè, Domenico; Ferrari, Ferruccio

1997-11-01

A Microsoft Visual-Basic computer program for waveform analysis of seismic signals is presented. The program combines interactive and automatic processing of digital signals using data recorded by three-component seismic stations. The analysis procedure can be used in either an interactive earthquake analysis or an automatic on-line processing of seismic recordings. The algorithm works in the time domain using the Covariance Matrix Decomposition method (CMD), so that polarization characteristics may be computed continuously in real time and seismic phases can be identified and discriminated. Visual inspection of the particle motion in hortogonal planes of projection (hodograms) reduces the danger of misinterpretation derived from the application of the polarization filter. The choice of time window and frequency intervals improves the quality of the extracted polarization information. In fact, the program uses a band-pass Butterworth filter to process the signals in the frequency domain by analysis of a selected signal window into a series of narrow frequency bands. Significant results supported by well defined polarizations and source azimuth estimates for P and S phases are also obtained for short-period seismic events (local microearthquakes).

Blind estimation of reverberation time

NASA Astrophysics Data System (ADS)

Ratnam, Rama; Jones, Douglas L.; Wheeler, Bruce C.; O'Brien, William D.; Lansing, Charissa R.; Feng, Albert S.

2003-11-01

The reverberation time (RT) is an important parameter for characterizing the quality of an auditory space. Sounds in reverberant environments are subject to coloration. This affects speech intelligibility and sound localization. Many state-of-the-art audio signal processing algorithms, for example in hearing-aids and telephony, are expected to have the ability to characterize the listening environment, and turn on an appropriate processing strategy accordingly. Thus, a method for characterization of room RT based on passively received microphone signals represents an important enabling technology. Current RT estimators, such as Schroeder's method, depend on a controlled sound source, and thus cannot produce an online, blind RT estimate. Here, a method for estimating RT without prior knowledge of sound sources or room geometry is presented. The diffusive tail of reverberation was modeled as an exponentially damped Gaussian white noise process. The time-constant of the decay, which provided a measure of the RT, was estimated using a maximum-likelihood procedure. The estimates were obtained continuously, and an order-statistics filter was used to extract the most likely RT from the accumulated estimates. The procedure was illustrated for connected speech. Results obtained for simulated and real room data are in good agreement with the real RT values.

Online estimation of room reverberation time

NASA Astrophysics Data System (ADS)

Ratnam, Rama; Jones, Douglas L.; Wheeler, Bruce C.; Feng, Albert S.

2003-04-01

The reverberation time (RT) is an important parameter for characterizing the quality of an auditory space. Sounds in reverberant environments are subject to coloration. This affects speech intelligibility and sound localization. State-of-the-art signal processing algorithms for hearing aids are expected to have the ability to evaluate the characteristics of the listening environment and turn on an appropriate processing strategy accordingly. Thus, a method for the characterization of room RT based on passively received microphone signals represents an important enabling technology. Current RT estimators, such as Schroeder's method or regression, depend on a controlled sound source, and thus cannot produce an online, blind RT estimate. Here, we describe a method for estimating RT without prior knowledge of sound sources or room geometry. The diffusive tail of reverberation was modeled as an exponentially damped Gaussian white noise process. The time constant of the decay, which provided a measure of the RT, was estimated using a maximum-likelihood procedure. The estimates were obtained continuously, and an order-statistics filter was used to extract the most likely RT from the accumulated estimates. The procedure was illustrated for connected speech. Results obtained for simulated and real room data are in good agreement with the real RT values.

Parallel Processing Systems for Passive Ranging During Helicopter Flight

NASA Technical Reports Server (NTRS)

Sridhar, Bavavar; Suorsa, Raymond E.; Showman, Robert D. (Technical Monitor)

1994-01-01

The complexity of rotorcraft missions involving operations close to the ground result in high pilot workload. In order to allow a pilot time to perform mission-oriented tasks, sensor-aiding and automation of some of the guidance and control functions are highly desirable. Images from an electro-optical sensor provide a covert way of detecting objects in the flight path of a low-flying helicopter. Passive ranging consists of processing a sequence of images using techniques based on optical low computation and recursive estimation. The passive ranging algorithm has to extract obstacle information from imagery at rates varying from five to thirty or more frames per second depending on the helicopter speed. We have implemented and tested the passive ranging algorithm off-line using helicopter-collected images. However, the real-time data and computation requirements of the algorithm are beyond the capability of any off-the-shelf microprocessor or digital signal processor. This paper describes the computational requirements of the algorithm and uses parallel processing technology to meet these requirements. Various issues in the selection of a parallel processing architecture are discussed and four different computer architectures are evaluated regarding their suitability to process the algorithm in real-time. Based on this evaluation, we conclude that real-time passive ranging is a realistic goal and can be achieved with a short time.

Development of High Data Rate Acoustic Multiple-Input/Multiple-Output Modems

DTIC Science & Technology

2015-09-30

communication capabilities of underwater platforms and facilitate real-time adaptive operations in the ocean. OBJECTIVES The ...signaling at the transmitter and low-complexity time reversal processing at the receiver. APPROACH Underwater acoustic (UWA) communication is useful...digital communications in shallow water environments. The advancement has direct impacts on defense appliations since underwater acoustic modems

Development of Parallel Architectures for Sensor Array Processing. Volume 1

DTIC Science & Technology

1993-08-01

required for the DOA estimation [ 1-7]. The Multiple Signal Classification ( MUSIC ) [ 1] and the Estimation of Signal Parameters by Rotational...manifold and the estimated subspace. Although MUSIC is a high resolution algorithm, it has several drawbacks including the fact that complete knowledge of...thoroughly, MUSIC algorithm was selected to develop special purpose hardware for real time computation. Summary of the MUSIC algorithm is as follows

Classification of Respiratory Sounds by Using An Artificial Neural Network

DTIC Science & Technology

2001-10-28

CLASSIFICATION OF RESPIRATORY SOUNDS BY USING AN ARTIFICIAL NEURAL NETWORK M.C. Sezgin, Z. Dokur, T. Ölmez, M. Korürek Department of Electronics and...successfully classified by the GAL network. Keywords-Respiratory Sounds, Classification of Biomedical Signals, Artificial Neural Network . I. INTRODUCTION...process, feature extraction, and classification by the artificial neural network . At first, the RS signal obtained from a real-time measurement equipment is

Real-Time Single Molecule Visualization of SH2 Domain Membrane Recruitment in Growth Factor Stimulated Cells.

PubMed

Oh, Dongmyung

2017-01-01

In the last decade, single molecule tracking (SMT) techniques have emerged as a versatile tool for molecular cell biology research. This approach allows researchers to monitor the real-time behavior of individual molecules in living cells with nanometer and millisecond resolution. As a result, it is possible to visualize biological processes as they occur at a molecular level in real time. Here we describe a method for the real-time visualization of SH2 domain membrane recruitment from the cytoplasm to epidermal growth factor (EGF) induced phosphotyrosine sites on the EGF receptor. Further, we describe methods that utilize SMT data to define SH2 domain membrane dynamics parameters such as binding (τ), dissociation (k d ), and diffusion (D) rates. Together these methods may allow us to gain greater understanding of signal transduction dynamics and the molecular basis of disease-related aberrant pathways.

Design of real-time voice over internet protocol system under bandwidth network

NASA Astrophysics Data System (ADS)

Zhang, Li; Gong, Lina

2017-04-01

With the increasing bandwidth of the network and network convergence accelerating, VoIP means of communication across the network is becoming increasingly popular phenomenon. The real-time identification and analysis for VOIP flow over backbone network become the urgent needs and research hotspot of network operations management. Based on this, the paper proposes a VoIP business management system over backbone network. The system first filters VoIP data stream over backbone network and further resolves the call signaling information and media voice. The system can also be able to design appropriate rules to complete real-time reduction and presentation of specific categories of calls. Experimental results show that the system can parse and process real-time backbone of the VoIP call, and the results are presented accurately in the management interface, VoIP-based network traffic management and maintenance provide the necessary technical support.

Correlation processing for correction of phase distortions in subaperture imaging.

PubMed

Tavh, B; Karaman, M

1999-01-01

Ultrasonic subaperture imaging combines synthetic aperture and phased array approaches and permits low-cost systems with improved image quality. In subaperture processing, a large array is synthesized using echo signals collected from a number of receive subapertures by multiple firings of a phased transmit subaperture. Tissue inhomogeneities and displacements in subaperture imaging may cause significant phase distortions on received echo signals. Correlation processing on reference echo signals can be used for correction of the phase distortions, for which the accuracy and robustness are critically limited by the signal correlation. In this study, we explore correlation processing techniques for adaptive subaperture imaging with phase correction for motion and tissue inhomogeneities. The proposed techniques use new subaperture data acquisition schemes to produce reference signal sets with improved signal correlation. The experimental test results were obtained using raw radio frequency (RF) data acquired from two different phantoms with 3.5 MHz, 128-element transducer array. The results show that phase distortions can effectively be compensated by the proposed techniques in real-time adaptive subaperture imaging.

A PC-based system for predicting movement from deep brain signals in Parkinson's disease.

PubMed

Loukas, Constantinos; Brown, Peter

2012-07-01

There is much current interest in deep brain stimulation (DBS) of the subthalamic nucleus (STN) for the treatment of Parkinson's disease (PD). This type of surgery has enabled unprecedented access to deep brain signals in the awake human. In this paper we present an easy-to-use computer based system for recording, displaying, archiving, and processing electrophysiological signals from the STN. The system was developed for predicting self-paced hand-movements in real-time via the online processing of the electrophysiological activity of the STN. It is hoped that such a computerised system might have clinical and experimental applications. For example, those sites within the STN most relevant to the processing of voluntary movement could be identified through the predictive value of their activities with respect to the timing of future movement. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Method for Real-Time Model Based Structural Anomaly Detection

NASA Technical Reports Server (NTRS)

Urnes, James M., Sr. (Inventor); Smith, Timothy A. (Inventor); Reichenbach, Eric Y. (Inventor)

2015-01-01

A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

Real Time Calibration Method for Signal Conditioning Amplifiers

NASA Technical Reports Server (NTRS)

Medelius, Pedro J. (Inventor); Mata, Carlos T. (Inventor); Eckhoff, Anthony (Inventor); Perotti, Jose (Inventor); Lucena, Angel (Inventor)

2004-01-01

A signal conditioning amplifier receives an input signal from an input such as a transducer. The signal is amplified and processed through an analog to digital converter and sent to a processor. The processor estimates the input signal provided by the transducer to the amplifier via a multiplexer. The estimated input signal is provided as a calibration voltage to the amplifier immediately following the receipt of the amplified input signal. The calibration voltage is amplified by the amplifier and provided to the processor as an amplified calibration voltage. The amplified calibration voltage is compared to the amplified input signal, and if a significant error exists, the gain and/or offset of the amplifier may be adjusted as necessary.

Real-Time Spatio-Temporal Twice Whitening for MIMO Energy Detector

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

Humble, Travis S; Mitra, Pramita; Barhen, Jacob

2010-01-01

While many techniques exist for local spectrum sensing of a primary user, each represents a computationally demanding task to secondary user receivers. In software-defined radio, computational complexity lengthens the time for a cognitive radio to recognize changes in the transmission environment. This complexity is even more significant for spatially multiplexed receivers, e.g., in SIMO and MIMO, where the spatio-temporal data sets grow in size with the number of antennae. Limits on power and space for the processor hardware further constrain SDR performance. In this report, we discuss improvements in spatio-temporal twice whitening (STTW) for real-time local spectrum sensing by demonstratingmore » a form of STTW well suited for MIMO environments. We implement STTW on the Coherent Logix hx3100 processor, a multicore processor intended for low-power, high-throughput software-defined signal processing. These results demonstrate how coupling the novel capabilities of emerging multicore processors with algorithmic advances can enable real-time, software-defined processing of large spatio-temporal data sets.« less

Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation †

PubMed Central

Ibrahim, Ali; Gastaldo, Paolo; Chible, Hussein; Valle, Maurizio

2017-01-01

Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted. PMID:28287448

Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation.

PubMed

Ibrahim, Ali; Gastaldo, Paolo; Chible, Hussein; Valle, Maurizio

2017-03-10

Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted.

Energy shadowing correction of ultrasonic pulse-echo records by digital signal processing

NASA Technical Reports Server (NTRS)

Kishoni, D.; Heyman, J. S.

1986-01-01

Attention is given to a numerical algorithm that, via signal processing, enables the dynamic correction of the shadowing effect of reflections on ultrasonic displays. The algorithm was applied to experimental data from graphite-epoxy composite material immersed in a water bath. It is concluded that images of material defects with the shadowing corrections allow for a more quantitative interpretation of the material state. It is noted that the proposed algorithm is fast and simple enough to be adopted for real time applications in industry.

Spectrometer gun

DOEpatents

Waechter, David A.; Wolf, Michael A.; Umbarger, C. John

1985-01-01

A hand-holdable, battery-operated, microprocessor-based spectrometer gun includes a low-power matrix display and sufficient memory to permit both real-time observation and extended analysis of detected radiation pulses. Universality of the incorporated signal processing circuitry permits operation with various detectors having differing pulse detection and sensitivity parameters.

Cortical control of intraspinal microstimulation: Toward a new approach for restoration of function after spinal cord injury.

PubMed

Shahdoost, Shahab; Frost, Shawn; Dunham, Caleb; DeJong, Stacey; Barbay, Scott; Nudo, Randolph; Mohseni, Pedram

2015-08-01

Approximately 6 million people in the United States are currently living with paralysis in which 23% of the cases are related to spinal cord injury (SCI). Miniaturized closed-loop neural interfaces have the potential for restoring function and mobility lost to debilitating neural injuries such as SCI by leveraging recent advancements in bioelectronics and a better understanding of the processes that underlie functional and anatomical reorganization in an injured nervous system. This paper describes our current progress toward developing a miniaturized brain-machine-spinal cord interface (BMSI) that converts in real time the neural command signals recorded from the cortical motor regions to electrical stimuli delivered to the spinal cord below the injury level. Using a combination of custom integrated circuit (IC) technology for corticospinal interfacing and field-programmable gate array (FPGA)-based technology for embedded signal processing, we demonstrate proof-of-concept of distinct muscle pattern activation via intraspinal microstimulation (ISMS) controlled in real time by intracortical neural spikes in an anesthetized laboratory rat.

Low-Latency Digital Signal Processing for Feedback and Feedforward in Quantum Computing and Communication

NASA Astrophysics Data System (ADS)

Salathé, Yves; Kurpiers, Philipp; Karg, Thomas; Lang, Christian; Andersen, Christian Kraglund; Akin, Abdulkadir; Krinner, Sebastian; Eichler, Christopher; Wallraff, Andreas

2018-03-01

Quantum computing architectures rely on classical electronics for control and readout. Employing classical electronics in a feedback loop with the quantum system allows us to stabilize states, correct errors, and realize specific feedforward-based quantum computing and communication schemes such as deterministic quantum teleportation. These feedback and feedforward operations are required to be fast compared to the coherence time of the quantum system to minimize the probability of errors. We present a field-programmable-gate-array-based digital signal processing system capable of real-time quadrature demodulation, a determination of the qubit state, and a generation of state-dependent feedback trigger signals. The feedback trigger is generated with a latency of 110 ns with respect to the timing of the analog input signal. We characterize the performance of the system for an active qubit initialization protocol based on the dispersive readout of a superconducting qubit and discuss potential applications in feedback and feedforward algorithms.

Hardware in-the-Loop Demonstration of Real-Time Orbit Determination in High Earth Orbits

NASA Technical Reports Server (NTRS)

Moreau, Michael; Naasz, Bo; Leitner, Jesse; Carpenter, J. Russell; Gaylor, Dave

2005-01-01

This paper presents results from a study conducted at Goddard Space Flight Center (GSFC) to assess the real-time orbit determination accuracy of GPS-based navigation in a number of different high Earth orbital regimes. Measurements collected from a GPS receiver (connected to a GPS radio frequency (RF) signal simulator) were processed in a navigation filter in real-time, and resulting errors in the estimated states were assessed. For the most challenging orbit simulated, a 12 hour Molniya orbit with an apogee of approximately 39,000 km, mean total position and velocity errors were approximately 7 meters and 3 mm/s respectively. The study also makes direct comparisons between the results from the above hardware in-the-loop tests and results obtained by processing GPS measurements generated from software simulations. Care was taken to use the same models and assumptions in the generation of both the real-time and software simulated measurements, in order that the real-time data could be used to help validate the assumptions and models used in the software simulations. The study makes use of the unique capabilities of the Formation Flying Test Bed at GSFC, which provides a capability to interface with different GPS receivers and to produce real-time, filtered orbit solutions even when less than four satellites are visible. The result is a powerful tool for assessing onboard navigation performance in a wide range of orbital regimes, and a test-bed for developing software and procedures for use in real spacecraft applications.

Integrated control system environment for high-throughput tomography

NASA Astrophysics Data System (ADS)

Khokhriakov, Igor; Lottermoser, Lars; Beckmann, Felix

2017-10-01

The extensive progress in hardware in recent years makes it now possible to develop nearly real time control system for tomography experiments. Such system can perform all the routines that are necessary for the experiment and provide real time feedback to the user. This feedback can be used for instant monitoring and/or for real time reconstruction. The initial design and implementation of such system was presented in the SPIE publication in 2014 [1]. In this paper an update to the system is presented. The paper will cover the following 4 topics. The first topic simply gives an overview of the system. The second topic presents the way how we integrate different software components to achieve simplicity and flexibility. As it is still in research and design phase we need a possibility to easily adjust the system to our needs introducing new components or removing old ones. The third topic presents a hardware driven tomography experiment design implemented at one of our beamlines. The basic idea is that a hardware signal is sent to the instrument hardware (camera, shutter etc). This signal is emitted by the controller of the sample axis which defines the moment when the system is ready to capture the next image i.e. next rotation angle. Finally as our software is in a constant process of evaluation a continuous integration process was implemented to reduce the time cost of redeployment and configuration of new versions.

Simultaneous estimation of deterministic and fractal stochastic components in non-stationary time series

NASA Astrophysics Data System (ADS)

García, Constantino A.; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G.

2018-07-01

In the past few decades, it has been recognized that 1 / f fluctuations are ubiquitous in nature. The most widely used mathematical models to capture the long-term memory properties of 1 / f fluctuations have been stochastic fractal models. However, physical systems do not usually consist of just stochastic fractal dynamics, but they often also show some degree of deterministic behavior. The present paper proposes a model based on fractal stochastic and deterministic components that can provide a valuable basis for the study of complex systems with long-term correlations. The fractal stochastic component is assumed to be a fractional Brownian motion process and the deterministic component is assumed to be a band-limited signal. We also provide a method that, under the assumptions of this model, is able to characterize the fractal stochastic component and to provide an estimate of the deterministic components present in a given time series. The method is based on a Bayesian wavelet shrinkage procedure that exploits the self-similar properties of the fractal processes in the wavelet domain. This method has been validated over simulated signals and over real signals with economical and biological origin. Real examples illustrate how our model may be useful for exploring the deterministic-stochastic duality of complex systems, and uncovering interesting patterns present in time series.

Design of area array CCD image acquisition and display system based on FPGA

NASA Astrophysics Data System (ADS)

Li, Lei; Zhang, Ning; Li, Tianting; Pan, Yue; Dai, Yuming

2014-09-01

With the development of science and technology, CCD(Charge-coupled Device) has been widely applied in various fields and plays an important role in the modern sensing system, therefore researching a real-time image acquisition and display plan based on CCD device has great significance. This paper introduces an image data acquisition and display system of area array CCD based on FPGA. Several key technical challenges and problems of the system have also been analyzed and followed solutions put forward .The FPGA works as the core processing unit in the system that controls the integral time sequence .The ICX285AL area array CCD image sensor produced by SONY Corporation has been used in the system. The FPGA works to complete the driver of the area array CCD, then analog front end (AFE) processes the signal of the CCD image, including amplification, filtering, noise elimination, CDS correlation double sampling, etc. AD9945 produced by ADI Corporation to convert analog signal to digital signal. Developed Camera Link high-speed data transmission circuit, and completed the PC-end software design of the image acquisition, and realized the real-time display of images. The result through practical testing indicates that the system in the image acquisition and control is stable and reliable, and the indicators meet the actual project requirements.

Ultrafast chirped optical waveform recording using referenced heterodyning and a time microscope

DOEpatents

Bennett, Corey Vincent

2010-06-15

A new technique for capturing both the amplitude and phase of an optical waveform is presented. This technique can capture signals with many THz of bandwidths in a single shot (e.g., temporal resolution of about 44 fs), or be operated repetitively at a high rate. That is, each temporal window (or frame) is captured single shot, in real time, but the process may be run repeatedly or single-shot. This invention expands upon previous work in temporal imaging by adding heterodyning, which can be self-referenced for improved precision and stability, to convert frequency chirp (the second derivative of phase with respect to time) into a time varying intensity modulation. By also including a variety of possible demultiplexing techniques, this process is scalable to recoding continuous signals.

Self spectrum window method in wigner-ville distribution.

PubMed

Liu, Zhongguo; Liu, Changchun; Liu, Boqiang; Lv, Yangsheng; Lei, Yinsheng; Yu, Mengsun

2005-01-01

Wigner-Ville distribution (WVD) is an important type of time-frequency analysis in biomedical signal processing. The cross-term interference in WVD has a disadvantageous influence on its application. In this research, the Self Spectrum Window (SSW) method was put forward to suppress the cross-term interference, based on the fact that the cross-term and auto-WVD- terms in integral kernel function are orthogonal. With the Self Spectrum Window (SSW) algorithm, a real auto-WVD function was used as a template to cross-correlate with the integral kernel function, and the Short Time Fourier Transform (STFT) spectrum of the signal was used as window function to process the WVD in time-frequency plane. The SSW method was confirmed by computer simulation with good analysis results. Satisfactory time- frequency distribution was obtained.

Ultrafast chirped optical waveform recorder using referenced heterodyning and a time microscope

DOEpatents

Bennett, Corey Vincent [Livermore, CA

2011-11-22

A new technique for capturing both the amplitude and phase of an optical waveform is presented. This technique can capture signals with many THz of bandwidths in a single shot (e.g., temporal resolution of about 44 fs), or be operated repetitively at a high rate. That is, each temporal window (or frame) is captured single shot, in real time, but the process may be run repeatedly or single-shot. This invention expands upon previous work in temporal imaging by adding heterodyning, which can be self-referenced for improved precision and stability, to convert frequency chirp (the second derivative of phase with respect to time) into a time varying intensity modulation. By also including a variety of possible demultiplexing techniques, this process is scalable to recoding continuous signals.

A high precision position sensor design and its signal processing algorithm for a maglev train.

PubMed

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.

A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train

PubMed Central

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run. PMID:22778582

Real-time acquisition and preprocessing system of transient electromagnetic data based on LabVIEW

NASA Astrophysics Data System (ADS)

Zhao, Huinan; Zhang, Shuang; Gu, Lingjia; Sun, Jian

2014-09-01

Transient electromagnetic method (TEM) is regarded as an everlasting issue for geological exploration. It is widely used in many research fields, such as mineral exploration, hydrogeology survey, engineering exploration and unexploded ordnance detection. The traditional measurement systems are often based on ARM DSP or FPGA, which have not real-time display, data preprocessing and data playback functions. In order to overcome the defects, a real-time data acquisition and preprocessing system based on LabVIEW virtual instrument development platform is proposed in the paper, moreover, a calibration model is established for TEM system based on a conductivity loop. The test results demonstrated that the system can complete real-time data acquisition and system calibration. For Transmit-Loop-Receive (TLR) response, the correlation coefficient between the measured results and the calculated results is 0.987. The measured results are basically consistent with the calculated results. Through the late inversion process for TLR, the signal of underground conductor was obtained. In the complex test environment, abnormal values usually exist in the measured data. In order to solve this problem, the judgment and revision algorithm of abnormal values is proposed in the paper. The test results proved that the proposed algorithm can effectively eliminate serious disturbance signals from the measured transient electromagnetic data.

Research on motor rotational speed measurement in regenerative braking system of electric vehicle

NASA Astrophysics Data System (ADS)

Pan, Chaofeng; Chen, Liao; Chen, Long; Jiang, Haobin; Li, Zhongxing; Wang, Shaohua

2016-01-01

Rotational speed signals acquisition and processing techniques are widely used in rotational machinery. In order to realized precise and real-time control of motor drive and regenerative braking process, rotational speed measurement techniques are needed in electric vehicles. Obtaining accurate motor rotational speed signal will contribute to the regenerative braking force control steadily and realized higher energy recovery rate. This paper aims to develop a method that provides instantaneous speed information in the form of motor rotation. It addresses principles of motor rotational speed measurement in the regenerative braking systems of electric vehicle firstly. The paper then presents ideal and actual Hall position sensor signals characteristics, the relation between the motor rotational speed and the Hall position sensor signals is revealed. Finally, Hall position sensor signals conditioning and processing circuit and program for motor rotational speed measurement have been carried out based on measurement error analysis.

High frequency signal acquisition and control system based on DSP+FPGA

NASA Astrophysics Data System (ADS)

Liu, Xiao-qi; Zhang, Da-zhi; Yin, Ya-dong

2017-10-01

This paper introduces a design and implementation of high frequency signal acquisition and control system based on DSP + FPGA. The system supports internal/external clock and internal/external trigger sampling. It has a maximum sampling rate of 400MBPS and has a 1.4GHz input bandwidth for the ADC. Data can be collected continuously or periodically in systems and they are stored in DDR2. At the same time, the system also supports real-time acquisition, the collected data after digital frequency conversion and Cascaded Integrator-Comb (CIC) filtering, which then be sent to the CPCI bus through the high-speed DSP, can be assigned to the fiber board for subsequent processing. The system integrates signal acquisition and pre-processing functions, which uses high-speed A/D, high-speed DSP and FPGA mixed technology and has a wide range of uses in data acquisition and recording. In the signal processing, the system can be seamlessly connected to the dedicated processor board. The system has the advantages of multi-selectivity, good scalability and so on, which satisfies the different requirements of different signals in different projects.

Comparison of formant detection methods used in speech processing applications

NASA Astrophysics Data System (ADS)

Belean, Bogdan

2013-11-01

The paper describes time frequency representations of speech signal together with the formant significance in speech processing applications. Speech formants can be used in emotion recognition, sex discrimination or diagnosing different neurological diseases. Taking into account the various applications of formant detection in speech signal, two methods for detecting formants are presented. First, the poles resulted after a complex analysis of LPC coefficients are used for formants detection. The second approach uses the Kalman filter for formant prediction along the speech signal. Results are presented for both approaches on real life speech spectrograms. A comparison regarding the features of the proposed methods is also performed, in order to establish which method is more suitable in case of different speech processing applications.

Implementation of an Antenna Array Signal Processing Breadboard for the Deep Space Network

NASA Technical Reports Server (NTRS)

Navarro, Robert

2006-01-01

The Deep Space Network Large Array will replace/augment 34 and 70 meter antenna assets. The array will mainly be used to support NASA's deep space telemetry, radio science, and navigation requirements. The array project will deploy three complexes in the western U.S., Australia, and European longitude each with 400 12m downlink antennas and a DSN central facility at JPL. THis facility will remotely conduct all real-time monitor and control for the network. Signal processing objectives include: provide a means to evaluate the performance of the Breadboard Array's antenna subsystem; design and build prototype hardware; demonstrate and evaluate proposed signal processing techniques; and gain experience with various technologies that may be used in the Large Array. Results are summarized..

Noise removal in extended depth of field microscope images through nonlinear signal processing.

PubMed

Zahreddine, Ramzi N; Cormack, Robert H; Cogswell, Carol J

2013-04-01

Extended depth of field (EDF) microscopy, achieved through computational optics, allows for real-time 3D imaging of live cell dynamics. EDF is achieved through a combination of point spread function engineering and digital image processing. A linear Wiener filter has been conventionally used to deconvolve the image, but it suffers from high frequency noise amplification and processing artifacts. A nonlinear processing scheme is proposed which extends the depth of field while minimizing background noise. The nonlinear filter is generated via a training algorithm and an iterative optimizer. Biological microscope images processed with the nonlinear filter show a significant improvement in image quality and signal-to-noise ratio over the conventional linear filter.

Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

PubMed

Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya

2016-09-01

We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. Copyright © 2016 Elsevier Ltd. All rights reserved.

Extraction of ECG signal with adaptive filter for hearth abnormalities detection

NASA Astrophysics Data System (ADS)

Turnip, Mardi; Saragih, Rijois. I. E.; Dharma, Abdi; Esti Kusumandari, Dwi; Turnip, Arjon; Sitanggang, Delima; Aisyah, Siti

2018-04-01

This paper demonstrates an adaptive filter method for extraction ofelectrocardiogram (ECG) feature in hearth abnormalities detection. In particular, electrocardiogram (ECG) is a recording of the heart's electrical activity by capturing a tracingof cardiac electrical impulse as it moves from the atrium to the ventricles. The applied algorithm is to evaluate and analyze ECG signals for abnormalities detection based on P, Q, R and S peaks. In the first phase, the real-time ECG data is acquired and pre-processed. In the second phase, the procured ECG signal is subjected to feature extraction process. The extracted features detect abnormal peaks present in the waveform. Thus the normal and abnormal ECG signal could be differentiated based on the features extracted.

Applying matching pursuit decomposition time-frequency processing to UGS footstep classification

NASA Astrophysics Data System (ADS)

Larsen, Brett W.; Chung, Hugh; Dominguez, Alfonso; Sciacca, Jacob; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Allee, David R.

2013-06-01

The challenge of rapid footstep detection and classification in remote locations has long been an important area of study for defense technology and national security. Also, as the military seeks to create effective and disposable unattended ground sensors (UGS), computational complexity and power consumption have become essential considerations in the development of classification techniques. In response to these issues, a research project at the Flexible Display Center at Arizona State University (ASU) has experimented with footstep classification using the matching pursuit decomposition (MPD) time-frequency analysis method. The MPD provides a parsimonious signal representation by iteratively selecting matched signal components from a pre-determined dictionary. The resulting time-frequency representation of the decomposed signal provides distinctive features for different types of footsteps, including footsteps during walking or running activities. The MPD features were used in a Bayesian classification method to successfully distinguish between the different activities. The computational cost of the iterative MPD algorithm was reduced, without significant loss in performance, using a modified MPD with a dictionary consisting of signals matched to cadence temporal gait patterns obtained from real seismic measurements. The classification results were demonstrated with real data from footsteps under various conditions recorded using a low-cost seismic sensor.

The design of photoelectric signal processing system for a nuclear magnetic resonance gyroscope based on FPGA

NASA Astrophysics Data System (ADS)

Zhang, Xian; Zhou, Binquan; Li, Hong; Zhao, Xinghua; Mu, Weiwei; Wu, Wenfeng

2017-10-01

Navigation technology is crucial to the national defense and military, which can realize the measurement of orientation, positioning, attitude and speed for moving object. Inertial navigation is not only autonomous, real-time, continuous, hidden, undisturbed but also no time-limited and environment-limited. The gyroscope is the core component of the inertial navigation system, whose precision and size are the bottleneck of the performance. However, nuclear magnetic resonance gyroscope is characteristic of the advantage of high precision and small size. Nuclear magnetic resonance gyroscope can meet the urgent needs of high-tech weapons and equipment development of new generation. This paper mainly designs a set of photoelectric signal processing system for nuclear magnetic resonance gyroscope based on FPGA, which process and control the information of detecting laser .The photoelectric signal with high frequency carrier is demodulated by in-phase and quadrature demodulation method. Finally, the processing system of photoelectric signal can compensate the residual magnetism of the shielding barrel and provide the information of nuclear magnetic resonance gyroscope angular velocity.

Digital Intermediate Frequency Receiver Module For Use In Airborne Sar Applications

DOEpatents

Tise, Bertice L.; Dubbert, Dale F.

2005-03-08

A digital IF receiver (DRX) module directly compatible with advanced radar systems such as synthetic aperture radar (SAR) systems. The DRX can combine a 1 G-Sample/sec 8-bit ADC with high-speed digital signal processor, such as high gate-count FPGA technology or ASICs to realize a wideband IF receiver. DSP operations implemented in the DRX can include quadrature demodulation and multi-rate, variable-bandwidth IF filtering. Pulse-to-pulse (Doppler domain) filtering can also be implemented in the form of a presummer (accumulator) and an azimuth prefilter. An out of band noise source can be employed to provide a dither signal to the ADC, and later be removed by digital signal processing. Both the range and Doppler domain filtering operations can be implemented using a unique pane architecture which allows on-the-fly selection of the filter decimation factor, and hence, the filter bandwidth. The DRX module can include a standard VME-64 interface for control, status, and programming. An interface can provide phase history data to the real-time image formation processors. A third front-panel data port (FPDP) interface can send wide bandwidth, raw phase histories to a real-time phase history recorder for ground processing.

Nonlinear Real-Time Optical Signal Processing

DTIC Science & Technology

1990-09-01

pattern recognition. Additional work concerns the relationship of parallel computation paradigms to optical computing and halftone screen techniques...paradigms to optical computing and halftone screen techniques for implementing general nonlinear functions. 3\\ 2 Research Progress This section...Vol. 23, No. 8, pp. 34-57, 1986. 2.4 Nonlinear Optical Processing with Halftones : Degradation and Compen- sation Models This paper is concerned with

The BEFWM system for detection and phase conjugation of a weak laser beam

NASA Astrophysics Data System (ADS)

Khizhnyak, Anatoliy; Markov, Vladimir

2007-09-01

Real environmental conditions, such as atmospheric turbulence and aero-optics effects, make practical implementation of the object-in-the-loop (TIL) algorithm a very difficult task, especially when the system is set to operate with a signal from the diffuse surface image-resolved object. The problem becomes even more complex since for the remote object the intensity of the returned signal is extremely low. This presentation discusses the results of an analysis and experimental verification of a thresholdless coherent signal receiving system, capable not only in high-sensitivity detection of an ultra weak object-scattered light, but also in its high-gain amplification and phase conjugation. The process of coherent detection by using the Brillouin Enhanced Four Wave Mixing (BEFWM) enables retrieval of complete information on the received signal, including accurate measurement of its wavefront. This information can be used for direct real-time control of the adaptive mirror.

Method of detecting system function by measuring frequency response

NASA Technical Reports Server (NTRS)

Morrison, John L. (Inventor); Morrison, William H. (Inventor); Christophersen, Jon P. (Inventor)

2012-01-01

Real-time battery impedance spectrum is acquired using a one-time record. Fast Summation Transformation (FST) is a parallel method of acquiring a real-time battery impedance spectrum using a one-time record that enables battery diagnostics. An excitation current to a battery is a sum of equal amplitude sine waves of frequencies that are octave harmonics spread over a range of interest. A sample frequency is also octave and harmonically related to all frequencies in the sum. The time profile of this signal has a duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known and octave and harmonically related, a simple algorithm, FST, processes the time record by rectifying relative to the sine and cosine of each frequency. Another algorithm yields real and imaginary components for each frequency.

Method of detecting system function by measuring frequency response

DOEpatents

Morrison, John L [Butte, MT; Morrison, William H [Manchester, CT; Christophersen, Jon P [Idaho Falls, ID

2012-04-03

Real-time battery impedance spectrum is acquired using a one-time record. Fast Summation Transformation (FST) is a parallel method of acquiring a real-time battery impedance spectrum using a one-time record that enables battery diagnostics. An excitation current to a battery is a sum of equal amplitude sine waves of frequencies that are octave harmonics spread over a range of interest. A sample frequency is also octave and harmonically related to all frequencies in the sum. The time profile of this signal has a duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known and octave and harmonically related, a simple algorithm, FST, processes the time record by rectifying relative to the sine and cosine of each frequency. Another algorithm yields real and imaginary components for each frequency.

Sample-based engine noise synthesis using an enhanced pitch-synchronous overlap-and-add method.

PubMed

Jagla, Jan; Maillard, Julien; Martin, Nadine

2012-11-01

An algorithm for the real time synthesis of internal combustion engine noise is presented. Through the analysis of a recorded engine noise signal of continuously varying engine speed, a dataset of sound samples is extracted allowing the real time synthesis of the noise induced by arbitrary evolutions of engine speed. The sound samples are extracted from a recording spanning the entire engine speed range. Each sample is delimitated such as to contain the sound emitted during one cycle of the engine plus the necessary overlap to ensure smooth transitions during the synthesis. The proposed approach, an extension of the PSOLA method introduced for speech processing, takes advantage of the specific periodicity of engine noise signals to locate the extraction instants of the sound samples. During the synthesis stage, the sound samples corresponding to the target engine speed evolution are concatenated with an overlap and add algorithm. It is shown that this method produces high quality audio restitution with a low computational load. It is therefore well suited for real time applications.

A real-time classification algorithm for EEG-based BCI driven by self-induced emotions.

PubMed

Iacoviello, Daniela; Petracca, Andrea; Spezialetti, Matteo; Placidi, Giuseppe

2015-12-01

The aim of this paper is to provide an efficient, parametric, general, and completely automatic real time classification method of electroencephalography (EEG) signals obtained from self-induced emotions. The particular characteristics of the considered low-amplitude signals (a self-induced emotion produces a signal whose amplitude is about 15% of a really experienced emotion) require exploring and adapting strategies like the Wavelet Transform, the Principal Component Analysis (PCA) and the Support Vector Machine (SVM) for signal processing, analysis and classification. Moreover, the method is thought to be used in a multi-emotions based Brain Computer Interface (BCI) and, for this reason, an ad hoc shrewdness is assumed. The peculiarity of the brain activation requires ad-hoc signal processing by wavelet decomposition, and the definition of a set of features for signal characterization in order to discriminate different self-induced emotions. The proposed method is a two stages algorithm, completely parameterized, aiming at a multi-class classification and may be considered in the framework of machine learning. The first stage, the calibration, is off-line and is devoted at the signal processing, the determination of the features and at the training of a classifier. The second stage, the real-time one, is the test on new data. The PCA theory is applied to avoid redundancy in the set of features whereas the classification of the selected features, and therefore of the signals, is obtained by the SVM. Some experimental tests have been conducted on EEG signals proposing a binary BCI, based on the self-induced disgust produced by remembering an unpleasant odor. Since in literature it has been shown that this emotion mainly involves the right hemisphere and in particular the T8 channel, the classification procedure is tested by using just T8, though the average accuracy is calculated and reported also for the whole set of the measured channels. The obtained classification results are encouraging with percentage of success that is, in the average for the whole set of the examined subjects, above 90%. An ongoing work is the application of the proposed procedure to map a large set of emotions with EEG and to establish the EEG headset with the minimal number of channels to allow the recognition of a significant range of emotions both in the field of affective computing and in the development of auxiliary communication tools for subjects affected by severe disabilities. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

An advanced real-time digital signal processing system for linear systems emulation, with special emphasis on network and acoustic response characterization

NASA Astrophysics Data System (ADS)

Gaydecki, Patrick; Fernandes, Bosco

2003-11-01

A fast digital signal processing (DSP) system is described that can perform real-time emulation of a wide variety of linear audio-bandwidth systems and networks, such as reverberant spaces, musical instrument bodies and very high order filter networks. The hardware design is based upon a Motorola DSP56309 operating at 110 million multiplication-accumulations per second and a dual-channel 24 bit codec with a maximum sampling frequency of 192 kHz. High level software has been developed to express complex vector frequency responses as both infinite impulse response (IIR) and finite impulse response (FIR) coefficients, in a form suitable for real-time convolution by the firmware installed in the DSP system memory. An algorithm has also been devised to express IIR filters as equivalent FIR structures, thereby obviating the potential instabilities associated with recursive equations and negating the traditional deficiencies of FIR filters respecting equivalent analogue designs. The speed and dynamic range of the system is such that, when sampling at 48 kHz, the frequency response can be specified to a spectral precision of 22 Hz when sampling at 10 kHz, this resolution increases to 0.9 Hz. Moreover, it is also possible to control the phase of any frequency band with a theoretical precision of 10-5 degrees in all cases. The system has been applied in the study of analogue filter networks, real-time Hilbert transformation, phase-shift systems and musical instrument body emulation, where it is providing valuable new insights into the understanding of psychoacoustic mechanisms.

Design and development of a highly sensitive, field portable plasma source instrument for on-line liquid stream monitoring and real-time sample analysis

NASA Astrophysics Data System (ADS)

Duan, Yixiang; Su, Yongxuan; Jin, Zhe; Abeln, Stephen P.

2000-03-01

The development of a highly sensitive, field portable, low-powered instrument for on-site, real-time liquid waste stream monitoring is described in this article. A series of factors such as system sensitivity and portability, plasma source, sample introduction, desolvation system, power supply, and the instrument configuration, were carefully considered in the design of the portable instrument. A newly designed, miniature, modified microwave plasma source was selected as the emission source for spectroscopy measurement, and an integrated small spectrometer with a charge-coupled device detector was installed for signal processing and detection. An innovative beam collection system with optical fibers was designed and used for emission signal collection. Microwave plasma can be sustained with various gases at relatively low power, and it possesses high detection capabilities for both metal and nonmetal pollutants, making it desirable to use for on-site, real-time, liquid waste stream monitoring. An effective in situ sampling system was coupled with a high efficiency desolvation device for direct-sampling liquid samples into the plasma. A portable computer control system is used for data processing. The new, integrated instrument can be easily used for on-site, real-time monitoring in the field. The system possesses a series of advantages, including high sensitivity for metal and nonmetal elements; in situ sampling; compact structure; low cost; and ease of operation and handling. These advantages will significantly overcome the limitations of previous monitoring techniques and make great contributions to environmental restoration and monitoring.

The Additional Secondary Phase Correction System for AIS Signals

PubMed Central

Wang, Xiaoye; Zhang, Shufang; Sun, Xiaowen

2017-01-01

This paper looks at the development and implementation of the additional secondary phase factor (ASF) real-time correction system for the Automatic Identification System (AIS) signal. A large number of test data were collected using the developed ASF correction system and the propagation characteristics of the AIS signal that transmits at sea and the ASF real-time correction algorithm of the AIS signal were analyzed and verified. Accounting for the different hardware of the receivers in the land-based positioning system and the variation of the actual environmental factors, the ASF correction system corrects original measurements of positioning receivers in real time and provides corrected positioning accuracy within 10 m. PMID:28362330

A Novel Approach to ECG Classification Based upon Two-Layered HMMs in Body Sensor Networks

PubMed Central

Liang, Wei; Zhang, Yinlong; Tan, Jindong; Li, Yang

2014-01-01

This paper presents a novel approach to ECG signal filtering and classification. Unlike the traditional techniques which aim at collecting and processing the ECG signals with the patient being still, lying in bed in hospitals, our proposed algorithm is intentionally designed for monitoring and classifying the patient's ECG signals in the free-living environment. The patients are equipped with wearable ambulatory devices the whole day, which facilitates the real-time heart attack detection. In ECG preprocessing, an integral-coefficient-band-stop (ICBS) filter is applied, which omits time-consuming floating-point computations. In addition, two-layered Hidden Markov Models (HMMs) are applied to achieve ECG feature extraction and classification. The periodic ECG waveforms are segmented into ISO intervals, P subwave, QRS complex and T subwave respectively in the first HMM layer where expert-annotation assisted Baum-Welch algorithm is utilized in HMM modeling. Then the corresponding interval features are selected and applied to categorize the ECG into normal type or abnormal type (PVC, APC) in the second HMM layer. For verifying the effectiveness of our algorithm on abnormal signal detection, we have developed an ECG body sensor network (BSN) platform, whereby real-time ECG signals are collected, transmitted, displayed and the corresponding classification outcomes are deduced and shown on the BSN screen. PMID:24681668

Dual Key Speech Encryption Algorithm Based Underdetermined BSS

PubMed Central

Zhao, Huan; Chen, Zuo; Zhang, Xixiang

2014-01-01

When the number of the mixed signals is less than that of the source signals, the underdetermined blind source separation (BSS) is a significant difficult problem. Due to the fact that the great amount data of speech communications and real-time communication has been required, we utilize the intractability of the underdetermined BSS problem to present a dual key speech encryption method. The original speech is mixed with dual key signals which consist of random key signals (one-time pad) generated by secret seed and chaotic signals generated from chaotic system. In the decryption process, approximate calculation is used to recover the original speech signals. The proposed algorithm for speech signals encryption can resist traditional attacks against the encryption system, and owing to approximate calculation, decryption becomes faster and more accurate. It is demonstrated that the proposed method has high level of security and can recover the original signals quickly and efficiently yet maintaining excellent audio quality. PMID:24955430

Ultrasensitive microchip based on smart microgel for real-time online detection of trace threat analytes.

PubMed

Lin, Shuo; Wang, Wei; Ju, Xiao-Jie; Xie, Rui; Liu, Zhuang; Yu, Hai-Rong; Zhang, Chuan; Chu, Liang-Yin

2016-02-23

Real-time online detection of trace threat analytes is critical for global sustainability, whereas the key challenge is how to efficiently convert and amplify analyte signals into simple readouts. Here we report an ultrasensitive microfluidic platform incorporated with smart microgel for real-time online detection of trace threat analytes. The microgel can swell responding to specific stimulus in flowing solution, resulting in efficient conversion of the stimulus signal into significantly amplified signal of flow-rate change; thus highly sensitive, fast, and selective detection can be achieved. We demonstrate this by incorporating ion-recognizable microgel for detecting trace Pb(2+), and connecting our platform with pipelines of tap water and wastewater for real-time online Pb(2+) detection to achieve timely pollution warning and terminating. This work provides a generalizable platform for incorporating myriad stimuli-responsive microgels to achieve ever-better performance for real-time online detection of various trace threat molecules, and may expand the scope of applications of detection techniques.

Real-time implementation of second generation of audio multilevel information coding

NASA Astrophysics Data System (ADS)

Ali, Murtaza; Tewfik, Ahmed H.; Viswanathan, V.

1994-03-01

This paper describes real-time implementation of a novel wavelet- based audio compression method. This method is based on the discrete wavelet (DWT) representation of signals. A bit allocation procedure is used to allocate bits to the transform coefficients in an adaptive fashion. The bit allocation procedure has been designed to take advantage of the masking effect in human hearing. The procedure minimizes the number of bits required to represent each frame of audio signals at a fixed distortion level. The real-time implementation provides almost transparent compression of monophonic CD quality audio signals (samples at 44.1 KHz and quantized using 16 bits/sample) at bit rates of 64-78 Kbits/sec. Our implementation uses two ASPI Elf boards, each of which is built around a TI TMS230C31 DSP chip. The time required for encoding of a mono CD signal is about 92 percent of real time and that for decoding about 61 percent.

Spectrometer gun

DOEpatents

Waechter, D.A.; Wolf, M.A.; Umbarger, C.J.

1981-11-03

A hand-holdable, battery-operated, microprocessor-based spectrometer gun is described that includes a low-power matrix display and sufficient memory to permit both real-time observation and extended analysis of detected radiation pulses. Universality of the incorporated signal processing circuitry permits operation with various detectors having differing pulse detection and sensitivity parameters.

Multichannel Detection in High-Performance Liquid Chromatography.

ERIC Educational Resources Information Center

Miller, James C.; And Others

1982-01-01

A linear photodiode array is used as the photodetector element in a new ultraviolet-visible detection system for high-performance liquid chromatography (HPLC). Using a computer network, the system processes eight different chromatographic signals simultaneously in real-time and acquires spectra manually/automatically. Applications in fast HPLC…

On-board computational efficiency in real time UAV embedded terrain reconstruction

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Agadakos, Ioannis; Athanasiou, Vasilis; Papaefstathiou, Ioannis; Mertikas, Stylianos; Kyritsis, Sarantis; Tripolitsiotis, Achilles; Zervos, Panagiotis

2014-05-01

In the last few years, there is a surge of applications for object recognition, interpretation and mapping using unmanned aerial vehicles (UAV). Specifications in constructing those UAVs are highly diverse with contradictory characteristics including cost-efficiency, carrying weight, flight time, mapping precision, real time processing capabilities, etc. In this work, a hexacopter UAV is employed for near real time terrain mapping. The main challenge addressed is to retain a low cost flying platform with real time processing capabilities. The UAV weight limitation affecting the overall flight time, makes the selection of the on-board processing components particularly critical. On the other hand, surface reconstruction, as a computational demanding task, calls for a highly demanding processing unit on board. To merge these two contradicting aspects along with customized development, a System on a Chip (SoC) integrated circuit is proposed as a low-power, low-cost processor, which natively supports camera sensors and positioning and navigation systems. Modern SoCs, such as Omap3530 or Zynq, are classified as heterogeneous devices and provide a versatile platform, allowing access to both general purpose processors, such as the ARM11, as well as specialized processors, such as a digital signal processor and floating field-programmable gate array. A UAV equipped with the proposed embedded processors, allows on-board terrain reconstruction using stereo vision in near real time. Furthermore, according to the frame rate required, additional image processing may concurrently take place, such as image rectification andobject detection. Lastly, the onboard positioning and navigation (e.g., GNSS) chip may further improve the quality of the generated map. The resulting terrain maps are compared to ground truth geodetic measurements in order to access the accuracy limitations of the overall process. It is shown that with our proposed novel system,there is much potential in computational efficiency on board and in optimized time constraints.

Modeling Geodetic Processes with Levy α-Stable Distribution and FARIMA

NASA Astrophysics Data System (ADS)

Montillet, Jean-Philippe; Yu, Kegen

2015-04-01

Over the last years the scientific community has been using the auto regressive moving average (ARMA) model in the modeling of the noise in global positioning system (GPS) time series (daily solution). This work starts with the investigation of the limit of the ARMA model which is widely used in signal processing when the measurement noise is white. Since a typical GPS time series consists of geophysical signals (e.g., seasonal signal) and stochastic processes (e.g., coloured and white noise), the ARMA model may be inappropriate. Therefore, the application of the fractional auto-regressive integrated moving average (FARIMA) model is investigated. The simulation results using simulated time series as well as real GPS time series from a few selected stations around Australia show that the FARIMA model fits the time series better than other models when the coloured noise is larger than the white noise. The second fold of this work focuses on fitting the GPS time series with the family of Levy α-stable distributions. Using this distribution, a hypothesis test is developed to eliminate effectively coarse outliers from GPS time series, achieving better performance than using the rule of thumb of n standard deviations (with n chosen empirically).

Evaluation of cardiac signals using discrete wavelet transform with MATLAB graphical user interface.

PubMed

John, Agnes Aruna; Subramanian, Aruna Priyadharshni; Jaganathan, Saravana Kumar; Sethuraman, Balasubramanian

2015-01-01

To process the electrocardiogram (ECG) signals using MATLAB-based graphical user interface (GUI) and to classify the signals based on heart rate. The subject condition was identified using R-peak detection based on discrete wavelet transform followed by a Bayes classifier that classifies the ECG signals. The GUI was designed to display the ECG signal plot. Obtained from MIT database 18 patients had normal heart rate and 9 patients had abnormal heart rate; 14.81% of the patients suffered from tachycardia and 18.52% of the patients have bradycardia. The proposed GUI display was found useful to analyze the digitized ECG signal by a non-technical user and may help in diagnostics. Further improvement can be done by employing field programmable gate array for the real time processing of cardiac signals. Copyright © 2015 Cardiological Society of India. Published by Elsevier B.V. All rights reserved.

A New Statistical Model of Electroencephalogram Noise Spectra for Real-Time Brain-Computer Interfaces.

PubMed

Paris, Alan; Atia, George K; Vosoughi, Azadeh; Berman, Stephen A

2017-08-01

A characteristic of neurological signal processing is high levels of noise from subcellular ion channels up to whole-brain processes. In this paper, we propose a new model of electroencephalogram (EEG) background periodograms, based on a family of functions which we call generalized van der Ziel-McWhorter (GVZM) power spectral densities (PSDs). To the best of our knowledge, the GVZM PSD function is the only EEG noise model that has relatively few parameters, matches recorded EEG PSD's with high accuracy from 0 to over 30 Hz, and has approximately 1/f θ behavior in the midfrequencies without infinities. We validate this model using three approaches. First, we show how GVZM PSDs can arise in a population of ion channels at maximum entropy equilibrium. Second, we present a class of mixed autoregressive models, which simulate brain background noise and whose periodograms are asymptotic to the GVZM PSD. Third, we present two real-time estimation algorithms for steady-state visual evoked potential (SSVEP) frequencies, and analyze their performance statistically. In pairwise comparisons, the GVZM-based algorithms showed statistically significant accuracy improvement over two well-known and widely used SSVEP estimators. The GVZM noise model can be a useful and reliable technique for EEG signal processing. Understanding EEG noise is essential for EEG-based neurology and applications such as real-time brain-computer interfaces, which must make accurate control decisions from very short data epochs. The GVZM approach represents a successful new paradigm for understanding and managing this neurological noise.

A stethoscope with wavelet separation of cardiac and respiratory sounds for real time telemedicine implemented on field-programmable gate array

NASA Astrophysics Data System (ADS)

Castro, Víctor M.; Muñoz, Nestor A.; Salazar, Antonio J.

2015-01-01

Auscultation is one of the most utilized physical examination procedures for listening to lung, heart and intestinal sounds during routine consults and emergencies. Heart and lung sounds overlap in the thorax. An algorithm was used to separate them based on the discrete wavelet transform with multi-resolution analysis, which decomposes the signal into approximations and details. The algorithm was implemented in software and in hardware to achieve real-time signal separation. The heart signal was found in detail eight and the lung signal in approximation six. The hardware was used to separate the signals with a delay of 256 ms. Sending wavelet decomposition data - instead of the separated full signa - allows telemedicine applications to function in real time over low-bandwidth communication channels.

UWGSP7: a real-time optical imaging workstation

NASA Astrophysics Data System (ADS)

Bush, John E.; Kim, Yongmin; Pennington, Stan D.; Alleman, Andrew P.

1995-04-01

With the development of UWGSP7, the University of Washington Image Computing Systems Laboratory has a real-time workstation for continuous-wave (cw) optical reflectance imaging. Recent discoveries in optical science and imaging research have suggested potential practical use of the technology as a medical imaging modality and identified the need for a machine to support these applications in real time. The UWGSP7 system was developed to provide researchers with a high-performance, versatile tool for use in optical imaging experiments with the eventual goal of bringing the technology into clinical use. One of several major applications of cw optical reflectance imaging is tumor imaging which uses a light-absorbing dye that preferentially sequesters in tumor tissue. This property could be used to locate tumors and to identify tumor margins intraoperatively. Cw optical reflectance imaging consists of illumination of a target with a band-limited light source and monitoring the light transmitted by or reflected from the target. While continuously illuminating the target, a control image is acquired and stored. A dye is injected into a subject and a sequence of data images are acquired and processed. The data images are aligned with the control image and then subtracted to obtain a signal representing the change in optical reflectance over time. This signal can be enhanced by digital image processing and displayed in pseudo-color. This type of emerging imaging technique requires a computer system that is versatile and adaptable. The UWGSP7 utilizes a VESA local bus PC as a host computer running the Windows NT operating system and includes ICSL developed add-on boards for image acquisition and processing. The image acquisition board is used to digitize and format the analog signal from the input device into digital frames and to the average frames into images. To accommodate different input devices, the camera interface circuitry is designed in a small mezzanine board that supports the RS-170 standard. The image acquisition board is connected to the image- processing board using a direct connect port which provides a 66 Mbytes/s channel independent of the system bus. The image processing board utilizes the Texas Instruments TMS320C80 Multimedia Video Processor chip. This chip is capable of 2 billion operations per second providing the UWGSP7 with the capability to perform real-time image processing functions like median filtering, convolution and contrast enhancement. This processing power allows interactive analysis of the experiments as compared to current practice of off-line processing and analysis. Due to its flexibility and programmability, the UWGSP7 can be adapted into various research needs in intraoperative optical imaging.

Estimation of frequency offset in mobile satellite modems

NASA Technical Reports Server (NTRS)

Cowley, W. G.; Rice, M.; Mclean, A. N.

1993-01-01

In mobilesat applications, frequency offset on the received signal must be estimated and removed prior to further modem processing. A straightforward method of estimating the carrier frequency offset is to raise the received MPSK signal to the M-th power, and then estimate the location of the peak spectral component. An analysis of the lower signal to noise threshold of this method is carried out for BPSK signals. Predicted thresholds are compared to simulation results. It is shown how the method can be extended to pi/M MPSK signals. A real-time implementation of frequency offset estimation for the Australian mobile satellite system is described.

Cloudwave: distributed processing of "big data" from electrophysiological recordings for epilepsy clinical research using Hadoop.

PubMed

Jayapandian, Catherine P; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D; Zhang, Guo-Qiang; Sahoo, Satya S

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical "big data" consisting of more than 100 multi-channel signals with recordings from each patient generating 5-10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a "private cloud". Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with "montages" for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave).

Cloudwave: Distributed Processing of “Big Data” from Electrophysiological Recordings for Epilepsy Clinical Research Using Hadoop

PubMed Central

Jayapandian, Catherine P.; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D.; Zhang, Guo-Qiang; Sahoo, Satya S.

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50–60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical “big data” consisting of more than 100 multi-channel signals with recordings from each patient generating 5–10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a “private cloud”. Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with “montages” for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave) PMID:24551370

Efficient Processing of Data for Locating Lightning Strikes

NASA Technical Reports Server (NTRS)

Medelius, Pedro J.; Starr, Stan

2003-01-01

Two algorithms have been devised to increase the efficiency of processing of data in lightning detection and ranging (LDAR) systems so as to enable the accurate location of lightning strikes in real time. In LDAR, the location of a lightning strike is calculated by solving equations for the differences among the times of arrival (DTOAs) of the lightning signals at multiple antennas as functions of the locations of the antennas and the speed of light. The most difficult part of the problem is computing the DTOAs from digitized versions of the signals received by the various antennas. One way (a time-domain approach) to determine the DTOAs is to compute cross-correlations among variously differentially delayed replicas of the digitized signals and to select, as the DTOAs, those differential delays that yield the maximum correlations. Another way (a frequency-domain approach) to determine the DTOAs involves the computation of cross-correlations among Fourier transforms of variously differentially phased replicas of the digitized signals, along with utilization of the relationship among phase difference, time delay, and frequency.

Improving wavelet denoising based on an in-depth analysis of the camera color processing

NASA Astrophysics Data System (ADS)

Seybold, Tamara; Plichta, Mathias; Stechele, Walter

2015-02-01

While Denoising is an extensively studied task in signal processing research, most denoising methods are designed and evaluated using readily processed image data, e.g. the well-known Kodak data set. The noise model is usually additive white Gaussian noise (AWGN). This kind of test data does not correspond to nowadays real-world image data taken with a digital camera. Using such unrealistic data to test, optimize and compare denoising algorithms may lead to incorrect parameter tuning or suboptimal choices in research on real-time camera denoising algorithms. In this paper we derive a precise analysis of the noise characteristics for the different steps in the color processing. Based on real camera noise measurements and simulation of the processing steps, we obtain a good approximation for the noise characteristics. We further show how this approximation can be used in standard wavelet denoising methods. We improve the wavelet hard thresholding and bivariate thresholding based on our noise analysis results. Both the visual quality and objective quality metrics show the advantage of the proposed method. As the method is implemented using look-up-tables that are calculated before the denoising step, our method can be implemented with very low computational complexity and can process HD video sequences real-time in an FPGA.

Real-time, high frequency QRS electrocardiograph

NASA Technical Reports Server (NTRS)

Schlegel, Todd T. (Inventor); DePalma, Jude L. (Inventor); Moradi, Saeed (Inventor)

2006-01-01

Real time cardiac electrical data are received from a patient, manipulated to determine various useful aspects of the ECG signal, and displayed in real time in a useful form on a computer screen or monitor. The monitor displays the high frequency data from the QRS complex in units of microvolts, juxtaposed with a display of conventional ECG data in units of millivolts or microvolts. The high frequency data are analyzed for their root mean square (RMS) voltage values and the discrete RMS values and related parameters are displayed in real time. The high frequency data from the QRS complex are analyzed with imbedded algorithms to determine the presence or absence of reduced amplitude zones, referred to herein as RAZs. RAZs are displayed as go, no-go signals on the computer monitor. The RMS and related values of the high frequency components are displayed as time varying signals, and the presence or absence of RAZs may be similarly displayed over time.

Estimation of Fine and Oversize Particle Ratio in a Heterogeneous Compound with Acoustic Emissions.

PubMed

Nsugbe, Ejay; Ruiz-Carcel, Cristobal; Starr, Andrew; Jennions, Ian

2018-03-13

The final phase of powder production typically involves a mixing process where all of the particles are combined and agglomerated with a binder to form a single compound. The traditional means of inspecting the physical properties of the final product involves an inspection of the particle sizes using an offline sieving and weighing process. The main downside of this technique, in addition to being an offline-only measurement procedure, is its inability to characterise large agglomerates of powders due to sieve blockage. This work assesses the feasibility of a real-time monitoring approach using a benchtop test rig and a prototype acoustic-based measurement approach to provide information that can be correlated to product quality and provide the opportunity for future process optimisation. Acoustic emission (AE) was chosen as the sensing method due to its low cost, simple setup process, and ease of implementation. The performance of the proposed method was assessed in a series of experiments where the offline quality check results were compared to the AE-based real-time estimations using data acquired from a benchtop powder free flow rig. A designed time domain based signal processing method was used to extract particle size information from the acquired AE signal and the results show that this technique is capable of estimating the required ratio in the washing powder compound with an average absolute error of 6%.

Real time monitoring of powder blend bulk density for coupled feed-forward/feed-back control of a continuous direct compaction tablet manufacturing process.

PubMed

Singh, Ravendra; Román-Ospino, Andrés D; Romañach, Rodolfo J; Ierapetritou, Marianthi; Ramachandran, Rohit

2015-11-10

The pharmaceutical industry is strictly regulated, where precise and accurate control of the end product quality is necessary to ensure the effectiveness of the drug products. For such control, the process and raw materials variability ideally need to be fed-forward in real time into an automatic control system so that a proactive action can be taken before it can affect the end product quality. Variations in raw material properties (e.g., particle size), feeder hopper level, amount of lubrication, milling and blending action, applied shear in different processing stages can affect the blend density significantly and thereby tablet weight, hardness and dissolution. Therefore, real time monitoring of powder bulk density variability and its incorporation into the automatic control system so that its effect can be mitigated proactively and efficiently is highly desired. However, real time monitoring of powder bulk density is still a challenging task because of different level of complexities. In this work, powder bulk density which has a significant effect on the critical quality attributes (CQA's) has been monitored in real time in a pilot-plant facility, using a NIR sensor. The sensitivity of the powder bulk density on critical process parameters (CPP's) and CQA's has been analyzed and thereby feed-forward controller has been designed. The measured signal can be used for feed-forward control so that the corrective actions on the density variations can be taken before they can influence the product quality. The coupled feed-forward/feed-back control system demonstrates improved control performance and improvements in the final product quality in the presence of process and raw material variations. Copyright © 2015 Elsevier B.V. All rights reserved.

Optical multichannel monitoring of skin blood pulsations for cardiovascular assessment

NASA Astrophysics Data System (ADS)

Spigulis, Janis; Erts, Renars; Ozols, Maris

2004-07-01

Time resolved detection and analysis of the skin back-scattered optical signals (reflection photoplethysmography or PPG) provide rich information on skin blood volume pulsations and can serve for cardiovascular assessment. The multichannel PPG concept has been developed and clinically verified in this work. Simultaneous data flow from several body locations allows to study the heartbeat pulse wave propagation in real time and to evaluate the vascular resistance. Portable two- and four-channel PPG monitoring devices and special software have been designed for real-time data acquisition and processing. The multi-channel devices were successfully applied for cardiovascular fitness tests and for early detection of arterial occlusions.

Minimum Requirements for Accurate and Efficient Real-Time On-Chip Spike Sorting

PubMed Central

Navajas, Joaquin; Barsakcioglu, Deren Y.; Eftekhar, Amir; Jackson, Andrew; Constandinou, Timothy G.; Quiroga, Rodrigo Quian

2014-01-01

Background Extracellular recordings are performed by inserting electrodes in the brain, relaying the signals to external power-demanding devices, where spikes are detected and sorted in order to identify the firing activity of different putative neurons. A main caveat of these recordings is the necessity of wires passing through the scalp and skin in order to connect intracortical electrodes to external amplifiers. The aim of this paper is to evaluate the feasibility of an implantable platform (i.e. a chip) with the capability to wirelessly transmit the neural signals and perform real-time on-site spike sorting. New Method We computationally modelled a two-stage implementation for online, robust, and efficient spike sorting. In the first stage, spikes are detected on-chip and streamed to an external computer where mean templates are created and sent back to the chip. In the second stage, spikes are sorted in real-time through template matching. Results We evaluated this procedure using realistic simulations of extracellular recordings and describe a set of specifications that optimise performance while keeping to a minimum the signal requirements and the complexity of the calculations. Comparison with Existing Methods A key bottleneck for the development of long-term BMIs is to find an inexpensive method for real-time spike sorting. Here, we simulated a solution to this problem that uses both offline and online processing of the data. Conclusions Hardware implementations of this method therefore enable low-power long-term wireless transmission of multiple site extracellular recordings, with application to wireless BMIs or closed-loop stimulation designs. PMID:24769170

Real-Time Noise Reduction for Mossbauer Spectroscopy through Online Implementation of a Modified Kalman Filter

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

Abrecht, David G.; Schwantes, Jon M.; Kukkadapu, Ravi K.

2015-02-01

Spectrum-processing software that incorporates a gaussian smoothing kernel within the statistics of first-order Kalman filtration has been developed to provide cross-channel spectral noise reduction for increased real-time signal-to-noise ratios for Mossbauer spectroscopy. The filter was optimized for the breadth of the gaussian using the Mossbauer spectrum of natural iron foil, and comparisons between the peak broadening, signal-to-noise ratios, and shifts in the calculated hyperfine parameters are presented. The results of optimization give a maximum improvement in the signal-to-noise ratio of 51.1% over the unfiltered spectrum at a gaussian breadth of 27 channels, or 2.5% of the total spectrum width. Themore » full-width half-maximum of the spectrum peaks showed an increase of 19.6% at this optimum point, indicating a relatively weak increase in the peak broadening relative to the signal enhancement, leading to an overall increase in the observable signal. Calculations of the hyperfine parameters showed no statistically significant deviations were introduced from the application of the filter, confirming the utility of this filter for spectroscopy applications.« less

Radio frequency switching network: a technique for infrared sensing

NASA Astrophysics Data System (ADS)

Mechtel, Deborah M.; Jenkins, R. Brian; Joyce, Peter J.; Nelson, Charles L.

2016-10-01

This paper describes a unique technique that implements photoconductive sensors in a radio frequency (RF) switching network designed to locate in real-time the position and intensity of IR radiation incident on a composite structure. In the implementation described here, photoconductive sensors act as rapid response switches in a two-layer RF network embedded in an FR-4 laminate. To detect radiation, phosphorous-doped silicon photoconductive sensors are inserted in GHz range RF transmission lines. By permitting signal propagation only when a sensor is illuminated, the RF signals are selectively routed from lower layer transmission lines to upper layer lines, thereby pinpointing the location and strength of incident radiation. Simulations based on a high frequency three-dimensional planar electromagnetics model are presented and compared to the experimental results. The experimental results are described for GHz range RF signal control for 300- and 180-mW incident energy from 975- to 1060-nm wavelength lasers, respectively, where upon illumination, RF transmission line signal output power doubled when compared to nonilluminated results. The experimental results are also reported for 100-W incident energy from a 1060-nm laser. Test results illustrate real-time signal processing would permit a structure to be controlled in response to incident radiation.

Adaptive filtering in biological signal processing.

PubMed

Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

1990-01-01

The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

Identification and human condition analysis based on the human voice analysis

NASA Astrophysics Data System (ADS)

Mieshkov, Oleksandr Yu.; Novikov, Oleksandr O.; Novikov, Vsevolod O.; Fainzilberg, Leonid S.; Kotyra, Andrzej; Smailova, Saule; Kozbekova, Ainur; Imanbek, Baglan

2017-08-01

The paper presents a two-stage biotechnical system for human condition analysis that is based on analysis of human voice signal. At the initial stage, the voice signal is pre-processed and its characteristics in time domain are determined. At the first stage, the developed system is capable of identifying the person in the database on the basis of the extracted characteristics. At the second stage, the model of a human voice is built on the basis of the real voice signals after clustering the whole database.

Rapid Protein Global Fold Determination Using Ultrasparse Sampling, High-Dynamic Range Artifact Suppression, and Time-Shared NOESY

PubMed Central

Coggins, Brian E.; Werner-Allen, Jonathan W.; Yan, Anthony; Zhou, Pei

2012-01-01

In structural studies of large proteins by NMR, global fold determination plays an increasingly important role in providing a first look at a target’s topology and reducing assignment ambiguity in NOESY spectra of fully-protonated samples. In this work, we demonstrate the use of ultrasparse sampling, a new data processing algorithm, and a 4-D time-shared NOESY experiment (1) to collect all NOEs in 2H/13C/15N-labeled protein samples with selectively-protonated amide and ILV methyl groups at high resolution in only four days, and (2) to calculate global folds from this data using fully automated resonance assignment. The new algorithm, SCRUB, incorporates the CLEAN method for iterative artifact removal, but applies an additional level of iteration, permitting real signals to be distinguished from noise and allowing nearly all artifacts generated by real signals to be eliminated. In simulations with 1.2% of the data required by Nyquist sampling, SCRUB achieves a dynamic range over 10000:1 (250× better artifact suppression than CLEAN) and completely quantitative reproduction of signal intensities, volumes, and lineshapes. Applied to 4-D time-shared NOESY data, SCRUB processing dramatically reduces aliasing noise from strong diagonal signals, enabling the identification of weak NOE crosspeaks with intensities 100× less than diagonal signals. Nearly all of the expected peaks for interproton distances under 5 Å were observed. The practical benefit of this method is demonstrated with structure calculations for 23 kDa and 29 kDa test proteins using the automated assignment protocol of CYANA, in which unassigned 4-D time-shared NOESY peak lists produce accurate and well-converged global fold ensembles, whereas 3-D peak lists either fail to converge or produce significantly less accurate folds. The approach presented here succeeds with an order of magnitude less sampling than required by alternative methods for processing sparse 4-D data. PMID:22946863

Real-time optically sectioned wide-field microscopy employing structured light illumination and a CMOS detector

NASA Astrophysics Data System (ADS)

Mitic, Jelena; Anhut, Tiemo; Serov, Alexandre; Lasser, Theo; Bourquin, Stephane

2003-07-01

Real-time optically sectioned microscopy is demonstrated using an AC-sensitive detection concept realized with smart CMOS image sensor and structured light illumination by a continuously moving periodic pattern. We describe two different detection systems based on CMOS image sensors for the detection and on-chip processing of the sectioned images in real time. A region-of-interest is sampled at high frame rate. The demodulated signal delivered by the detector corresponds to the depth discriminated image of the sample. The measured FWHM of the axial response depends on the spatial frequency of the projected grid illumination and is in the μm-range. The effect of using broadband incoherent illumination is discussed. The performance of these systems is demonstrated by imaging technical as well as biological samples.

Imaging of a Defect in Thin Plates Using the Time Reversal of Single Mode Lamb Waves

NASA Astrophysics Data System (ADS)

Jeong, Hyunjo; Lee, Jung-Sik; Bae, Sung-Min

2011-06-01

This paper presents an analytical investigation for a baseline-free imaging of a defect in plate-like structures using the time-reversal of Lamb waves. We first consider the flexural wave (A0 mode) propagation in a plate containing a defect, and reception and time reversal process of the output signal at the receiver. The received output signal is then composed of two parts: a directly propagated wave and a scattered wave from the defect. The time reversal of these waves recovers the original input signal, and produces two additional sidebands that contain the time-of-flight information on the defect location. One of the side band signals is then extracted as a pure defect signal. A defect localization image is then constructed from a beamforming technique based on the time-frequency analysis of the side band signal for each transducer pair in a network of sensors. The simulation results show that the proposed scheme enables the accurate, baseline-free detection of a defect, so that experimental studies are needed to verify the proposed method and to be applied to real structure.

Net Photorefractive Gain In Gallium Arsenide

NASA Technical Reports Server (NTRS)

Liu, Tsuen-Hsi; Cheng, Li-Jen

1990-01-01

Prerequisite includes applied electric field. Electric field applied to GaAs crystal in which two infrared beams interfere. Depending on quality of sample and experimental conditions, net photorefractive gain obtained. Results offer possibility of new developments in real-time optical processing of signals by use of near-infrared lasers of low power.

Optical fibre multi-parameter sensing with secure cloud based signal capture and processing

NASA Astrophysics Data System (ADS)

Newe, Thomas; O'Connell, Eoin; Meere, Damien; Yuan, Hongwei; Leen, Gabriel; O'Keeffe, Sinead; Lewis, Elfed

2016-05-01

Recent advancements in cloud computing technologies in the context of optical and optical fibre based systems are reported. The proliferation of real time and multi-channel based sensor systems represents significant growth in data volume. This coupled with a growing need for security presents many challenges and presents a huge opportunity for an evolutionary step in the widespread application of these sensing technologies. A tiered infrastructural system approach is adopted that is designed to facilitate the delivery of Optical Fibre-based "SENsing as a Service- SENaaS". Within this infrastructure, novel optical sensing platforms, deployed within different environments, are interfaced with a Cloud-based backbone infrastructure which facilitates the secure collection, storage and analysis of real-time data. Feedback systems, which harness this data to affect a change within the monitored location/environment/condition, are also discussed. The cloud based system presented here can also be used with chemical and physical sensors that require real-time data analysis, processing and feedback.

Playback system designed for X-Band SAR

NASA Astrophysics Data System (ADS)

Yuquan, Liu; Changyong, Dou

2014-03-01

SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement.

Development and testing of controller performance evaluation methodology for multi-input/multi-output digital control systems

NASA Technical Reports Server (NTRS)

Pototzky, Anthony; Wieseman, Carol; Hoadley, Sherwood Tiffany; Mukhopadhyay, Vivek

1991-01-01

Described here is the development and implementation of on-line, near real time controller performance evaluation (CPE) methods capability. Briefly discussed are the structure of data flow, the signal processing methods used to process the data, and the software developed to generate the transfer functions. This methodology is generic in nature and can be used in any type of multi-input/multi-output (MIMO) digital controller application, including digital flight control systems, digitally controlled spacecraft structures, and actively controlled wind tunnel models. Results of applying the CPE methodology to evaluate (in near real time) MIMO digital flutter suppression systems being tested on the Rockwell Active Flexible Wing (AFW) wind tunnel model are presented to demonstrate the CPE capability.

Earthquake forecasting studies using radon time series data in Taiwan

NASA Astrophysics Data System (ADS)

Walia, Vivek; Kumar, Arvind; Fu, Ching-Chou; Lin, Shih-Jung; Chou, Kuang-Wu; Wen, Kuo-Liang; Chen, Cheng-Hong

2017-04-01

For few decades, growing number of studies have shown usefulness of data in the field of seismogeochemistry interpreted as geochemical precursory signals for impending earthquakes and radon is idendified to be as one of the most reliable geochemical precursor. Radon is recognized as short-term precursor and is being monitored in many countries. This study is aimed at developing an effective earthquake forecasting system by inspecting long term radon time series data. The data is obtained from a network of radon monitoring stations eastblished along different faults of Taiwan. The continuous time series radon data for earthquake studies have been recorded and some significant variations associated with strong earthquakes have been observed. The data is also examined to evaluate earthquake precursory signals against environmental factors. An automated real-time database operating system has been developed recently to improve the data processing for earthquake precursory studies. In addition, the study is aimed at the appraisal and filtrations of these environmental parameters, in order to create a real-time database that helps our earthquake precursory study. In recent years, automatic operating real-time database has been developed using R, an open source programming language, to carry out statistical computation on the data. To integrate our data with our working procedure, we use the popular and famous open source web application solution, AMP (Apache, MySQL, and PHP), creating a website that could effectively show and help us manage the real-time database.

New digital capacitive measurement system for blade clearances

NASA Astrophysics Data System (ADS)

Moenich, Marcel; Bailleul, Gilles

This paper presents a totally new concept for tip blade clearance evaluation in turbine engines. This system is able to detect exact 'measurands' even under high temperature and severe conditions like ionization. The system is based on a heavy duty probe head, a miniaturized thick-film hybrid electronic circuit and a signal processing unit for real time computing. The high frequency individual measurement values are digitally filtered and linearized in real time. The electronic is built in hybrid technology and therefore can be kept extremely small and robust, so that the system can be used on actual flights.

The Serendip II design. [narrowband astronautical radio signal search for extraterrestrial intelligence

NASA Technical Reports Server (NTRS)

Werthimer, D.; Tarter, J.; Bowyer, S.

1985-01-01

Serendip II is an automated system designed to perform a real time search for narrow band radio signals in the spectra of sources in a regularly scheduled, non-Seti, astronomical observing program. Because Serendip II is expected to run continuously without requiring dedicated observing time, it is hoped that a large portion of the sky will be surveyed at high sensitivity and low cost. Serendip II will compute the power spectrum using a 65,536 channel fast Fourier transform processor with a real time bandwidth of 128 KHz and 2 Hz per channel resolution. After searching for peaks in a 100 KHz portion of the radio telescope's IF band, Serendip II will move to the next 100 KHz portion using a programmable frequency synthesizer; when the whole IF band has been scanned, the process will start again. Unidentified peaks in the power spectra are candidates for further study and their celestial coordinates will be recorded along with the time and power, IF and RF frequency, and bandwidth of the peak.

Real-Time Prediction of Temperature Elevation During Robotic Bone Drilling Using the Torque Signal.

PubMed

Feldmann, Arne; Gavaghan, Kate; Stebinger, Manuel; Williamson, Tom; Weber, Stefan; Zysset, Philippe

2017-09-01

Bone drilling is a surgical procedure commonly required in many surgical fields, particularly orthopedics, dentistry and head and neck surgeries. While the long-term effects of thermal bone necrosis are unknown, the thermal damage to nerves in spinal or otolaryngological surgeries might lead to partial paralysis. Previous models to predict the temperature elevation have been suggested, but were not validated or have the disadvantages of computation time and complexity which does not allow real time predictions. Within this study, an analytical temperature prediction model is proposed which uses the torque signal of the drilling process to model the heat production of the drill bit. A simple Green's disk source function is used to solve the three dimensional heat equation along the drilling axis. Additionally, an extensive experimental study was carried out to validate the model. A custom CNC-setup with a load cell and a thermal camera was used to measure the axial drilling torque and force as well as temperature elevations. Bones with different sets of bone volume fraction were drilled with two drill bits ([Formula: see text]1.8 mm and [Formula: see text]2.5 mm) and repeated eight times. The model was calibrated with 5 of 40 measurements and successfully validated with the rest of the data ([Formula: see text]C). It was also found that the temperature elevation can be predicted using only the torque signal of the drilling process. In the future, the model could be used to monitor and control the drilling process of surgeries close to vulnerable structures.

Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning

NASA Astrophysics Data System (ADS)

García Plaza, E.; Núñez López, P. J.

2018-01-01

On-line monitoring of surface finish in machining processes has proven to be a substantial advancement over traditional post-process quality control techniques by reducing inspection times and costs and by avoiding the manufacture of defective products. This study applied techniques for processing cutting force signals based on the wavelet packet transform (WPT) method for the monitoring of surface finish in computer numerical control (CNC) turning operations. The behaviour of 40 mother wavelets was analysed using three techniques: global packet analysis (G-WPT), and the application of two packet reduction criteria: maximum energy (E-WPT) and maximum entropy (SE-WPT). The optimum signal decomposition level (Lj) was determined to eliminate noise and to obtain information correlated to surface finish. The results obtained with the G-WPT method provided an in-depth analysis of cutting force signals, and frequency ranges and signal characteristics were correlated to surface finish with excellent results in the accuracy and reliability of the predictive models. The radial and tangential cutting force components at low frequency provided most of the information for the monitoring of surface finish. The E-WPT and SE-WPT packet reduction criteria substantially reduced signal processing time, but at the expense of discarding packets with relevant information, which impoverished the results. The G-WPT method was observed to be an ideal procedure for processing cutting force signals applied to the real-time monitoring of surface finish, and was estimated to be highly accurate and reliable at a low analytical-computational cost.

Intermediate frequency band digitized high dynamic range radiometer system for plasma diagnostics and real-time Tokamak control

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

Bongers, W. A.; Beveren, V. van; Westerhof, E.

2011-06-15

An intermediate frequency (IF) band digitizing radiometer system in the 100-200 GHz frequency range has been developed for Tokamak diagnostics and control, and other fields of research which require a high flexibility in frequency resolution combined with a large bandwidth and the retrieval of the full wave information of the mm-wave signals under investigation. The system is based on directly digitizing the IF band after down conversion. The enabling technology consists of a fast multi-giga sample analog to digital converter that has recently become available. Field programmable gate arrays (FPGA) are implemented to accomplish versatile real-time data analysis. A prototypemore » system has been developed and tested and its performance has been compared with conventional electron cyclotron emission (ECE) spectrometer systems. On the TEXTOR Tokamak a proof of principle shows that ECE, together with high power injected and scattered radiation, becomes amenable to measurement by this device. In particular, its capability to measure the phase of coherent signals in the spectrum offers important advantages in diagnostics and control. One case developed in detail employs the FPGA in real-time fast Fourier transform (FFT) and additional signal processing. The major benefit of such a FFT-based system is the real-time trade-off that can be made between frequency and time resolution. For ECE diagnostics this corresponds to a flexible spatial resolution in the plasma, with potential application in smart sensing of plasma instabilities such as the neoclassical tearing mode (NTM) and sawtooth instabilities. The flexible resolution would allow for the measurement of the full mode content of plasma instabilities contained within the system bandwidth.« less

Real-time recognition of feedback error-related potentials during a time-estimation task.

PubMed

Lopez-Larraz, Eduardo; Iturrate, Iñaki; Montesano, Luis; Minguez, Javier

2010-01-01

Feedback error-related potentials are a promising brain process in the field of rehabilitation since they are related to human learning. Due to the fact that many therapeutic strategies rely on the presentation of feedback stimuli, potentials generated by these stimuli could be used to ameliorate the patient's progress. In this paper we propose a method that can identify, in real-time, feedback evoked potentials in a time-estimation task. We have tested our system with five participants in two different days with a separation of three weeks between them, achieving a mean single-trial detection performance of 71.62% for real-time recognition, and 78.08% in offline classification. Additionally, an analysis of the stability of the signal between the two days is performed, suggesting that the feedback responses are stable enough to be used without the needing of training again the user.

SU-G-BRA-01: A Real-Time Tumor Localization and Guidance Platform for Radiotherapy Using US and MRI

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

Bednarz, B; Culberson, W; Bassetti, M

Purpose: To develop and validate a real-time motion management platform for radiotherapy that directly tracks tumor motion using ultrasound and MRI. This will be a cost-effective and non-invasive real-time platform combining the excellent temporal resolution of ultrasound with the excellent soft-tissue contrast of MRI. Methods: A 4D planar ultrasound acquisition during the treatment that is coupled to a pre-treatment calibration training image set consisting of a simultaneous 4D ultrasound and 4D MRI acquisition. The image sets will be rapidly matched using advanced image and signal processing algorithms, allowing the display of virtual MR images of the tumor/organ motion in real-timemore » from an ultrasound acquisition. Results: The completion of this work will result in several innovations including: a (2D) patch-like, MR and LINAC compatible 4D planar ultrasound transducer that is electronically steerable for hands-free operation to provide real-time virtual MR and ultrasound imaging for motion management during radiation therapy; a multi- modal tumor localization strategy that uses ultrasound and MRI; and fast and accurate image processing algorithms that provide real-time information about the motion and location of tumor or related soft-tissue structures within the patient. Conclusion: If successful, the proposed approach will provide real-time guidance for radiation therapy without degrading image or treatment plan quality. The approach would be equally suitable for image-guided proton beam or heavy ion-beam therapy. This work is partially funded by NIH grant R01CA190298.« less

Real-time photonic sampling with improved signal-to-noise and distortion ratio using polarization-dependent modulators

NASA Astrophysics Data System (ADS)

Liang, Dong; Zhang, Zhiyao; Liu, Yong; Li, Xiaojun; Jiang, Wei; Tan, Qinggui

2018-04-01

A real-time photonic sampling structure with effective nonlinearity suppression and excellent signal-to-noise ratio (SNR) performance is proposed. The key points of this scheme are the polarization-dependent modulators (P-DMZMs) and the sagnac loop structure. Thanks to the polarization sensitive characteristic of P-DMZMs, the differences between transfer functions of the fundamental signal and the distortion become visible. Meanwhile, the selection of specific biases in P-DMZMs is helpful to achieve a preferable linearized performance with a low noise level for real-time photonic sampling. Compared with the quadrature-biased scheme, the proposed scheme is capable of valid nonlinearity suppression and is able to provide a better SNR performance even in a large frequency range. The proposed scheme is proved to be effective and easily implemented for real time photonic applications.

Ridge extraction from the time-frequency representation (TFR) of signals based on an image processing approach: application to the analysis of uterine electromyogram AR TFR.

PubMed

Terrien, Jérémy; Marque, Catherine; Germain, Guy

2008-05-01

Time-frequency representations (TFRs) of signals are increasingly being used in biomedical research. Analysis of such representations is sometimes difficult, however, and is often reduced to the extraction of ridges, or local energy maxima. In this paper, we describe a new ridge extraction method based on the image processing technique of active contours or snakes. We have tested our method on several synthetic signals and for the analysis of uterine electromyogram or electrohysterogram (EHG) recorded during gestation in monkeys. We have also evaluated a postprocessing algorithm that is especially suited for EHG analysis. Parameters are evaluated on real EHG signals in different gestational periods. The presented method gives good results when applied to synthetic as well as EHG signals. We have been able to obtain smaller ridge extraction errors when compared to two other methods specially developed for EHG. The gradient vector flow (GVF) snake method, or GVF-snake method, appears to be a good ridge extraction tool, which could be used on TFR of mono or multicomponent signals with good results.

Parallel Processing of Large Scale Microphone Arrays for Sound Capture

NASA Astrophysics Data System (ADS)

Jan, Ea-Ee.

1995-01-01

Performance of microphone sound pick up is degraded by deleterious properties of the acoustic environment, such as multipath distortion (reverberation) and ambient noise. The degradation becomes more prominent in a teleconferencing environment in which the microphone is positioned far away from the speaker. Besides, the ideal teleconference should feel as easy and natural as face-to-face communication with another person. This suggests hands-free sound capture with no tether or encumbrance by hand-held or body-worn sound equipment. Microphone arrays for this application represent an appropriate approach. This research develops new microphone array and signal processing techniques for high quality hands-free sound capture in noisy, reverberant enclosures. The new techniques combine matched-filtering of individual sensors and parallel processing to provide acute spatial volume selectivity which is capable of mitigating the deleterious effects of noise interference and multipath distortion. The new method outperforms traditional delay-and-sum beamformers which provide only directional spatial selectivity. The research additionally explores truncated matched-filtering and random distribution of transducers to reduce complexity and improve sound capture quality. All designs are first established by computer simulation of array performance in reverberant enclosures. The simulation is achieved by a room model which can efficiently calculate the acoustic multipath in a rectangular enclosure up to a prescribed order of images. It also calculates the incident angle of the arriving signal. Experimental arrays were constructed and their performance was measured in real rooms. Real room data were collected in a hard-walled laboratory and a controllable variable acoustics enclosure of similar size, approximately 6 x 6 x 3 m. An extensive speech database was also collected in these two enclosures for future research on microphone arrays. The simulation results are shown to be consistent with the real room data. Localization of sound sources has been explored using cross-power spectrum time delay estimation and has been evaluated using real room data under slightly, moderately and highly reverberant conditions. To improve the accuracy and reliability of the source localization, an outlier detector that removes incorrect time delay estimation has been invented. To provide speaker selectivity for microphone array systems, a hands-free speaker identification system has been studied. A recently invented feature using selected spectrum information outperforms traditional recognition methods. Measured results demonstrate the capabilities of speaker selectivity from a matched-filtered array. In addition, simulation utilities, including matched -filtering processing of the array and hands-free speaker identification, have been implemented on the massively -parallel nCube super-computer. This parallel computation highlights the requirements for real-time processing of array signals.

Visualization of Cortical Dynamics

NASA Astrophysics Data System (ADS)

Grinvald, Amiram

2003-03-01

Recent progress in studies of cortical dynamics will be reviewed including the combination of real time optical imaging based on voltage sensitive dyes, single and multi- unit recordings, LFP, intracellular recordings and microstimulation. To image the flow of neuronal activity from one cortical site to the next, in real time, we have used optical imaging based on newly designed voltage sensitive dyes and a Fuji 128x 128 fast camera which we modified. A factor of 20-40 fold improvement in the signal to noise ratio was obtained with the new dye during in vivo imaging experiments. This improvements has facilitates the exploration of cortical dynamics without signal averaging in the millisecond time domain. We confirmed that the voltage sensitive dye signal indeed reflects membrane potential changes in populations of neurons by showing that the time course of the intracellular activity recorded intracellularly from a single neuron was highly correlated in many cases with the optical signal from a small patch of cortex recorded nearby. We showed that the firing of single cortical neurons is not a random process but occurs when the on-going pattern of million of neurons is similar to the functional architecture map which correspond to the tuning properties of that neuron. Chronic optical imaging, combined with electrical recordings and microstimulation, over a long period of times of more than a year, was successfully applied also to the study of higher brain functions in the behaving macaque monkey.

Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

NASA Astrophysics Data System (ADS)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

Digital resolver for helicopter model blade motion analysis

NASA Technical Reports Server (NTRS)

Daniels, T. S.; Berry, J. D.; Park, S.

1992-01-01

The paper reports the development and initial testing of a digital resolver to replace existing analog signal processing instrumentation. Radiometers, mounted directly on one of the fully articulated blades, are electrically connected through a slip ring to analog signal processing circuitry. The measured signals are periodic with azimuth angle and are resolved into harmonic components, with 0 deg over the tail. The periodic nature of the helicopter blade motion restricts the frequency content of each flapping and yaw signal to the fundamental and harmonics of the rotor rotational frequency. A minicomputer is employed to collect these data and then plot them graphically in real time. With this and other information generated by the instrumentation, a helicopter test pilot can then adjust the helicopter model's controls to achieve the desired aerodynamic test conditions.

DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals

DTIC Science & Technology

2014-09-30

repeating pulse-like signals were investigated. Software prototypes were developed and integrated into distinct streams of reseach ; projects...to study complex sound archives spanning large spatial and temporal scales. A new post processing method for detection and classifcation was also...false positive rates. HK-ANN was successfully tested for a large minke whale dataset, but could easily be used on other signal types. Various

Optical fiber sensor technique for strain measurement during materials deposition, chemical reaction, and relaxation

DOEpatents

Butler, M.A.; Ginley, D.S.

1988-01-21

Laser light from a common source is split and conveyed through two similar optical fibers and emitted at their respective ends to form an interference pattern, one of the optical fibers having a portion thereof subjected to a strain. Changes in the strain cause changes in the optical path length of the strain fiber, and generate corresponding changes in the interference pattern. The interference pattern is received and transduced into signals representative of fringe shifts corresponding to changes in the strain experienced by the strained one of the optical fibers. These signals are then processed to evaluate strain as a function of time, typical examples of the application of the apparatus including electrodeposition of a metallic film on a conductive surface provided on the outside of the optical fiber being strained, so that strains generated in the optical fiber during the course of the electrodeposition are measurable as a function of time. In one aspect of the invention, signals relating to the fringe shift are stored for subsequent processing and analysis, whereas in another aspect of the invention the signals are processed for real-time display of the strain changes under study. 9 figs.

Dynamic fiber Bragg grating strain sensor interrogation with real-time measurement

NASA Astrophysics Data System (ADS)

Park, Jinwoo; Kwon, Yong Seok; Ko, Myeong Ock; Jeon, Min Yong

2017-11-01

We demonstrate a 1550 nm band resonance Fourier-domain mode-locked (FDML) fiber laser with fiber Bragg grating (FBG) array. Using the FDML fiber laser, we successfully demonstrate real-time monitoring of dynamic FBG strain sensor interrogation for structural health monitoring. The resonance FDML fiber laser consists of six multiplexed FBGs, which are arranged in series with delay fiber lengths. It is operated by driving the fiber Fabry-Perot tunable filter (FFP-TF) with a sinusoidal waveform at a frequency corresponding to the round-trip time of the laser cavity. Each FBG forms a laser cavity independently in the FDML fiber laser because the light travels different length for each FBG. The very closely positioned two FBGs in a pair are operated simultaneously with a frequency in the FDML fiber laser. The spatial positions of the sensing pair can be distinguished from the variation of the applied frequency to the FFP-TF. One of the FBGs in the pair is used as a reference signal and the other one is fixed on the piezoelectric transducer stack to apply the dynamic strain. We successfully achieve real-time measurement of the abrupt change of the frequencies applied to the FBG without any signal processing delay. The real-time monitoring system is displayed simultaneously on the monitor for the variation of the two peaks, the modulation interval of the two peaks, and their fast Fourier transform spectrum. The frequency resolution of the dynamic variation could reach up to 0.5 Hz for 2 s integration time. It depends on the integration time to measure the dynamic variation. We believe that the real-time monitoring system will have a potential application for structural health monitoring.

Improved particle swarm optimization algorithm for android medical care IOT using modified parameters.

PubMed

Sung, Wen-Tsai; Chiang, Yen-Chun

2012-12-01

This study examines wireless sensor network with real-time remote identification using the Android study of things (HCIOT) platform in community healthcare. An improved particle swarm optimization (PSO) method is proposed to efficiently enhance physiological multi-sensors data fusion measurement precision in the Internet of Things (IOT) system. Improved PSO (IPSO) includes: inertia weight factor design, shrinkage factor adjustment to allow improved PSO algorithm data fusion performance. The Android platform is employed to build multi-physiological signal processing and timely medical care of things analysis. Wireless sensor network signal transmission and Internet links allow community or family members to have timely medical care network services.

Strong and Long Makes Short: Strong-Pump Strong-Probe Spectroscopy.

PubMed

Gelin, Maxim F; Egorova, Dassia; Domcke, Wolfgang

2011-01-20

We propose a new time-domain spectroscopic technique that is based on strong pump and probe pulses. The strong-pump strong-probe (SPSP) technique provides temporal resolution that is not limited by the durations of the pump and probe pulses. By numerically exact simulations of SPSP signals for a multilevel vibronic model, we show that the SPSP signals exhibit electronic and vibrational beatings on time scales which are significantly shorter than the pulse durations. This suggests the possible application of SPSP spectroscopy for the real-time investigation of molecular processes that cannot be temporally resolved by pump-probe spectroscopy with weak pump and probe pulses.

Real-Time Reconfigurable Adaptive Speech Recognition Command and Control Apparatus and Method

NASA Technical Reports Server (NTRS)

Salazar, George A. (Inventor); Haynes, Dena S. (Inventor); Sommers, Marc J. (Inventor)

1998-01-01

An adaptive speech recognition and control system and method for controlling various mechanisms and systems in response to spoken instructions and in which spoken commands are effective to direct the system into appropriate memory nodes, and to respective appropriate memory templates corresponding to the voiced command is discussed. Spoken commands from any of a group of operators for which the system is trained may be identified, and voice templates are updated as required in response to changes in pronunciation and voice characteristics over time of any of the operators for which the system is trained. Provisions are made for both near-real-time retraining of the system with respect to individual terms which are determined not be positively identified, and for an overall system training and updating process in which recognition of each command and vocabulary term is checked, and in which the memory templates are retrained if necessary for respective commands or vocabulary terms with respect to an operator currently using the system. In one embodiment, the system includes input circuitry connected to a microphone and including signal processing and control sections for sensing the level of vocabulary recognition over a given period and, if recognition performance falls below a given level, processing audio-derived signals for enhancing recognition performance of the system.

Exploratory data analysis of acceleration signals to select light-weight and accurate features for real-time activity recognition on smartphones.

PubMed

Khan, Adil Mehmood; Siddiqi, Muhammad Hameed; Lee, Seok-Won

2013-09-27

Smartphone-based activity recognition (SP-AR) recognizes users' activities using the embedded accelerometer sensor. Only a small number of previous works can be classified as online systems, i.e., the whole process (pre-processing, feature extraction, and classification) is performed on the device. Most of these online systems use either a high sampling rate (SR) or long data-window (DW) to achieve high accuracy, resulting in short battery life or delayed system response, respectively. This paper introduces a real-time/online SP-AR system that solves this problem. Exploratory data analysis was performed on acceleration signals of 6 activities, collected from 30 subjects, to show that these signals are generated by an autoregressive (AR) process, and an accurate AR-model in this case can be built using a low SR (20 Hz) and a small DW (3 s). The high within class variance resulting from placing the phone at different positions was reduced using kernel discriminant analysis to achieve position-independent recognition. Neural networks were used as classifiers. Unlike previous works, true subject-independent evaluation was performed, where 10 new subjects evaluated the system at their homes for 1 week. The results show that our features outperformed three commonly used features by 40% in terms of accuracy for the given SR and DW.

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

NASA Technical Reports Server (NTRS)

Harrivel, Angela; Hearn, Tristan

2013-01-01

Functional near infrared spectroscopy (fNIRS) is an emerging optical neuroimaging technology that indirectly measures neuronal activity in the cortex via neurovascular coupling. It quantifies hemoglobin concentration ([Hb]) and thus measures the same hemodynamic response as functional magnetic resonance imaging (fMRI), but is portable, non-confining, relatively inexpensive, and is appropriate for long-duration monitoring and use at the bedside. Like fMRI, it is noninvasive and safe for repeated measurements. Patterns of [Hb] changes are used to classify cognitive state. Thus, fNIRS technology offers much potential for application in operational contexts. For instance, the use of fNIRS to detect the mental state of commercial aircraft operators in near real time could allow intelligent flight decks of the future to optimally support human performance in the interest of safety by responding to hazardous mental states of the operator. However, many opportunities remain for improving robustness and reliability. It is desirable to reduce the impact of motion and poor optical coupling of probes to the skin. Such artifacts degrade signal quality and thus cognitive state classification accuracy. Field application calls for further development of algorithms and filters for the automation of bad channel detection and dynamic artifact removal. This work introduces a novel adaptive filter method for automated real-time fNIRS signal quality detection and improvement. The output signal (after filtering) will have had contributions from motion and poor coupling reduced or removed, thus leaving a signal more indicative of changes due to hemodynamic brain activations of interest. Cognitive state classifications based on these signals reflect brain activity more reliably. The filter has been tested successfully with both synthetic and real human subject data, and requires no auxiliary measurement. This method could be implemented as a real-time filtering option or bad channel rejection feature of software used with frequency domain fNIRS instruments for signal acquisition and processing. Use of this method could improve the reliability of any operational or real-world application of fNIRS in which motion is an inherent part of the functional task of interest. Other optical diagnostic techniques (e.g., for NIR medical diagnosis) also may benefit from the reduction of probe motion artifact during any use in which motion avoidance would be impractical or limit usability.

A real-time signal combining system for Ka-band feed arrays using maximum-likelihood weight estimates

NASA Technical Reports Server (NTRS)

Vilnrotter, V. A.; Rodemich, E. R.

1990-01-01

A real-time digital signal combining system for use with Ka-band feed arrays is proposed. The combining system attempts to compensate for signal-to-noise ratio (SNR) loss resulting from antenna deformations induced by gravitational and atmospheric effects. The combining weights are obtained directly from the observed samples by using a sliding-window implementation of a vector maximum-likelihood parameter estimator. It is shown that with averaging times of about 0.1 second, combining loss for a seven-element array can be limited to about 0.1 dB in a realistic operational environment. This result suggests that the real-time combining system proposed here is capable of recovering virtually all of the signal power captured by the feed array, even in the presence of severe wind gusts and similar disturbances.

Digital Signal Processing by Virtual Instrumentation of a MEMS Magnetic Field Sensor for Biomedical Applications

PubMed Central

Juárez-Aguirre, Raúl; Domínguez-Nicolás, Saúl M.; Manjarrez, Elías; Tapia, Jesús A.; Figueras, Eduard; Vázquez-Leal, Héctor; Aguilera-Cortés, Luz A.; Herrera-May, Agustín L.

2013-01-01

We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing. The virtual instrument includes an algorithm to implement different configurations of infinite impulse response (IIR) filters. The PCB contains a precision instrumentation amplifier, a demodulator, a low-pass filter (LPF) and a buffer with operational amplifier. The proposed prototype is used for real-time non-invasive monitoring of magnetic flux density in the thoracic cage of rats. The response of the rat respiratory magnetogram displays a similar behavior as the rat electromyogram (EMG). PMID:24196434

Digital signal processing by virtual instrumentation of a MEMS magnetic field sensor for biomedical applications.

PubMed

Juárez-Aguirre, Raúl; Domínguez-Nicolás, Saúl M; Manjarrez, Elías; Tapia, Jesús A; Figueras, Eduard; Vázquez-Leal, Héctor; Aguilera-Cortés, Luz A; Herrera-May, Agustín L

2013-11-05

We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing. The virtual instrument includes an algorithm to implement different configurations of infinite impulse response (IIR) filters. The PCB contains a precision instrumentation amplifier, a demodulator, a low-pass filter (LPF) and a buffer with operational amplifier. The proposed prototype is used for real-time non-invasive monitoring of magnetic flux density in the thoracic cage of rats. The response of the rat respiratory magnetogram displays a similar behavior as the rat electromyogram (EMG).

Spin-Off Successes of SETI Research at Berkeley

NASA Astrophysics Data System (ADS)

Douglas, K. A.; Anderson, D. P.; Bankay, R.; Chen, H.; Cobb, J.; Korpela, E. J.; Lebofsky, M.; Parsons, A.; von Korff, J.; Werthimer, D.

2009-12-01

Our group contributes to the Search for Extra-Terrestrial Intelligence (SETI) by developing and using world-class signal processing computers to analyze data collected on the Arecibo telescope. Although no patterned signal of extra-terrestrial origin has yet been detected, and the immediate prospects for making such a detection are highly uncertain, the SETI@home project has nonetheless proven the value of pursuing such research through its impact on the fields of distributed computing, real-time signal processing, and radio astronomy. The SETI@home project has spun off the Center for Astronomy Signal Processing and Electronics Research (CASPER) and the Berkeley Open Infrastructure for Networked Computing (BOINC), both of which are responsible for catalyzing a smorgasbord of new research in scientific disciplines in countries around the world. Futhermore, the data collected and archived for the SETI@home project is proving valuable in data-mining experiments for mapping neutral galatic hydrogen and for detecting black-hole evaporation.

Stanford Hardware Development Program

NASA Technical Reports Server (NTRS)

Peterson, A.; Linscott, I.; Burr, J.

1986-01-01

Architectures for high performance, digital signal processing, particularly for high resolution, wide band spectrum analysis were developed. These developments are intended to provide instrumentation for NASA's Search for Extraterrestrial Intelligence (SETI) program. The real time signal processing is both formal and experimental. The efficient organization and optimal scheduling of signal processing algorithms were investigated. The work is complemented by efforts in processor architecture design and implementation. A high resolution, multichannel spectrometer that incorporates special purpose microcoded signal processors is being tested. A general purpose signal processor for the data from the multichannel spectrometer was designed to function as the processing element in a highly concurrent machine. The processor performance required for the spectrometer is in the range of 1000 to 10,000 million instructions per second (MIPS). Multiple node processor configurations, where each node performs at 100 MIPS, are sought. The nodes are microprogrammable and are interconnected through a network with high bandwidth for neighboring nodes, and medium bandwidth for nodes at larger distance. The implementation of both the current mutlichannel spectrometer and the signal processor as Very Large Scale Integration CMOS chip sets was commenced.

Improved Signal Processing Technique Leads to More Robust Self Diagnostic Accelerometer System

NASA Technical Reports Server (NTRS)

Tokars, Roger; Lekki, John; Jaros, Dave; Riggs, Terrence; Evans, Kenneth P.

2010-01-01

The self diagnostic accelerometer (SDA) is a sensor system designed to actively monitor the health of an accelerometer. In this case an accelerometer is considered healthy if it can be determined that it is operating correctly and its measurements may be relied upon. The SDA system accomplishes this by actively monitoring the accelerometer for a variety of failure conditions including accelerometer structural damage, an electrical open circuit, and most importantly accelerometer detachment. In recent testing of the SDA system in emulated engine operating conditions it has been found that a more robust signal processing technique was necessary. An improved accelerometer diagnostic technique and test results of the SDA system utilizing this technique are presented here. Furthermore, the real time, autonomous capability of the SDA system to concurrently compensate for effects from real operating conditions such as temperature changes and mechanical noise, while monitoring the condition of the accelerometer health and attachment, will be demonstrated.

Robust Nonlinear Causality Analysis of Nonstationary Multivariate Physiological Time Series.

PubMed

Schack, Tim; Muma, Michael; Feng, Mengling; Guan, Cuntai; Zoubir, Abdelhak M

2018-06-01

An important research area in biomedical signal processing is that of quantifying the relationship between simultaneously observed time series and to reveal interactions between the signals. Since biomedical signals are potentially nonstationary and the measurements may contain outliers and artifacts, we introduce a robust time-varying generalized partial directed coherence (rTV-gPDC) function. The proposed method, which is based on a robust estimator of the time-varying autoregressive (TVAR) parameters, is capable of revealing directed interactions between signals. By definition, the rTV-gPDC only displays the linear relationships between the signals. We therefore suggest to approximate the residuals of the TVAR process, which potentially carry information about the nonlinear causality by a piece-wise linear time-varying moving-average model. The performance of the proposed method is assessed via extensive simulations. To illustrate the method's applicability to real-world problems, it is applied to a neurophysiological study that involves intracranial pressure, arterial blood pressure, and brain tissue oxygenation level (PtiO2) measurements. The rTV-gPDC reveals causal patterns that are in accordance with expected cardiosudoral meachanisms and potentially provides new insights regarding traumatic brain injuries. The rTV-gPDC is not restricted to the above problem but can be useful in revealing interactions in a broad range of applications.

Online frequency estimation with applications to engine and generator sets

NASA Astrophysics Data System (ADS)

Manngård, Mikael; Böling, Jari M.

2017-07-01

Frequency and spectral analysis based on the discrete Fourier transform is a fundamental task in signal processing and machine diagnostics. This paper aims at presenting computationally efficient methods for real-time estimation of stationary and time-varying frequency components in signals. A brief survey of the sliding time window discrete Fourier transform and Goertzel filter is presented, and two filter banks consisting of: (i) sliding time window Goertzel filters (ii) infinite impulse response narrow bandpass filters are proposed for estimating instantaneous frequencies. The proposed methods show excellent results on both simulation studies and on a case study using angular speed data measurements of the crankshaft of a marine diesel engine-generator set.

A comparative evaluation between real time Roche COBas TAQMAN 48 HCV and bDNA Bayer Versant HCV 3.0.

PubMed

Giraldi, Cristina; Noto, Alessandra; Tenuta, Robert; Greco, Francesca; Perugini, Daniela; Spadafora, Mario; Bianco, Anna Maria Lo; Savino, Olga; Natale, Alfonso

2006-10-01

The HCV virus is a common human pathogen made of a single stranded RNA genome with 9600nt. This work compared two different commercial methods used for HCV viral load, the bDNA Bayer Versant HCV 3.0 and the RealTime Roche COBAS TaqMan 48 HCV. We compared the reproducibility and linearity of the two methods. Seventy-five plasma samples with genotypes 1 to 4, which represent the population (45% genotype 1; 24% genotype 2; 13% genotype 3; 18% genotype 4) were directly processed with the Versanto method based upon signal amplification; the same samples were first extracted (COBAS Ampliprep - TNAI) and then amplified using RealTime PCR (COBAS TaqMan 48). The results obtained indicate the same performance for both methods if they have genotype 1, but in samples with genotypes 2, 3 and 4 the RealTime PCR Roche method gave an underestimation in respect to the Bayer bDNA assay.

Nondestructive online testing method for friction stir welding using acoustic emission

NASA Astrophysics Data System (ADS)

Levikhina, Anastasiya

2017-12-01

The paper reviews the possibility of applying the method of acoustic emission for online monitoring of the friction stir welding process. It is shown that acoustic emission allows the detection of weld defects and their location in real time. The energy of an acoustic signal and the median frequency are suggested to be used as informative parameters. The method of calculating the median frequency with the use of a short time Fourier transform is applied for the identification of correlations between the defective weld structure and properties of the acoustic emission signals received during welding.

Real-time implementation of electromyogram pattern recognition as a control command of man-machine interface.

PubMed

Chang, G C; Kang, W J; Luh, J J; Cheng, C K; Lai, J S; Chen, J J; Kuo, T S

1996-10-01

The purpose of this study was to develop a real-time electromyogram (EMG) discrimination system to provide control commands for man-machine interface applications. A host computer with a plug-in data acquisition and processing board containing a TMS320 C31 floating-point digital signal processor was used to attain real-time EMG classification. Two-channel EMG signals were collected by two pairs of surface electrodes located bilaterally between the sternocleidomastoid and the upper trapezius. Five motions of the neck and shoulders were discriminated for each subject. The zero-crossing rate was employed to detect the onset of muscle contraction. The cepstral coefficients, derived from autoregressive coefficients and estimated by a recursive least square algorithm, were used as the recognition features. These features were then discriminated using a modified maximum likelihood distance classifier. The total response time of this EMG discrimination system was achieved about within 0.17 s. Four able bodied and two C5/6 quadriplegic subjects took part in the experiment, and achieved 95% mean recognition rate in discrimination between the five specific motions. The response time and the reliability of recognition indicate that this system has the potential to discriminate body motions for man-machine interface applications.

AN OPTIMIZED 64X64 POINT TWO-DIMENSIONAL FAST FOURIER TRANSFORM

NASA Technical Reports Server (NTRS)

Miko, J.

1994-01-01

Scientists at Goddard have developed an efficient and powerful program-- An Optimized 64x64 Point Two-Dimensional Fast Fourier Transform-- which combines the performance of real and complex valued one-dimensional Fast Fourier Transforms (FFT's) to execute a two-dimensional FFT and its power spectrum coefficients. These coefficients can be used in many applications, including spectrum analysis, convolution, digital filtering, image processing, and data compression. The program's efficiency results from its technique of expanding all arithmetic operations within one 64-point FFT; its high processing rate results from its operation on a high-speed digital signal processor. For non-real-time analysis, the program requires as input an ASCII data file of 64x64 (4096) real valued data points. As output, this analysis produces an ASCII data file of 64x64 power spectrum coefficients. To generate these coefficients, the program employs a row-column decomposition technique. First, it performs a radix-4 one-dimensional FFT on each row of input, producing complex valued results. Then, it performs a one-dimensional FFT on each column of these results to produce complex valued two-dimensional FFT results. Finally, the program sums the squares of the real and imaginary values to generate the power spectrum coefficients. The program requires a Banshee accelerator board with 128K bytes of memory from Atlanta Signal Processors (404/892-7265) installed on an IBM PC/AT compatible computer (DOS ver. 3.0 or higher) with at least one 16-bit expansion slot. For real-time operation, an ASPI daughter board is also needed. The real-time configuration reads 16-bit integer input data directly into the accelerator board, operating on 64x64 point frames of data. The program's memory management also allows accumulation of the coefficient results. The real-time processing rate to calculate and accumulate the 64x64 power spectrum output coefficients is less than 17.0 mSec. Documentation is included in the price of the program. Source code is written in C, 8086 Assembly, and Texas Instruments TMS320C30 Assembly Languages. This program is available on a 5.25 inch 360K MS-DOS format diskette. IBM and IBM PC are registered trademarks of International Business Machines. MS-DOS is a registered trademark of Microsoft Corporation.

Development and application of a modified wireless tracer for disaster prevention

NASA Astrophysics Data System (ADS)

Chung Yang, Han; Su, Chih Chiang

2016-04-01

Typhoon-induced flooding causes water overflow in a river channel, which results in general and bridge scour and soil erosion, thus leading to bridge failure, debris flow and landslide collapse. Therefore, dynamic measurement technology should be developed to assess scour in channels and landslide as a disaster-prevention measure against bridge failure and debris flow. This paper presents a wireless tracer that enables monitoring general scour in river channels and soil erosion in hillsides. The wireless tracer comprises a wireless high-power radio modem, various electronic components, and a self-designed printed circuit board that are all combined with a 9-V battery pack and an auto switch. The entire device is sealed in a jar by silicon. After it was modified, the wireless tracer underwent the following tests for practical applications: power continuation and durability, water penetration, and signal transmission during floating. A regression correlation between the wireless tracer's transmission signal and distance was also established. This device can be embedded at any location where scouring is monitored, and, in contrast to its counterparts that detect scour depth by identifying and analyzing received signals, it enables real-time observation of the scouring process. In summary, the wireless tracer developed in this study provides a dynamic technology for real-time monitoring of scouring (or erosion) and forecasting of landslide hazards. Keywords: wireless tracer; scour; real-time monitoring; landslide hazard.

Vehicular headways on signalized intersections: theory, models, and reality

NASA Astrophysics Data System (ADS)

Krbálek, Milan; Šleis, Jiří

2015-01-01

We discuss statistical properties of vehicular headways measured on signalized crossroads. On the basis of mathematical approaches, we formulate theoretical and empirically inspired criteria for the acceptability of theoretical headway distributions. Sequentially, the multifarious families of statistical distributions (commonly used to fit real-road headway statistics) are confronted with these criteria, and with original empirical time clearances gauged among neighboring vehicles leaving signal-controlled crossroads after a green signal appears. Using three different numerical schemes, we demonstrate that an arrangement of vehicles on an intersection is a consequence of the general stochastic nature of queueing systems, rather than a consequence of traffic rules, driver estimation processes, or decision-making procedures.

Kurtosis-Based Blind Source Extraction of Complex Non-Circular Signals with Application in EEG Artifact Removal in Real-Time

PubMed Central

Javidi, Soroush; Mandic, Danilo P.; Took, Clive Cheong; Cichocki, Andrzej

2011-01-01

A new class of complex domain blind source extraction algorithms suitable for the extraction of both circular and non-circular complex signals is proposed. This is achieved through sequential extraction based on the degree of kurtosis and in the presence of non-circular measurement noise. The existence and uniqueness analysis of the solution is followed by a study of fast converging variants of the algorithm. The performance is first assessed through simulations on well understood benchmark signals, followed by a case study on real-time artifact removal from EEG signals, verified using both qualitative and quantitative metrics. The results illustrate the power of the proposed approach in real-time blind extraction of general complex-valued sources. PMID:22319461

Optimal causal filtering for 1 /fα-type noise in single-electrode EEG signals.

PubMed

Paris, Alan; Atia, George; Vosoughi, Azadeh; Berman, Stephen A

2016-08-01

Understanding the mode of generation and the statistical structure of neurological noise is one of the central problems of biomedical signal processing. We have developed a broad class of abstract biological noise sources we call hidden simplicial tissues. In the simplest cases, such tissue emits what we have named generalized van der Ziel-McWhorter (GVZM) noise which has a roughly 1/fα spectral roll-off. Our previous work focused on the statistical structure of GVZM frequency spectra. However, causality of processing operations (i.e., dependence only on the past) is an essential requirement for real-time applications to seizure detection and brain-computer interfacing. In this paper we outline the theoretical background for optimal causal time-domain filtering of deterministic signals embedded in GVZM noise. We present some of our early findings concerning the optimal filtering of EEG signals for the detection of steady-state visual evoked potential (SSVEP) responses and indicate the next steps in our ongoing research.

Acoustic emission evolution during sliding friction of Hadfield steel single crystal

NASA Astrophysics Data System (ADS)

Lychagin, D. V.; Novitskaya, O. S.; Kolubaev, A. V.; Sizova, O. V.

2017-12-01

Friction is a complex dynamic process. Direct observation of processes occurring in the friction zone is impossible due to a small size of a real contact area and, as a consequence, requires various additional methods applicable to monitor a tribological contact state. One of such methods consists in the analysis of acoustic emission data of a tribological contact. The use of acoustic emission entails the problem of interpreting physical sources of signals. In this paper, we analyze the evolution of acoustic emission signal frames in friction of Hadfield steel single crystals. The chosen crystallographic orientation of single crystals enables to identify four stages related to friction development as well as acoustic emission signals inherent in these stages. Acoustic emission signal parameters are studied in more detail by the short-time Fourier transform used to determine the time variation of the median frequency and its power spectrum. The results obtained will facilitate the development of a more precise method to monitor the tribological contact based on the acoustic emission method.

Antenna data storage concept for phased array radio astronomical instruments

NASA Astrophysics Data System (ADS)

Gunst, André W.; Kruithof, Gert H.

2018-04-01

Low frequency Radio Astronomy instruments like LOFAR and SKA-LOW use arrays of dipole antennas for the collection of radio signals from the sky. Due to the large number of antennas involved, the total data rate produced by all the antennas is enormous. Storage of the antenna data is both economically and technologically infeasible using the current state of the art storage technology. Therefore, real-time processing of the antenna voltage data using beam forming and correlation is applied to achieve a data reduction throughout the signal chain. However, most science could equally well be performed using an archive of raw antenna voltage data coming straight from the A/D converters instead of capturing and processing the antenna data in real time over and over again. Trends on storage and computing technology make such an approach feasible on a time scale of approximately 10 years. The benefits of such a system approach are more science output and a higher flexibility with respect to the science operations. In this paper we present a radically new system concept for a radio telescope based on storage of raw antenna data. LOFAR is used as an example for such a future instrument.

Real-time, high frequency QRS electrocardiograph with reduced amplitude zone detection

NASA Technical Reports Server (NTRS)

Schlegel, Todd T. (Inventor); DePalma, Jude L. (Inventor); Moradi, Saeed (Inventor)

2009-01-01

Real time cardiac electrical data are received from a patient, manipulated to determine various useful aspects of the ECG signal, and displayed in real time in a useful form on a computer screen or monitor. The monitor displays the high frequency data from the QRS complex in units of microvolts, juxtaposed with a display of conventional ECG data in units of millivolts or microvolts. The high frequency data are analyzed for their root mean square (RMS) voltage values and the discrete RMS values and related parameters are displayed in real time. The high frequency data from the QRS complex are analyzed with imbedded algorithms to determine the presence or absence of reduced amplitude zones, referred to herein as ''RAZs''. RAZs are displayed as ''go, no-go'' signals on the computer monitor. The RMS and related values of the high frequency components are displayed as time varying signals, and the presence or absence of RAZs may be similarly displayed over time.

A QRS Detection and R Point Recognition Method for Wearable Single-Lead ECG Devices.

PubMed

Chen, Chieh-Li; Chuang, Chun-Te

2017-08-26

In the new-generation wearable Electrocardiogram (ECG) system, signal processing with low power consumption is required to transmit data when detecting dangerous rhythms and to record signals when detecting abnormal rhythms. The QRS complex is a combination of three of the graphic deflection seen on a typical ECG. This study proposes a real-time QRS detection and R point recognition method with low computational complexity while maintaining a high accuracy. The enhancement of QRS segments and restraining of P and T waves are carried out by the proposed ECG signal transformation, which also leads to the elimination of baseline wandering. In this study, the QRS fiducial point is determined based on the detected crests and troughs of the transformed signal. Subsequently, the R point can be recognized based on four QRS waveform templates and preliminary heart rhythm classification can be also achieved at the same time. The performance of the proposed approach is demonstrated using the benchmark of the MIT-BIH Arrhythmia Database, where the QRS detected sensitivity (Se) and positive prediction (+P) are 99.82% and 99.81%, respectively. The result reveals the approach's advantage of low computational complexity, as well as the feasibility of the real-time application on a mobile phone and an embedded system.

Real-time bicycle detection at signalized intersections using thermal imaging technology

NASA Astrophysics Data System (ADS)

Collaert, Robin

2013-02-01

More and more governments and authorities around the world are promoting the use of bicycles in cities, as this is healthy for the bicyclist and improves the quality of life in general. Safety and efficiency of bicyclists has become a major focus. To achieve this, there is a need for a smarter approach towards the control of signalized intersections. Various traditional detection technologies, such as video, microwave radar and electromagnetic loops, can be used to detect vehicles at signalized intersections, but none of these can consistently separate bikes from other traffic, day and night and in various weather conditions. As bikes should get a higher priority and also require longer green time to safely cross the signalized intersection, traffic managers are looking for alternative detection systems that can make the distinction between bicycles and other vehicles near the stop bar. In this paper, the drawbacks of a video-based approach are presented, next to the benefits of a thermal-video-based approach for vehicle presence detection with separation of bicycles. Also, the specific technical challenges are highlighted in developing a system that combines thermal image capturing, image processing and output triggering to the traffic light controller in near real-time and in a single housing.

Parameter Estimation for Real Filtered Sinusoids

DTIC Science & Technology

1997-09-01

Statistical Signal Processing: Detection, Estimation and Time Series Analysis. New York: Addison-Wesley, 1991. 74. Serway , Raymond A . Physics for...Dr. Yung Kee Yeo, Dean’s Representative Dr. Robert A . Calico, Jr., Dean Table of Contents Page List of Abbreviations...Contributions ....... ...................... 5-4 5.4 Summary ........ ............................. 5-6 Appendix A . Vector-Matrix Differentiation

ARSRP Signal Processing Software

DTIC Science & Technology

1993-02-01

Hardcopy of plot? Y or N : Y Enter name of postscript output file. : wave2 .ps Postscript file created. Another plot? Y or N :N 19 The two plots...created and stored in wavel.ps and wave2 .ps are shown in Figures 4 and 5 with the corresponding MSS real- time plots from the ARSRP Monitoring Support

Integrated test system of infrared and laser data based on USB 3.0

NASA Astrophysics Data System (ADS)

Fu, Hui Quan; Tang, Lin Bo; Zhang, Chao; Zhao, Bao Jun; Li, Mao Wen

2017-07-01

Based on USB3.0, this paper presents the design method of an integrated test system for both infrared image data and laser signal data processing module. The core of the design is FPGA logic control, the design uses dual-chip DDR3 SDRAM to achieve high-speed laser data cache, and receive parallel LVDS image data through serial-to-parallel conversion chip, and it achieves high-speed data communication between the system and host computer through the USB3.0 bus. The experimental results show that the developed PC software realizes the real-time display of 14-bit LVDS original image after 14-to-8 bit conversion and JPEG2000 compressed image after decompression in software, and can realize the real-time display of the acquired laser signal data. The correctness of the test system design is verified, indicating that the interface link is normal.

The NIST Real-Time Control System (RCS): A Reference Model Architecture for Computational Intelligence

NASA Technical Reports Server (NTRS)

Albus, James S.

1996-01-01

The Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades defines a reference model architecture for design and analysis of complex intelligent control systems. The RCS architecture consists of a hierarchically layered set of functional processing modules connected by a network of communication pathways. The primary distinguishing feature of the layers is the bandwidth of the control loops. The characteristic bandwidth of each level is determined by the spatial and temporal integration window of filters, the temporal frequency of signals and events, the spatial frequency of patterns, and the planning horizon and granularity of the planners that operate at each level. At each level, tasks are decomposed into sequential subtasks, to be performed by cooperating sets of subordinate agents. At each level, signals from sensors are filtered and correlated with spatial and temporal features that are relevant to the control function being implemented at that level.

Listening to the Deep: live monitoring of ocean noise and cetacean acoustic signals.

PubMed

André, M; van der Schaar, M; Zaugg, S; Houégnigan, L; Sánchez, A M; Castell, J V

2011-01-01

The development and broad use of passive acoustic monitoring techniques have the potential to help assessing the large-scale influence of artificial noise on marine organisms and ecosystems. Deep-sea observatories have the potential to play a key role in understanding these recent acoustic changes. LIDO (Listening to the Deep Ocean Environment) is an international project that is allowing the real-time long-term monitoring of marine ambient noise as well as marine mammal sounds at cabled and standalone observatories. Here, we present the overall development of the project and the use of passive acoustic monitoring (PAM) techniques to provide the scientific community with real-time data at large spatial and temporal scales. Special attention is given to the extraction and identification of high frequency cetacean echolocation signals given the relevance of detecting target species, e.g. beaked whales, in mitigation processes, e.g. during military exercises. Copyright © 2011. Published by Elsevier Ltd.

Wearable Biomedical Measurement Systems for Assessment of Mental Stress of Combatants in Real Time

PubMed Central

Seoane, Fernando; Mohino-Herranz, Inmaculada; Ferreira, Javier; Alvarez, Lorena; Buendia, Ruben; Ayllón, David; Llerena, Cosme; Gil-Pita, Roberto

2014-01-01

The Spanish Ministry of Defense, through its Future Combatant program, has sought to develop technology aids with the aim of extending combatants' operational capabilities. Within this framework the ATREC project funded by the “Coincidente” program aims at analyzing diverse biometrics to assess by real time monitoring the stress levels of combatants. This project combines multidisciplinary disciplines and fields, including wearable instrumentation, textile technology, signal processing, pattern recognition and psychological analysis of the obtained information. In this work the ATREC project is described, including the different execution phases, the wearable biomedical measurement systems, the experimental setup, the biomedical signal analysis and speech processing performed. The preliminary results obtained from the data analysis collected during the first phase of the project are presented, indicating the good classification performance exhibited when using features obtained from electrocardiographic recordings and electrical bioimpedance measurements from the thorax. These results suggest that cardiac and respiration activity offer better biomarkers for assessment of stress than speech, galvanic skin response or skin temperature when recorded with wearable biomedical measurement systems. PMID:24759113

Wearable biomedical measurement systems for assessment of mental stress of combatants in real time.

PubMed

Seoane, Fernando; Mohino-Herranz, Inmaculada; Ferreira, Javier; Alvarez, Lorena; Buendia, Ruben; Ayllón, David; Llerena, Cosme; Gil-Pita, Roberto

2014-04-22

The Spanish Ministry of Defense, through its Future Combatant program, has sought to develop technology aids with the aim of extending combatants' operational capabilities. Within this framework the ATREC project funded by the "Coincidente" program aims at analyzing diverse biometrics to assess by real time monitoring the stress levels of combatants. This project combines multidisciplinary disciplines and fields, including wearable instrumentation, textile technology, signal processing, pattern recognition and psychological analysis of the obtained information. In this work the ATREC project is described, including the different execution phases, the wearable biomedical measurement systems, the experimental setup, the biomedical signal analysis and speech processing performed. The preliminary results obtained from the data analysis collected during the first phase of the project are presented, indicating the good classification performance exhibited when using features obtained from electrocardiographic recordings and electrical bioimpedance measurements from the thorax. These results suggest that cardiac and respiration activity offer better biomarkers for assessment of stress than speech, galvanic skin response or skin temperature when recorded with wearable biomedical measurement systems.

A wearable biofeedback control system based body area network for freestyle swimming.

PubMed

Rui Li; Zibo Cai; WeeSit Lee; Lai, Daniel T H

2016-08-01

Wearable posture measurement units are capable of enabling real-time performance evaluation and providing feedback to end users. This paper presents a wearable feedback prototype designed for freestyle swimming with focus on trunk rotation measurement. The system consists of a nine-degree-of-freedom inertial sensor, which is built in a central data collection and processing unit, and two vibration motors for delivering real-time feedback. Theses devices form a fundamental body area network (BAN). In the experiment setup, four recreational swimmers were asked to do two sets of 4 x 25m freestyle swimming without and with feedback provided respectively. Results showed that real-time biofeedback mechanism improves swimmers kinematic performance by an average of 4.5% reduction in session time. Swimmers can gradually adapt to feedback signals, and the biofeedback control system can be employed in swimmers daily training for fitness maintenance.

Real-time noble gas release signaling rock deformation

NASA Astrophysics Data System (ADS)

Bauer, S. J.; Gardner, W. P.; Lee, H.

2016-12-01

We present empirical results/relationships of rock strain, microfracture density, acoustic emissions, and noble gas release from laboratory triaxial experiments for a granite and basalt. Noble gases are contained in most crustal rock at inter/intra granular sites, their release during natural and manmade stress and strain changes represents a signal of brittle/semi brittle deformation. The gas composition depends on lithology, geologic history and age, fluids present, and uranium, thorium and potassium-40 concentrations in the rocks that affect radiogenic noble gases (helium, argon) production. Noble gas emission and its relationship to crustal processes have been studied, including correlations to tectonic velocities and qualitative estimates of deep permeability from surface measurements, finger prints of nuclear weapon detonation, and as potential precursory signals to earthquakes attributed to gas release due to pre-seismic stress, dilatancy and/or rock fracturing. Helium emission has been shown as a precursor of volcanic activity. Real-time noble gas release is observed using an experimental system utilizing mass spectrometers to measure gases released during triaxial rock deformation. Noble gas release is shown to represent a sensitive precursor signal of rock deformation by relating real-time noble gas release to stress-strain state changes and acoustic emissions. We propose using noble gas release to also signal rock deformation in boreholes, mines and nuclear waste repositories. We postulate each rock exhibits a gas release signature which is microstructure, stress/strain state, and or permanent deformation dependent. Such relationships, when calibrated, may be used to sense rock deformation and then develop predictive models. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corp., for the US Dept. of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. SAND2016-7468 A

A portable platform to collect and review behavioral data simultaneously with neurophysiological signals.

PubMed

Tianxiao Jiang; Siddiqui, Hasan; Ray, Shruti; Asman, Priscella; Ozturk, Musa; Ince, Nuri F

2017-07-01

This paper presents a portable platform to collect and review behavioral data simultaneously with neurophysiological signals. The whole system is comprised of four parts: a sensor data acquisition interface, a socket server for real-time data streaming, a Simulink system for real-time processing and an offline data review and analysis toolbox. A low-cost microcontroller is used to acquire data from external sensors such as accelerometer and hand dynamometer. The micro-controller transfers the data either directly through USB or wirelessly through a bluetooth module to a data server written in C++ for MS Windows OS. The data server also interfaces with the digital glove and captures HD video from webcam. The acquired sensor data are streamed under User Datagram Protocol (UDP) to other applications such as Simulink/Matlab for real-time analysis and recording. Neurophysiological signals such as electroencephalography (EEG), electrocorticography (ECoG) and local field potential (LFP) recordings can be collected simultaneously in Simulink and fused with behavioral data. In addition, we developed a customized Matlab Graphical User Interface (GUI) software to review, annotate and analyze the data offline. The software provides a fast, user-friendly data visualization environment with synchronized video playback feature. The software is also capable of reviewing long-term neural recordings. Other featured functions such as fast preprocessing with multithreaded filters, annotation, montage selection, power-spectral density (PSD) estimate, time-frequency map and spatial spectral map are also implemented.

Radar image processing module development program, phase 3

NASA Technical Reports Server (NTRS)

1977-01-01

The feasibility of using charge coupled devices in an IPM for processing synthetic aperture radar signals onboard the NASA Convair 990 (CV990) aircraft was demonstrated. Radar data onboard the aircraft was recorded and processed using a CCD sampler and digital tape recorder. A description of equipment and testing was provided. The derivation of the digital presum filter was documented. Photographs of the sampler/tape recorder, real time display and circuit boards in the IPM were also included.

Real-Time In Vivo Monitoring of Reactive Oxygen Species in Guard Cells.

PubMed

Park, Ky Young; Roubelakis-Angelakis, Kalliopi A

2018-01-01

The intra-/intercellular homeostasis of reactive oxygen species (ROS), and especially of superoxides (O 2 .- ) and hydrogen peroxide (O 2 .- ) participate in signalling cascades which dictate developmental processes and reactions to biotic/abiotic stresses. Polyamine oxidases terminally oxidize/back convert polyamines generating H 2 O 2 . Recently, an NADPH-oxidase/Polyamine oxidase feedback loop was identified to control oxidative burst under salinity. Thus, the real-time localization/monitoring of ROS in specific cells, such as the guard cells, can be of great interest. Here we present a detailed description of the real-time in vivo monitoring of ROS in the guard cells using H 2 O 2 - and O 2 .- specific fluorescing probes, which can be used for studying ROS accumulation generated from any source, including the amine oxidases-dependent pathway, during development and stress.

Real time non invasive imaging of fatty acid uptake in vivo

PubMed Central

Henkin, Amy H.; Cohen, Allison S.; Dubikovskaya, Elena A.; Park, Hyo Min; Nikitin, Gennady F.; Auzias, Mathieu G.; Kazantzis, Melissa; Bertozzi, Carolyn R.; Stahl, Andreas

2012-01-01

Detection and quantification of fatty acid fluxes in animal model systems following physiological, pathological, or pharmacological challenges is key to our understanding of complex metabolic networks as these macronutrients also activate transcription factors and modulate signaling cascades including insulin-sensitivity. To enable non-invasive, real-time, spatiotemporal quantitative imaging of fatty acid fluxes in animals, we created a bioactivatable molecular imaging probe based on long-chain fatty acids conjugated to a reporter molecule (luciferin). We show that this probe faithfully recapitulates cellular fatty acid uptake and can be used in animal systems as a valuable tool to localize and quantitate in real-time lipid fluxes such as intestinal fatty acid absorption and brown adipose tissue activation. This imaging approach should further our understanding of basic metabolic processes and pathological alterations in multiple disease models. PMID:22928772

Real-Time, General-Purpose, High-Speed Signal Processing Systems for Underwater Research. Proceedings of a Working Level Conference held at Supreme Allied Commander, Atlantic, Anti-Submarine Warfare Research Center (SACLANTCEN) on 18-21 September 1979. Part 1. Sessions I to III.

DTIC Science & Technology

1979-12-01

intelligent graphics terminals in real-tim processing S (e) 5-1 to 5-9 MIel ita|ger The application of high-speed processors to propagation e.piriamnts...interface SACLANTCEN CP-25 5-2 M IM M STEIGER: Intelligent graphics terminals The less desirable features of the terminal are listed below. reiatively small...hours. Dismantling of the equipment is normally performed in less than one-half hour and often while waiting to clear customs. Transportation of the

Optical non-invasive monitoring of skin blood pulsations

NASA Astrophysics Data System (ADS)

Spīgulis, Jānis

2005-08-01

Time resolved detection and analysis of the skin backscattered optical signals (remission photoplethysmography or PPG) provide rich information on skin blood volume pulsations and can serve for reliable cardiovascular assessment. The single- and multi-channel PPG concepts are discussed in this work. Simultaneous data flow from several body locations allows one to study the heartbeat pulse wave propagation in real time and evaluate the vascular resistance. Portable single-, dual- and four-channel PPG monitoring devices with special software have been designed for real-time data acquisition and processing. The clinical studies confirmed their potential in the monitoring of heart arrhythmias, drug tests, steady-state cardiovascular assessment, body fitness control, and express diagnostics of the arterial occlusions.

Optical noninvasive monitoring of skin blood pulsations

NASA Astrophysics Data System (ADS)

Spigulis, Janis

2005-04-01

Time-resolved detection and analysis of skin backscattered optical signals (remission photoplethysmography or PPG) provide rich information on skin blood volume pulsations and can serve for reliable cardiovascular assessment. Single- and multiple-channel PPG concepts are discussed. Simultaneous data flow from several locations on the human body allows us to study heartbeat pulse-wave propagation in real time and to evaluate vascular resistance. Portable single-, dual-, and four-channel PPG monitoring devices with special software have been designed for real-time data acquisition and processing. The prototype devices have been clinically studied, and their potential for monitoring heart arrhythmias, drug-efficiency tests, steady-state cardiovascular assessment, body fitness control, and express diagnostics of the arterial occlusions has been confirmed.

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

PubMed Central

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-01-01

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully. PMID:29495301

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time.

PubMed

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-02-24

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90-94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7-5.6% per millisecond, with most satellites acquired successfully.

Noiseless intensity amplification of repetitive signals by coherent addition using the temporal Talbot effect

PubMed Central

Maram, Reza; Van Howe, James; Li, Ming; Azaña, José

2014-01-01

Amplification of signal intensity is essential for initiating physical processes, diagnostics, sensing, communications and measurement. During traditional amplification, the signal is amplified by multiplying the signal carriers through an active gain process, requiring the use of an external power source. In addition, the signal is degraded by noise and distortions that typically accompany active gain processes. We show noiseless intensity amplification of repetitive optical pulse waveforms with gain from 2 to ~20 without using active gain. The proposed method uses a dispersion-induced temporal self-imaging (Talbot) effect to redistribute and coherently accumulate energy of the original repetitive waveforms into fewer replica waveforms. In addition, we show how our passive amplifier performs a real-time average of the wave-train to reduce its original noise fluctuation, as well as enhances the extinction ratio of pulses to stand above the noise floor. Our technique is applicable to repetitive waveforms in any spectral region or wave system. PMID:25319207

Imaging synthetic aperture radar

DOEpatents

Burns, Bryan L.; Cordaro, J. Thomas

1997-01-01

A linear-FM SAR imaging radar method and apparatus to produce a real-time image by first arranging the returned signals into a plurality of subaperture arrays, the columns of each subaperture array having samples of dechirped baseband pulses, and further including a processing of each subaperture array to obtain coarse-resolution in azimuth, then fine-resolution in range, and lastly, to combine the processed subapertures to obtain the final fine-resolution in azimuth. Greater efficiency is achieved because both the transmitted signal and a local oscillator signal mixed with the returned signal can be varied on a pulse-to-pulse basis as a function of radar motion. Moreover, a novel circuit can adjust the sampling location and the A/D sample rate of the combined dechirped baseband signal which greatly reduces processing time and hardware. The processing steps include implementing a window function, stabilizing either a central reference point and/or all other points of a subaperture with respect to doppler frequency and/or range as a function of radar motion, sorting and compressing the signals using a standard fourier transforms. The stabilization of each processing part is accomplished with vector multiplication using waveforms generated as a function of radar motion wherein these waveforms may be synthesized in integrated circuits. Stabilization of range migration as a function of doppler frequency by simple vector multiplication is a particularly useful feature of the invention; as is stabilization of azimuth migration by correcting for spatially varying phase errors prior to the application of an autofocus process.

Signal processing and display interface studies. [performance tests - design analysis/equipment specifications

NASA Technical Reports Server (NTRS)

1975-01-01

Signal processing equipment specifications, operating and test procedures, and systems design and engineering are described. Five subdivisions of the overall circuitry are treated: (1) the spectrum analyzer; (2) the spectrum integrator; (3) the velocity discriminator; (4) the display interface; and (5) the formatter. They function in series: (1) first in analog form to provide frequency resolution, (2) then in digital form to achieve signal to noise improvement (video integration) and frequency discrimination, and (3) finally in analog form again for the purpose of real-time display of the significant velocity data. The formatter collects binary data from various points in the processor and provides a serial output for bi-phase recording. Block diagrams are used to illustrate the system.

Phytometric intelligence sensors

NASA Technical Reports Server (NTRS)

Seelig, Hans-Dieter (Inventor); Stoner, II, Richard J. (Inventor); Hoehn, Alexander (Inventor); Adams, III, William Walter (Inventor)

2010-01-01

Methods and apparatus for determining when plants require watering, and methods of attending to the watering of plants including signaling the grower that the plants are in need of hydration are provided. The novel methods include real-time measurement of plant metabolics and phytometric physiology changes of intrinsic physical or behavioral traits within the plant such as determining physiological flux measurement of enzyme flux due to environmental changes such as the wind and drought stress, soil and plant mineral deficiencies, or the interaction with a bio-control for organic disease control including, cell movement, signal transduction, internal chemical processes and external environmental processes including when plants require watering, and methods of attending to the watering of plants including signaling the grower that the plants are in need of hydration.

Real-Time Evaluation of Live Cancer Cells by an in Situ Surface Plasmon Resonance and Electrochemical Study.

PubMed

Wu, Changyu; Rehman, Fawad Ur; Li, Jingyuan; Ye, Jing; Zhang, Yuanyuan; Su, Meina; Jiang, Hui; Wang, Xuemei

2015-11-11

This work presents a new strategy of the combination of surface plasmon resonance (SPR) and electrochemical study for real-time evaluation of live cancer cells treated with daunorubicin (DNR) at the interface of the SPR chip and living cancer cells. The observations demonstrate that the SPR signal changes could be closely related to the morphology and mass changes of adsorbed cancer cells and the variation of the refractive index of the medium solution. The results of light microscopy images and 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide studies also illustrate the release or desorption of HepG2 cancer cells, which were due to their apoptosis after treatment with DNR. It is evident that the extracellular concentration of DNR residue can be readily determined through electrochemical measurements. The decreases in the magnitudes of SPR signals were linearly related to cell survival rates, and the combination of SPR with electrochemical study could be utilized to evaluate the potential therapeutic efficiency of bioactive agents to cells. Thus, this label-free, real-time SPR-electrochemical detection technique has great promise in bioanalysis or monitoring of relevant treatment processes in clinical applications.

Audio signal analysis for tool wear monitoring in sheet metal stamping

NASA Astrophysics Data System (ADS)

Ubhayaratne, Indivarie; Pereira, Michael P.; Xiang, Yong; Rolfe, Bernard F.

2017-02-01

Stamping tool wear can significantly degrade product quality, and hence, online tool condition monitoring is a timely need in many manufacturing industries. Even though a large amount of research has been conducted employing different sensor signals, there is still an unmet demand for a low-cost easy to set up condition monitoring system. Audio signal analysis is a simple method that has the potential to meet this demand, but has not been previously used for stamping process monitoring. Hence, this paper studies the existence and the significance of the correlation between emitted sound signals and the wear state of sheet metal stamping tools. The corrupting sources generated by the tooling of the stamping press and surrounding machinery have higher amplitudes compared to that of the sound emitted by the stamping operation itself. Therefore, a newly developed semi-blind signal extraction technique was employed as a pre-processing technique to mitigate the contribution of these corrupting sources. The spectral analysis results of the raw and extracted signals demonstrate a significant qualitative relationship between wear progression and the emitted sound signature. This study lays the basis for employing low-cost audio signal analysis in the development of a real-time industrial tool condition monitoring system.

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

Fault finder

DOEpatents

Bunch, Richard H.

1986-01-01

A fault finder for locating faults along a high voltage electrical transmission line. Real time monitoring of background noise and improved filtering of input signals is used to identify the occurrence of a fault. A fault is detected at both a master and remote unit spaced along the line. A master clock synchronizes operation of a similar clock at the remote unit. Both units include modulator and demodulator circuits for transmission of clock signals and data. All data is received at the master unit for processing to determine an accurate fault distance calculation.

SisPorto 4.0 - computer analysis following the 2015 FIGO Guidelines for intrapartum fetal monitoring.

PubMed

Ayres-de-Campos, Diogo; Rei, Mariana; Nunes, Inês; Sousa, Paulo; Bernardes, João

2017-01-01

SisPorto 4.0 is the most recent version of a program for the computer analysis of cardiotocographic (CTG) signals and ST events, which has been adapted to the 2015 International Federation of Gynaecology and Obstetrics (FIGO) guidelines for intrapartum foetal monitoring. This paper provides a detailed description of the analysis performed by the system, including the signal-processing algorithms involved in identification of basic CTG features and the resulting real-time alerts.

Review of wireless and wearable electroencephalogram systems and brain-computer interfaces--a mini-review.

PubMed

Lin, Chin-Teng; Ko, Li-Wei; Chang, Meng-Hsiu; Duann, Jeng-Ren; Chen, Jing-Ying; Su, Tung-Ping; Jung, Tzyy-Ping

2010-01-01

Biomedical signal monitoring systems have rapidly advanced in recent years, propelled by significant advances in electronic and information technologies. Brain-computer interface (BCI) is one of the important research branches and has become a hot topic in the study of neural engineering, rehabilitation, and brain science. Traditionally, most BCI systems use bulky, wired laboratory-oriented sensing equipments to measure brain activity under well-controlled conditions within a confined space. Using bulky sensing equipments not only is uncomfortable and inconvenient for users, but also impedes their ability to perform routine tasks in daily operational environments. Furthermore, owing to large data volumes, signal processing of BCI systems is often performed off-line using high-end personal computers, hindering the applications of BCI in real-world environments. To be practical for routine use by unconstrained, freely-moving users, BCI systems must be noninvasive, nonintrusive, lightweight and capable of online signal processing. This work reviews recent online BCI systems, focusing especially on wearable, wireless and real-time systems. Copyright 2009 S. Karger AG, Basel.

A low cost Doppler system for vascular dialysis access surveillance.

PubMed

Molina, P S C; Moraes, R; Baggio, J F R; Tognon, E A

2004-01-01

The National Kidney Foundation guidelines for vascular access recommend access surveillance to avoid morbidity among patients undergoing hemodialysis. Methods to detect access failure based on CW Doppler system are being proposed to implement surveillance programs at lower cost. This work describes a low cost Doppler system implemented in a PC notebook designed to carry out this task. A Doppler board samples the blood flow velocity and delivers demodulated quadrature Doppler signals. These signals are sampled by a notebook sound card. Software for Windows OS (running at the notebook) applies CFFT to consecutive 11.6 ms intervals of Doppler signals. The sonogram is presented on the screen in real time. The software also calculates the maximum and the intensity weighted mean frequency envelopes. Since similar systems employ DSP boards to process the Doppler signals, cost reduction was achieved. The Doppler board electronic circuits and routines to process the Doppler signals are presented.

The design and realization of a three-dimensional video system by means of a CCD array

NASA Astrophysics Data System (ADS)

Boizard, J. L.

1985-12-01

Design features and principles and initial tests of a prototype three-dimensional robot vision system based on a laser source and a CCD detector array is described. The use of a laser as a coherent illumination source permits the determination of the relief using one emitter since the location of the source is a known quantity with low distortion. The CCD signal detector array furnishes an acceptable signal/noise ratio and, when wired to an appropriate signal processing system, furnishes real-time data on the return signals, i.e., the characteristic points of an object being scanned. Signal processing involves integration of 29 kB of data per 100 samples, with sampling occurring at a rate of 5 MHz (the CCDs) and yielding an image every 12 msec. Algorithms for filtering errors from the data stream are discussed.

Spectral analysis method and sample generation for real time visualization of speech

NASA Astrophysics Data System (ADS)

Hobohm, Klaus

A method for translating speech signals into optical models, characterized by high sound discrimination and learnability and designed to provide to deaf persons a feedback towards control of their way of speaking, is presented. Important properties of speech production and perception processes and organs involved in these mechanisms are recalled in order to define requirements for speech visualization. It is established that the spectral representation of time, frequency and amplitude resolution of hearing must be fair and continuous variations of acoustic parameters of speech signal must be depicted by a continuous variation of images. A color table was developed for dynamic illustration and sonograms were generated with five spectral analysis methods such as Fourier transformations and linear prediction coding. For evaluating sonogram quality, test persons had to recognize consonant/vocal/consonant words and an optimized analysis method was achieved with a fast Fourier transformation and a postprocessor. A hardware concept of a real time speech visualization system, based on multiprocessor technology in a personal computer, is presented.

Method and apparatus for real time weld monitoring

DOEpatents

Leong, Keng H.; Hunter, Boyd V.

1997-01-01

An improved method and apparatus are provided for real time weld monitoring. An infrared signature emitted by a hot weld surface during welding is detected and this signature is compared with an infrared signature emitted by the weld surface during steady state conditions. The result is correlated with weld penetration. The signal processing is simpler than for either UV or acoustic techniques. Changes in the weld process, such as changes in the transmitted laser beam power, quality or positioning of the laser beam, change the resulting weld surface features and temperature of the weld surface, thereby resulting in a change in the direction and amount of infrared emissions. This change in emissions is monitored by an IR sensitive detecting apparatus that is sensitive to the appropriate wavelength region for the hot weld surface.

Method, system and computer-readable media for measuring impedance of an energy storage device

DOEpatents

Morrison, John L.; Morrison, William H.; Christophersen, Jon P.; Motloch, Chester G.

2016-01-26

Real-time battery impedance spectrum is acquired using a one-time record. Fast Summation Transformation (FST) is a parallel method of acquiring a real-time battery impedance spectrum using a one-time record that enables battery diagnostics. An excitation current to a battery is a sum of equal amplitude sine waves of frequencies that are octave harmonics spread over a range of interest. A sample frequency is also octave and harmonically related to all frequencies in the sum. A time profile of this sampled signal has a duration that is a few periods of the lowest frequency. A voltage response of the battery, average deleted, is an impedance of the battery in a time domain. Since the excitation frequencies are known and octave and harmonically related, a simple algorithm, FST, processes the time profile by rectifying relative to sine and cosine of each frequency. Another algorithm yields real and imaginary components for each frequency.

SU-E-T-66: A Prototype for Couch Based Real-Time Dosimetry in External Beam Radiotherapy

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

Ramachandran, P

Purpose: The main purpose of this study is to design a prototype for couch-based based real time dosimetry system in external beam radiotherapy Methods: A prototype of 100 ionization chambers was designed on a printed circuit board by etching the copper layer and each ionization chamber was wired to a 50 pin connector. The signals from the two 50 pin connectors collected from the ionization chambers were then transferred to a PXI module from National Instruments. The PXI module houses a current amplifier that amplifies the charge collected from the ionization chamber. The amplified signal is then sent to amore » digital multimeter module for converting the analog signal to digital signal. A software was designed in labview to read and display the signals obtained from the PXI module. A couch attachment frame was designed to house the 100 ionization chamber module. The frame was fixed underneath the treatment couch for measuring the dose during treatment. Resutls: The ionization chamber based prototype dosimetry was tested for simple radiotherapy treatment fields and found to be a useful device for measuring real time dosimetry at the treatment couch plane. This information could be used to assess the delivered dose to a patient during radiotherapy. It could be used as an invivo dosimeter during radiotherapy. Conclusion: In this study, a prototype for couch based real time dosimetry system was designed and tested. The prototype forms a basis for the development of large scale couch based real time dosimetry system that could be used to perform morning QA prior to treatment, assess real time doses delivered to patient and as a device to monitor the output of the treatment beam. Peter MacCallum Cancer Foundation.« less

Adaptive tracking of a time-varying field with a quantum sensor

NASA Astrophysics Data System (ADS)

Bonato, Cristian; Berry, Dominic W.

2017-05-01

Sensors based on single spins can enable magnetic-field detection with very high sensitivity and spatial resolution. Previous work has concentrated on sensing of a constant magnetic field or a periodic signal. Here, we instead investigate the problem of estimating a field with nonperiodic variation described by a Wiener process. We propose and study, by numerical simulations, an adaptive tracking protocol based on Bayesian estimation. The tracking protocol updates the probability distribution for the magnetic field based on measurement outcomes and adapts the choice of sensing time and phase in real time. By taking the statistical properties of the signal into account, our protocol strongly reduces the required measurement time. This leads to a reduction of the error in the estimation of a time-varying signal by up to a factor of four compare with protocols that do not take this information into account.

Coincidence ion imaging with a fast frame camera

NASA Astrophysics Data System (ADS)

Lee, Suk Kyoung; Cudry, Fadia; Lin, Yun Fei; Lingenfelter, Steven; Winney, Alexander H.; Fan, Lin; Li, Wen

2014-12-01

A new time- and position-sensitive particle detection system based on a fast frame CMOS (complementary metal-oxide semiconductors) camera is developed for coincidence ion imaging. The system is composed of four major components: a conventional microchannel plate/phosphor screen ion imager, a fast frame CMOS camera, a single anode photomultiplier tube (PMT), and a high-speed digitizer. The system collects the positional information of ions from a fast frame camera through real-time centroiding while the arrival times are obtained from the timing signal of a PMT processed by a high-speed digitizer. Multi-hit capability is achieved by correlating the intensity of ion spots on each camera frame with the peak heights on the corresponding time-of-flight spectrum of a PMT. Efficient computer algorithms are developed to process camera frames and digitizer traces in real-time at 1 kHz laser repetition rate. We demonstrate the capability of this system by detecting a momentum-matched co-fragments pair (methyl and iodine cations) produced from strong field dissociative double ionization of methyl iodide.

RTX Correction Accuracy and Real-Time Data Processing of the New Integrated SeismoGeodetic System with Real-Time Acceleration and Displacement Measurements for Earthquake Characterization Based on High-Rate Seismic and GPS Data

NASA Astrophysics Data System (ADS)

Zimakov, L. G.; Raczka, J.; Barrientos, S. E.

2016-12-01

We will discuss and show the results obtained from an integrated SeismoGeodetic System, model SG160-09, installed in the Chile (Chilean National Network), Italy (University of Naples Network), and California. The SG160-09 provides the user high rate GNSS and accelerometer data, full epoch-by-epoch measurement integrity and the ability to create combined GNSS and accelerometer high-rate (200Hz) displacement time series in real-time. The SG160-09 combines seismic recording with GNSS geodetic measurement in a single compact, ruggedized case. The system includes a low-power, 220-channel GNSS receiver powered by the latest Trimble-precise Maxwell™6 technology and supports tracking GPS, GLONASS and Galileo signals. The receiver incorporates on-board GNSS point positioning using Real-Time Precise Point Positioning (PPP) technology with satellite clock and orbit corrections delivered over IP networks. The seismic recording includes an ANSS Class A, force balance accelerometer with the latest, low power, 24-bit A/D converter, producing high-resolution seismic data. The SG160-09 processor acquires and packetizes both seismic and geodetic data and transmits it to the central station using an advanced, error-correction protocol providing data integrity between the field and the processing center. The SG160-09 has been installed in three seismic stations in different geographic locations with different Trimble global reference stations coverage The hardware includes the SG160-09 system, external Zephyr Geodetic-2 GNSS antenna, both radio and high-speed Internet communication media. Both acceleration and displacement data was transmitted in real-time to the centralized Data Acquisition Centers for real-time data processing. Command/Control of the field station and real-time GNSS position correction are provided via the Pivot platform. Data from the SG160-09 system was used for seismic event characterization along with data from traditional seismic and geodetic stations installed in the network. Our presentation will focus on the key improvements of the network installation with the SG160-09 system, RTX correction accuracy obtained from Trimble Global RTX tracking network, rapid data transmission, and real-time data processing for strong seismic events and aftershock characterization.

[Design and implementation of real-time continuous glucose monitoring instrument].

PubMed

Huang, Yonghong; Liu, Hongying; Tian, Senfu; Jia, Ziru; Wang, Zi; Pi, Xitian

2017-12-01

Real-time continuous glucose monitoring can help diabetics to control blood sugar levels within the normal range. However, in the process of practical monitoring, the output of real-time continuous glucose monitoring system is susceptible to glucose sensor and environment noise, which will influence the measurement accuracy of the system. Aiming at this problem, a dual-calibration algorithm for the moving-window double-layer filtering algorithm combined with real-time self-compensation calibration algorithm is proposed in this paper, which can realize the signal drift compensation for current data. And a real-time continuous glucose monitoring instrument based on this study was designed. This real-time continuous glucose monitoring instrument consisted of an adjustable excitation voltage module, a current-voltage converter module, a microprocessor and a wireless transceiver module. For portability, the size of the device was only 40 mm × 30 mm × 5 mm and its weight was only 30 g. In addition, a communication command code algorithm was designed to ensure the security and integrity of data transmission in this study. Results of experiments in vitro showed that current detection of the device worked effectively. A 5-hour monitoring of blood glucose level in vivo showed that the device could continuously monitor blood glucose in real time. The relative error of monitoring results of the designed device ranged from 2.22% to 7.17% when comparing to a portable blood meter.

Characteristic Markers of the WNT Signaling Pathways Are Differentially Expressed in Osteoarthritic Cartilage

PubMed Central

Dehne, T.; Lindahl, A.; Brittberg, M.; Pruss, A.; Ringe, J.; Sittinger, M.; Karlsson, C.

2012-01-01

Objective: It is well known that expression of markers for WNT signaling is dysregulated in osteoarthritic (OA) bone. However, it is still not fully known if the expression of these markers also is affected in OA cartilage. The aim of this study was therefore to examine this issue. Methods: Human cartilage biopsies from OA and control donors were subjected to genome-wide oligonucleotide microarrays. Genes involved in WNT signaling were selected using the BioRetis database, KEGG pathway analysis was searched using DAVID software tools, and cluster analysis was performed using Genesis software. Results from the microarray analysis were verified using quantitative real-time PCR and immunohistochemistry. In order to study the impact of cytokines for the dysregulated WNT signaling, OA and control chondrocytes were stimulated with interleukin-1 and analyzed with real-time PCR for their expression of WNT-related genes. Results: Several WNT markers displayed a significantly altered expression in OA compared to normal cartilage. Interestingly, inhibitors of the canonical and planar cell polarity WNT signaling pathways displayed significantly increased expression in OA cartilage, while the Ca2+/WNT signaling pathway was activated. Both real-time PCR and immunohistochemistry verified the microarray results. Real-time PCR analysis demonstrated that interleukin-1 upregulated expression of important WNT markers. Conclusions: WNT signaling is significantly affected in OA cartilage. The result suggests that both the canonical and planar cell polarity WNT signaling pathways were partly inhibited while the Ca2+/WNT pathway was activated in OA cartilage. PMID:26069618

The UTMOST: A Hybrid Digital Signal Processor Transforms the Molonglo Observatory Synthesis Telescope

NASA Astrophysics Data System (ADS)

Bailes, M.; Jameson, A.; Flynn, C.; Bateman, T.; Barr, E. D.; Bhandari, S.; Bunton, J. D.; Caleb, M.; Campbell-Wilson, D.; Farah, W.; Gaensler, B.; Green, A. J.; Hunstead, R. W.; Jankowski, F.; Keane, E. F.; Krishnan, V. Venkatraman; Murphy, Tara; O'Neill, M.; Osłowski, S.; Parthasarathy, A.; Ravi, V.; Rosado, P.; Temby, D.

2017-10-01

The Molonglo Observatory Synthesis Telescope (MOST) is an 18000 m2 radio telescope located 40 km from Canberra, Australia. Its operating band (820-851 MHz) is partly allocated to telecommunications, making radio astronomy challenging. We describe how the deployment of new digital receivers, Field Programmable Gate Array-based filterbanks, and server-class computers equipped with 43 Graphics Processing Units, has transformed the telescope into a versatile new instrument (UTMOST) for studying the radio sky on millisecond timescales. UTMOST has 10 times the bandwidth and double the field of view compared to the MOST, and voltage record and playback capability has facilitated rapid implementaton of many new observing modes, most of which operate commensally. UTMOST can simultaneously excise interference, make maps, coherently dedisperse pulsars, and perform real-time searches of coherent fan-beams for dispersed single pulses. UTMOST operates as a robotic facility, deciding how to efficiently target pulsars and how long to stay on source via real-time pulsar folding, while searching for single pulse events. Regular timing of over 300 pulsars has yielded seven pulsar glitches and three Fast Radio Bursts during commissioning. UTMOST demonstrates that if sufficient signal processing is applied to voltage streams, innovative science remains possible even in hostile radio frequency environments.

[Application of recombinase polymerase amplification in the detection of Pseudomonas aeruginosa].

PubMed

Jin, X J; Gong, Y L; Yang, L; Mo, B H; Peng, Y Z; He, P; Zhao, J N; Li, X L

2018-04-20

Objective: To establish an optimized method of recombinase polymerase amplification (RPA) to rapidly detect Pseudomonas aeruginosa in clinic. Methods: (1) The DNA templates of one standard Pseudomonas aeruginosa strain was extracted and detected by polymerase chain reaction (PCR), real-time fluorescence quantitative PCR and RPA. Time of sample loading, time of amplification, and time of detection of the three methods were recorded. (2) One standard Pseudomonas aeruginosa strain was diluted in 7 concentrations of 1×10(7,) 1×10(6,) 1×10(5,) 1×10(4,) 1×10(3,) 1×10(2,) and 1×10(1) colony forming unit (CFU)/mL after recovery and cultivation. The DNA templates of Pseudomonas aeruginosa and negative control strain Pseudomonas putida were extracted and detected by PCR, real-time fluorescence quantitative PCR, and RPA separately. The sensitivity of the three methods in detecting Pseudomonas aeruginosa was analyzed. (3) The DNA templates of one standard Pseudomonas aeruginosa strain and four negative control strains ( Staphylococcus aureus, Acinetobacter baumanii, Candida albicans, and Pseudomonas putida ) were extracted separately, and then they were detected by PCR, real-time fluorescence quantitative PCR, and RPA. The specificity of the three methods in detecting Pseudomonas aeruginosa was analyzed. (4) The DNA templates of 28 clinical strains of Pseudomonas aeruginosa preserved in glycerin, 1 clinical strain of which was taken by cotton swab, and negative control strain Pseudomonas putida were extracted separately, and then they were detected by RPA. Positive amplification signals of the clinical strains were observed, and the detection rate was calculated. All experiments were repeated for 3 times. Sensitivity results were analyzed by GraphPad Prism 5.01 statistical software. Results: (1) The loading time of RPA, PCR, and real-time fluorescence quantitative PCR for detecting Pseudomonas aeruginosa were all 20 minutes. In PCR, time of amplification was 98 minutes, time of gel detection was 20 minutes, and the total time was 138 minutes. In real-time fluorescence quantitative PCR, amplification and detection could be completed simultaneously, which took 90 minutes, and the total time was 110 minutes. In RPA, amplification and detection could also be completed simultaneously, which took 15 minutes, and the total time was 35 minutes. (2) Pseudomonas putida did not show positive amplification signals or gel positive results in any of the three detection methods. The detection limit of Pseudomonas aeruginosa in real-time fluorescence quantitative PCR and PCR was 1×10(1) CFU/mL, and that of Pseudomonas aeruginosa in RPA was 1×10(2) CFU/mL. In RPA and real-time fluorescence quantitative PCR, the higher the concentration of Pseudomonas aeruginosa, the shorter threshold time and smaller the number of cycles, namely shorter time for detecting the positive amplified signal. In real-time fluorescence quantitative PCR, all positive amplification signal could be detected when the concentration of Pseudomonas aeruginosa was 1×10(1)-1×10(7) CFU/mL. In RPA, the detection rate of positive amplification signal was 0 when the concentration of Pseudomonas aeruginosa was 1×10(1) CFU/mL, while the detection rate of positive amplification signal was 67% when the concentration of Pseudomonas aeruginosa was 1×10(2) CFU/mL, and the detection rate of positive amplification signal was 100% when the concentration of Pseudomonas aeruginosa was 1×10(3)-1×10(7) CFU/mL. (3) In RPA, PCR, and real-time fluorescence quantitative PCR, Pseudomonas aeruginosa showed positive amplification signals and gel positive results, but there were no positive amplification signals or gel positive results in four negative control strains of Acinetobacter baumannii, Staphylococcus aureus, Candida albicans, and Pseudomonas putida . (4) In RPA, 28 clinical strains of Pseudomonas aeruginosa preserved in glycerin and 1 clinical strain of Pseudomonas aeruginosa taken by cotton swab showed positive amplification signals, while Pseudomonas putida did not show positive amplification signal. The detection rate of positive amplification signal of 29 clinical strains of Pseudomonas aeruginosa in RPA was 100%. Conclusions: The established optimized RPA technology for fast detection of Pseudomonas aeruginosa requires shorter time, with high sensitivity and specificity. It was of great value in fast detection of Pseudomonas aeruginosa infection in clinic.

A preferential design approach for energy-efficient and robust implantable neural signal processing hardware.

PubMed

Narasimhan, Seetharam; Chiel, Hillel J; Bhunia, Swarup

2009-01-01

For implantable neural interface applications, it is important to compress data and analyze spike patterns across multiple channels in real time. Such a computational task for online neural data processing requires an innovative circuit-architecture level design approach for low-power, robust and area-efficient hardware implementation. Conventional microprocessor or Digital Signal Processing (DSP) chips would dissipate too much power and are too large in size for an implantable system. In this paper, we propose a novel hardware design approach, referred to as "Preferential Design" that exploits the nature of the neural signal processing algorithm to achieve a low-voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate the critical components with respect to system performance and design them more conservatively compared to the noncritical ones. This allows aggressive voltage scaling for low power operation while ensuring robustness and area efficiency. We have applied the proposed approach to a neural signal processing algorithm using the Discrete Wavelet Transform (DWT) and observed significant improvement in power and robustness over conventional design.

Multiple disturbances classifier for electric signals using adaptive structuring neural networks

NASA Astrophysics Data System (ADS)

Lu, Yen-Ling; Chuang, Cheng-Long; Fahn, Chin-Shyurng; Jiang, Joe-Air

2008-07-01

This work proposes a novel classifier to recognize multiple disturbances for electric signals of power systems. The proposed classifier consists of a series of pipeline-based processing components, including amplitude estimator, transient disturbance detector, transient impulsive detector, wavelet transform and a brand-new neural network for recognizing multiple disturbances in a power quality (PQ) event. Most of the previously proposed methods usually treated a PQ event as a single disturbance at a time. In practice, however, a PQ event often consists of various types of disturbances at the same time. Therefore, the performances of those methods might be limited in real power systems. This work considers the PQ event as a combination of several disturbances, including steady-state and transient disturbances, which is more analogous to the real status of a power system. Six types of commonly encountered power quality disturbances are considered for training and testing the proposed classifier. The proposed classifier has been tested on electric signals that contain single disturbance or several disturbances at a time. Experimental results indicate that the proposed PQ disturbance classification algorithm can achieve a high accuracy of more than 97% in various complex testing cases.

The LUX experiment - trigger and data acquisition systems

NASA Astrophysics Data System (ADS)

Druszkiewicz, Eryk

2013-04-01

The Large Underground Xenon (LUX) detector is a two-phase xenon time projection chamber designed to detect interactions of dark matter particles with the xenon nuclei. Signals from the detector PMTs are processed by custom-built analog electronics which provide properly shaped signals for the trigger and data acquisition (DAQ) systems. During calibrations, both systems must be able to handle high rates and have large dynamic ranges; during dark matter searches, maximum sensitivity requires low thresholds. The trigger system uses eight-channel 64-MHz digitizers (DDC-8) connected to a Trigger Builder (TB). The FPGA cores on the digitizers perform real-time pulse identification (discriminating between S1 and S2-like signals) and event localization. The TB uses hit patterns, hit maps, and maximum response detection to make trigger decisions, which are reached within few microseconds after the occurrence of an event of interest. The DAQ system is comprised of commercial digitizers with customized firmware. Its real-time baseline suppression allows for a maximum event acquisition rate in excess of 1.5 kHz, which results in virtually no deadtime. The performance of the trigger and DAQ systems during the commissioning runs of LUX will be discussed.

Control and monitoring method and system for electromagnetic forming process

DOEpatents

Kunerth, Dennis C.; Lassahn, Gordon D.

1990-01-01

A process, system, and improvement for a process for electromagnetic forming of a workpiece in which characteristics of the workpiece such as its geometry, electrical conductivity, quality, and magnetic permeability can be determined by monitoring the current and voltage in the workcoil. In an electromagnet forming process in which a power supply provides current to a workcoil and the electromagnetic field produced by the workcoil acts to form the workpiece, the dynamic interaction of the electromagnetic fields produced by the workcoil with the geometry, electrical conductivity, and magnetic permeability of the workpiece, provides information pertinent to the physical condition of the workpiece that is available for determination of quality and process control. This information can be obtained by deriving in real time the first several time derivatives of the current and voltage in the workcoil. In addition, the process can be extended by injecting test signals into the workcoil during the electromagnetic forming and monitoring the response to the test signals in the workcoil.