Improved signal recovery for flow cytometry based on ‘spatially modulated emission’

NASA Astrophysics Data System (ADS)

Quint, S.; Wittek, J.; Spang, P.; Levanon, N.; Walther, T.; Baßler, M.

2017-09-01

Recently, the technique of ‘spatially modulated emission’ has been introduced (Baßler et al 2008 US Patent 0080181827A1; Kiesel et al 2009 Appl. Phys. Lett. 94 041107; Kiesel et al 2011 Cytometry A 79A 317-24) improving the signal-to-noise ratio (SNR) for detecting bio-particles in the field of flow cytometry. Based on this concept, we developed two advanced signal processing methods which further enhance the SNR and selectivity for cell detection. The improvements are achieved by adapting digital filtering methods from RADAR technology and mainly address inherent offset elimination, increased signal dynamics and moreover reduction of erroneous detections due to processing artifacts. We present a comprehensive theory on SNR gain and provide experimental results of our concepts.

Trends in non-stationary signal processing techniques applied to vibration analysis of wind turbine drive train - A contemporary survey

NASA Astrophysics Data System (ADS)

Uma Maheswari, R.; Umamaheswari, R.

2017-02-01

Condition Monitoring System (CMS) substantiates potential economic benefits and enables prognostic maintenance in wind turbine-generator failure prevention. Vibration Monitoring and Analysis is a powerful tool in drive train CMS, which enables the early detection of impending failure/damage. In variable speed drives such as wind turbine-generator drive trains, the vibration signal acquired is of non-stationary and non-linear. The traditional stationary signal processing techniques are inefficient to diagnose the machine faults in time varying conditions. The current research trend in CMS for drive-train focuses on developing/improving non-linear, non-stationary feature extraction and fault classification algorithms to improve fault detection/prediction sensitivity and selectivity and thereby reducing the misdetection and false alarm rates. In literature, review of stationary signal processing algorithms employed in vibration analysis is done at great extent. In this paper, an attempt is made to review the recent research advances in non-linear non-stationary signal processing algorithms particularly suited for variable speed wind turbines.

Smart Sensors: Why and when the origin was and why and where the future will be

NASA Astrophysics Data System (ADS)

Corsi, C.

2013-12-01

Smart Sensors is a technique developed in the 70's when the processing capabilities, based on readout integrated with signal processing, was still far from the complexity needed in advanced IR surveillance and warning systems, because of the enormous amount of noise/unwanted signals emitted by operating scenario especially in military applications. The Smart Sensors technology was kept restricted within a close military environment exploding in applications and performances in the 90's years thanks to the impressive improvements in the integrated signal read-out and processing achieved by CCD-CMOS technologies in FPA. In fact the rapid advances of "very large scale integration" (VLSI) processor technology and mosaic EO detector array technology allowed to develop new generations of Smart Sensors with much improved signal processing by integrating microcomputers and other VLSI signal processors. inside the sensor structure achieving some basic functions of living eyes (dynamic stare, non-uniformity compensation, spatial and temporal filtering). New and future technologies (Nanotechnology, Bio-Organic Electronics, Bio-Computing) are lightning a new generation of Smart Sensors extending the Smartness from the Space-Time Domain to Spectroscopic Functional Multi-Domain Signal Processing. History and future forecasting of Smart Sensors will be reported.

Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications

PubMed Central

Verma, Arjun; Fratto, Brian E.; Privman, Vladimir; Katz, Evgeny

2016-01-01

We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed. PMID:27399702

Device design and signal processing for multiple-input multiple-output multimode fiber links

NASA Astrophysics Data System (ADS)

Appaiah, Kumar; Vishwanath, Sriram; Bank, Seth R.

2012-01-01

Multimode fibers (MMFs) are limited in data rate capabilities owing to modal dispersion. However, their large core diameter simplifies alignment and packaging, and makes them attractive for short and medium length links. Recent research has shown that the use of signal processing and techniques such as multiple-input multiple-output (MIMO) can greatly improve the data rate capabilities of multimode fibers. In this paper, we review recent experimental work using MIMO and signal processing for multimode fibers, and the improvements in data rates achievable with these techniques. We then present models to design as well as simulate the performance benefits obtainable with arrays of lasers and detectors in conjunction with MIMO, using channel capacity as the metric to optimize. We also discuss some aspects related to complexity of the algorithms needed for signal processing and discuss techniques for low complexity implementation.

Doppler ultrasound monitoring technology.

PubMed

Docker, M F

1993-03-01

Developments in the signal processing of Doppler ultrasound used for the detection of fetal heart rate (FHR) have improved the operation of cardiotocographs. These developments are reviewed and the advantages and disadvantages of the various Doppler and signal processing methods are compared.

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

System for monitoring non-coincident, nonstationary process signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.

2005-01-04

An improved system for monitoring non-coincident, non-stationary, process signals. The mean, variance, and length of a reference signal is defined by an automated system, followed by the identification of the leading and falling edges of a monitored signal and the length of the monitored signal. The monitored signal is compared to the reference signal, and the monitored signal is resampled in accordance with the reference signal. The reference signal is then correlated with the resampled monitored signal such that the reference signal and the resampled monitored signal are coincident in time with each other. The resampled monitored signal is then compared to the reference signal to determine whether the resampled monitored signal is within a set of predesignated operating conditions.

lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain.

PubMed

Sepehrband, Farshid; Choupan, Jeiran; Caruyer, Emmanuel; Kurniawan, Nyoman D; Gal, Yaniv; Tieng, Quang M; McMahon, Katie L; Vegh, Viktor; Reutens, David C; Yang, Zhengyi

2014-01-01

We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.

Research on signal processing method for total organic carbon of water quality online monitor

NASA Astrophysics Data System (ADS)

Ma, R.; Xie, Z. X.; Chu, D. Z.; Zhang, S. W.; Cao, X.; Wu, N.

2017-08-01

At present, there is no rapid, stable and effective approach of total organic carbon (TOC) measurement in the Marine environmental online monitoring field. Therefore, this paper proposes an online TOC monitor of chemiluminescence signal processing method. The weak optical signal detected by photomultiplier tube can be enhanced and converted by a series of signal processing module: phase-locked amplifier module, fourth-order band pass filter module and AD conversion module. After a long time of comparison test & measurement, compared with the traditional method, on the premise of sufficient accuracy, this chemiluminescence signal processing method can offer greatly improved measuring speed and high practicability for online monitoring.

Correlation ion mobility spectroscopy

DOEpatents

Pfeifer, Kent B [Los Lunas, NM; Rohde, Steven B [Corrales, NM

2008-08-26

Correlation ion mobility spectrometry (CIMS) uses gating modulation and correlation signal processing to improve IMS instrument performance. Closely spaced ion peaks can be resolved by adding discriminating codes to the gate and matched filtering for the received ion current signal, thereby improving sensitivity and resolution of an ion mobility spectrometer. CIMS can be used to improve the signal-to-noise ratio even for transient chemical samples. CIMS is especially advantageous for small geometry IMS drift tubes that can otherwise have poor resolution due to their small size.

Signal Restoration of Non-stationary Acoustic Signals in the Time Domain

NASA Technical Reports Server (NTRS)

Babkin, Alexander S.

1988-01-01

Signal restoration is a method of transforming a nonstationary signal acquired by a ground based microphone to an equivalent stationary signal. The benefit of the signal restoration is a simplification of the flight test requirements because it could dispense with the need to acquire acoustic data with another aircraft flying in concert with the rotorcraft. The data quality is also generally improved because the contamination of the signal by the propeller and wind noise is not present. The restoration methodology can also be combined with other data acquisition methods, such as a multiple linear microphone array for further improvement of the test results. The methodology and software are presented for performing the signal restoration in the time domain. The method has no restrictions on flight path geometry or flight regimes. Only requirement is that the aircraft spatial position be known relative to the microphone location and synchronized with the acoustic data. The restoration process assumes that the moving source radiates a stationary signal, which is then transformed into a nonstationary signal by various modulation processes. The restoration contains only the modulation due to the source motion.

Understanding nitrate uptake, signaling and remobilisation for improving plant nitrogen use efficiency.

PubMed

Kant, Surya

2018-02-01

The majority of terrestrial plants use nitrate as their main source of nitrogen. Nitrate also acts as an important signalling molecule in vital physiological processes required for optimum plant growth and development. Improving nitrate uptake and transport, through activation by nitrate sensing, signalling and regulatory processes, would enhance plant growth, resulting in improved crop yields. The increased remobilisation of nitrate, and assimilated nitrogenous compounds, from source to sink tissues further ensures higher yields and quality. An updated knowledge of various transporters, genes, activators, and microRNAs, involved in nitrate uptake, transport, remobilisation, and nitrate-mediated root growth, is presented. An enhanced understanding of these components will allow for their orchestrated fine tuning in efforts to improving nitrogen use efficiency in plants. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Analysis of acoustic emission signals and monitoring of machining processes

PubMed

Govekar; Gradisek; Grabec

2000-03-01

Monitoring of a machining process on the basis of sensor signals requires a selection of informative inputs in order to reliably characterize and model the process. In this article, a system for selection of informative characteristics from signals of multiple sensors is presented. For signal analysis, methods of spectral analysis and methods of nonlinear time series analysis are used. With the aim of modeling relationships between signal characteristics and the corresponding process state, an adaptive empirical modeler is applied. The application of the system is demonstrated by characterization of different parameters defining the states of a turning machining process, such as: chip form, tool wear, and onset of chatter vibration. The results show that, in spite of the complexity of the turning process, the state of the process can be well characterized by just a few proper characteristics extracted from a representative sensor signal. The process characterization can be further improved by joining characteristics from multiple sensors and by application of chaotic characteristics.

Naval sensor data database (NSDD)

NASA Astrophysics Data System (ADS)

Robertson, Candace J.; Tubridy, Lisa H.

1999-08-01

The Naval Sensor Data database (NSDD) is a multi-year effort to archive, catalogue, and disseminate data from all types of sensors to the mine warfare, signal and image processing, and sensor development communities. The purpose is to improve and accelerate research and technology. Providing performers with the data required to develop and validate improvements in hardware, simulation, and processing will foster advances in sensor and system performance. The NSDD will provide a centralized source of sensor data in its associated ground truth, which will support an improved understanding will be benefited in the areas of signal processing, computer-aided detection and classification, data compression, data fusion, and geo-referencing, as well as sensor and sensor system design.

Signal-processing theory for the TurboRogue receiver

NASA Technical Reports Server (NTRS)

Thomas, J. B.

1995-01-01

Signal-processing theory for the TurboRogue receiver is presented. The signal form is traced from its formation at the GPS satellite, to the receiver antenna, and then through the various stages of the receiver, including extraction of phase and delay. The analysis treats the effects of ionosphere, troposphere, signal quantization, receiver components, and system noise, covering processing in both the 'code mode' when the P code is not encrypted and in the 'P-codeless mode' when the P code is encrypted. As a possible future improvement to the current analog front end, an example of a highly digital front end is analyzed.

Acoustic Signal Processing for Pipe Condition Assessment (WaterRF Report 4360)

EPA Science Inventory

Unique to prestressed concrete cylinder pipe (PCCP), individual wire breaks create an excitation in the pipe wall that may vary in response to the remaining compression of the pipe core. This project was designed to improve acoustic signal processing for pipe condition assessment...

Application of Advanced Signal Processing Techniques to Angle of Arrival Estimation in ATC Navigation and Surveillance Systems

DTIC Science & Technology

1982-06-23

Administration Systems Research and Development Service 14, Spseq Aese Ce ’ Washington, D.C. 20591 It. SeppkW•aae metm The work reported in this document was...consider sophisticated signal processing techniques as an alternative method of improving system performanceH Some work in this area has already taken place...demands on the frequency spectrum. As noted in Table 1-1, there has been considerable work on advanced signal processing in the MLS context

Electrocardiogram signal denoising based on a new improved wavelet thresholding

NASA Astrophysics Data System (ADS)

Han, Guoqiang; Xu, Zhijun

2016-08-01

Good quality electrocardiogram (ECG) is utilized by physicians for the interpretation and identification of physiological and pathological phenomena. In general, ECG signals may mix various noises such as baseline wander, power line interference, and electromagnetic interference in gathering and recording process. As ECG signals are non-stationary physiological signals, wavelet transform is investigated to be an effective tool to discard noises from corrupted signals. A new compromising threshold function called sigmoid function-based thresholding scheme is adopted in processing ECG signals. Compared with other methods such as hard/soft thresholding or other existing thresholding functions, the new algorithm has many advantages in the noise reduction of ECG signals. It perfectly overcomes the discontinuity at ±T of hard thresholding and reduces the fixed deviation of soft thresholding. The improved wavelet thresholding denoising can be proved to be more efficient than existing algorithms in ECG signal denoising. The signal to noise ratio, mean square error, and percent root mean square difference are calculated to verify the denoising performance as quantitative tools. The experimental results reveal that the waves including P, Q, R, and S waves of ECG signals after denoising coincide with the original ECG signals by employing the new proposed method.

Direct position determination for digital modulation signals based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yu, Wan-Ting; Yu, Hong-yi; Du, Jian-Ping; Wang, Ding

2018-04-01

The Direct Position Determination (DPD) algorithm has been demonstrated to achieve a better accuracy with known signal waveforms. However, the signal waveform is difficult to be completely known in the actual positioning process. To solve the problem, we proposed a DPD method for digital modulation signals based on improved particle swarm optimization algorithm. First, a DPD model is established for known modulation signals and a cost function is obtained on symbol estimation. Second, as the optimization of the cost function is a nonlinear integer optimization problem, an improved Particle Swarm Optimization (PSO) algorithm is considered for the optimal symbol search. Simulations are carried out to show the higher position accuracy of the proposed DPD method and the convergence of the fitness function under different inertia weight and population size. On the one hand, the proposed algorithm can take full advantage of the signal feature to improve the positioning accuracy. On the other hand, the improved PSO algorithm can improve the efficiency of symbol search by nearly one hundred times to achieve a global optimal solution.

Progress and opportunities in EELS and EDS tomography.

PubMed

Collins, Sean M; Midgley, Paul A

2017-09-01

Electron tomography using energy loss and X-ray spectroscopy in the electron microscope continues to develop in rapidly evolving and diverse directions, enabling new insight into the three-dimensional chemistry and physics of nanoscale volumes. Progress has been made recently in improving reconstructions from EELS and EDS signals in electron tomography by applying compressed sensing methods, characterizing new detector technologies in detail, deriving improved models of signal generation, and exploring machine learning approaches to signal processing. These disparate threads can be brought together in a cohesive framework in terms of a model-based approach to analytical electron tomography. Models incorporate information on signal generation and detection as well as prior knowledge of structures in the spectrum image data. Many recent examples illustrate the flexibility of this approach and its feasibility for addressing challenges in non-linear or limited signals in EELS and EDS tomography. Further work in combining multiple imaging and spectroscopy modalities, developing synergistic data acquisition, processing, and reconstruction approaches, and improving the precision of quantitative spectroscopic tomography will expand the frontiers of spatial resolution, dose limits, and maximal information recovery. Copyright © 2017 Elsevier B.V. All rights reserved.

A portable system for acquiring and removing motion artefact from ECG signals

NASA Astrophysics Data System (ADS)

Griffiths, A.; Das, A.; Fernandes, B.; Gaydecki, P.

2007-07-01

A novel electrocardiograph (ECG) signal acquisition and display system is under development. It is designed for patients ranging from the elderly to athletes. The signals are obtained from electrodes integrated into a vest, amplified, digitally processed and transmitted via Bluetooth to a PC with a Labview ® interface. Digital signal processing is performed to remove movement artefact and electromyographic (EMG) noise, which severely distorts signal morphology and complicates clinical diagnosis. Independent component analysis (ICA) is also used to improve the signal quality. The complete system will integrate the electronics into a single module which will be embedded in the vest.

Combined analysis of cortical (EEG) and nerve stump signals improves robotic hand control.

PubMed

Tombini, Mario; Rigosa, Jacopo; Zappasodi, Filippo; Porcaro, Camillo; Citi, Luca; Carpaneto, Jacopo; Rossini, Paolo Maria; Micera, Silvestro

2012-01-01

Interfacing an amputee's upper-extremity stump nerves to control a robotic hand requires training of the individual and algorithms to process interactions between cortical and peripheral signals. To evaluate for the first time whether EEG-driven analysis of peripheral neural signals as an amputee practices could improve the classification of motor commands. Four thin-film longitudinal intrafascicular electrodes (tf-LIFEs-4) were implanted in the median and ulnar nerves of the stump in the distal upper arm for 4 weeks. Artificial intelligence classifiers were implemented to analyze LIFE signals recorded while the participant tried to perform 3 different hand and finger movements as pictures representing these tasks were randomly presented on a screen. In the final week, the participant was trained to perform the same movements with a robotic hand prosthesis through modulation of tf-LIFE-4 signals. To improve the classification performance, an event-related desynchronization/synchronization (ERD/ERS) procedure was applied to EEG data to identify the exact timing of each motor command. Real-time control of neural (motor) output was achieved by the participant. By focusing electroneurographic (ENG) signal analysis in an EEG-driven time window, movement classification performance improved. After training, the participant regained normal modulation of background rhythms for movement preparation (α/β band desynchronization) in the sensorimotor area contralateral to the missing limb. Moreover, coherence analysis found a restored α band synchronization of Rolandic area with frontal and parietal ipsilateral regions, similar to that observed in the opposite hemisphere for movement of the intact hand. Of note, phantom limb pain (PLP) resolved for several months. Combining information from both cortical (EEG) and stump nerve (ENG) signals improved the classification performance compared with tf-LIFE signals processing alone; training led to cortical reorganization and mitigation of PLP.

A de-noising method using the improved wavelet threshold function based on noise variance estimation

NASA Astrophysics Data System (ADS)

Liu, Hui; Wang, Weida; Xiang, Changle; Han, Lijin; Nie, Haizhao

2018-01-01

The precise and efficient noise variance estimation is very important for the processing of all kinds of signals while using the wavelet transform to analyze signals and extract signal features. In view of the problem that the accuracy of traditional noise variance estimation is greatly affected by the fluctuation of noise values, this study puts forward the strategy of using the two-state Gaussian mixture model to classify the high-frequency wavelet coefficients in the minimum scale, which takes both the efficiency and accuracy into account. According to the noise variance estimation, a novel improved wavelet threshold function is proposed by combining the advantages of hard and soft threshold functions, and on the basis of the noise variance estimation algorithm and the improved wavelet threshold function, the research puts forth a novel wavelet threshold de-noising method. The method is tested and validated using random signals and bench test data of an electro-mechanical transmission system. The test results indicate that the wavelet threshold de-noising method based on the noise variance estimation shows preferable performance in processing the testing signals of the electro-mechanical transmission system: it can effectively eliminate the interference of transient signals including voltage, current, and oil pressure and maintain the dynamic characteristics of the signals favorably.

Ensemble Empirical Mode Decomposition based methodology for ultrasonic testing of coarse grain austenitic stainless steels.

PubMed

Sharma, Govind K; Kumar, Anish; Jayakumar, T; Purnachandra Rao, B; Mariyappa, N

2015-03-01

A signal processing methodology is proposed in this paper for effective reconstruction of ultrasonic signals in coarse grained high scattering austenitic stainless steel. The proposed methodology is comprised of the Ensemble Empirical Mode Decomposition (EEMD) processing of ultrasonic signals and application of signal minimisation algorithm on selected Intrinsic Mode Functions (IMFs) obtained by EEMD. The methodology is applied to ultrasonic signals obtained from austenitic stainless steel specimens of different grain size, with and without defects. The influence of probe frequency and data length of a signal on EEMD decomposition is also investigated. For a particular sampling rate and probe frequency, the same range of IMFs can be used to reconstruct the ultrasonic signal, irrespective of the grain size in the range of 30-210 μm investigated in this study. This methodology is successfully employed for detection of defects in a 50mm thick coarse grain austenitic stainless steel specimens. Signal to noise ratio improvement of better than 15 dB is observed for the ultrasonic signal obtained from a 25 mm deep flat bottom hole in 200 μm grain size specimen. For ultrasonic signals obtained from defects at different depths, a minimum of 7 dB extra enhancement in SNR is achieved as compared to the sum of selected IMF approach. The application of minimisation algorithm with EEMD processed signal in the proposed methodology proves to be effective for adaptive signal reconstruction with improved signal to noise ratio. This methodology was further employed for successful imaging of defects in a B-scan. Copyright © 2014. Published by Elsevier B.V.

Surface Electromyography Signal Processing and Classification Techniques

PubMed Central

Chowdhury, Rubana H.; Reaz, Mamun B. I.; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A. A.; Chellappan, Kalaivani; Chang, Tae. G.

2013-01-01

Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:24048337

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.

Performance Analysis of a Hardware Implemented Complex Signal Kurtosis Radio-Frequency Interference Detector

NASA Technical Reports Server (NTRS)

Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark

2016-01-01

Radio-frequency interference (RFI) is a known problem for passive remote sensing as evidenced in the L-band radiometers SMOS, Aquarius and more recently, SMAP. Various algorithms have been developed and implemented on SMAP to improve science measurements. This was achieved by the use of a digital microwave radiometer. RFI mitigation becomes more challenging for microwave radiometers operating at higher frequencies in shared allocations. At higher frequencies larger bandwidths are also desirable for lower measurement noise further adding to processing challenges. This work focuses on finding improved RFI mitigation techniques that will be effective at additional frequencies and at higher bandwidths. To aid the development and testing of applicable detection and mitigation techniques, a wide-band RFI algorithm testing environment has been developed using the Reconfigurable Open Architecture Computing Hardware System (ROACH) built by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Group. The testing environment also consists of various test equipment used to reproduce typical signals that a radiometer may see including those with and without RFI. The testing environment permits quick evaluations of RFI mitigation algorithms as well as show that they are implementable in hardware. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The complex signal kurtosis detector showed improved performance over the real kurtosis detector under certain conditions. The real kurtosis is implemented on SMAP at 24 MHz bandwidth. The complex signal kurtosis algorithm was then implemented in hardware at 200 MHz bandwidth using the ROACH. In this work, performance of the complex signal kurtosis and the real signal kurtosis are compared. Performance evaluations and comparisons in both simulation as well as experimental hardware implementations were done with the use of receiver operating characteristic (ROC) curves. The complex kurtosis algorithm has the potential to reduce data rate due to onboard processing in addition to improving RFI detection performance.

Digital signal processing for velocity measurements in dynamical material's behaviour studies.

PubMed

Devlaminck, Julien; Luc, Jérôme; Chanal, Pierre-Yves

2014-03-01

In this work, we describe different configurations of optical fiber interferometers (types Michelson and Mach-Zehnder) used to measure velocities during dynamical material's behaviour studies. We detail the algorithms of processing developed and optimized to improve the performance of these interferometers especially in terms of time and frequency resolutions. Three methods of analysis of interferometric signals were studied. For Michelson interferometers, the time-frequency analysis of signals by Short-Time Fourier Transform (STFT) is compared to a time-frequency analysis by Continuous Wavelet Transform (CWT). The results have shown that the CWT was more suitable than the STFT for signals with low signal-to-noise, and low velocity and high acceleration areas. For Mach-Zehnder interferometers, the measurement is carried out by analyzing the phase shift between three interferometric signals (Triature processing). These three methods of digital signal processing were evaluated, their measurement uncertainties estimated, and their restrictions or operational limitations specified from experimental results performed on a pulsed power machine.

Improving Walkability Through Control Strategies at Signalized Intersections

DOT National Transportation Integrated Search

2017-01-01

As cities and communities nationwide seek to develop Complete Streets that foster livability and accommodate all modes, signal timing control strategies that include pedestrians in the operational decision process are gaining importance. This researc...

Wavelet-Based Processing for Fiber Optic Sensing Systems

NASA Technical Reports Server (NTRS)

Hamory, Philip J. (Inventor); Parker, Allen R., Jr. (Inventor)

2016-01-01

The present invention is an improved method of processing conglomerate data. The method employs a Triband Wavelet Transform that decomposes and decimates the conglomerate signal to obtain a final result. The invention may be employed to improve performance of Optical Frequency Domain Reflectometry systems.

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

An open-loop system design for deep space signal processing applications

NASA Astrophysics Data System (ADS)

Tang, Jifei; Xia, Lanhua; Mahapatra, Rabi

2018-06-01

A novel open-loop system design with high performance is proposed for space positioning and navigation signal processing. Divided by functions, the system has four modules, bandwidth selectable data recorder, narrowband signal analyzer, time-delay difference of arrival estimator and ANFIS supplement processor. A hardware-software co-design approach is made to accelerate computing capability and improve system efficiency. Embedded with the proposed signal processing algorithms, the designed system is capable of handling tasks with high accuracy over long period of continuous measurements. The experiment results show the Doppler frequency tracking root mean square error during 3 h observation is 0.0128 Hz, while the TDOA residue analysis in correlation power spectrum is 0.1166 rad.

Method and apparatus for improving resolution in spectrometers processing output steps from non-ideal signal sources

DOEpatents

Warburton, William K.; Momayezi, Michael

2006-06-20

A method and apparatus for processing step-like output signals (primary signals) generated by non-ideal, for example, nominally single-pole ("N-1P ") devices. An exemplary method includes creating a set of secondary signals by directing the primary signal along a plurality of signal paths to a signal summation point, summing the secondary signals reaching the signal summation point after propagating along the signal paths to provide a summed signal, performing a filtering or delaying operation in at least one of said signal paths so that the secondary signals reaching said summing point have a defined time correlation with respect to one another, applying a set of weighting coefficients to the secondary signals propagating along said signal paths, and performing a capturing operation after any filtering or delaying operations so as to provide a weighted signal sum value as a measure of the integrated area Q_gT of the input signal.

Neural Correlates and Mechanisms of Spatial Release From Masking: Single-Unit and Population Responses in the Inferior Colliculus

PubMed Central

Lane, Courtney C.; Delgutte, Bertrand

2007-01-01

Spatial release from masking (SRM), a factor in listening in noisy environments, is the improvement in auditory signal detection obtained when a signal is separated in space from a masker. To study the neural mechanisms of SRM, we recorded from single units in the inferior colliculus (IC) of barbiturate-anesthetized cats, focusing on low-frequency neurons sensitive to interaural time differences. The stimulus was a broadband chirp train with a 40-Hz repetition rate in continuous broadband noise, and the unit responses were measured for several signal and masker (virtual) locations. Masked thresholds (the lowest signal-to-noise ratio, SNR, for which the signal could be detected for 75% of the stimulus presentations) changed systematically with signal and masker location. Single-unit thresholds did not necessarily improve with signal and masker separation; instead, they tended to reflect the units’ azimuth preference. Both how the signal was detected (through a rate increase or decrease) and how the noise masked the signal response (suppressive or excitatory masking) changed with signal and masker azimuth, consistent with a cross-correlator model of binaural processing. However, additional processing, perhaps related to the signal’s amplitude modulation rate, appeared to influence the units’ responses. The population masked thresholds (the most sensitive unit’s threshold at each signal and masker location) did improve with signal and masker separation as a result of the variety of azimuth preferences in our unit sample. The population thresholds were similar to human behavioral thresholds in both SNR value and shape, indicating that these units may provide a neural substrate for low-frequency SRM. PMID:15857966

Radar signal pre-processing to suppress surface bounce and multipath

DOEpatents

Paglieroni, David W; Mast, Jeffrey E; Beer, N. Reginald

2013-12-31

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 that 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.

Improved Reconstruction of Radio Holographic Signal for Forward Scatter Radar Imaging

PubMed Central

Hu, Cheng; Liu, Changjiang; Wang, Rui; Zeng, Tao

2016-01-01

Forward scatter radar (FSR), as a specially configured bistatic radar, is provided with the capabilities of target recognition and classification by the Shadow Inverse Synthetic Aperture Radar (SISAR) imaging technology. This paper mainly discusses the reconstruction of radio holographic signal (RHS), which is an important procedure in the signal processing of FSR SISAR imaging. Based on the analysis of signal characteristics, the method for RHS reconstruction is improved in two parts: the segmental Hilbert transformation and the reconstruction of mainlobe RHS. In addition, a quantitative analysis of the method’s applicability is presented by distinguishing between the near field and far field in forward scattering. Simulation results validated the method’s advantages in improving the accuracy of RHS reconstruction and imaging. PMID:27164114

Application of wavelet filtering and Barker-coded pulse compression hybrid method to air-coupled ultrasonic testing

NASA Astrophysics Data System (ADS)

Zhou, Zhenggan; Ma, Baoquan; Jiang, Jingtao; Yu, Guang; Liu, Kui; Zhang, Dongmei; Liu, Weiping

2014-10-01

Air-coupled ultrasonic testing (ACUT) technique has been viewed as a viable solution in defect detection of advanced composites used in aerospace and aviation industries. However, the giant mismatch of acoustic impedance in air-solid interface makes the transmission efficiency of ultrasound low, and leads to poor signal-to-noise (SNR) ratio of received signal. The utilisation of signal-processing techniques in non-destructive testing is highly appreciated. This paper presents a wavelet filtering and phase-coded pulse compression hybrid method to improve the SNR and output power of received signal. The wavelet transform is utilised to filter insignificant components from noisy ultrasonic signal, and pulse compression process is used to improve the power of correlated signal based on cross-correction algorithm. For the purpose of reasonable parameter selection, different families of wavelets (Daubechies, Symlet and Coiflet) and decomposition level in discrete wavelet transform are analysed, different Barker codes (5-13 bits) are also analysed to acquire higher main-to-side lobe ratio. The performance of the hybrid method was verified in a honeycomb composite sample. Experimental results demonstrated that the proposed method is very efficient in improving the SNR and signal strength. The applicability of the proposed method seems to be a very promising tool to evaluate the integrity of high ultrasound attenuation composite materials using the ACUT.

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.

Platform for Post-Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Don J.

2010-01-01

Signal- and image-processing methods are commonly needed to extract information from the waves, improve resolution of, and highlight defects in an image. Since some similarity exists for all waveform-based nondestructive evaluation (NDE) methods, it would seem that a common software platform containing multiple signal- and image-processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. NDE Wave & Image Processor Version 2.0 software provides a single, integrated signal- and image-processing and analysis environment for total NDE data processing and analysis. It brings some of the most useful algorithms developed for NDE over the past 20 years into a commercial-grade product. The software can import signal/spectroscopic data, image data, and image series data. This software offers the user hundreds of basic and advanced signal- and image-processing capabilities including esoteric 1D and 2D wavelet-based de-noising, de-trending, and filtering. Batch processing is included for signal- and image-processing capability so that an optimized sequence of processing operations can be applied to entire folders of signals, spectra, and images. Additionally, an extensive interactive model-based curve-fitting facility has been included to allow fitting of spectroscopy data such as from Raman spectroscopy. An extensive joint-time frequency module is included for analysis of non-stationary or transient data such as that from acoustic emission, vibration, or earthquake data.

System theory in industrial patient monitoring: an overview.

PubMed

Baura, G D

2004-01-01

Patient monitoring refers to the continuous observation of repeating events of physiologic function to guide therapy or to monitor the effectiveness of interventions, and is used primarily in the intensive care unit and operating room. Commonly processed signals are the electrocardiogram, intraarterial blood pressure, arterial saturation of oxygen, and cardiac output. To this day, the majority of physiologic waveform processing in patient monitors is conducted using heuristic curve fitting. However in the early 1990s, a few enterprising engineers and physicians began using system theory to improve their core processing. Applications included improvement of signal-to-noise ratio, either due to low signal levels or motion artifact, and improvement in feature detection. The goal of this mini-symposium is to review the early work in this emerging field, which has led to technologic breakthroughs. In this overview talk, the process of system theory algorithm research and development is discussed. Research for industrial monitors involves substantial data collection, with some data used for algorithm training and the remainder used for validation. Once the algorithms are validated, they are translated into detailed specifications. Development then translates these specifications into DSP code. The DSP code is verified and validated per the Good Manufacturing Practices mandated by FDA.

Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review.

PubMed

Du, Jiaying; Gerdtman, Christer; Lindén, Maria

2018-04-06

Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented.

Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review

PubMed Central

Gerdtman, Christer

2018-01-01

Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented. PMID:29642412

Grey signal processing and data reconstruction in the non-diffracting beam triangulation measurement system

NASA Astrophysics Data System (ADS)

Meng, Hao; Wang, Zhongyu; Fu, Jihua

2008-12-01

The non-diffracting beam triangulation measurement system possesses the advantages of longer measurement range, higher theoretical measurement accuracy and higher resolution over the traditional laser triangulation measurement system. Unfortunately the measurement accuracy of the system is greatly degraded due to the speckle noise, the CCD photoelectric noise and the background light noise in practical applications. Hence, some effective signal processing methods must be applied to improve the measurement accuracy. In this paper a novel effective method for removing the noises in the non-diffracting beam triangulation measurement system is proposed. In the method the grey system theory is used to process and reconstruct the measurement signal. Through implementing the grey dynamic filtering based on the dynamic GM(1,1), the noises can be effectively removed from the primary measurement data and the measurement accuracy of the system can be improved as a result.

Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

NASA Astrophysics Data System (ADS)

Si, Qian

Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

[A modified speech enhancement algorithm for electronic cochlear implant and its digital signal processing realization].

PubMed

Wang, Yulin; Tian, Xuelong

2014-08-01

In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients.

Burst design and signal processing for the speed of sound measurement of fluids with the pulse-echo technique

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

Dubberke, Frithjof H.; Baumhögger, Elmar; Vrabec, Jadran, E-mail: jadran.vrabec@upb.de

2015-05-15

The pulse-echo technique determines the propagation time of acoustic wave bursts in a fluid over a known propagation distance. It is limited by the signal quality of the received echoes of the acoustic wave bursts, which degrades with decreasing density of the fluid due to acoustic impedance and attenuation effects. Signal sampling is significantly improved in this work by burst design and signal processing such that a wider range of thermodynamic states can be investigated. Applying a Fourier transformation based digital filter on acoustic wave signals increases their signal-to-noise ratio and enhances their time and amplitude resolutions, improving the overallmore » measurement accuracy. In addition, burst design leads to technical advantages for determining the propagation time due to the associated conditioning of the echo. It is shown that the according operation procedure enlarges the measuring range of the pulse-echo technique for supercritical argon and nitrogen at 300 K down to 5 MPa, where it was limited to around 20 MPa before.« less

True-Triaxial Experimental Study of the Evolutionary Features of the Acoustic Emissions and Sounds of Rockburst Processes

NASA Astrophysics Data System (ADS)

Su, Guoshao; Shi, Yanjiong; Feng, Xiating; Jiang, Jianqing; Zhang, Jie; Jiang, Quan

2018-02-01

Rockbursts are markedly characterized by the ejection of rock fragments from host rocks at certain speeds. The rockburst process is always accompanied by acoustic signals that include acoustic emissions (AE) and sounds. A deep insight into the evolutionary features of AE and sound signals is important to improve the accuracy of rockburst prediction. To investigate the evolutionary features of AE and sound signals, rockburst tests on granite rock specimens under true-triaxial loading conditions were performed using an improved rockburst testing system, and the AE and sounds during rockburst development were recorded and analyzed. The results show that the evolutionary features of the AE and sound signals were obvious and similar. On the eve of a rockburst, a `quiescent period' could be observed in both the evolutionary process of the AE hits and the sound waveform. Furthermore, the time-dependent fractal dimensions of the AE hits and sound amplitude both showed a tendency to continuously decrease on the eve of the rockbursts. In addition, on the eve of the rockbursts, the main frequency of the AE and sound signals both showed decreasing trends, and the frequency spectrum distributions were both characterized by low amplitudes, wide frequency bands and multiple peak shapes. Thus, the evolutionary features of sound signals on the eve of rockbursts, as well as that of AE signals, can be used as beneficial information for rockburst prediction.

Dictionary-based image reconstruction for superresolution in integrated circuit imaging.

PubMed

Cilingiroglu, T Berkin; Uyar, Aydan; Tuysuzoglu, Ahmet; Karl, W Clem; Konrad, Janusz; Goldberg, Bennett B; Ünlü, M Selim

2015-06-01

Resolution improvement through signal processing techniques for integrated circuit imaging is becoming more crucial as the rapid decrease in integrated circuit dimensions continues. Although there is a significant effort to push the limits of optical resolution for backside fault analysis through the use of solid immersion lenses, higher order laser beams, and beam apodization, signal processing techniques are required for additional improvement. In this work, we propose a sparse image reconstruction framework which couples overcomplete dictionary-based representation with a physics-based forward model to improve resolution and localization accuracy in high numerical aperture confocal microscopy systems for backside optical integrated circuit analysis. The effectiveness of the framework is demonstrated on experimental data.

Intelligent diagnosis of short hydraulic signal based on improved EEMD and SVM with few low-dimensional training samples

NASA Astrophysics Data System (ADS)

Zhang, Meijun; Tang, Jian; Zhang, Xiaoming; Zhang, Jiaojiao

2016-03-01

The high accurate classification ability of an intelligent diagnosis method often needs a large amount of training samples with high-dimensional eigenvectors, however the characteristics of the signal need to be extracted accurately. Although the existing EMD(empirical mode decomposition) and EEMD(ensemble empirical mode decomposition) are suitable for processing non-stationary and non-linear signals, but when a short signal, such as a hydraulic impact signal, is concerned, their decomposition accuracy become very poor. An improve EEMD is proposed specifically for short hydraulic impact signals. The improvements of this new EEMD are mainly reflected in four aspects, including self-adaptive de-noising based on EEMD, signal extension based on SVM(support vector machine), extreme center fitting based on cubic spline interpolation, and pseudo component exclusion based on cross-correlation analysis. After the energy eigenvector is extracted from the result of the improved EEMD, the fault pattern recognition based on SVM with small amount of low-dimensional training samples is studied. At last, the diagnosis ability of improved EEMD+SVM method is compared with the EEMD+SVM and EMD+SVM methods, and its diagnosis accuracy is distinctly higher than the other two methods no matter the dimension of the eigenvectors are low or high. The improved EEMD is very propitious for the decomposition of short signal, such as hydraulic impact signal, and its combination with SVM has high ability for the diagnosis of hydraulic impact faults.

Effects of Cr2O3 Activating Flux on the Plasma Plume in Pulsed Laser Welding

NASA Astrophysics Data System (ADS)

Yi, Luo; Yunfei, Du; Xiaojian, Xie; Rui, Wan; Liang, Zhu; Jingtao, Han

2016-11-01

The effects of Cr2O3 activating flux on pulsed YAG laser welding of stainless steel and, particularly, on the behavior of the plasma plume in the welding process were investigated. According to the acoustic emission (AE) signals detected in the welding process, the possible mechanism for the improvement in penetration depth was discussed. The results indicated that the AE signals detected in the welding process reflected the behavior of the plasma plume as pulsed laser energy affecting the molten pool. The root-mean-square (RMS) waveform, AE count, and power spectrum of AE signals were three effective means to characterize the behavior of the plasma plume, which indicated the characteristics of energy released by the plasma plume. The activating flux affected by the laser beam helped to increase the duration and intensity of energy released by the plasma plume, which improved the recoil force and thermal effect transferred from the plasma plume to the molten pool. These results were the main mechanism for Cr2O3 activating flux addition improving the penetration depth in pulsed YAG laser welding.

A data processing method based on tracking light spot for the laser differential confocal component parameters measurement system

NASA Astrophysics Data System (ADS)

Shao, Rongjun; Qiu, Lirong; Yang, Jiamiao; Zhao, Weiqian; Zhang, Xin

2013-12-01

We have proposed the component parameters measuring method based on the differential confocal focusing theory. In order to improve the positioning precision of the laser differential confocal component parameters measurement system (LDDCPMS), the paper provides a data processing method based on tracking light spot. To reduce the error caused by the light point moving in collecting the axial intensity signal, the image centroiding algorithm is used to find and track the center of Airy disk of the images collected by the laser differential confocal system. For weakening the influence of higher harmonic noises during the measurement, Gaussian filter is used to process the axial intensity signal. Ultimately the zero point corresponding to the focus of the objective in a differential confocal system is achieved by linear fitting for the differential confocal axial intensity data. Preliminary experiments indicate that the method based on tracking light spot can accurately collect the axial intensity response signal of the virtual pinhole, and improve the anti-interference ability of system. Thus it improves the system positioning accuracy.

Utilization of a balanced steady state free precession signal model for improved fat/water decomposition.

PubMed

Henze Bancroft, Leah C; Strigel, Roberta M; Hernando, Diego; Johnson, Kevin M; Kelcz, Frederick; Kijowski, Richard; Block, Walter F

2016-03-01

Chemical shift based fat/water decomposition methods such as IDEAL are frequently used in challenging imaging environments with large B0 inhomogeneity. However, they do not account for the signal modulations introduced by a balanced steady state free precession (bSSFP) acquisition. Here we demonstrate improved performance when the bSSFP frequency response is properly incorporated into the multipeak spectral fat model used in the decomposition process. Balanced SSFP allows for rapid imaging but also introduces a characteristic frequency response featuring periodic nulls and pass bands. Fat spectral components in adjacent pass bands will experience bulk phase offsets and magnitude modulations that change the expected constructive and destructive interference between the fat spectral components. A bSSFP signal model was incorporated into the fat/water decomposition process and used to generate images of a fat phantom, and bilateral breast and knee images in four normal volunteers at 1.5 Tesla. Incorporation of the bSSFP signal model into the decomposition process improved the performance of the fat/water decomposition. Incorporation of this model allows rapid bSSFP imaging sequences to use robust fat/water decomposition methods such as IDEAL. While only one set of imaging parameters were presented, the method is compatible with any field strength or repetition time. © 2015 Wiley Periodicals, Inc.

Digital phonocardiographic experiments and signal processing in multidisciplinary fields of university education

NASA Astrophysics Data System (ADS)

Nagy, Tamás; Vadai, Gergely; Gingl, Zoltán

2017-09-01

Modern measurement of physical signals is based on the use of sensors, electronic signal conditioning, analog-to-digital conversion and digital signal processing carried out by dedicated software. The same signal chain is used in many devices such as home appliances, automotive electronics, medical instruments, and smartphones. Teaching the theoretical, experimental, and signal processing background must be an essential part of improving the standard of higher education, and it fits well to the increasingly multidisciplinary nature of physics and engineering too. In this paper, we show how digital phonocardiography can be used in university education as a universal, highly scalable, exciting, and inspiring laboratory practice and as a demonstration at various levels and complexity. We have developed open-source software templates in modern programming languages to support immediate use and to serve as a basis of further modifications using personal computers, tablets, and smartphones.

Improving the signal analysis for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Niu, Zhenyu; Yang, Ping; Wei, Dan; Tang, Shuo; Wei, Xunbin

2015-03-01

At early stage of cancer, a small number of circulating tumor cells (CTCs) appear in the blood circulation. Thus, early detection of malignant circulating tumor cells has great significance for timely treatment to reduce the cancer death rate. We have developed an in vivo photoacoustic flow cytometry (PAFC) to monitor the metastatic process of CTCs and record the signals from target cells. Information of target cells which is helpful to the early therapy would be obtained through analyzing and processing the signals. The raw signal detected from target cells often contains some noise caused by electronic devices, such as background noise and thermal noise. We choose the Wavelet denoising method to effectively distinguish the target signal from background noise. Processing in time domain and frequency domain would be combined to analyze the signal after denoising. This algorithm contains time domain filter and frequency transformation. The frequency spectrum image of the signal contains distinctive features that can be used to analyze the property of target cells or particles. The PAFC technique can detect signals from circulating tumor cells or other particles. The processing methods have a great potential for analyzing signals accurately and rapidly.

Nonlinear Blind Compensation for Array Signal Processing Application

PubMed Central

Ma, Hong; Jin, Jiang; Zhang, Hua

2018-01-01

Recently, nonlinear blind compensation technique has attracted growing attention in array signal processing application. However, due to the nonlinear distortion stemming from array receiver which consists of multi-channel radio frequency (RF) front-ends, it is too difficult to estimate the parameters of array signal accurately. A novel nonlinear blind compensation algorithm aims at the nonlinearity mitigation of array receiver and its spurious-free dynamic range (SFDR) improvement, which will be more precise to estimate the parameters of target signals such as their two-dimensional directions of arrival (2-D DOAs). Herein, the suggested method is designed as follows: the nonlinear model parameters of any channel of RF front-end are extracted to synchronously compensate the nonlinear distortion of the entire receiver. Furthermore, a verification experiment on the array signal from a uniform circular array (UCA) is adopted to testify the validity of our approach. The real-world experimental results show that the SFDR of the receiver is enhanced, leading to a significant improvement of the 2-D DOAs estimation performance for weak target signals. And these results demonstrate that our nonlinear blind compensation algorithm is effective to estimate the parameters of weak array signal in concomitance with strong jammers. PMID:29690571

Research on on-line monitoring technology for steel ball's forming process based on load signal analysis method

NASA Astrophysics Data System (ADS)

Li, Ying-jun; Ai, Chang-sheng; Men, Xiu-hua; Zhang, Cheng-liang; Zhang, Qi

2013-04-01

This paper presents a novel on-line monitoring technology to obtain forming quality in steel ball's forming process based on load signal analysis method, in order to reveal the bottom die's load characteristic in initial cold heading forging process of steel balls. A mechanical model of the cold header producing process is established and analyzed by using finite element method. The maximum cold heading force is calculated. The results prove that the monitoring on the cold heading process with upsetting force is reasonable and feasible. The forming defects are inflected on the three feature points of the bottom die signals, which are the initial point, infection point, and peak point. A novel PVDF piezoelectric force sensor which is simple on construction and convenient on installation is designed. The sensitivity of the PVDF force sensor is calculated. The characteristics of PVDF force sensor are analyzed by FEM. The PVDF piezoelectric force sensor is fabricated to acquire the actual load signals in the cold heading process, and calibrated by a special device. The measuring system of on-line monitoring is built. The characteristics of the actual signals recognized by learning and identification algorithm are in consistence with simulation results. Identification of actual signals shows that the timing difference values of all feature points for qualified products are not exceed ±6 ms, and amplitude difference values are less than ±3%. The calibration and application experiments show that PVDF force sensor has good static and dynamic performances, and is competent at dynamic measuring on upsetting force. It greatly improves automatic level and machining precision. Equipment capacity factor with damages identification method depends on grade of steel has been improved to 90%.

Fault Detection of Roller-Bearings Using Signal Processing and Optimization Algorithms

PubMed Central

Kwak, Dae-Ho; Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2014-01-01

This study presents a fault detection of roller bearings through signal processing and optimization techniques. After the occurrence of scratch-type defects on the inner race of bearings, variations of kurtosis values are investigated in terms of two different data processing techniques: minimum entropy deconvolution (MED), and the Teager-Kaiser Energy Operator (TKEO). MED and the TKEO are employed to qualitatively enhance the discrimination of defect-induced repeating peaks on bearing vibration data with measurement noise. Given the perspective of the execution sequence of MED and the TKEO, the study found that the kurtosis sensitivity towards a defect on bearings could be highly improved. Also, the vibration signal from both healthy and damaged bearings is decomposed into multiple intrinsic mode functions (IMFs), through empirical mode decomposition (EMD). The weight vectors of IMFs become design variables for a genetic algorithm (GA). The weights of each IMF can be optimized through the genetic algorithm, to enhance the sensitivity of kurtosis on damaged bearing signals. Experimental results show that the EMD-GA approach successfully improved the resolution of detectability between a roller bearing with defect, and an intact system. PMID:24368701

Digitally Enhanced Heterodyne Interferometry

NASA Technical Reports Server (NTRS)

Shaddock, Daniel; Ware, Brent; Lay, Oliver; Dubovitsky, Serge

2010-01-01

Spurious interference limits the performance of many interferometric measurements. Digitally enhanced interferometry (DEI) improves measurement sensitivity by augmenting conventional heterodyne interferometry with pseudo-random noise (PRN) code phase modulation. DEI effectively changes the measurement problem from one of hardware (optics, electronics), which may deteriorate over time, to one of software (modulation, digital signal processing), which does not. DEI isolates interferometric signals based on their delay. Interferometric signals are effectively time-tagged by phase-modulating the laser source with a PRN code. DEI improves measurement sensitivity by exploiting the autocorrelation properties of the PRN to isolate only the signal of interest and reject spurious interference. The properties of the PRN code determine the degree of isolation.

On the Use of a Signal Quality Index Applying at Tracking Stage Level to Assist the RAIM System of a GNSS Receiver.

PubMed

Berardo, Mattia; Lo Presti, Letizia

2016-07-02

In this work, a novel signal processing method is proposed to assist the Receiver Autonomous Integrity Monitoring (RAIM) module used in a receiver of Global Navigation Satellite Systems (GNSS) to improve the integrity of the estimated position. The proposed technique represents an evolution of the Multipath Distance Detector (MPDD), thanks to the introduction of a Signal Quality Index (SQI), which is both a metric able to evaluate the goodness of the signal, and a parameter used to improve the performance of the RAIM modules. Simulation results show the effectiveness of the proposed method.

[An Extraction and Recognition Method of the Distributed Optical Fiber Vibration Signal Based on EMD-AWPP and HOSA-SVM Algorithm].

PubMed

Zhang, Yanjun; Liu, Wen-zhe; Fu, Xing-hu; Bi, Wei-hong

2016-02-01

Given that the traditional signal processing methods can not effectively distinguish the different vibration intrusion signal, a feature extraction and recognition method of the vibration information is proposed based on EMD-AWPP and HOSA-SVM, using for high precision signal recognition of distributed fiber optic intrusion detection system. When dealing with different types of vibration, the method firstly utilizes the adaptive wavelet processing algorithm based on empirical mode decomposition effect to reduce the abnormal value influence of sensing signal and improve the accuracy of signal feature extraction. Not only the low frequency part of the signal is decomposed, but also the high frequency part the details of the signal disposed better by time-frequency localization process. Secondly, it uses the bispectrum and bicoherence spectrum to accurately extract the feature vector which contains different types of intrusion vibration. Finally, based on the BPNN reference model, the recognition parameters of SVM after the implementation of the particle swarm optimization can distinguish signals of different intrusion vibration, which endows the identification model stronger adaptive and self-learning ability. It overcomes the shortcomings, such as easy to fall into local optimum. The simulation experiment results showed that this new method can effectively extract the feature vector of sensing information, eliminate the influence of random noise and reduce the effects of outliers for different types of invasion source. The predicted category identifies with the output category and the accurate rate of vibration identification can reach above 95%. So it is better than BPNN recognition algorithm and improves the accuracy of the information analysis effectively.

Study on De-noising Technology of Radar Life Signal

NASA Astrophysics Data System (ADS)

Yang, Xiu-Fang; Wang, Lian-Huan; Ma, Jiang-Fei; Wang, Pei-Pei

2016-05-01

Radar detection is a kind of novel life detection technology, which can be applied to medical monitoring, anti-terrorism and disaster relief street fighting, etc. As the radar life signal is very weak, it is often submerged in the noise. Because of non-stationary and randomness of these clutter signals, it is necessary to denoise efficiently before extracting and separating the useful signal. This paper improves the radar life signal's theoretical model of the continuous wave, does de-noising processing by introducing lifting wavelet transform and determine the best threshold function through comparing the de-noising effects of different threshold functions. The result indicates that both SNR and MSE of the signal are better than the traditional ones by introducing lifting wave transform and using a new improved soft threshold function de-noising method..

Research and Implementation of Heart Sound Denoising

NASA Astrophysics Data System (ADS)

Liu, Feng; Wang, Yutai; Wang, Yanxiang

Heart sound is one of the most important signals. However, the process of getting heart sound signal can be interfered with many factors outside. Heart sound is weak electric signal and even weak external noise may lead to the misjudgment of pathological and physiological information in this signal, thus causing the misjudgment of disease diagnosis. As a result, it is a key to remove the noise which is mixed with heart sound. In this paper, a more systematic research and analysis which is involved in heart sound denoising based on matlab has been made. The study of heart sound denoising based on matlab firstly use the powerful image processing function of matlab to transform heart sound signals with noise into the wavelet domain through wavelet transform and decomposition these signals in muli-level. Then for the detail coefficient, soft thresholding is made using wavelet transform thresholding to eliminate noise, so that a signal denoising is significantly improved. The reconstructed signals are gained with stepwise coefficient reconstruction for the processed detail coefficient. Lastly, 50HZ power frequency and 35 Hz mechanical and electrical interference signals are eliminated using a notch filter.

Digital Signal Processing Based on a Clustering Algorithm for Ir/Au TES Microcalorimeter

NASA Astrophysics Data System (ADS)

Zen, N.; Kunieda, Y.; Takahashi, H.; Hiramoto, K.; Nakazawa, M.; Fukuda, D.; Ukibe, M.; Ohkubo, M.

2006-02-01

In recent years, cryogenic microcalorimeters using their superconducting transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy resolution of superconducting transition edge sensors (TES), several correction methods have been developed. Among them, a clustering method based on digital signal processing has recently been proposed. In this paper, we applied the clustering method to Ir/Au bilayer TES. This method resulted in almost a 10% improvement in the energy resolution. Conversely, from the point of view of imaging X-ray spectroscopy, we applied the clustering method to pixellated Ir/Au-TES devices. We will thus show how a clustering method which sorts signals by their shapes is also useful for position identification

Solar loading thermography: Time-lapsed thermographic survey and advanced thermographic signal processing for the inspection of civil engineering and cultural heritage structures

NASA Astrophysics Data System (ADS)

Ibarra-Castanedo, Clemente; Sfarra, Stefano; Klein, Matthieu; Maldague, Xavier

2017-05-01

The experimental results from infrared thermography surveys over two buildings externally exposed walls are presented. Data acquisition was performed on a static configuration by recording direct and indirect solar loading during several days and was processed using advanced signal processing techniques in order to increase signal-to-noise ratio and signature contrast of the elements of interest. It is demonstrated that it is possible to detect the thermal signature of large internal structures as well as surface features under such thermographic scenarios. Results from a long-wave microbolometer compared favorably to those from a mid-wave cooled infrared camera for the detection of large subsurface features from unprocessed images. In both cases, however, advanced signal processing greatly improved contrast of the internal features.

RASSP signal processing architectures

NASA Astrophysics Data System (ADS)

Shirley, Fred; Bassett, Bob; Letellier, J. P.

1995-06-01

The rapid prototyping of application specific signal processors (RASSP) program is an ARPA/tri-service effort to dramatically improve the process by which complex digital systems, particularly embedded signal processors, are specified, designed, documented, manufactured, and supported. The domain of embedded signal processing was chosen because it is important to a variety of military and commercial applications as well as for the challenge it presents in terms of complexity and performance demands. The principal effort is being performed by two major contractors, Lockheed Sanders (Nashua, NH) and Martin Marietta (Camden, NJ). For both, improvements in methodology are to be exercised and refined through the performance of individual 'Demonstration' efforts. The Lockheed Sanders' Demonstration effort is to develop an infrared search and track (IRST) processor. In addition, both contractors' results are being measured by a series of externally administered (by Lincoln Labs) six-month Benchmark programs that measure process improvement as a function of time. The first two Benchmark programs are designing and implementing a synthetic aperture radar (SAR) processor. Our demonstration team is using commercially available VME modules from Mercury Computer to assemble a multiprocessor system scalable from one to hundreds of Intel i860 microprocessors. Custom modules for the sensor interface and display driver are also being developed. This system implements either proprietary or Navy owned algorithms to perform the compute-intensive IRST function in real time in an avionics environment. Our Benchmark team is designing custom modules using commercially available processor ship sets, communication submodules, and reconfigurable logic devices. One of the modules contains multiple vector processors optimized for fast Fourier transform processing. Another module is a fiberoptic interface that accepts high-rate input data from the sensors and provides video-rate output data to a display. This paper discusses the impact of simulation on choosing signal processing algorithms and architectures, drawing from the experiences of the Demonstration and Benchmark inter-company teams at Lockhhed Sanders, Motorola, Hughes, and ISX.

Enhancing Soundtracks From Old Movies

NASA Technical Reports Server (NTRS)

Frazer, Robert E.

1992-01-01

Proposed system enhances soundtracks of old movies. Signal on optical soundtrack of film digitized and processed to reduce noise and improve quality; timing signals added, and signal recorded on compact disk. Digital comparator and voltage-controlled oscillator synchronizes speed of film-drive motor and compact disk motor. Frame-coded detector reads binary frame-identifying marks on film. Digital comparator generates error signal if marks on film do not match those on compact disk.

Analysis on electronic control unit of continuously variable transmission

NASA Astrophysics Data System (ADS)

Cao, Shuanggui

Continuously variable transmission system can ensure that the engine work along the line of best fuel economy, improve fuel economy, save fuel and reduce harmful gas emissions. At the same time, continuously variable transmission allows the vehicle speed is more smooth and improves the ride comfort. Although the CVT technology has made great development, but there are many shortcomings in the CVT. The CVT system of ordinary vehicles now is still low efficiency, poor starting performance, low transmission power, and is not ideal controlling, high cost and other issues. Therefore, many scholars began to study some new type of continuously variable transmission. The transmission system with electronic systems control can achieve automatic control of power transmission, give full play to the characteristics of the engine to achieve optimal control of powertrain, so the vehicle is always traveling around the best condition. Electronic control unit is composed of the core processor, input and output circuit module and other auxiliary circuit module. Input module collects and process many signals sent by sensor and , such as throttle angle, brake signals, engine speed signal, speed signal of input and output shaft of transmission, manual shift signals, mode selection signals, gear position signal and the speed ratio signal, so as to provide its corresponding processing for the controller core.

Improving Signal Detection using Allan and Theo Variances

NASA Astrophysics Data System (ADS)

Hardy, Andrew; Broering, Mark; Korsch, Wolfgang

2017-09-01

Precision measurements often deal with small signals buried within electronic noise. Extracting these signals can be enhanced through digital signal processing. Improving these techniques provide signal to noise ratios. Studies presently performed at the University of Kentucky are utilizing the electro-optic Kerr effect to understand cell charging effects within ultra-cold neutron storage cells. This work is relevant for the neutron electric dipole moment (nEDM) experiment at Oak Ridge National Laboratory. These investigations, and future investigations in general, will benefit from the illustrated improved analysis techniques. This project will showcase various methods for determining the optimum duration that data should be gathered for. Typically, extending the measuring time of an experimental run reduces the averaged noise. However, experiments also encounter drift due to fluctuations which mitigate the benefits of extended data gathering. Through comparing FFT averaging techniques, along with Allan and Theo variance measurements, quantifiable differences in signal detection will be presented. This research is supported by DOE Grants: DE-FG02-99ER411001, DE-AC05-00OR22725.

Augmenting the decomposition of EMG signals using supervised feature extraction techniques.

PubMed

Parsaei, Hossein; Gangeh, Mehrdad J; Stashuk, Daniel W; Kamel, Mohamed S

2012-01-01

Electromyographic (EMG) signal decomposition is the process of resolving an EMG signal into its constituent motor unit potential trains (MUPTs). In this work, the possibility of improving the decomposing results using two supervised feature extraction methods, i.e., Fisher discriminant analysis (FDA) and supervised principal component analysis (SPCA), is explored. Using the MUP labels provided by a decomposition-based quantitative EMG system as a training data for FDA and SPCA, the MUPs are transformed into a new feature space such that the MUPs of a single MU become as close as possible to each other while those created by different MUs become as far as possible. The MUPs are then reclassified using a certainty-based classification algorithm. Evaluation results using 10 simulated EMG signals comprised of 3-11 MUPTs demonstrate that FDA and SPCA on average improve the decomposition accuracy by 6%. The improvement for the most difficult-to-decompose signal is about 12%, which shows the proposed approach is most beneficial in the decomposition of more complex signals.

Evaluation of arterial stiffness by finger-toe pulse wave velocity: optimization of signal processing and clinical validation.

PubMed

Obeid, Hasan; Khettab, Hakim; Marais, Louise; Hallab, Magid; Laurent, Stéphane; Boutouyrie, Pierre

2017-08-01

Carotid-femoral pulse wave velocity (PWV) (cf-PWV) is the gold standard for measuring aortic stiffness. Finger-toe PWV (ft-PWV) is a simpler noninvasive method for measuring arterial stiffness. Although the validity of the method has been previously assessed, its accuracy can be improved. ft-PWV is determined on the basis of a patented height chart for the distance and the pulse transit time (PTT) between the finger and the toe pulpar arteries signals (ft-PTT). The objective of the first study, performed in 66 patients, was to compare different algorithms (intersecting tangents, maximum of the second derivative, 10% threshold and cross-correlation) for determining the foot of the arterial pulse wave, thus the ft-PTT. The objective of the second study, performed in 101 patients, was to investigate different signal processing chains to improve the concordance of ft-PWV with the gold-standard cf-PWV. Finger-toe PWV (ft-PWV) was calculated using the four algorithms. The best correlations relating ft-PWV and cf-PWV, and relating ft-PTT and carotid-femoral PTT were obtained with the maximum of the second derivative algorithm [PWV: r = 0.56, P < 0.0001, root mean square error (RMSE) = 0.9 m/s; PTT: r = 0.61, P < 0.001, RMSE = 12 ms]. The three other algorithms showed lower correlations. The correlation between ft-PTT and carotid-femoral PTT further improved (r = 0.81, P < 0.0001, RMSE = 5.4 ms) when the maximum of the second derivative algorithm was combined with an optimized signal processing chain. Selecting the maximum of the second derivative algorithm for detecting the foot of the pressure waveform, and combining it with an optimized signal processing chain, improved the accuracy of ft-PWV measurement in the current population sample. Thus, it makes ft-PWV very promising for the simple noninvasive determination of aortic stiffness in clinical practice.

[Analysis of scatterer microstructure feature based on Chirp-Z transform cepstrum].

PubMed

Guo, Jianzhong; Lin, Shuyu

2007-12-01

The fundamental research field of medical ultrasound has been the characterization of tissue scatterers. The signal processing method is widely used in this research field. A new method of Chirp-Z Transform Cepstrum for mean spacing estimation of tissue scatterers using ultrasonic scattered signals has been developed. By using this method together with conventional AR cepstrum method, we processed the backscattered signals of mimic tissue and pig liver in vitro. The results illustrated that the Chirp-Z Transform Cepstrum method is effective for signal analysis of ultrasonic scattering and characterization of tissue scatterers, and it can improve the resolution for mean spacing estimation of tissue scatterers.

Noise shaping in populations of coupled model neurons.

PubMed

Mar, D J; Chow, C C; Gerstner, W; Adams, R W; Collins, J J

1999-08-31

Biological information-processing systems, such as populations of sensory and motor neurons, may use correlations between the firings of individual elements to obtain lower noise levels and a systemwide performance improvement in the dynamic range or the signal-to-noise ratio. Here, we implement such correlations in networks of coupled integrate-and-fire neurons using inhibitory coupling and demonstrate that this can improve the system dynamic range and the signal-to-noise ratio in a population rate code. The improvement can surpass that expected for simple averaging of uncorrelated elements. A theory that predicts the resulting power spectrum is developed in terms of a stochastic point-process model in which the instantaneous population firing rate is modulated by the coupling between elements.

Statistical process control: separating signal from noise in emergency department operations.

PubMed

Pimentel, Laura; Barrueto, Fermin

2015-05-01

Statistical process control (SPC) is a visually appealing and statistically rigorous methodology very suitable to the analysis of emergency department (ED) operations. We demonstrate that the control chart is the primary tool of SPC; it is constructed by plotting data measuring the key quality indicators of operational processes in rationally ordered subgroups such as units of time. Control limits are calculated using formulas reflecting the variation in the data points from one another and from the mean. SPC allows managers to determine whether operational processes are controlled and predictable. We review why the moving range chart is most appropriate for use in the complex ED milieu, how to apply SPC to ED operations, and how to determine when performance improvement is needed. SPC is an excellent tool for operational analysis and quality improvement for these reasons: 1) control charts make large data sets intuitively coherent by integrating statistical and visual descriptions; 2) SPC provides analysis of process stability and capability rather than simple comparison with a benchmark; 3) SPC allows distinction between special cause variation (signal), indicating an unstable process requiring action, and common cause variation (noise), reflecting a stable process; and 4) SPC keeps the focus of quality improvement on process rather than individual performance. Because data have no meaning apart from their context, and every process generates information that can be used to improve it, we contend that SPC should be seriously considered for driving quality improvement in emergency medicine. Copyright © 2015 Elsevier Inc. All rights reserved.

Experimental photonic generation of chirped pulses using nonlinear dispersion-based incoherent processing.

PubMed

Rius, Manuel; Bolea, Mario; Mora, José; Ortega, Beatriz; Capmany, José

2015-05-18

We experimentally demonstrate, for the first time, a chirped microwave pulses generator based on the processing of an incoherent optical signal by means of a nonlinear dispersive element. Different capabilities have been demonstrated such as the control of the time-bandwidth product and the frequency tuning increasing the flexibility of the generated waveform compared to coherent techniques. Moreover, the use of differential detection improves considerably the limitation over the signal-to-noise ratio related to incoherent processing.

Spot restoration for GPR image post-processing

DOEpatents

Paglieroni, David W; Beer, N. Reginald

2014-05-20

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.

Multi-template image matching using alpha-rooted biquaternion phase correlation with application to logo recognition

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2011-06-01

Hypercomplex approaches are seeing increased application to signal and image processing problems. The use of multicomponent hypercomplex numbers, such as quaternions, enables the simultaneous co-processing of multiple signal or image components. This joint processing capability can provide improved exploitation of the information contained in the data, thereby leading to improved performance in detection and recognition problems. In this paper, we apply hypercomplex processing techniques to the logo image recognition problem. Specifically, we develop an image matcher by generalizing classical phase correlation to the biquaternion case. We further incorporate biquaternion Fourier domain alpha-rooting enhancement to create Alpha-Rooted Biquaternion Phase Correlation (ARBPC). We present the mathematical properties which justify use of ARBPC as an image matcher. We present numerical performance results of a logo verification problem using real-world logo data, demonstrating the performance improvement obtained using the hypercomplex approach. We compare results of the hypercomplex approach to standard multi-template matching approaches.

A crossover trial comparing wide dynamic range compression and frequency compression in hearing aids for tinnitus therapy.

PubMed

Hodgson, Shirley-Anne; Herdering, Regina; Singh Shekhawat, Giriraj; Searchfield, Grant D

2017-01-01

It has been suggested that frequency lowering may be a superior tinnitus reducing digital signal processing (DSP) strategy in hearing aids than conventional amplification. A crossover trial was undertaken to determine if frequency compression (FC) was superior to wide dynamic range compression (WDRC) in reducing tinnitus. A 6-8-week crossover trial of two digital signal-processing techniques (WDRC and 2 WDRC with FC) was undertaken in 16 persons with high-frequency sensorineural hearing loss and chronic tinnitus. WDRC resulted in larger improvements in Tinnitus Functional Index and rating scale scores than WDRC with FC. The tinnitus improvements obtained with both processing types appear to be due to reduced hearing handicap and possibly decreased tinnitus audibility. Hearing aids are useful assistive devices in the rehabilitation of tinnitus. FC was very successful in a few individuals but was not superior to WDRC across the sample. It is recommended that WDRC remain as the default first choice tinnitus hearing aid processing strategy for tinnitus. FC should be considered as one of the many other options for selection based on individual hearing needs. Implications of Rehabilitation Hearing aids can significantly reduce the effects of tinnitus after 6-8 weeks of use. Addition of frequency compression digital signal processing does not appear superior to standard amplitude compression alone. Improvements in tinnitus were correlated with reductions in hearing handicap.

All-optical simultaneous multichannel quadrature phase shift keying signal regeneration based on phase-sensitive amplification

NASA Astrophysics Data System (ADS)

Wang, Hongxiang; Wang, Qi; Bai, Lin; Ji, Yuefeng

2018-01-01

A scheme is proposed to realize the all-optical phase regeneration of four-channel quadrature phase shift keying (QPSK) signal based on phase-sensitive amplification. By utilizing conjugate pump and common pump in a highly nonlinear optical fiber, degenerate four-wave mixing process is observed, and QPSK signals are regenerated. The number of waves is reduced to decrease the cross talk caused by undesired nonlinear interaction during the coherent superposition process. In addition, to avoid the effect of overlapping frequency, frequency spans between pumps and signals are set to be nonintegral multiples. Optical signal-to-noise ratio improvement is validated by bit error rate measurements. Compared with single-channel regeneration, multichannel regeneration brings 0.4-dB OSNR penalty when the value of BER is 10-3, which shows the cross talk in regeneration process is negligible.

Detecting the spatial chirp signals by fractional Fourier lens with transformation materials

NASA Astrophysics Data System (ADS)

Chen, J.; Hu, J.

2018-02-01

Fractional Fourier transform (FrFT) is the general form of the Fourier transform and is an important tool in signal processing. As one typical application of FrFT, detecting the chirp rate (CR, or known as the rate of frequency change) of a chirp signal is important in many optical measurements. The optical FrFT that based on graded index lens fails to detect the high CR chirp because the short wave propagation distance of the impulse in the lens will weaken the paraxial approximation condition. With the help of transformation optics, the improved FrFT lens is proposed to adjust the high CR as well as the impulse location of the given input chirp signal. The designed transformation materials can implement the effect of space compression, making the input chirp signal is equivalent to have lower CR, therefore the system can satisfy the paraxial approximation better. As a result, this lens can improve the detection precision for the high CR. The numerical simulations verified the design. The proposed device may have both theoretical and practical values, and the design demonstrates the ability and flexibility of TO in spatial signal processing.

Improved MIMO radar GMTI via cyclic-shift transmission of orthogonal frequency division signals

NASA Astrophysics Data System (ADS)

Li, Fuyou; He, Feng; Dong, Zhen; Wu, Manqing

2018-05-01

Minimum detectable velocity (MDV) and maximum detectable velocity are both important in ground moving target indication (GMTI) systems. Smaller MDV can be achieved by longer baseline via multiple-input multiple-output (MIMO) radar. Maximum detectable velocity is decided by blind velocities associated with carrier frequencies, and blind velocities can be mitigated by orthogonal frequency division signals. However, the scattering echoes from different carrier frequencies are independent, which is not good for improving MDV performance. An improved cyclic-shift transmission is applied in MIMO GMTI system in this paper. MDV performance is improved due to the longer baseline, and maximum detectable velocity performance is improved due to the mitigation of blind velocities via multiple carrier frequencies. The signal model for this mode is established, the principle of mitigating blind velocities with orthogonal frequency division signals is presented; the performance of different MIMO GMTI waveforms is analysed; and the performance of different array configurations is analysed. Simulation results by space-time-frequency adaptive processing proves that our proposed method is a valid way to improve GMTI performance.

Electroencephalography Based Fusion Two-Dimensional (2D)-Convolution Neural Networks (CNN) Model for Emotion Recognition System.

PubMed

Kwon, Yea-Hoon; Shin, Sae-Byuk; Kim, Shin-Dug

2018-04-30

The purpose of this study is to improve human emotional classification accuracy using a convolution neural networks (CNN) model and to suggest an overall method to classify emotion based on multimodal data. We improved classification performance by combining electroencephalogram (EEG) and galvanic skin response (GSR) signals. GSR signals are preprocessed using by the zero-crossing rate. Sufficient EEG feature extraction can be obtained through CNN. Therefore, we propose a suitable CNN model for feature extraction by tuning hyper parameters in convolution filters. The EEG signal is preprocessed prior to convolution by a wavelet transform while considering time and frequency simultaneously. We use a database for emotion analysis using the physiological signals open dataset to verify the proposed process, achieving 73.4% accuracy, showing significant performance improvement over the current best practice models.

Improving the signal-to-noise ratio in ultrasound-modulated optical tomography by a lock-in amplifier

NASA Astrophysics Data System (ADS)

Zhu, Lili; Wu, Jingping; Lin, Guimin; Hu, Liangjun; Li, Hui

2016-10-01

With high spatial resolution of ultrasonic location and high sensitivity of optical detection, ultrasound-modulated optical tomography (UOT) is a promising noninvasive biological tissue imaging technology. In biological tissue, the ultrasound-modulated light signals are very weak and are overwhelmed by the strong unmodulated light signals. It is a difficulty and key to efficiently pick out the weak modulated light from strong unmodulated light in UOT. Under the effect of an ultrasonic field, the scattering light intensity presents a periodic variation as the ultrasonic frequency changes. So the modulated light signals would be escape from the high unmodulated light signals, when the modulated light signals and the ultrasonic signal are processed cross correlation operation by a lock-in amplifier and without a chopper. Experimental results indicated that the signal-to-noise ratio of UOT is significantly improved by a lock-in amplifier, and the higher the repetition frequency of pulsed ultrasonic wave, the better the signal-to-noise ratio of UOT.

Stepped-frequency GPR for utility line detection using polarization-dependent scattering

NASA Astrophysics Data System (ADS)

Jensen, Ole K.; Gregersen, Ole G.

2000-04-01

A GPR for detection of buried cables and pipes is developed by Ekko Dane Production in cooperation with Aalborg University. The appearance is a 'lawn mower' model including antennas, electronics and on-line data processing. A successful result is obtained by combining dedicated hardware and signal processing. The inherent signal to clutter ratio is bad, but making measurements at many polarization angles and subsequent signal processing improves the ratio. A simple model of the polarization dependence of the scattering from the target is used. The method is improved by combining the polarization filtering with averaging over small horizontal displacements. A stepped frequency measurement system is used. The method often implies long measurement times, but this problem is overcome by development of fast RF-electronics. Standard signal processors are used for real-time data processing. Several antenna array configurations are tested and optimized for low coupling between transmitter and receiver and for a short impulse response. A large number of tests have been made for different targets, e.g. metal cables and plastic pipes filled with air or water. Tests have been made under realistic ground conditions, including sand, wet clay, pavements and grass covered soil. The results show reliable detection even when the conditions are difficult.

Estimating the delay-Doppler of target echo in a high clutter underwater environment using wideband linear chirp signals: Evaluation of performance with experimental data.

PubMed

Yu, Ge; Yang, T C; Piao, Shengchun

2017-10-01

A chirp signal is a signal with linearly varying instantaneous frequency over the signal bandwidth, also known as a linear frequency modulated (LFM) signal. It is widely used in communication, radar, active sonar, and other applications due to its Doppler tolerance property in signal detection using the matched filter (MF) processing. Modern sonar uses high-gain, wideband signals to improve the signal to reverberation ratio. High gain implies a high product of the signal bandwidth and duration. However, wideband and/or long duration LFM signals are no longer Doppler tolerant. The shortcoming of the standard MF processing is loss of performance, and bias in range estimation. This paper uses the wideband ambiguity function and the fractional Fourier transform method to estimate the target velocity and restore the performance. Target velocity or Doppler provides a clue for differentiating the target from the background reverberation and clutter. The methods are applied to simulated and experimental data.

A systems approach for data compression and latency reduction in cortically controlled brain machine interfaces.

PubMed

Oweiss, Karim G

2006-07-01

This paper suggests a new approach for data compression during extracutaneous transmission of neural signals recorded by high-density microelectrode array in the cortex. The approach is based on exploiting the temporal and spatial characteristics of the neural recordings in order to strip the redundancy and infer the useful information early in the data stream. The proposed signal processing algorithms augment current filtering and amplification capability and may be a viable replacement to on chip spike detection and sorting currently employed to remedy the bandwidth limitations. Temporal processing is devised by exploiting the sparseness capabilities of the discrete wavelet transform, while spatial processing exploits the reduction in the number of physical channels through quasi-periodic eigendecomposition of the data covariance matrix. Our results demonstrate that substantial improvements are obtained in terms of lower transmission bandwidth, reduced latency and optimized processor utilization. We also demonstrate the improvements qualitatively in terms of superior denoising capabilities and higher fidelity of the obtained signals.

A survey on signals and systems in ambulatory blood pressure monitoring using pulse transit time.

PubMed

Buxi, Dilpreet; Redouté, Jean-Michel; Yuce, Mehmet Rasit

2015-03-01

Blood pressure monitoring based on pulse transit or arrival time has been the focus of much research in order to design ambulatory blood pressure monitors. The accuracy of these monitors is limited by several challenges, such as acquisition and processing of physiological signals as well as changes in vascular tone and the pre-ejection period. In this work, a literature survey covering recent developments is presented in order to identify gaps in the literature. The findings of the literature are classified according to three aspects. These are the calibration of pulse transit/arrival times to blood pressure, acquisition and processing of physiological signals and finally, the design of fully integrated blood pressure measurement systems. Alternative technologies as well as locations for the measurement of the pulse wave signal should be investigated in order to improve the accuracy during calibration. Furthermore, the integration and validation of monitoring systems needs to be improved in current ambulatory blood pressure monitors.

Model-based ultrasound temperature visualization during and following HIFU exposure.

PubMed

Ye, Guoliang; Smith, Penny Probert; Noble, J Alison

2010-02-01

This paper describes the application of signal processing techniques to improve the robustness of ultrasound feedback for displaying changes in temperature distribution in treatment using high-intensity focused ultrasound (HIFU), especially at the low signal-to-noise ratios that might be expected in in vivo abdominal treatment. Temperature estimation is based on the local displacements in ultrasound images taken during HIFU treatment, and a method to improve robustness to outliers is introduced. The main contribution of the paper is in the application of a Kalman filter, a statistical signal processing technique, which uses a simple analytical temperature model of heat dispersion to improve the temperature estimation from the ultrasound measurements during and after HIFU exposure. To reduce the sensitivity of the method to previous assumptions on the material homogeneity and signal-to-noise ratio, an adaptive form is introduced. The method is illustrated using data from HIFU exposure of ex vivo bovine liver. A particular advantage of the stability it introduces is that the temperature can be visualized not only in the intervals between HIFU exposure but also, for some configurations, during the exposure itself. 2010 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Digital methods of recording color television images on film tape

NASA Astrophysics Data System (ADS)

Krivitskaya, R. Y.; Semenov, V. M.

1985-04-01

Three methods are now available for recording color television images on film tape, directly or after appropriate finish of signal processing. Conventional recording of images from the screens of three kinescopes with synthetic crystal face plates is still most effective for high fidelity. This method was improved by digital preprocessing of brightness color-difference signal. Frame-by-frame storage of these signals in the memory in digital form is followed by gamma and aperture correction and electronic correction of crossover distortions in the color layers of the film with fixing in accordance with specific emulsion procedures. The newer method of recording color television images with line arrays of light-emitting diodes involves dichromic superposing mirrors and a movable scanning mirror. This method allows the use of standard movie cameras, simplifies interlacing-to-linewise conversion and the mechanical equipment, and lengthens exposure time while it shortens recording time. The latest image transform method requires an audio-video recorder, a memory disk, a digital computer, and a decoder. The 9-step procedure includes preprocessing the total color television signal with reduction of noise level and time errors, followed by frame frequency conversion and setting the number of lines. The total signal is then resolved into its brightness and color-difference components and phase errors and image blurring are also reduced. After extraction of R,G,B signals and colorimetric matching of TV camera and film tape, the simultaneous R,B, B signals are converted from interlacing to sequential triades of color-quotient frames with linewise scanning at triple frequency. Color-quotient signals are recorded with an electron beam on a smoothly moving black-and-white film tape under vacuum. While digital techniques improve the signal quality and simplify the control of processes, not requiring stabilization of circuits, image processing is still analog.

Sparse signal representation and its applications in ultrasonic NDE.

PubMed

Zhang, Guang-Ming; Zhang, Cheng-Zhong; Harvey, David M

2012-03-01

Many sparse signal representation (SSR) algorithms have been developed in the past decade. The advantages of SSR such as compact representations and super resolution lead to the state of the art performance of SSR for processing ultrasonic non-destructive evaluation (NDE) signals. Choosing a suitable SSR algorithm and designing an appropriate overcomplete dictionary is a key for success. After a brief review of sparse signal representation methods and the design of overcomplete dictionaries, this paper addresses the recent accomplishments of SSR for processing ultrasonic NDE signals. The advantages and limitations of SSR algorithms and various overcomplete dictionaries widely-used in ultrasonic NDE applications are explored in depth. Their performance improvement compared to conventional signal processing methods in many applications such as ultrasonic flaw detection and noise suppression, echo separation and echo estimation, and ultrasonic imaging is investigated. The challenging issues met in practical ultrasonic NDE applications for example the design of a good dictionary are discussed. Representative experimental results are presented for demonstration. Copyright © 2011 Elsevier B.V. All rights reserved.

Biomolecular filters for improved separation of output signals in enzyme logic systems applied to biomedical analysis.

PubMed

Halámek, Jan; Zhou, Jian; Halámková, Lenka; Bocharova, Vera; Privman, Vladimir; Wang, Joseph; Katz, Evgeny

2011-11-15

Biomolecular logic systems processing biochemical input signals and producing "digital" outputs in the form of YES/NO were developed for analysis of physiological conditions characteristic of liver injury, soft tissue injury, and abdominal trauma. Injury biomarkers were used as input signals for activating the logic systems. Their normal physiological concentrations were defined as logic-0 level, while their pathologically elevated concentrations were defined as logic-1 values. Since the input concentrations applied as logic 0 and 1 values were not sufficiently different, the output signals being at low and high values (0, 1 outputs) were separated with a short gap making their discrimination difficult. Coupled enzymatic reactions functioning as a biomolecular signal processing system with a built-in filter property were developed. The filter process involves a partial back-conversion of the optical-output-signal-yielding product, but only at its low concentrations, thus allowing the proper discrimination between 0 and 1 output values.

A study of FM threshold extension techniques

NASA Technical Reports Server (NTRS)

Arndt, G. D.; Loch, F. J.

1972-01-01

The characteristics of three postdetection threshold extension techniques are evaluated with respect to the ability of such techniques to improve the performance of a phase lock loop demodulator. These techniques include impulse-noise elimination, signal correlation for the detection of impulse noise, and delta modulation signal processing. Experimental results from signal to noise ratio data and bit error rate data indicate that a 2- to 3-decibel threshold extension is readily achievable by using the various techniques. This threshold improvement is in addition to the threshold extension that is usually achieved through the use of a phase lock loop demodulator.

Improved Imaging With Laser-Induced Eddy Currents

NASA Technical Reports Server (NTRS)

Chern, Engmin J.

1993-01-01

System tests specimen of material nondestructively by laser-induced eddy-current imaging improved by changing method of processing of eddy-current signal. Changes in impedance of eddy-current coil measured in absolute instead of relative units.

Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

PubMed

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

NASA Astrophysics Data System (ADS)

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Investigation of signal models and methods for evaluating structures of processing telecommunication information exchange systems under acoustic noise conditions

NASA Astrophysics Data System (ADS)

Kropotov, Y. A.; Belov, A. A.; Proskuryakov, A. Y.; Kolpakov, A. A.

2018-05-01

The paper considers models and methods for estimating signals during the transmission of information messages in telecommunication systems of audio exchange. One-dimensional probability distribution functions that can be used to isolate useful signals, and acoustic noise interference are presented. An approach to the estimation of the correlation and spectral functions of the parameters of acoustic signals is proposed, based on the parametric representation of acoustic signals and the components of the noise components. The paper suggests an approach to improving the efficiency of interference cancellation and highlighting the necessary information when processing signals from telecommunications systems. In this case, the suppression of acoustic noise is based on the methods of adaptive filtering and adaptive compensation. The work also describes the models of echo signals and the structure of subscriber devices in operational command telecommunications systems.

Retrograde Signals: Integrators of Interorganellar Communication and Orchestrators of Plant Development.

PubMed

de Souza, Amancio; Wang, Jin-Zheng; Dehesh, Katayoon

2017-04-28

Interorganellar cooperation maintained via exquisitely controlled retrograde-signaling pathways is an evolutionary necessity for maintenance of cellular homeostasis. This signaling feature has therefore attracted much research attention aimed at improving understanding of the nature of these communication signals, how the signals are sensed, and ultimately the mechanism by which they integrate targeted processes that collectively culminate in organellar cooperativity. The answers to these questions will provide insight into how retrograde-signal-mediated regulatory mechanisms are recruited and which biological processes are targeted, and will advance our understanding of how organisms balance metabolic investments in growth against adaptation to environmental stress. This review summarizes the present understanding of the nature and the functional complexity of retrograde signals as integrators of interorganellar communication and orchestrators of plant development, and offers a perspective on the future of this critical and dynamic area of research.

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.

Central Auditory Processing of Temporal and Spectral-Variance Cues in Cochlear Implant Listeners

PubMed Central

Pham, Carol Q.; Bremen, Peter; Shen, Weidong; Yang, Shi-Ming; Middlebrooks, John C.; Zeng, Fan-Gang; Mc Laughlin, Myles

2015-01-01

Cochlear implant (CI) listeners have difficulty understanding speech in complex listening environments. This deficit is thought to be largely due to peripheral encoding problems arising from current spread, which results in wide peripheral filters. In normal hearing (NH) listeners, central processing contributes to segregation of speech from competing sounds. We tested the hypothesis that basic central processing abilities are retained in post-lingually deaf CI listeners, but processing is hampered by degraded input from the periphery. In eight CI listeners, we measured auditory nerve compound action potentials to characterize peripheral filters. Then, we measured psychophysical detection thresholds in the presence of multi-electrode maskers placed either inside (peripheral masking) or outside (central masking) the peripheral filter. This was intended to distinguish peripheral from central contributions to signal detection. Introduction of temporal asynchrony between the signal and masker improved signal detection in both peripheral and central masking conditions for all CI listeners. Randomly varying components of the masker created spectral-variance cues, which seemed to benefit only two out of eight CI listeners. Contrastingly, the spectral-variance cues improved signal detection in all five NH listeners who listened to our CI simulation. Together these results indicate that widened peripheral filters significantly hamper central processing of spectral-variance cues but not of temporal cues in post-lingually deaf CI listeners. As indicated by two CI listeners in our study, however, post-lingually deaf CI listeners may retain some central processing abilities similar to NH listeners. PMID:26176553

Window and Overlap Processing Effects on Power Estimates from Spectra

NASA Astrophysics Data System (ADS)

Trethewey, M. W.

2000-03-01

Fast Fourier transform (FFT) spectral processing is based on the assumption of stationary ergodic data. In engineering practice, the assumption is often violated and non-stationary data processed. Data windows are commonly used to reduce leakage by decreasing the signal amplitudes near the boundaries of the discrete samples. With certain combinations of non-stationary signals and windows, the temporal weighting may attenuate important signal characteristics to adversely affect any subsequent processing. In other words, the window artificially reduces a significant section of the time signal. Consequently, spectra and overall power estimated from the affected samples are unreliable. FFT processing can be particularly problematic when the signal consists of randomly occurring transients superimposed on a more continuous signal. Overlap processing is commonly used in this situation to improve the estimates. However, the results again depend on the temporal character of the signal in relation to the window weighting. A worst-case scenario, a short-duration half sine pulse, is used to illustrate the relationship between overlap percentage and resulting power estimates. The power estimates are shown to depend on the temporal behaviour of the square of overlapped window segments. An analysis shows that power estimates may be obtained to within 0.27 dB for the following windows and overlap combinations: rectangular (0% overlap), Hanning (62.5% overlap), Hamming (60.35% overlap) and flat-top (82.25% overlap).

Research and design on orthogonal diffraction grating-based 3D nanometer displacement sensor

NASA Astrophysics Data System (ADS)

Liu, Baoshuai; Yuan, Yibao; Yin, Zhehao

2017-10-01

This study concerns an orthogonal diffraction grating-based nanometer displacement sensor. In this study, we performed calculation of displacements in the XYZ directions. In the optical measured path part, we used a two-dimensional orthogonal motion grating and a two-dimensional orthogonal reference grating with the pitch of 0.5um to measure the displacement of XYZ in three directions by detecting ±1st diffraction fringes. The self-collimated structure of the grating greatly extended the Z-axis range. We also simulated the optical path of the sensor with ZEMAX software and verified the feasibility of the scheme. For signal subdivision and processing, we combined large number counting (completed grating line) with small number counting (digital subdivision), realizing high multiples of subdivision of grating interference signals. We used PC to process the interference fringes and greatly improved the processing speed. In the scheme, the theoretical multiples of subdivision could reach 1024 with 10-bit AD conversion, but the actual multiples of subdivision was limited by the quality of the grating interference signals. So we introduced an orthogonal compensation circuit and a filter circuit to improve the signal quality.

Improvements in Speed and Functionality of a 670-GHz Imaging Radar

NASA Technical Reports Server (NTRS)

Dengler, Robert J.; Cooper, Ken B.; Mehdi, Imran; Siegel, Peter H.; Tarsala, Jan A.; Bryllert, Thomas E.

2011-01-01

Significant improvements have been made in the instrument originally described in a prior NASA Tech Briefs article: Improved Speed and Functionality of a 580-GHz Imaging Radar (NPO-45156), Vol. 34, No. 7 (July 2010), p. 51. First, the wideband YIG oscillator has been replaced with a JPL-designed and built phase-locked, low-noise chirp source. Second, further refinements to the data acquisition and signal processing software have been performed by moving critical code sections to C code, and compiling those sections to Windows DLLs, which are then invoked from the main LabVIEW executive. This system is an active, single-pixel scanned imager operating at 670 GHz. The actual chirp signals for the RF and LO chains were generated by a pair of MITEQ 2.5 3.3 GHz chirp sources. Agilent benchtop synthesizers operating at fixed frequencies around 13 GHz were then used to up-convert the chirp sources to 15.5 16.3 GHz. The resulting signals were then multiplied 36 times by a combination of off-the-shelf millimeter- wave components, and JPL-built 200- GHz doublers and 300- and 600-GHz triplers. The power required to drive the submillimeter-wave multipliers was provided by JPL-built W-band amplifiers. The receive and transmit signal paths were combined using a thin, high-resistivity silicon wafer as a beam splitter. While the results at present are encouraging, the system still lacks sufficient speed to be usable for practical applications in a contraband detection. Ideally, an image acquisition speed of ten seconds, or a factor of 30 improvement, is desired. However, the system improvements to date have resulted in a factor of five increase in signal acquisition speed, as well as enhanced signal processing algorithms, permitting clearer imaging of contraband objects hidden underneath clothing. In particular, advances in three distinct areas have enabled these performance enhancements: base source phase noise reduction, chirp rate, and signal processing. Additionally, a second pixel was added, automatically reducing the imaging time by a factor of two. Although adding a second pixel to the system doubles the amount of submillimeter components required, some savings in microwave hardware can be realized by using a common low-noise source.

Upgraded Readout Electronics for the ATLAS Liquid Argon Calorimeters at the High Luminosity LHC

NASA Astrophysics Data System (ADS)

Andeen, Timothy R.; ATLAS Liquid Argon Calorimeter Group

2012-12-01

The ATLAS liquid-argon calorimeters produce a total of 182,486 signals which are digitized and processed by the front-end and back-end electronics at every triggered event. In addition, the front-end electronics sum analog signals to provide coarsely grained energy sums, called trigger towers, to the first-level trigger system, which is optimized for nominal LHC luminosities. However, the pile-up background expected during the high luminosity phases of the LHC will be increased by factors of 3 to 7. An improved spatial granularity of the trigger primitives is therefore proposed in order to improve the identification performance for trigger signatures, like electrons or photons, at high background rejection rates. For the first upgrade phase in 2018, new Liquid Argon Trigger Digitizer Boards are being designed to receive higher granularity signals, digitize them on detector and send them via fast optical links to a new, off-detector digital processing system. The digital processing system applies digital filtering and identifies significant energy depositions. The refined trigger primitives are then transmitted to the first level trigger system to extract improved trigger signatures. The general concept of the upgraded liquid-argon calorimeter readout together with the various electronics components to be developed for such a complex system is presented. The research activities and architectural studies undertaken by the ATLAS Liquid Argon Calorimeter Group are described, particularly details of the on-going design of mixed-signal front-end electronics, of radiation tolerant optical-links, and of the high-speed off-detector digital processing system.

Performance Analysis of a Hardware Implemented Complex Signal Kurtosis Radio-Frequency Interference Detector

NASA Technical Reports Server (NTRS)

Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark

2016-01-01

Radio-frequency interference (RFI) is a known problem for passive remote sensing as evidenced in the L-band radiometers SMOS, Aquarius and more recently, SMAP. Various algorithms have been developed and implemented on SMAP to improve science measurements. This was achieved by the use of a digital microwave radiometer. RFI mitigation becomes more challenging for microwave radiometers operating at higher frequencies in shared allocations. At higher frequencies larger bandwidths are also desirable for lower measurement noise further adding to processing challenges. This work focuses on finding improved RFI mitigation techniques that will be effective at additional frequencies and at higher bandwidths. To aid the development and testing of applicable detection and mitigation techniques, a wide-band RFI algorithm testing environment has been developed using the Reconfigurable Open Architecture Computing Hardware System (ROACH) built by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Group. The testing environment also consists of various test equipment used to reproduce typical signals that a radiometer may see including those with and without RFI. The testing environment permits quick evaluations of RFI mitigation algorithms as well as show that they are implementable in hardware. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The complex signal kurtosis detector showed improved performance over the real kurtosis detector under certain conditions. The real kurtosis is implemented on SMAP at 24 MHz bandwidth. The complex signal kurtosis algorithm was then implemented in hardware at 200 MHz bandwidth using the ROACH. In this work, performance of the complex signal kurtosis and the real signal kurtosis are compared. Performance evaluations and comparisons in both simulation as well as experimental hardware implementations were done with the use of receiver operating characteristic (ROC) curves.

Spatially assisted down-track median filter for GPR image post-processing

DOEpatents

Paglieroni, David W; Beer, N Reginald

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.

An Improved WiFi Indoor Positioning Algorithm by Weighted Fusion

PubMed Central

Ma, Rui; Guo, Qiang; Hu, Changzhen; Xue, Jingfeng

2015-01-01

The rapid development of mobile Internet has offered the opportunity for WiFi indoor positioning to come under the spotlight due to its low cost. However, nowadays the accuracy of WiFi indoor positioning cannot meet the demands of practical applications. To solve this problem, this paper proposes an improved WiFi indoor positioning algorithm by weighted fusion. The proposed algorithm is based on traditional location fingerprinting algorithms and consists of two stages: the offline acquisition and the online positioning. The offline acquisition process selects optimal parameters to complete the signal acquisition, and it forms a database of fingerprints by error classification and handling. To further improve the accuracy of positioning, the online positioning process first uses a pre-match method to select the candidate fingerprints to shorten the positioning time. After that, it uses the improved Euclidean distance and the improved joint probability to calculate two intermediate results, and further calculates the final result from these two intermediate results by weighted fusion. The improved Euclidean distance introduces the standard deviation of WiFi signal strength to smooth the WiFi signal fluctuation and the improved joint probability introduces the logarithmic calculation to reduce the difference between probability values. Comparing the proposed algorithm, the Euclidean distance based WKNN algorithm and the joint probability algorithm, the experimental results indicate that the proposed algorithm has higher positioning accuracy. PMID:26334278

An Improved WiFi Indoor Positioning Algorithm by Weighted Fusion.

PubMed

Ma, Rui; Guo, Qiang; Hu, Changzhen; Xue, Jingfeng

2015-08-31

The rapid development of mobile Internet has offered the opportunity for WiFi indoor positioning to come under the spotlight due to its low cost. However, nowadays the accuracy of WiFi indoor positioning cannot meet the demands of practical applications. To solve this problem, this paper proposes an improved WiFi indoor positioning algorithm by weighted fusion. The proposed algorithm is based on traditional location fingerprinting algorithms and consists of two stages: the offline acquisition and the online positioning. The offline acquisition process selects optimal parameters to complete the signal acquisition, and it forms a database of fingerprints by error classification and handling. To further improve the accuracy of positioning, the online positioning process first uses a pre-match method to select the candidate fingerprints to shorten the positioning time. After that, it uses the improved Euclidean distance and the improved joint probability to calculate two intermediate results, and further calculates the final result from these two intermediate results by weighted fusion. The improved Euclidean distance introduces the standard deviation of WiFi signal strength to smooth the WiFi signal fluctuation and the improved joint probability introduces the logarithmic calculation to reduce the difference between probability values. Comparing the proposed algorithm, the Euclidean distance based WKNN algorithm and the joint probability algorithm, the experimental results indicate that the proposed algorithm has higher positioning accuracy.

Buried object detection in GPR images

DOEpatents

Paglieroni, David W; Chambers, David H; Bond, Steven W; Beer, W. Reginald

2014-04-29

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.

Signal processing for smart cards

NASA Astrophysics Data System (ADS)

Quisquater, Jean-Jacques; Samyde, David

2003-06-01

In 1998, Paul Kocher showed that when a smart card computes cryptographic algorithms, for signatures or encryption, its consumption or its radiations leak information. The keys or the secrets hidden in the card can then be recovered using a differential measurement based on the intercorrelation function. A lot of silicon manufacturers use desynchronization countermeasures to defeat power analysis. In this article we detail a new resynchronization technic. This method can be used to facilitate the use of a neural network to do the code recognition. It becomes possible to reverse engineer a software code automatically. Using data and clock separation methods, we show how to optimize the synchronization using signal processing. Then we compare these methods with watermarking methods for 1D and 2D signal. The very last watermarking detection improvements can be applied to signal processing for smart cards with very few modifications. Bayesian processing is one of the best ways to do Differential Power Analysis, and it is possible to extract a PIN code from a smart card in very few samples. So this article shows the need to continue to set up effective countermeasures for cryptographic processors. Although the idea to use advanced signal processing operators has been commonly known for a long time, no publication explains that results can be obtained. The main idea of differential measurement is to use the cross-correlation of two random variables and to repeat consumption measurements on the processor to be analyzed. We use two processors clocked at the same external frequency and computing the same data. The applications of our design are numerous. Two measurements provide the inputs of a central operator. With the most accurate operator we can improve the signal noise ratio, re-synchronize the acquisition clock with the internal one, or remove jitter. The analysis based on consumption or electromagnetic measurements can be improved using our structure. At first sight the same results can be obtained with only one smart card, but this idea is not completely true because the statistical properties of the signal are not the same. As the two smart cards are submitted to the same external noise during the measurement, it is more easy to reduce the influence of perturbations. This paper shows the importance of accurate countermeasures against differential analysis.

Velocity interferometer signal de-noising using modified Wiener filter

NASA Astrophysics Data System (ADS)

Rav, Amit; Joshi, K. D.; Roy, Kallol; Kaushik, T. C.

2017-05-01

The accuracy and precision of the non-contact velocity interferometer system for any reflector (VISAR) depends not only on the good optical design and linear optical-to- electrical conversion system, but also on accurate and robust post-processing techniques. The performance of these techniques, such as the phase unwrapping algorithm, depends on the signal-to-noise ratio (SNR) of the recorded signal. In the present work, a novel method of improving the SNR of the recorded VISAR signal, based on the knowledge of the noise characteristic of the signal conversion and recording system, is presented. The proposed method uses a modified Wiener filter, for which the signal power spectrum estimation is obtained using a spectral subtraction method (SSM), and the noise power spectrum estimation is obtained by taking the average of the recorded signal during the period when no target movement is expected. Since the noise power spectrum estimate is dynamic in nature, and obtained for each experimental record individually, the improved signal quality is high. The proposed method is applied to the simulated standard signals, and is not only found to be better than the SSM, but is also less sensitive to the selection of the noise floor during signal power spectrum estimation. Finally, the proposed method is applied to the recorded experimental signal and an improvement in the SNR is reported.

Emotion regulation during threat: Parsing the time course and consequences of safety signal processing

PubMed Central

HEFNER, KATHRYN R.; VERONA, EDELYN; CURTIN, JOHN. J.

2017-01-01

Improved understanding of fear inhibition processes can inform the etiology and treatment of anxiety disorders. Safety signals can reduce fear to threat, but precise mechanisms remain unclear. Safety signals may acquire attentional salience and affective properties (e.g., relief) independent of the threat; alternatively, safety signals may only hold affective value in the presence of simultaneous threat. To clarify such mechanisms, an experimental paradigm assessed independent processing of threat and safety cues. Participants viewed a series of red and green words from two semantic categories. Shocks were administered following red words (cue+). No shocks followed green words (cue−). Words from one category were defined as safety signals (SS); no shocks were administered on cue+ trials. Words from the other (control) category did not provide information regarding shock administration. Threat (cue+ vs. cue−) and safety (SS+ vs. SS−) were fully crossed. Startle response and ERPs were recorded. Startle response was increased during cue+ versus cue−. Safety signals reduced startle response during cue+, but had no effect on startle response during cue−. ERP analyses (PD130 and P3) suggested that participants parsed threat and safety signal information in parallel. Motivated attention was not associated with safety signals in the absence of threat. Overall, these results confirm that fear can be reduced by safety signals. Furthermore, safety signals do not appear to hold inherent hedonic salience independent of their effect during threat. Instead, safety signals appear to enable participants to engage in effective top-down emotion regulatory processes. PMID:27088643

Unusual Applications of Ultrasound in Industry

NASA Astrophysics Data System (ADS)

Keilman, George

The application of physical acoustics in industry has been accelerated by increased understanding of the physics of industrial processes, coupled with rapid advancements in transducers, microelectronics, data acquisition, signal processing, and related software fields. This has led to some unusual applications of ultrasound to improve industrial processes.

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.

Psychoacoustic processing of test signals

NASA Astrophysics Data System (ADS)

Kadlec, Frantisek

2003-10-01

For the quantitative evaluation of electroacoustic system properties and for psychoacoustic testing it is possible to utilize harmonic signals with fixed frequency, sweeping signals, random signals or their combination. This contribution deals with the design of various test signals with emphasis on audible perception. During the digital generation of signals, some additional undesirable frequency components and noise are produced, which are dependent on signal amplitude and sampling frequency. A mathematical analysis describes the origin of this distortion. By proper selection of signal frequency and amplitude it is possible to minimize those undesirable components. An additional step is to minimize the audible perception of this signal distortion by the application of additional noise (dither). For signals intended for listening tests a dither with triangular or Gaussian probability density function was found to be most effective. Signals modified this way may be further improved by the application of noise shaping, which transposes those undesirable products into frequency regions where they are perceived less, according to psychoacoustic principles. The efficiency of individual processing steps was confirmed both by measurements and by listening tests. [Work supported by the Czech Science Foundation.

Electrocardiogram signal denoising based on empirical mode decomposition technique: an overview

NASA Astrophysics Data System (ADS)

Han, G.; Lin, B.; Xu, Z.

2017-03-01

Electrocardiogram (ECG) signal is nonlinear and non-stationary weak signal which reflects whether the heart is functioning normally or abnormally. ECG signal is susceptible to various kinds of noises such as high/low frequency noises, powerline interference and baseline wander. Hence, the removal of noises from ECG signal becomes a vital link in the ECG signal processing and plays a significant role in the detection and diagnosis of heart diseases. The review will describe the recent developments of ECG signal denoising based on Empirical Mode Decomposition (EMD) technique including high frequency noise removal, powerline interference separation, baseline wander correction, the combining of EMD and Other Methods, EEMD technique. EMD technique is a quite potential and prospective but not perfect method in the application of processing nonlinear and non-stationary signal like ECG signal. The EMD combined with other algorithms is a good solution to improve the performance of noise cancellation. The pros and cons of EMD technique in ECG signal denoising are discussed in detail. Finally, the future work and challenges in ECG signal denoising based on EMD technique are clarified.

Acoustic emission detection of macro-cracks on engraving tool steel inserts during the injection molding cycle using PZT sensors.

PubMed

Svečko, Rajko; Kusić, Dragan; Kek, Tomaž; Sarjaš, Andrej; Hančič, Aleš; Grum, Janez

2013-05-14

This paper presents an improved monitoring system for the failure detection of engraving tool steel inserts during the injection molding cycle. This system uses acoustic emission PZT sensors mounted through acoustic waveguides on the engraving insert. We were thus able to clearly distinguish the defect through measured AE signals. Two engraving tool steel inserts were tested during the production of standard test specimens, each under the same processing conditions. By closely comparing the captured AE signals on both engraving inserts during the filling and packing stages, we were able to detect the presence of macro-cracks on one engraving insert. Gabor wavelet analysis was used for closer examination of the captured AE signals' peak amplitudes during the filling and packing stages. The obtained results revealed that such a system could be used successfully as an improved tool for monitoring the integrity of an injection molding process.

Acoustic Emission Detection of Macro-Cracks on Engraving Tool Steel Inserts during the Injection Molding Cycle Using PZT Sensors

PubMed Central

Svečko, Rajko; Kusić, Dragan; Kek, Tomaž; Sarjaš, Andrej; Hančič, Aleš; Grum, Janez

2013-01-01

This paper presents an improved monitoring system for the failure detection of engraving tool steel inserts during the injection molding cycle. This system uses acoustic emission PZT sensors mounted through acoustic waveguides on the engraving insert. We were thus able to clearly distinguish the defect through measured AE signals. Two engraving tool steel inserts were tested during the production of standard test specimens, each under the same processing conditions. By closely comparing the captured AE signals on both engraving inserts during the filling and packing stages, we were able to detect the presence of macro-cracks on one engraving insert. Gabor wavelet analysis was used for closer examination of the captured AE signals' peak amplitudes during the filling and packing stages. The obtained results revealed that such a system could be used successfully as an improved tool for monitoring the integrity of an injection molding process. PMID:23673677

Image-plane processing of visual information

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Park, S. K.; Samms, R. W.

1984-01-01

Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

Research on oral test modeling based on multi-feature fusion

NASA Astrophysics Data System (ADS)

Shi, Yuliang; Tao, Yiyue; Lei, Jun

2018-04-01

In this paper, the spectrum of speech signal is taken as an input of feature extraction. The advantage of PCNN in image segmentation and other processing is used to process the speech spectrum and extract features. And a new method combining speech signal processing and image processing is explored. At the same time of using the features of the speech map, adding the MFCC to establish the spectral features and integrating them with the features of the spectrogram to further improve the accuracy of the spoken language recognition. Considering that the input features are more complicated and distinguishable, we use Support Vector Machine (SVM) to construct the classifier, and then compare the extracted test voice features with the standard voice features to achieve the spoken standard detection. Experiments show that the method of extracting features from spectrograms using PCNN is feasible, and the fusion of image features and spectral features can improve the detection accuracy.

Research on the Wire Network Signal Prediction Based on the Improved NNARX Model

NASA Astrophysics Data System (ADS)

Zhang, Zipeng; Fan, Tao; Wang, Shuqing

It is difficult to obtain accurately the wire net signal of power system's high voltage power transmission lines in the process of monitoring and repairing. In order to solve this problem, the signal measured in remote substation or laboratory is employed to make multipoint prediction to gain the needed data. But, the obtained power grid frequency signal is delay. In order to solve the problem, an improved NNARX network which can predict frequency signal based on multi-point data collected by remote substation PMU is describes in this paper. As the error curved surface of the NNARX network is more complicated, this paper uses L-M algorithm to train the network. The result of the simulation shows that the NNARX network has preferable predication performance which provides accurate real time data for field testing and maintenance.

Interpolation algorithm for asynchronous ADC-data

NASA Astrophysics Data System (ADS)

Bramburger, Stefan; Zinke, Benny; Killat, Dirk

2017-09-01

This paper presents a modified interpolation algorithm for signals with variable data rate from asynchronous ADCs. The Adaptive weights Conjugate gradient Toeplitz matrix (ACT) algorithm is extended to operate with a continuous data stream. An additional preprocessing of data with constant and linear sections and a weighted overlap of step-by-step into spectral domain transformed signals improve the reconstruction of the asycnhronous ADC signal. The interpolation method can be used if asynchronous ADC data is fed into synchronous digital signal processing.

Event Compression Using Recursive Least Squares Signal Processing.

DTIC Science & Technology

1980-07-01

decimation of the Burstl signal with and without all-pole prefiltering to reduce aliasing . Figures 3.32a-c and 3.33a-c show the same examples but with 4/1...to reduce aliasing , w~t found that it did not improve the quality of the event compressed signals . If filtering must be performed, all-pole filtering...A-AO89 785 MASSACHUSETTS IN T OF TECH CAMBRIDGE RESEARCH LAB OF--ETC F/B 17/9 EVENT COMPRESSION USING RECURSIVE LEAST SQUARES SIGNAL PROCESSI-ETC(t

A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments

PubMed Central

Colburn, H. Steven

2016-01-01

Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model. PMID:27698261

A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments.

PubMed

Mi, Jing; Colburn, H Steven

2016-10-03

Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model. © The Author(s) 2016.

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.

The Time-Domain Matched Filter and the Spectral-Domain Matched Filter in 1-Dimensional NMR Spectroscopy.

PubMed

Spencer, Richard G

2010-09-01

A type of "matched filter" (MF), used extensively in the processing of one-dimensional spectra, is defined by multiplication of a free-induction decay (FID) by a decaying exponential with the same time constant as that of the FID. This maximizes, in a sense to be defined, the signal-to-noise ratio (SNR) in the spectrum obtained after Fourier transformation. However, a different entity known also as the matched filter was introduced by van Vleck in the context of pulse detection in the 1940's and has become widely integrated into signal processing practice. These two types of matched filters appear to be quite distinct. In the NMR case, the "filter", that is, the exponential multiplication, is defined by the characteristics of, and applied to, a time domain signal in order to achieve improved SNR in the spectral domain. In signal processing, the filter is defined by the characteristics of a signal in the spectral domain, and applied in order to improve the SNR in the temporal (pulse) domain. We reconcile these two distinct implementations of the matched filter, demonstrating that the NMR "matched filter" is a special case of the matched filter more rigorously defined in the signal processing literature. In addition, two limitations in the use of the MF are highlighted. First, application of the MF distorts resonance ratios as defined by amplitudes, although not as defined by areas. Second, the MF maximizes SNR with respect to resonance amplitude, while intensities are often more appropriately defined by areas. Maximizing the SNR with respect to area requires a somewhat different approach to matched filtering.

Wavelet analysis to decompose a vibration simulation signal to improve pre-distribution testing of packaging

NASA Astrophysics Data System (ADS)

Griffiths, K. R.; Hicks, B. J.; Keogh, P. S.; Shires, D.

2016-08-01

In general, vehicle vibration is non-stationary and has a non-Gaussian probability distribution; yet existing testing methods for packaging design employ Gaussian distributions to represent vibration induced by road profiles. This frequently results in over-testing and/or over-design of the packaging to meet a specification and correspondingly leads to wasteful packaging and product waste, which represent 15bn per year in the USA and €3bn per year in the EU. The purpose of the paper is to enable a measured non-stationary acceleration signal to be replaced by a constructed signal that includes as far as possible any non-stationary characteristics from the original signal. The constructed signal consists of a concatenation of decomposed shorter duration signals, each having its own kurtosis level. Wavelet analysis is used for the decomposition process into inner and outlier signal components. The constructed signal has a similar PSD to the original signal, without incurring excessive acceleration levels. This allows an improved and more representative simulated input signal to be generated that can be used on the current generation of shaker tables. The wavelet decomposition method is also demonstrated experimentally through two correlation studies. It is shown that significant improvements over current international standards for packaging testing are achievable; hence the potential for more efficient packaging system design is possible.

Visemic Processing in Audiovisual Discrimination of Natural Speech: A Simultaneous fMRI-EEG Study

ERIC Educational Resources Information Center

Dubois, Cyril; Otzenberger, Helene; Gounot, Daniel; Sock, Rudolph; Metz-Lutz, Marie-Noelle

2012-01-01

In a noisy environment, visual perception of articulatory movements improves natural speech intelligibility. Parallel to phonemic processing based on auditory signal, visemic processing constitutes a counterpart based on "visemes", the distinctive visual units of speech. Aiming at investigating the neural substrates of visemic processing in a…

State of the art in perceptual design of hearing aids

NASA Astrophysics Data System (ADS)

Edwards, Brent W.; van Tasell, Dianne J.

2002-05-01

Hearing aid capabilities have increased dramatically over the past six years, in large part due to the development of small, low-power digital signal processing chips suitable for hearing aid applications. As hearing aid signal processing capabilities increase, there will be new opportunities to apply perceptually based knowledge to technological development. Most hearing loss compensation techniques in today's hearing aids are based on simple estimates of audibility and loudness. As our understanding of the psychoacoustical and physiological characteristics of sensorineural hearing loss improves, the result should be improved design of hearing aids and fitting methods. The state of the art in hearing aids will be reviewed, including form factors, user requirements, and technology that improves speech intelligibility, sound quality, and functionality. General areas of auditory perception that remain unaddressed by current hearing aid technology will be discussed.

Noise in any frequency range can enhance information transmission in a sensory neuron

NASA Astrophysics Data System (ADS)

Levin, Jacob E.

1997-05-01

The effect of noise on the neural encoding of broadband signals was investigated in the cricket cercal system, a mechanosensory system sensitive to small near-field air particle disturbances. Known air current stimuli were presented to the cricket through audio speakers in a controlled environment in a variety of background noise conditions. Spike trains from the second layer of neuronal processing, the primary sensory interneurons, were recorded with intracellular Electrodes and the performance of these neurons characterized with the tools of information theory. SNR, mutual information rates, and other measures of encoding accuracy were calculated for single frequency, narrowband, and broadband signals over the entire amplitude sensitivity range of the cells, in the presence of uncorrelated noise background also spanning the cells' frequency and amplitude sensitivity range. Significant enhancements of transmitted information through the addition of external noise were observed regardless of the frequency range of either the signal or noise waveforms, provided both were within the operating range of the cell. Considerable improvements in signal encoding were observed for almost an entire order of magnitude of near-threshold signal amplitudes. This included sinusoidal signals embedded in broadband white noise, broadband signals in broadband noise, and even broadband signals presented with narrowband noise in a completely non-overlapping frequency range. The noise related increases in mutual information rate for broadband signals were as high as 150%, and up to 600% increases in SNR were observed for sinusoidal signals. Additionally, it was shown that the amount of information about the signal carried, on average, by each spike was INCREASED for small signals when presented with noise—implying that added input noise can, in certain situations, actually improve the accuracy of the encoding process itself.

Signal processor for processing ultrasonic receiver signals

DOEpatents

Fasching, George E.

1980-01-01

A signal processor is provided which uses an analog integrating circuit in conjunction with a set of digital counters controlled by a precision clock for sampling timing to provide an improved presentation of an ultrasonic transmitter/receiver signal. The signal is sampled relative to the transmitter trigger signal timing at precise times, the selected number of samples are integrated and the integrated samples are transferred and held for recording on a strip chart recorder or converted to digital form for storage. By integrating multiple samples taken at precisely the same time with respect to the trigger for the ultrasonic transmitter, random noise, which is contained in the ultrasonic receiver signal, is reduced relative to the desired useful signal.

Analysis and improved design considerations for airborne pulse Doppler radar signal processing in the detection of hazardous windshear

NASA Technical Reports Server (NTRS)

Lee, Jonggil

1990-01-01

High resolution windspeed profile measurements are needed to provide reliable detection of hazardous low altitude windshear with an airborne pulse Doppler radar. The system phase noise in a Doppler weather radar may degrade the spectrum moment estimation quality and the clutter cancellation capability which are important in windshear detection. Also the bias due to weather return Doppler spectrum skewness may cause large errors in pulse pair spectral parameter estimates. These effects are analyzed for the improvement of an airborne Doppler weather radar signal processing design. A method is presented for the direct measurement of windspeed gradient using low pulse repetition frequency (PRF) radar. This spatial gradient is essential in obtaining the windshear hazard index. As an alternative, the modified Prony method is suggested as a spectrum mode estimator for both the clutter and weather signal. Estimation of Doppler spectrum modes may provide the desired windshear hazard information without the need of any preliminary processing requirement such as clutter filtering. The results obtained by processing a NASA simulation model output support consideration of mode identification as one component of a windshear detection algorithm.

Improvement of the energy resolution via an optimized digital signal processing in GERDA Phase I

NASA Astrophysics Data System (ADS)

Agostini, M.; Allardt, M.; Bakalyarov, A. M.; Balata, M.; Barabanov, I.; Barros, N.; Baudis, L.; Bauer, C.; Becerici-Schmidt, N.; Bellotti, E.; Belogurov, S.; Belyaev, S. T.; Benato, G.; Bettini, A.; Bezrukov, L.; Bode, T.; Borowicz, D.; Brudanin, V.; Brugnera, R.; Budjáš, D.; Caldwell, A.; Cattadori, C.; Chernogorov, A.; D'Andrea, V.; Demidova, E. V.; Vacri, A. di; Domula, A.; Doroshkevich, E.; Egorov, V.; Falkenstein, R.; Fedorova, O.; Freund, K.; Frodyma, N.; Gangapshev, A.; Garfagnini, A.; Grabmayr, P.; Gurentsov, V.; Gusev, K.; Hegai, A.; Heisel, M.; Hemmer, S.; Heusser, G.; Hofmann, W.; Hult, M.; Inzhechik, L. V.; Janicskó Csáthy, J.; Jochum, J.; Junker, M.; Kazalov, V.; Kihm, T.; Kirpichnikov, I. V.; Kirsch, A.; Klimenko, A.; Knöpfle, K. T.; Kochetov, O.; Kornoukhov, V. N.; Kuzminov, V. V.; Laubenstein, ********************M.; Lazzaro, A.; Lebedev, V. I.; Lehnert, B.; Liao, H. Y.; Lindner, M.; Lippi, I.; Lubashevskiy, A.; Lubsandorzhiev, B.; Lutter, G.; Macolino, C.; Majorovits, B.; Maneschg, W.; Medinaceli, E.; Misiaszek, M.; Moseev, P.; Nemchenok, I.; Palioselitis, D.; Panas, K.; Pandola, L.; Pelczar, K.; Pullia, A.; Riboldi, S.; Rumyantseva, N.; Sada, C.; Salathe, M.; Schmitt, C.; Schneider, B.; Schönert, S.; Schreiner, J.; Schütz, A.-K.; Schulz, O.; Schwingenheuer, B.; Selivanenko, O.; Shirchenko, M.; Simgen, H.; Smolnikov, A.; Stanco, L.; Stepaniuk, M.; Ur, C. A.; Vanhoefer, L.; Vasenko, A. A.; Veresnikova, A.; von Sturm, K.; Wagner, V.; Walter, M.; Wegmann, A.; Wester, T.; Wilsenach, H.; Wojcik, M.; Yanovich, E.; Zavarise, P.; Zhitnikov, I.; Zhukov, S. V.; Zinatulina, D.; Zuber, K.; Zuzel, G.

2015-06-01

An optimized digital shaping filter has been developed for the Gerda experiment which searches for neutrinoless double beta decay in Ge. The Gerda Phase I energy calibration data have been reprocessed and an average improvement of 0.3 keV in energy resolution (FWHM) corresponding to 10 % at the value for decay in Ge is obtained. This is possible thanks to the enhanced low-frequency noise rejection of this Zero Area Cusp (ZAC) signal shaping filter.

Improvement of range spatial resolution of medical ultrasound imaging by element-domain signal processing

NASA Astrophysics Data System (ADS)

Hasegawa, Hideyuki

2017-07-01

The range spatial resolution is an important factor determining the image quality in ultrasonic imaging. The range spatial resolution in ultrasonic imaging depends on the ultrasonic pulse length, which is determined by the mechanical response of the piezoelectric element in an ultrasonic probe. To improve the range spatial resolution without replacing the transducer element, in the present study, methods based on maximum likelihood (ML) estimation and multiple signal classification (MUSIC) were proposed. The proposed methods were applied to echo signals received by individual transducer elements in an ultrasonic probe. The basic experimental results showed that the axial half maximum of the echo from a string phantom was improved from 0.21 mm (conventional method) to 0.086 mm (ML) and 0.094 mm (MUSIC).

An improved PSO-SVM model for online recognition defects in eddy current testing

NASA Astrophysics Data System (ADS)

Liu, Baoling; Hou, Dibo; Huang, Pingjie; Liu, Banteng; Tang, Huayi; Zhang, Wubo; Chen, Peihua; Zhang, Guangxin

2013-12-01

Accurate and rapid recognition of defects is essential for structural integrity and health monitoring of in-service device using eddy current (EC) non-destructive testing. This paper introduces a novel model-free method that includes three main modules: a signal pre-processing module, a classifier module and an optimisation module. In the signal pre-processing module, a kind of two-stage differential structure is proposed to suppress the lift-off fluctuation that could contaminate the EC signal. In the classifier module, multi-class support vector machine (SVM) based on one-against-one strategy is utilised for its good accuracy. In the optimisation module, the optimal parameters of classifier are obtained by an improved particle swarm optimisation (IPSO) algorithm. The proposed IPSO technique can improve convergence performance of the primary PSO through the following strategies: nonlinear processing of inertia weight, introductions of the black hole and simulated annealing model with extremum disturbance. The good generalisation ability of the IPSO-SVM model has been validated through adding additional specimen into the testing set. Experiments show that the proposed algorithm can achieve higher recognition accuracy and efficiency than other well-known classifiers and the superiorities are more obvious with less training set, which contributes to online application.

[An improved algorithm for electrohysterogram envelope extraction].

PubMed

Lu, Yaosheng; Pan, Jie; Chen, Zhaoxia; Chen, Zhaoxia

2017-02-01

Extraction uterine contraction signal from abdominal uterine electromyogram(EMG) signal is considered as the most promising method to replace the traditional tocodynamometer(TOCO) for detecting uterine contractions activity. The traditional root mean square(RMS) algorithm has only some limited values in canceling the impulsive noise. In our study, an improved algorithm for uterine EMG envelope extraction was proposed to overcome the problem. Firstly, in our experiment, zero-crossing detection method was used to separate the burst of uterine electrical activity from the raw uterine EMG signal. After processing the separated signals by employing two filtering windows which have different width, we used the traditional RMS algorithm to extract uterus EMG envelope. To assess the performance of the algorithm, the improved algorithm was compared with two existing intensity of uterine electromyogram(IEMG) extraction algorithms. The results showed that the improved algorithm was better than the traditional ones in eliminating impulsive noise present in the uterine EMG signal. The measurement sensitivity and positive predictive value(PPV) of the improved algorithm were 0.952 and 0.922, respectively, which were not only significantly higher than the corresponding values(0.859 and 0.847) of the first comparison algorithm, but also higher than the values(0.928 and 0.877) of the second comparison algorithm. Thus the new method is reliable and effective.

Modeling borehole microseismic and strain signals measured by a distributed fiber optic sensor

NASA Astrophysics Data System (ADS)

Mellors, R. J.; Sherman, C. S.; Ryerson, F. J.; Morris, J.; Allen, G. S.; Messerly, M. J.; Carr, T.; Kavousi, P.

2017-12-01

The advent of distributed fiber optic sensors installed in boreholes provides a new and data-rich perspective on the subsurface environment. This includes the long-term capability for vertical seismic profiles, monitoring of active borehole processes such as well stimulation, and measuring of microseismic signals. The distributed fiber sensor, which measures strain (or strain-rate), is an active sensor with highest sensitivity parallel to the fiber and subject to varying types of noise, both external and internal. We take a systems approach and include the response of the electronics, fiber/cable, and subsurface to improve interpretation of the signals. This aids in understanding noise sources, assessing error bounds on amplitudes, and developing appropriate algorithms for improving the image. Ultimately, a robust understanding will allow identification of areas for future improvement and possible optimization in fiber and cable design. The subsurface signals are simulated in two ways: 1) a massively parallel multi-physics code that is capable of modeling hydraulic stimulation of heterogeneous reservoir with a pre-existing discrete fracture network, and 2) a parallelized 3D finite difference code for high-frequency seismic signals. Geometry and parameters for the simulations are derived from fiber deployments, including the Marcellus Shale Energy and Environment Laboratory (MSEEL) project in West Virginia. The combination mimics both the low-frequency strain signals generated during the fracture process and high-frequency signals from microseismic and perforation shots. Results are compared with available fiber data and demonstrate that quantitative interpretation of the fiber data provides valuable constraints on the fracture geometry and microseismic activity. These constraints appear difficult, if not impossible, to obtain otherwise.

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.

Creep and slip: Seismic precursors to the Nuugaatsiaq landslide (Greenland)

NASA Astrophysics Data System (ADS)

Poli, Piero

2017-09-01

Precursory signals to material's failure are predicted by numerical models and observed in laboratory experiments or using field data. These precursory signals are a marker of slip acceleration on weak regions, such as crustal faults. Observation of these precursory signals of catastrophic natural events, such as earthquakes and landslides, is necessary for improving our knowledge about the physics of the nucleation process. Furthermore, observing such precursory signals may help to forecast these catastrophic events or reduce their hazard. I report here the observation of seismic precursors to the Nuugaatsiaq landslide in Greenland. Time evolution of the detected precursors implies that an aseismic slip event is taking place for hours before the landslide, with an exponential increase of slip velocity. Furthermore, time evolution of the precursory signals' amplitude sheds light on the evolution of the fault physics during the nucleation process.

Phase editing as a signal pre-processing step for automated bearing fault detection

NASA Astrophysics Data System (ADS)

Barbini, L.; Ompusunggu, A. P.; Hillis, A. J.; du Bois, J. L.; Bartic, A.

2017-07-01

Scheduled maintenance and inspection of bearing elements in industrial machinery contributes significantly to the operating costs. Savings can be made through automatic vibration-based damage detection and prognostics, to permit condition-based maintenance. However automation of the detection process is difficult due to the complexity of vibration signals in realistic operating environments. The sensitivity of existing methods to the choice of parameters imposes a requirement for oversight from a skilled operator. This paper presents a novel approach to the removal of unwanted vibrational components from the signal: phase editing. The approach uses a computationally-efficient full-band demodulation and requires very little oversight. Its effectiveness is tested on experimental data sets from three different test-rigs, and comparisons are made with two state-of-the-art processing techniques: spectral kurtosis and cepstral pre- whitening. The results from the phase editing technique show a 10% improvement in damage detection rates compared to the state-of-the-art while simultaneously improving on the degree of automation. This outcome represents a significant contribution in the pursuit of fully automatic fault detection.

Spatially adaptive migration tomography for multistatic GPR imaging

DOEpatents

Paglieroni, David W; Beer, N. Reginald

2013-08-13

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.

Synthetic aperture integration (SAI) algorithm for SAR imaging

DOEpatents

Chambers, David H; Mast, Jeffrey E; Paglieroni, David W; Beer, N. Reginald

2013-07-09

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.

Zero source insertion technique to account for undersampling in GPR imaging

DOEpatents

Chambers, David H; Mast, Jeffrey E; Paglieroni, David W

2014-02-25

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.

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.

Verification of Non-Invasive Blood Glucose Measurement Method Based on Pulse Wave Signal Detected by FBG Sensor System.

PubMed

Kurasawa, Shintaro; Koyama, Shouhei; Ishizawa, Hiroaki; Fujimoto, Keisaku; Chino, Shun

2017-11-23

This paper describes and verifies a non-invasive blood glucose measurement method using a fiber Bragg grating (FBG) sensor system. The FBG sensor is installed on the radial artery, and the strain (pulse wave) that is propagated from the heartbeat is measured. The measured pulse wave signal was used as a collection of feature vectors for multivariate analysis aiming to determine the blood glucose level. The time axis of the pulse wave signal was normalized by two signal processing methods: the shortest-time-cut process and 1-s-normalization process. The measurement accuracy of the calculated blood glucose level was compared with the accuracy of these signal processing methods. It was impossible to calculate a blood glucose level exceeding 200 mg/dL in the calibration curve that was constructed by the shortest-time-cut process. In the 1-s-normalization process, the measurement accuracy of the blood glucose level was improved, and a blood glucose level exceeding 200 mg/dL could be calculated. By verifying the loading vector of each calibration curve to calculate the blood glucose level with a high measurement accuracy, we found the gradient of the peak of the pulse wave at the acceleration plethysmogram greatly affected.

Ultra-low-power and robust digital-signal-processing hardware for implantable neural interface microsystems.

PubMed

Narasimhan, S; Chiel, H J; Bhunia, S

2011-04-01

Implantable microsystems for monitoring or manipulating brain activity typically require on-chip real-time processing of multichannel neural data using ultra low-power, miniaturized electronics. In this paper, we propose an integrated-circuit/architecture-level hardware design framework for neural signal processing that exploits the nature of the signal-processing algorithm. First, we consider different power reduction techniques and compare the energy efficiency between the ultra-low frequency subthreshold and conventional superthreshold design. We show that the superthreshold design operating at a much higher frequency can achieve comparable energy dissipation by taking advantage of extensive power gating. It also provides significantly higher robustness of operation and yield under large process variations. Next, we propose an architecture level preferential design approach for further energy reduction by isolating the critical computation blocks (with respect to the quality of the output signal) and assigning them higher delay margins compared to the noncritical ones. Possible delay failures under parameter variations are confined to the noncritical components, allowing graceful degradation in quality under voltage scaling. Simulation results using prerecorded neural data from the sea-slug (Aplysia californica) show that the application of the proposed design approach can lead to significant improvement in total energy, without compromising the output signal quality under process variations, compared to conventional design approaches.

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.

Improved PLL For FM Demodulator

NASA Technical Reports Server (NTRS)

Kirkham, Harold; Jackson, Shannon P.

1992-01-01

Phase-locked loop (PLL) for frequency demodulator contains improved frequency-to-voltage converter producing less ripple than conventional phase detector. In improved PLL, phase detector replaced by state estimator, implemented by ramp/sample-and-hold circuit. Intended to reduce noise in receiver of frequency-modulated (FM) telemetry link without sacrificing bandwidth. Also applicable to processing received FM signals.

A Software Platform for Post-Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Donald J.; Martin, Richard E.; Seebo, Jeff P.; Trinh, Long B.; Walker, James L.; Winfree, William P.

2007-01-01

Ultrasonic, microwave, and terahertz nondestructive evaluation imaging systems generally require the acquisition of waveforms at each scan point to form an image. For such systems, signal and image processing methods are commonly needed to extract information from the waves and improve resolution of, and highlight, defects in the image. Since some similarity exists for all waveform-based NDE methods, it would seem a common software platform containing multiple signal and image processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. This presentation describes NASA Glenn Research Center's approach in developing a common software platform for processing waveform-based NDE signals and images. This platform is currently in use at NASA Glenn and at Lockheed Martin Michoud Assembly Facility for processing of pulsed terahertz and ultrasonic data. Highlights of the software operation will be given. A case study will be shown for use with terahertz data. The authors also request scientists and engineers who are interested in sharing customized signal and image processing algorithms to contribute to this effort by letting the authors code up and include these algorithms in future releases.

An optimal filter for short photoplethysmogram signals

PubMed Central

Liang, Yongbo; Elgendi, Mohamed; Chen, Zhencheng; Ward, Rabab

2018-01-01

A photoplethysmogram (PPG) contains a wealth of cardiovascular system information, and with the development of wearable technology, it has become the basic technique for evaluating cardiovascular health and detecting diseases. However, due to the varying environments in which wearable devices are used and, consequently, their varying susceptibility to noise interference, effective processing of PPG signals is challenging. Thus, the aim of this study was to determine the optimal filter and filter order to be used for PPG signal processing to make the systolic and diastolic waves more salient in the filtered PPG signal using the skewness quality index. Nine types of filters with 10 different orders were used to filter 219 (2.1s) short PPG signals. The signals were divided into three categories by PPG experts according to their noise levels: excellent, acceptable, or unfit. Results show that the Chebyshev II filter can improve the PPG signal quality more effectively than other types of filters and that the optimal order for the Chebyshev II filter is the 4th order. PMID:29714722

Time-Frequency Signal Representations Using Interpolations in Joint-Variable Domains

DTIC Science & Technology

2016-06-14

distribution kernels,” IEEE Trans. Signal Process., vol. 42, no. 5, pp. 1156–1165, May 1994. [25] G. S. Cunningham and W. J. Williams , “Kernel...interpolated data. For comparison, we include sparse reconstruction and WVD and Choi– Williams distribution (CWD) [23], which are directly applied to...Prentice-Hall, 1995. [23] H. I. Choi and W. J. Williams , “Improved time-frequency representa- tion of multicomponent signals using exponential kernels

Improved signal processing approaches in an offline simulation of a hybrid brain–computer interface

PubMed Central

Brunner, Clemens; Allison, Brendan Z.; Krusienski, Dean J.; Kaiser, Vera; Müller-Putz, Gernot R.; Pfurtscheller, Gert; Neuper, Christa

2012-01-01

In a conventional brain–computer interface (BCI) system, users perform mental tasks that yield specific patterns of brain activity. A pattern recognition system determines which brain activity pattern a user is producing and thereby infers the user’s mental task, allowing users to send messages or commands through brain activity alone. Unfortunately, despite extensive research to improve classification accuracy, BCIs almost always exhibit errors, which are sometimes so severe that effective communication is impossible. We recently introduced a new idea to improve accuracy, especially for users with poor performance. In an offline simulation of a “hybrid” BCI, subjects performed two mental tasks independently and then simultaneously. This hybrid BCI could use two different types of brain signals common in BCIs – event-related desynchronization (ERD) and steady-state evoked potentials (SSEPs). This study suggested that such a hybrid BCI is feasible. Here, we re-analyzed the data from our initial study. We explored eight different signal processing methods that aimed to improve classification and further assess both the causes and the extent of the benefits of the hybrid condition. Most analyses showed that the improved methods described here yielded a statistically significant improvement over our initial study. Some of these improvements could be relevant to conventional BCIs as well. Moreover, the number of illiterates could be reduced with the hybrid condition. Results are also discussed in terms of dual task interference and relevance to protocol design in hybrid BCIs. PMID:20153371

Design and Processing of a Novel Chaos-Based Stepped Frequency Synthesized Wideband Radar Signal.

PubMed

Zeng, Tao; Chang, Shaoqiang; Fan, Huayu; Liu, Quanhua

2018-03-26

The linear stepped frequency and linear frequency shift keying (FSK) signal has been widely used in radar systems. However, such linear modulation signals suffer from the range-Doppler coupling that degrades radar multi-target resolution. Moreover, the fixed frequency-hopping or frequency-coded sequence can be easily predicted by the interception receiver in the electronic countermeasures (ECM) environments, which limits radar anti-jamming performance. In addition, the single FSK modulation reduces the radar low probability of intercept (LPI) performance, for it cannot achieve a large time-bandwidth product. To solve such problems, we propose a novel chaos-based stepped frequency (CSF) synthesized wideband signal in this paper. The signal introduces chaotic frequency hopping between the coherent stepped frequency pulses, and adopts a chaotic frequency shift keying (CFSK) and phase shift keying (PSK) composited coded modulation in a subpulse, called CSF-CFSK/PSK. Correspondingly, the processing method for the signal has been proposed. According to our theoretical analyses and the simulations, the proposed signal and processing method achieve better multi-target resolution and LPI performance. Furthermore, flexible modulation is able to increase the robustness against identification of the interception receiver and improve the anti-jamming performance of the radar.

[Cognitive aging mechanism of signaling effects on the memory for procedural sentences].

PubMed

Yamamoto, Hiroki; Shimada, Hideaki

2006-08-01

The aim of this study was to clarify the cognitive aging mechanism of signaling effects on the memory for procedural sentences. Participants were 60 younger adults (college students) and 60 older adults. Both age groups were assigned into two groups; half of each group was presented with procedural sentences with signals that highlighted their top-level structure and the other half with procedural sentences without them. Both groups were requested to perform the sentence arrangement task and the reconstruction task. Each task was composed of procedural sentences with or without signals. Results indicated that signaling supported changes in strategy utilization during the successive organizational processes and that changes in strategy utilization resulting from signaling improved the memory for procedural sentences. Moreover, age-related factors interfered with these signaling effects. This study clarified the cognitive aging mechanism of signaling effects in which signaling supports changes in the strategy utilization during organizational processes at encoding and this mediation promotes memory for procedural sentences, though disuse of the strategy utilization due to aging restrains their memory for procedural sentences.

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.

Nuclear test ban treaty verification: Improving test ban monitoring with empirical and model-based signal processing

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

Harris, David B.; Gibbons, Steven J.; Rodgers, Arthur J.

In this approach, small scale-length medium perturbations not modeled in the tomographic inversion might be described as random fields, characterized by particular distribution functions (e.g., normal with specified spatial covariance). Conceivably, random field parameters (scatterer density or scale length) might themselves be the targets of tomographic inversions of the scattered wave field. As a result, such augmented models may provide processing gain through the use of probabilistic signal sub spaces rather than deterministic waveforms.

Nuclear test ban treaty verification: Improving test ban monitoring with empirical and model-based signal processing

DOE PAGES

Harris, David B.; Gibbons, Steven J.; Rodgers, Arthur J.; ...

2012-05-01

In this approach, small scale-length medium perturbations not modeled in the tomographic inversion might be described as random fields, characterized by particular distribution functions (e.g., normal with specified spatial covariance). Conceivably, random field parameters (scatterer density or scale length) might themselves be the targets of tomographic inversions of the scattered wave field. As a result, such augmented models may provide processing gain through the use of probabilistic signal sub spaces rather than deterministic waveforms.

Dynamic single sideband modulation for realizing parametric loudspeaker

NASA Astrophysics Data System (ADS)

Sakai, Shinichi; Kamakura, Tomoo

2008-06-01

A parametric loudspeaker, that presents remarkably narrow directivity compared with a conventional loudspeaker, is newly produced and examined. To work the loudspeaker optimally, we prototyped digitally a single sideband modulator based on the Weaver method and appropriate signal processing. The processing techniques are to change the carrier amplitude dynamically depending on the envelope of audio signals, and then to operate the square root or fourth root to the carrier amplitude for improving input-output acoustic linearity. The usefulness of the present modulation scheme has been verified experimentally.

Use of Adaptive Digital Signal Processing to Improve Speech Communication for Normally Hearing aand Hearing-Impaired Subjects.

ERIC Educational Resources Information Center

Harris, Richard W.; And Others

1988-01-01

A two-microphone adaptive digital noise cancellation technique improved word-recognition ability for 20 normal and 12 hearing-impaired adults by reducing multitalker speech babble and speech spectrum noise 18-22 dB. Word recognition improvements averaged 37-50 percent for normal and 27-40 percent for hearing-impaired subjects. Improvement was best…

Brain-computer interfaces in neurological rehabilitation.

PubMed

Daly, Janis J; Wolpaw, Jonathan R

2008-11-01

Recent advances in analysis of brain signals, training patients to control these signals, and improved computing capabilities have enabled people with severe motor disabilities to use their brain signals for communication and control of objects in their environment, thereby bypassing their impaired neuromuscular system. Non-invasive, electroencephalogram (EEG)-based brain-computer interface (BCI) technologies can be used to control a computer cursor or a limb orthosis, for word processing and accessing the internet, and for other functions such as environmental control or entertainment. By re-establishing some independence, BCI technologies can substantially improve the lives of people with devastating neurological disorders such as advanced amyotrophic lateral sclerosis. BCI technology might also restore more effective motor control to people after stroke or other traumatic brain disorders by helping to guide activity-dependent brain plasticity by use of EEG brain signals to indicate to the patient the current state of brain activity and to enable the user to subsequently lower abnormal activity. Alternatively, by use of brain signals to supplement impaired muscle control, BCIs might increase the efficacy of a rehabilitation protocol and thus improve muscle control for the patient.

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.

A new approach for improving reliability of personal navigation devices under harsh GNSS signal conditions.

PubMed

Dhital, Anup; Bancroft, Jared B; Lachapelle, Gérard

2013-11-07

In natural and urban canyon environments, Global Navigation Satellite System (GNSS) signals suffer from various challenges such as signal multipath, limited or lack of signal availability and poor geometry. Inertial sensors are often employed to improve the solution continuity under poor GNSS signal quality and availability conditions. Various fault detection schemes have been proposed in the literature to detect and remove biased GNSS measurements to obtain a more reliable navigation solution. However, many of these methods are found to be sub-optimal and often lead to unavailability of reliability measures, mostly because of the improper characterization of the measurement errors. A robust filtering architecture is thus proposed which assumes a heavy-tailed distribution for the measurement errors. Moreover, the proposed filter is capable of adapting to the changing GNSS signal conditions such as when moving from open sky conditions to deep canyons. Results obtained by processing data collected in various GNSS challenged environments show that the proposed scheme provides a robust navigation solution without having to excessively reject usable measurements. The tests reported herein show improvements of nearly 15% and 80% for position accuracy and reliability, respectively, when applying the above approach.

A New Approach for Improving Reliability of Personal Navigation Devices under Harsh GNSS Signal Conditions

PubMed Central

Dhital, Anup; Bancroft, Jared B.; Lachapelle, Gérard

2013-01-01

In natural and urban canyon environments, Global Navigation Satellite System (GNSS) signals suffer from various challenges such as signal multipath, limited or lack of signal availability and poor geometry. Inertial sensors are often employed to improve the solution continuity under poor GNSS signal quality and availability conditions. Various fault detection schemes have been proposed in the literature to detect and remove biased GNSS measurements to obtain a more reliable navigation solution. However, many of these methods are found to be sub-optimal and often lead to unavailability of reliability measures, mostly because of the improper characterization of the measurement errors. A robust filtering architecture is thus proposed which assumes a heavy-tailed distribution for the measurement errors. Moreover, the proposed filter is capable of adapting to the changing GNSS signal conditions such as when moving from open sky conditions to deep canyons. Results obtained by processing data collected in various GNSS challenged environments show that the proposed scheme provides a robust navigation solution without having to excessively reject usable measurements. The tests reported herein show improvements of nearly 15% and 80% for position accuracy and reliability, respectively, when applying the above approach. PMID:24212120

The 2D analytic signal for envelope detection and feature extraction on ultrasound images.

PubMed

Wachinger, Christian; Klein, Tassilo; Navab, Nassir

2012-08-01

The fundamental property of the analytic signal is the split of identity, meaning the separation of qualitative and quantitative information in form of the local phase and the local amplitude, respectively. Especially the structural representation, independent of brightness and contrast, of the local phase is interesting for numerous image processing tasks. Recently, the extension of the analytic signal from 1D to 2D, covering also intrinsic 2D structures, was proposed. We show the advantages of this improved concept on ultrasound RF and B-mode images. Precisely, we use the 2D analytic signal for the envelope detection of RF data. This leads to advantages for the extraction of the information-bearing signal from the modulated carrier wave. We illustrate this, first, by visual assessment of the images, and second, by performing goodness-of-fit tests to a Nakagami distribution, indicating a clear improvement of statistical properties. The evaluation is performed for multiple window sizes and parameter estimation techniques. Finally, we show that the 2D analytic signal allows for an improved estimation of local features on B-mode images. Copyright © 2012 Elsevier B.V. All rights reserved.

A comparative analysis of frequency modulation threshold extension techniques

NASA Technical Reports Server (NTRS)

Arndt, G. D.; Loch, F. J.

1970-01-01

FM threshold extension for system performance improvement, comparing impulse noise elimination, correlation detection and delta modulation signal processing techniques implemented at demodulator output

Concepts for on-board satellite image registration. Volume 3: Impact of VLSI/VHSIC on satellite on-board signal processing

NASA Technical Reports Server (NTRS)

Aanstoos, J. V.; Snyder, W. E.

1981-01-01

Anticipated major advances in integrated circuit technology in the near future are described as well as their impact on satellite onboard signal processing systems. Dramatic improvements in chip density, speed, power consumption, and system reliability are expected from very large scale integration. Improvements are expected from very large scale integration enable more intelligence to be placed on remote sensing platforms in space, meeting the goals of NASA's information adaptive system concept, a major component of the NASA End-to-End Data System program. A forecast of VLSI technological advances is presented, including a description of the Defense Department's very high speed integrated circuit program, a seven-year research and development effort.

Recognition of digital characteristics based new improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Meng; Xu, Guoqiang; Lin, Zihao

2017-08-01

In the field of digital signal processing, Estimating the characteristics of signal modulation parameters is an significant research direction. The paper determines the set of eigenvalue which can show the difference of the digital signal modulation based on the deep research of the new improved genetic algorithm. Firstly take them as the best gene pool; secondly, The best gene pool will be changed in the genetic evolvement by selecting, overlapping and eliminating each other; Finally, Adapting the strategy of futher enhance competition and punishment to more optimizer the gene pool and ensure each generation are of high quality gene. The simulation results show that this method not only has the global convergence, stability and faster convergence speed.

Denoising embolic Doppler ultrasound signals using Dual Tree Complex Discrete Wavelet Transform.

PubMed

Serbes, Gorkem; Aydin, Nizamettin

2010-01-01

Early and accurate detection of asymptomatic emboli is important for monitoring of preventive therapy in stroke-prone patients. One of the problems in detection of emboli is the identification of an embolic signal caused by very small emboli. The amplitude of the embolic signal may be so small that advanced processing methods are required to distinguish these signals from Doppler signals arising from red blood cells. In this study instead of conventional discrete wavelet transform, the Dual Tree Complex Discrete Wavelet Transform was used for denoising embolic signals. Performances of both approaches were compared. Unlike the conventional discrete wavelet transform discrete complex wavelet transform is a shift invariant transform with limited redundancy. Results demonstrate that the Dual Tree Complex Discrete Wavelet Transform based denoising outperforms conventional discrete wavelet denoising. Approximately 8 dB improvement is obtained by using the Dual Tree Complex Discrete Wavelet Transform compared to the improvement provided by the conventional Discrete Wavelet Transform (less than 5 dB).

An Interactive User Interface for Drug Labeling to Improve Readability and Decision-Making

PubMed Central

Abedtash, Hamed; Duke, Jon D.

2015-01-01

FDA-approved prescribing information (also known as product labeling or labels) contain critical safety information for health care professionals. Drug labels have often been criticized, however, for being overly complex, difficult to read, and rife with overwarning, leading to high cognitive load. In this project, we aimed to improve the usability of drug labels by increasing the ‘signal-to-noise ratio’ and providing meaningful information to care providers based on patient-specific comorbidities and concomitant medications. In the current paper, we describe the design process and resulting web application, known as myDrugLabel. Using the Structured Product Label documents as a base, we describe the process of label personalization, readability improvements, and integration of diverse evidence sources, including the medical literature from PubMed, pharmacovigilance reports from FDA adverse event reporting system (FAERS), and social media signals directly into the label. PMID:26958158

An Interactive User Interface for Drug Labeling to Improve Readability and Decision-Making.

PubMed

Abedtash, Hamed; Duke, Jon D

FDA-approved prescribing information (also known as product labeling or labels) contain critical safety information for health care professionals. Drug labels have often been criticized, however, for being overly complex, difficult to read, and rife with overwarning, leading to high cognitive load. In this project, we aimed to improve the usability of drug labels by increasing the 'signal-to-noise ratio' and providing meaningful information to care providers based on patient-specific comorbidities and concomitant medications. In the current paper, we describe the design process and resulting web application, known as myDrugLabel. Using the Structured Product Label documents as a base, we describe the process of label personalization, readability improvements, and integration of diverse evidence sources, including the medical literature from PubMed, pharmacovigilance reports from FDA adverse event reporting system (FAERS), and social media signals directly into the label.

Emotional stress recognition using a new fusion link between electroencephalogram and peripheral signals

PubMed Central

Hosseini, Seyyed Abed; Khalilzadeh, Mohammad Ali; Naghibi-Sistani, Mohammad Bagher; Homam, Seyyed Mehran

2015-01-01

Background: This paper proposes a new emotional stress assessment system using multi-modal bio-signals. Electroencephalogram (EEG) is the reflection of brain activity and is widely used in clinical diagnosis and biomedical research. Methods: We design an efficient acquisition protocol to acquire the EEG signals in five channels (FP1, FP2, T3, T4 and Pz) and peripheral signals such as blood volume pulse, skin conductance (SC) and respiration, under images induction (calm-neutral and negatively excited) for the participants. The visual stimuli images are selected from the subset International Affective Picture System database. The qualitative and quantitative evaluation of peripheral signals are used to select suitable segments of EEG signals for improving the accuracy of signal labeling according to emotional stress states. After pre-processing, wavelet coefficients, fractal dimension, and Lempel-Ziv complexity are used to extract the features of the EEG signals. The vast number of features leads to the problem of dimensionality, which is solved using the genetic algorithm as a feature selection method. Results: The results show that the average classification accuracy is 89.6% for two categories of emotional stress states using the support vector machine (SVM). Conclusion: This is a great improvement in results compared to other similar researches. We achieve a noticeable improvement of 11.3% in accuracy using SVM classifier, in compared to previous studies. Therefore, a new fusion between EEG and peripheral signals are more robust in comparison to the separate signals. PMID:26622979

Emotional stress recognition using a new fusion link between electroencephalogram and peripheral signals.

PubMed

Hosseini, Seyyed Abed; Khalilzadeh, Mohammad Ali; Naghibi-Sistani, Mohammad Bagher; Homam, Seyyed Mehran

2015-07-06

This paper proposes a new emotional stress assessment system using multi-modal bio-signals. Electroencephalogram (EEG) is the reflection of brain activity and is widely used in clinical diagnosis and biomedical research. We design an efficient acquisition protocol to acquire the EEG signals in five channels (FP1, FP2, T3, T4 and Pz) and peripheral signals such as blood volume pulse, skin conductance (SC) and respiration, under images induction (calm-neutral and negatively excited) for the participants. The visual stimuli images are selected from the subset International Affective Picture System database. The qualitative and quantitative evaluation of peripheral signals are used to select suitable segments of EEG signals for improving the accuracy of signal labeling according to emotional stress states. After pre-processing, wavelet coefficients, fractal dimension, and Lempel-Ziv complexity are used to extract the features of the EEG signals. The vast number of features leads to the problem of dimensionality, which is solved using the genetic algorithm as a feature selection method. The results show that the average classification accuracy is 89.6% for two categories of emotional stress states using the support vector machine (SVM). This is a great improvement in results compared to other similar researches. We achieve a noticeable improvement of 11.3% in accuracy using SVM classifier, in compared to previous studies. Therefore, a new fusion between EEG and peripheral signals are more robust in comparison to the separate signals.

Novel Oversampling Technique for Improving Signal-to-Quantization Noise Ratio on Accelerometer-Based Smart Jerk Sensors in CNC Applications.

PubMed

Rangel-Magdaleno, Jose J; Romero-Troncoso, Rene J; Osornio-Rios, Roque A; Cabal-Yepez, Eduardo

2009-01-01

Jerk monitoring, defined as the first derivative of acceleration, has become a major issue in computerized numeric controlled (CNC) machines. Several works highlight the necessity of measuring jerk in a reliable way for improving production processes. Nowadays, the computation of jerk is done by finite differences of the acceleration signal, computed at the Nyquist rate, which leads to low signal-to-quantization noise ratio (SQNR) during the estimation. The novelty of this work is the development of a smart sensor for jerk monitoring from a standard accelerometer, which has improved SQNR. The proposal is based on oversampling techniques that give a better estimation of jerk than that produced by a Nyquist-rate differentiator. Simulations and experimental results are presented to show the overall methodology performance.

Improved Target Detection in Urban Structures Using Distributed Sensing and Fast Data Acquisition Techniques

DTIC Science & Technology

2013-04-01

Trans. Signal Process., vol. 57, no. 6, pp. 2275-2284, 2009. [83] A. Gurbuz, J. IVIcClellan, and W. Scott, "Compressive sensing for subsurface ... imaging using ground penetrating radar," Signal Pracess., vol. 89, no. 10, pp. 1959 -1972, 2009. [84] A. Gurbuz, J. McClellan, and W. Scott, "A

Coccomyxa Gloeobotrydiformis Improves Learning and Memory in Intrinsic Aging Rats.

PubMed

Sun, Luning; Jin, Ying; Dong, Liming; Sui, Hai-Juan; Sumi, Ryo; Jahan, Rabita; Hu, Dahai; Li, Zhi

2015-01-01

Declining in learning and memory is one of the most common and prominent problems during the aging process. Neurotransmitter changes, oxidative stress, mitochondrial dysfunction and abnormal signal transduction were considered to participate in this process. In the present study, we examined the effects of Coccomyxa gloeobotrydiformis (CGD) on learning and memory ability of intrinsic aging rats. As a result, CGD treated (50 mg/kg·d or 100 mg/kg ·d for a duration of 8 weeks) 22-month-old male rats, which have shown significant improvement on learning and spatial memory ability compared with control, which was evidently revealed in both the hidden platform tasks and probe trials. The following immunohistochemistry and Western blot experiments suggested that CGD could increase the content of Ach and thereby improve the function of the cholinergic neurons in the hippocampus, and therefore also improving learning and memory ability of the aged rats by acting as an anti-inflammatory agent. The effects of CGD on learning and memory might also have an association with the ERK/CREB signalling. The results above suggest that the naturally made drug CGD may have several great benefit as a multi-target drug in the process of prevention and/or treatment of age-dependent cognitive decline and aging process.

Adaptive windowing in contrast-enhanced intravascular ultrasound imaging

PubMed Central

Lindsey, Brooks D.; Martin, K. Heath; Jiang, Xiaoning; Dayton, Paul A.

2016-01-01

Intravascular ultrasound (IVUS) is one of the most commonly-used interventional imaging techniques and has seen recent innovations which attempt to characterize the risk posed by atherosclerotic plaques. One such development is the use of microbubble contrast agents to image vasa vasorum, fine vessels which supply oxygen and nutrients to the walls of coronary arteries and typically have diameters less than 200 µm. The degree of vasa vasorum neovascularization within plaques is positively correlated with plaque vulnerability. Having recently presented a prototype dual-frequency transducer for contrast agent-specific intravascular imaging, here we describe signal processing approaches based on minimum variance (MV) beamforming and the phase coherence factor (PCF) for improving the spatial resolution and contrast-to-tissue ratio (CTR) in IVUS imaging. These approaches are examined through simulations, phantom studies, ex vivo studies in porcine arteries, and in vivo studies in chicken embryos. In phantom studies, PCF processing improved CTR by a mean of 4.2 dB, while combined MV and PCF processing improved spatial resolution by 41.7%. Improvements of 2.2 dB in CTR and 37.2% in resolution were observed in vivo. Applying these processing strategies can enhance image quality in conventional B-mode IVUS or in contrast-enhanced IVUS, where signal-to-noise ratio is relatively low and resolution is at a premium. PMID:27161022

The influence of laser pulse duration and energy on ICP-MS signal intensity, elemental fractionation, and particle size distribution in NIR fs-LA-ICP-MS

PubMed Central

Diwakar, Prasoon K.; Harilal, Sivanandan S.; LaHaye, Nicole L.; Hassanein, Ahmed; Kulkarni, Pramod

2015-01-01

Laser parameters, typically wavelength, pulse width, irradiance, repetition rate, and pulse energy, are critical parameters which influence the laser ablation process and thereby influence the LA-ICP-MS signal. In recent times, femtosecond laser ablation has gained popularity owing to the reduction in fractionation related issues and improved analytical performance which can provide matrix-independent sampling. The advantage offered by fs-LA is due to shorter pulse duration of the laser as compared to the phonon relaxation time and heat diffusion time. Hence the thermal effects are minimized in fs-LA. Recently, fs-LA-ICP-MS demonstrated improved analytical performance as compared to ns-LA-ICP-MS, but detailed mechanisms and processes are still not clearly understood. Improvement of fs-LA-ICP-MS over ns-LA-ICP-MS elucidates the importance of laser pulse duration and related effects on the ablation process. In this study, we have investigated the influence of laser pulse width (40 fs to 0.3 ns) and energy on LA-ICP-MS signal intensity and repeatability using a brass sample. Experiments were performed in single spot ablation mode as well as rastering ablation mode to monitor the Cu/Zn ratio. The recorded ICP-MS signal was correlated with total particle counts generated during laser ablation as well as particle size distribution. Our results show the importance of pulse width effects in the fs regime that becomes more pronounced when moving from femtosecond to picosecond and nanosecond regimes. PMID:26664120

Multi-format all-optical processing based on a large-scale, hybridly integrated photonic circuit.

PubMed

Bougioukos, M; Kouloumentas, Ch; Spyropoulou, M; Giannoulis, G; Kalavrouziotis, D; Maziotis, A; Bakopoulos, P; Harmon, R; Rogers, D; Harrison, J; Poustie, A; Maxwell, G; Avramopoulos, H

2011-06-06

We investigate through numerical studies and experiments the performance of a large scale, silica-on-silicon photonic integrated circuit for multi-format regeneration and wavelength-conversion. The circuit encompasses a monolithically integrated array of four SOAs inside two parallel Mach-Zehnder structures, four delay interferometers and a large number of silica waveguides and couplers. Exploiting phase-incoherent techniques, the circuit is capable of processing OOK signals at variable bit rates, DPSK signals at 22 or 44 Gb/s and DQPSK signals at 44 Gbaud. Simulation studies reveal the wavelength-conversion potential of the circuit with enhanced regenerative capabilities for OOK and DPSK modulation formats and acceptable quality degradation for DQPSK format. Regeneration of 22 Gb/s OOK signals with amplified spontaneous emission (ASE) noise and DPSK data signals degraded with amplitude, phase and ASE noise is experimentally validated demonstrating a power penalty improvement up to 1.5 dB.

Hybrid Signal Processing Technique to Improve the Defect Estimation in Ultrasonic Non-Destructive Testing of Composite Structures

PubMed Central

Raisutis, Renaldas; Samaitis, Vykintas

2017-01-01

This work proposes a novel hybrid signal processing technique to extract information on disbond-type defects from a single B-scan in the process of non-destructive testing (NDT) of glass fiber reinforced plastic (GFRP) material using ultrasonic guided waves (GW). The selected GFRP sample has been a segment of wind turbine blade, which possessed an aerodynamic shape. Two disbond type defects having diameters of 15 mm and 25 mm were artificially constructed on its trailing edge. The experiment has been performed using the low-frequency ultrasonic system developed at the Ultrasound Institute of Kaunas University of Technology and only one side of the sample was accessed. A special configuration of the transmitting and receiving transducers fixed on a movable panel with a separation distance of 50 mm was proposed for recording the ultrasonic guided wave signals at each one-millimeter step along the scanning distance up to 500 mm. Finally, the hybrid signal processing technique comprising the valuable features of the three most promising signal processing techniques: cross-correlation, wavelet transform, and Hilbert–Huang transform has been applied to the received signals for the extraction of defects information from a single B-scan image. The wavelet transform and cross-correlation techniques have been combined in order to extract the approximated size and location of the defects and measurements of time delays. Thereafter, Hilbert–Huang transform has been applied to the wavelet transformed signal to compare the variation of instantaneous frequencies and instantaneous amplitudes of the defect-free and defective signals. PMID:29232845

Dysphagia Screening: Contributions of Cervical Auscultation Signals and Modern Signal-Processing Techniques

PubMed Central

Dudik, Joshua M.; Coyle, James L.

2015-01-01

Cervical auscultation is the recording of sounds and vibrations caused by the human body from the throat during swallowing. While traditionally done by a trained clinician with a stethoscope, much work has been put towards developing more sensitive and clinically useful methods to characterize the data obtained with this technique. The eventual goal of the field is to improve the effectiveness of screening algorithms designed to predict the risk that swallowing disorders pose to individual patients’ health and safety. This paper provides an overview of these signal processing techniques and summarizes recent advances made with digital transducers in hopes of organizing the highly varied research on cervical auscultation. It investigates where on the body these transducers are placed in order to record a signal as well as the collection of analog and digital filtering techniques used to further improve the signal quality. It also presents the wide array of methods and features used to characterize these signals, ranging from simply counting the number of swallows that occur over a period of time to calculating various descriptive features in the time, frequency, and phase space domains. Finally, this paper presents the algorithms that have been used to classify this data into ‘normal’ and ‘abnormal’ categories. Both linear as well as non-linear techniques are presented in this regard. PMID:26213659

Digital Front End for Wide-Band VLBI Science Receiver

NASA Technical Reports Server (NTRS)

Jongeling, Andre; Sigman, Elliott; Navarro, Robert; Goodhart, Charles; Rogstad, Steve; Chandra, Kumar; Finley, Sue; Trinh, Joseph; Soriano, Melissa; White, Les;

The Role of Ankle Proprioception for Balance Control in relation to Sports Performance and Injury.

PubMed

Han, Jia; Anson, Judith; Waddington, Gordon; Adams, Roger; Liu, Yu

2015-01-01

Balance control improvement is one of the most important goals in sports and exercise. Better balance is strongly positively associated with enhanced athletic performance and negatively associated with lower limb sports injuries. Proprioception plays an essential role in balance control, and ankle proprioception is arguably the most important. This paper reviews ankle proprioception and explores synergies with balance control, specifically in a sporting context. Central processing of ankle proprioceptive information, along with other sensory information, enables integration for balance control. When assessing ankle proprioception, the most generalizable findings arise from methods that are ecologically valid, allow proprioceptive signals to be integrated with general vision in the central nervous system, and reflect the signal-in-noise nature of central processing. Ankle proprioceptive intervention concepts driven by such a central processing theory are further proposed and discussed for the improvement of balance control in sport.

The Role of Ankle Proprioception for Balance Control in relation to Sports Performance and Injury

PubMed Central

Han, Jia; Waddington, Gordon; Adams, Roger; Liu, Yu

2015-01-01

Balance control improvement is one of the most important goals in sports and exercise. Better balance is strongly positively associated with enhanced athletic performance and negatively associated with lower limb sports injuries. Proprioception plays an essential role in balance control, and ankle proprioception is arguably the most important. This paper reviews ankle proprioception and explores synergies with balance control, specifically in a sporting context. Central processing of ankle proprioceptive information, along with other sensory information, enables integration for balance control. When assessing ankle proprioception, the most generalizable findings arise from methods that are ecologically valid, allow proprioceptive signals to be integrated with general vision in the central nervous system, and reflect the signal-in-noise nature of central processing. Ankle proprioceptive intervention concepts driven by such a central processing theory are further proposed and discussed for the improvement of balance control in sport. PMID:26583139

Multipath interference test method using synthesized chirped signal from directly modulated DFB-LD with digital-signal-processing technique.

PubMed

Aida, Kazuo; Sugie, Toshihiko

2011-12-12

We propose a method of testing transmission fiber lines and distributed amplifiers. Multipath interference (MPI) is detected as a beat spectrum between a multipath signal and a direct signal using a synthesized chirped test signal with lightwave frequencies of f(1) and f(2) periodically emitted from a distributed feedback laser diode (DFB-LD). This chirped test pulse is generated using a directly modulated DFB-LD with a drive signal calculated using a digital signal processing technique (DSP). A receiver consisting of a photodiode and an electrical spectrum analyzer (ESA) detects a baseband power spectrum peak appearing at the frequency of the test signal frequency deviation (f(1)-f(2)) as a beat spectrum of self-heterodyne detection. Multipath interference is converted from the spectrum peak power. This method improved the minimum detectable MPI to as low as -78 dB. We discuss the detailed design and performance of the proposed test method, including a DFB-LD drive signal calculation algorithm with DSP for synthesis of the chirped test signal and experiments on single-mode fibers with discrete reflections. © 2011 Optical Society of America

Application of Hilbert-Huang Transform for Improved Defect Detection in Terahertz NDE of Shuttle Tiles

NASA Technical Reports Server (NTRS)

Anastasi, Robert F.; Madaras, Eric I.

2005-01-01

Terahertz NDE is being examined as a method to inspect the adhesive bond-line of Space Shuttle tiles for defects. Terahertz signals are generated and detected, using optical excitation of biased semiconductors with femtosecond laser pulses. Shuttle tile samples were manufactured with defects that included repair regions unbond regions, and other conditions that occur in Shuttle structures. These samples were inspected with a commercial terahertz NDE system that scanned a tile and generated a data set of RF signals. The signals were post processed to generate C-scan type images that are typically seen in ultrasonic NDE. To improve defect visualization the Hilbert-Huang Transform, a transform that decomposes a signal into oscillating components called intrinsic mode functions, was applied to test signals identified as being in and out of the defect regions and then on a complete data set. As expected with this transform, the results showed that the decomposed low-order modes correspond to signal noise while the high-order modes correspond to low frequency oscillations in the signal and mid-order modes correspond to local signal oscillations. The local oscillations compare well with various reflection interfaces and the defect locations in the original signal.

Sparse Matrix for ECG Identification with Two-Lead Features.

PubMed

Tseng, Kuo-Kun; Luo, Jiao; Hegarty, Robert; Wang, Wenmin; Haiting, Dong

2015-01-01

Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods.

Enhancing speech recognition using improved particle swarm optimization based hidden Markov model.

PubMed

Selvaraj, Lokesh; Ganesan, Balakrishnan

2014-01-01

Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages, namely, (i) denoising, (ii) feature mining (iii), vector quantization, and (iv) IPSO based hidden Markov model (HMM) technique (IP-HMM). At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC), mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.

Variable sensory perception in autism.

PubMed

Haigh, Sarah M

2018-03-01

Autism is associated with sensory and cognitive abnormalities. Individuals with autism generally show normal or superior early sensory processing abilities compared to healthy controls, but deficits in complex sensory processing. In the current opinion paper, it will be argued that sensory abnormalities impact cognition by limiting the amount of signal that can be used to interpret and interact with environment. There is a growing body of literature showing that individuals with autism exhibit greater trial-to-trial variability in behavioural and cortical sensory responses. If multiple sensory signals that are highly variable are added together to process more complex sensory stimuli, then this might destabilise later perception and impair cognition. Methods to improve sensory processing have shown improvements in more general cognition. Studies that specifically investigate differences in sensory trial-to-trial variability in autism, and the potential changes in variability before and after treatment, could ascertain if trial-to-trial variability is a good mechanism to target for treatment in autism. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Application of Ensemble Detection and Analysis to Modeling Uncertainty in Non Stationary Process

NASA Technical Reports Server (NTRS)

Racette, Paul

2010-01-01

Characterization of non stationary and nonlinear processes is a challenge in many engineering and scientific disciplines. Climate change modeling and projection, retrieving information from Doppler measurements of hydrometeors, and modeling calibration architectures and algorithms in microwave radiometers are example applications that can benefit from improvements in the modeling and analysis of non stationary processes. Analyses of measured signals have traditionally been limited to a single measurement series. Ensemble Detection is a technique whereby mixing calibrated noise produces an ensemble measurement set. The collection of ensemble data sets enables new methods for analyzing random signals and offers powerful new approaches to studying and analyzing non stationary processes. Derived information contained in the dynamic stochastic moments of a process will enable many novel applications.

Improving the Response of Accelerometers for Automotive Applications by Using LMS Adaptive Filters: Part II

PubMed Central

Hernandez, Wilmar; de Vicente, Jesús; Sergiyenko, Oleg Y.; Fernández, Eduardo

2010-01-01

In this paper, the fast least-mean-squares (LMS) algorithm was used to both eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications, and improve the convergence rate of the filtering process based on the conventional LMS algorithm. The response of the accelerometer under test was corrupted by process and measurement noise, and the signal processing stage was carried out by using both conventional filtering, which was already shown in a previous paper, and optimal adaptive filtering. The adaptive filtering process relied on the LMS adaptive filtering family, which has shown to have very good convergence and robustness properties, and here a comparative analysis between the results of the application of the conventional LMS algorithm and the fast LMS algorithm to solve a real-life filtering problem was carried out. In short, in this paper the piezoresistive accelerometer was tested for a multi-frequency acceleration excitation. Due to the kind of test conducted in this paper, the use of conventional filtering was discarded and the choice of one adaptive filter over the other was based on the signal-to-noise ratio improvement and the convergence rate. PMID:22315579

Improved methods for signal processing in measurements of mercury by Tekran® 2537A and 2537B instruments

NASA Astrophysics Data System (ADS)

Ambrose, Jesse L.

2017-12-01

Atmospheric Hg measurements are commonly carried out using Tekran® Instruments Corporation's model 2537 Hg vapor analyzers, which employ gold amalgamation preconcentration sampling and detection by thermal desorption (TD) and atomic fluorescence spectrometry (AFS). A generally overlooked and poorly characterized source of analytical uncertainty in those measurements is the method by which the raw Hg atomic fluorescence (AF) signal is processed. Here I describe new software-based methods for processing the raw signal from the Tekran® 2537 instruments, and I evaluate the performances of those methods together with the standard Tekran® internal signal processing method. For test datasets from two Tekran® instruments (one 2537A and one 2537B), I estimate that signal processing uncertainties in Hg loadings determined with the Tekran® method are within ±[1 % + 1.2 pg] and ±[6 % + 0.21 pg], respectively. I demonstrate that the Tekran® method can produce significant low biases (≥ 5 %) not only at low Hg sample loadings (< 5 pg) but also at tropospheric background concentrations of gaseous elemental mercury (GEM) and total mercury (THg) (˜ 1 to 2 ng m-3) under typical operating conditions (sample loadings of 5-10 pg). Signal processing uncertainties associated with the Tekran® method can therefore represent a significant unaccounted for addition to the overall ˜ 10 to 15 % uncertainty previously estimated for Tekran®-based GEM and THg measurements. Signal processing bias can also add significantly to uncertainties in Tekran®-based gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) measurements, which often derive from Hg sample loadings < 5 pg. In comparison, estimated signal processing uncertainties associated with the new methods described herein are low, ranging from within ±0.053 pg, when the Hg thermal desorption peaks are defined manually, to within ±[2 % + 0.080 pg] when peak definition is automated. Mercury limits of detection (LODs) decrease by 31 to 88 % when the new methods are used in place of the Tekran® method. I recommend that signal processing uncertainties be quantified in future applications of the Tekran® 2537 instruments.

Is transcranial direct current stimulation a potential method for improving response inhibition?☆

PubMed Central

Kwon, Yong Hyun; Kwon, Jung Won

2013-01-01

Inhibitory control of movement in motor learning requires the ability to suppress an inappropriate action, a skill needed to stop a planned or ongoing motor response in response to changes in a variety of environments. This study used a stop-signal task to determine whether transcranial direct-current stimulation over the pre-supplementary motor area alters the reaction time in motor inhibition. Forty healthy subjects were recruited for this study and were randomly assigned to either the transcranial direct-current stimulation condition or a sham-transcranial direct-current stimulation condition. All subjects consecutively performed the stop-signal task before, during, and after the delivery of anodal transcranial direct-current stimulation over the pre-supplementary motor area (pre-transcranial direct-current stimulation phase, transcranial direct-current stimulation phase, and post-transcranial direct-current stimulation phase). Compared to the sham condition, there were significant reductions in the stop-signal processing times during and after transcranial direct-current stimulation, and change times were significantly greater in the transcranial direct-current stimulation condition. There was no significant change in go processing-times during or after transcranial direct-current stimulation in either condition. Anodal transcranial direct-current stimulation was feasibly coupled to an interactive improvement in inhibitory control. This coupling led to a decrease in the stop-signal process time required for the appropriate responses between motor execution and inhibition. However, there was no transcranial direct-current stimulation effect on the no-signal reaction time during the stop-signal task. Transcranial direct-current stimulation can adjust certain behaviors, and it could be a useful clinical intervention for patients who have difficulties with response inhibition. PMID:25206399

Is transcranial direct current stimulation a potential method for improving response inhibition?

PubMed

Kwon, Yong Hyun; Kwon, Jung Won

2013-04-15

Inhibitory control of movement in motor learning requires the ability to suppress an inappropriate action, a skill needed to stop a planned or ongoing motor response in response to changes in a variety of environments. This study used a stop-signal task to determine whether transcranial direct-current stimulation over the pre-supplementary motor area alters the reaction time in motor inhibition. Forty healthy subjects were recruited for this study and were randomly assigned to either the transcranial direct-current stimulation condition or a sham-transcranial direct-current stimulation condition. All subjects consecutively performed the stop-signal task before, during, and after the delivery of anodal transcranial direct-current stimulation over the pre-supplementary motor area (pre-transcranial direct-current stimulation phase, transcranial direct-current stimulation phase, and post-transcranial direct-current stimulation phase). Compared to the sham condition, there were significant reductions in the stop-signal processing times during and after transcranial direct-current stimulation, and change times were significantly greater in the transcranial direct-current stimulation condition. There was no significant change in go processing-times during or after transcranial direct-current stimulation in either condition. Anodal transcranial direct-current stimulation was feasibly coupled to an interactive improvement in inhibitory control. This coupling led to a decrease in the stop-signal process time required for the appropriate responses between motor execution and inhibition. However, there was no transcranial direct-current stimulation effect on the no-signal reaction time during the stop-signal task. Transcranial direct-current stimulation can adjust certain behaviors, and it could be a useful clinical intervention for patients who have difficulties with response inhibition.

Measuring Postural Stability: Strategies For Signal Acquisition And Processing

NASA Astrophysics Data System (ADS)

Riedel, Susan A.; Harris, Gerald F.

1987-01-01

A balance platform was used to collect postural stability data from 60 children, approximately half of whom have been diagnosed with cerebral palsy. The data was examined with respect to its frequency content, resulting in an improved strategy for frequency estimation. With a reliable assessment of the frequency domain characteristics, the signal stationarity could then be examined. Significant differences in signal stationarity were observed when the epoch length was changed, as well as between the normal and cerebral palsy populations.

Focus issue: teaching tools and learning opportunities.

PubMed

Gough, Nancy R

2010-04-27

Science Signaling provides authoring experience for students and resources for educators. Students experience the writing and revision process involved in authoring short commentary articles that are published in the Journal Club section. By publishing peer-reviewed teaching materials, Science Signaling provides instructors with feedback that improves their materials and an outlet to share their tips and techniques and digital resources with other teachers.

Evaluation of dispersive Bragg gratings (BG) structures for the processing of RF signals with large time delays and bandwidths

NASA Astrophysics Data System (ADS)

Kaba, M.; Zhou, F. C.; Lim, A.; Decoster, D.; Huignard, J.-P.; Tonda, S.; Dolfi, D.; Chazelas, J.

2007-11-01

The applications of microwave optoelectronics are extremely large since they extend from the Radio-over-Fibre to the Homeland security and defence systems. Then, the improved maturity of the optoelectronic components operating up to 40GHz permit to consider new optical processing functions (filtering, beamforming, ...) which can operate over very wideband microwave analogue signals. Specific performances are required which imply optical delay lines able to exhibit large Time-Bandwidth product values. It is proposed to evaluate slow light approach through highly dispersive structures based on either uniform or chirped Bragg Gratings. Therefore, we highlight the impact of the major parameters of such structures: index modulation depth, grating length, grating period, chirp coefficient and demonstrate the high potentiality of Bragg Grating for Large RF signals bandwidth processing under slow-light propagation.

Ionization Electron Signal Processing in Single Phase LArTPCs II. Data/Simulation Comparison and Performance in MicroBooNE

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

Adams, C.; et al.

The single-phase liquid argon time projection chamber (LArTPC) provides a large amount of detailed information in the form of fine-grained drifted ionization charge from particle traces. To fully utilize this information, the deposited charge must be accurately extracted from the raw digitized waveforms via a robust signal processing chain. Enabled by the ultra-low noise levels associated with cryogenic electronics in the MicroBooNE detector, the precise extraction of ionization charge from the induction wire planes in a single-phase LArTPC is qualitatively demonstrated on MicroBooNE data with event display images, and quantitatively demonstrated via waveform-level and track-level metrics. Improved performance of inductionmore » plane calorimetry is demonstrated through the agreement of extracted ionization charge measurements across different wire planes for various event topologies. In addition to the comprehensive waveform-level comparison of data and simulation, a calibration of the cryogenic electronics response is presented and solutions to various MicroBooNE-specific TPC issues are discussed. This work presents an important improvement in LArTPC signal processing, the foundation of reconstruction and therefore physics analyses in MicroBooNE.« less

Comparative intelligibility investigation of single-channel noise-reduction algorithms for Chinese, Japanese, and English.

PubMed

Li, Junfeng; Yang, Lin; Zhang, Jianping; Yan, Yonghong; Hu, Yi; Akagi, Masato; Loizou, Philipos C

2011-05-01

A large number of single-channel noise-reduction algorithms have been proposed based largely on mathematical principles. Most of these algorithms, however, have been evaluated with English speech. Given the different perceptual cues used by native listeners of different languages including tonal languages, it is of interest to examine whether there are any language effects when the same noise-reduction algorithm is used to process noisy speech in different languages. A comparative evaluation and investigation is taken in this study of various single-channel noise-reduction algorithms applied to noisy speech taken from three languages: Chinese, Japanese, and English. Clean speech signals (Chinese words and Japanese words) were first corrupted by three types of noise at two signal-to-noise ratios and then processed by five single-channel noise-reduction algorithms. The processed signals were finally presented to normal-hearing listeners for recognition. Intelligibility evaluation showed that the majority of noise-reduction algorithms did not improve speech intelligibility. Consistent with a previous study with the English language, the Wiener filtering algorithm produced small, but statistically significant, improvements in intelligibility for car and white noise conditions. Significant differences between the performances of noise-reduction algorithms across the three languages were observed.

Photonics for microwave systems and ultra-wideband signal processing

NASA Astrophysics Data System (ADS)

Ng, W.

2016-08-01

The advantages of using the broadband and low-loss distribution attributes of photonics to enhance the signal processing and sensing capabilities of microwave systems are well known. In this paper, we review the progress made in the topical areas of true-time-delay beamsteering, photonic-assisted analog-to-digital conversion, RF-photonic filtering and link performances. We also provide an outlook on the emerging field of integrated microwave photonics (MWP) that promise to reduce the cost of MWP subsystems and components, while providing significantly improved form-factors for system insertion.

Signal to Noise Studies on Thermographic Data with Fabricated Defects for Defense Structures

NASA Technical Reports Server (NTRS)

Zalameda, Joseph N.; Rajic, Nik; Genest, Marc

2006-01-01

There is a growing international interest in thermal inspection systems for asset life assessment and management of defense platforms. The efficacy of flash thermography is generally enhanced by applying image processing algorithms to the observations of raw temperature. Improving the defect signal to noise ratio (SNR) is of primary interest to reduce false calls and allow for easier interpretation of a thermal inspection image. Several factors affecting defect SNR were studied such as data compression and reconstruction using principal component analysis and time window processing.

Distributed MIMO chaotic radar based on wavelength-division multiplexing technology.

PubMed

Yao, Tingfeng; Zhu, Dan; Ben, De; Pan, Shilong

2015-04-15

A distributed multiple-input multiple-output chaotic radar based on wavelength-division multiplexing technology (WDM) is proposed and demonstrated. The wideband quasi-orthogonal chaotic signals generated by different optoelectronic oscillators (OEOs) are emitted by separated antennas to gain spatial diversity against the fluctuation of a target's radar cross section and enhance the detection capability. The received signals collected by the receive antennas and the reference signals from the OEOs are delivered to the central station for joint processing by exploiting WDM technology. The centralized signal processing avoids precise time synchronization of the distributed system and greatly simplifies the remote units, which improves the localization accuracy of the entire system. A proof-of-concept experiment for two-dimensional localization of a metal target is demonstrated. The maximum position error is less than 6.5 cm.

Reducing Artifacts in TMS-Evoked EEG

NASA Astrophysics Data System (ADS)

Fuertes, Juan José; Travieso, Carlos M.; Álvarez, A.; Ferrer, M. A.; Alonso, J. B.

Transcranial magnetic stimulation induces weak currents within the cranium to activate neuronal firing and its response is recorded using electroencephalography in order to study the brain directly. However, different artifacts contaminate the results. The goal of this study is to process these artifacts and reduce them digitally. Electromagnetic, blink and auditory artifacts are considered, and Signal-Space Projection, Independent Component Analysis and Wiener Filtering methods are used to reduce them. These last two produce a successful solution for electromagnetic artifacts. Regarding the other artifacts, processed with Signal-Space Projection, the method reduces the artifact but modifies the signal as well. Nonetheless, they are modified in an exactly known way and the vector used for the projection is conserved to be taken into account when analyzing the resulting signals. A system which combines the proposed methods would improve the quality of the information presented to physicians.

A hybrid voice/data modulation for the VHF aeronautical channels

NASA Technical Reports Server (NTRS)

Akos, Dennis M.

1993-01-01

A method of improving the spectral efficiency of the existing Very High Frequency (VHF) Amplitude Modulation (AM) voice communication channels is proposed. The technique is to phase modulate the existing voice amplitude modulated carrier with digital data. This allows the transmission of digital information over an existing AM voice channel with no change to the existing AM signal format. There is no modification to the existing AM receiver to demodulate the voice signal and an additional receiver module can be added for processing of the digital data. The existing VHF AM transmitter requires only a slight modification for the addition of the digital data signal. The past work in the area is summarized and presented together with an improved system design and the proposed implementation.

Remote photoacoustic detection of liquid contamination of a surface.

PubMed

Perrett, Brian; Harris, Michael; Pearson, Guy N; Willetts, David V; Pitter, Mark C

2003-08-20

A method for the remote detection and identification of liquid chemicals at ranges of tens of meters is presented. The technique uses pulsed indirect photoacoustic spectroscopy in the 10-microm wavelength region. Enhanced sensitivity is brought about by three main system developments: (1) increased laser-pulse energy (150 microJ/pulse), leading to increased strength of the generated photoacoustic signal; (2) increased microphone sensitivity and improved directionality by the use of a 60-cm-diameter parabolic dish; and (3) signal processing that allows improved discrimination of the signal from noise levels through prior knowledge of the pulse shape and pulse-repetition frequency. The practical aspects of applying the technique in a field environment are briefly examined, and possible applications of this technique are discussed.

Multiresponse imaging system design for improved resolution

NASA Technical Reports Server (NTRS)

Alter-Gartenberg, Rachel; Fales, Carl L.; Huck, Friedrich O.; Rahman, Zia-Ur; Reichenbach, Stephen E.

1991-01-01

Multiresponse imaging is a process that acquires A images, each with a different optical response, and reassembles them into a single image with an improved resolution that can approach 1/sq rt A times the photodetector-array sampling lattice. Our goals are to optimize the performance of this process in terms of the resolution and fidelity of the restored image and to assess the amount of information required to do so. The theoretical approach is based on the extension of both image restoration and rate-distortion theories from their traditional realm of signal processing to image processing which includes image gathering and display.

Algorithm for Aligning an Array of Receiving Radio Antennas

NASA Technical Reports Server (NTRS)

Rogstad, David

2006-01-01

A digital-signal-processing algorithm (somewhat arbitrarily) called SUMPLE has been devised as a means of aligning the outputs of multiple receiving radio antennas in a large array for the purpose of receiving a weak signal transmitted by a single distant source. As used here, aligning signifies adjusting the delays and phases of the outputs from the various antennas so that their relatively weak replicas of the desired signal can be added coherently to increase the signal-to-noise ratio (SNR) for improved reception, as though one had a single larger antenna. The method was devised to enhance spacecraft-tracking and telemetry operations in NASA's Deep Space Network (DSN); the method could also be useful in such other applications as both satellite and terrestrial radio communications and radio astronomy. Heretofore, most commonly, alignment has been effected by a process that involves correlation of signals in pairs. This approach necessitates the use of a large amount of hardware most notably, the N(N - 1)/2 correlators needed to process signals from all possible pairs of N antennas. Moreover, because the incoming signals typically have low SNRs, the delay and phase adjustments are poorly determined from the pairwise correlations. SUMPLE also involves correlations, but the correlations are not performed in pairs. Instead, in a partly iterative process, each signal is appropriately weighted and then correlated with a composite signal equal to the sum of the other signals (see Figure 1). One benefit of this approach is that only N correlators are needed; in an array of N much greater than 1 antennas, this results in a significant reduction of the amount of hardware. Another benefit is that once the array achieves coherence, the correlation SNR is N - 1 times that of a pair of antennas.

Non-invasive Fetal ECG Signal Quality Assessment for Multichannel Heart Rate Estimation.

PubMed

Andreotti, Fernando; Graser, Felix; Malberg, Hagen; Zaunseder, Sebastian

2017-12-01

The noninvasive fetal ECG (NI-FECG) from abdominal recordings offers novel prospects for prenatal monitoring. However, NI-FECG signals are corrupted by various nonstationary noise sources, making the processing of abdominal recordings a challenging task. In this paper, we present an online approach that dynamically assess the quality of NI-FECG to improve fetal heart rate (FHR) estimation. Using a naive Bayes classifier, state-of-the-art and novel signal quality indices (SQIs), and an existing adaptive Kalman filter, FHR estimation was improved. For the purpose of training and validating the proposed methods, a large annotated private clinical dataset was used. The suggested classification scheme demonstrated an accuracy of Krippendorff's alpha in determining the overall quality of NI-FECG signals. The proposed Kalman filter outperformed alternative methods for FHR estimation achieving accuracy. The proposed algorithm was able to reliably reflect changes of signal quality and can be used in improving FHR estimation. NI-ECG signal quality estimation and multichannel information fusion are largely unexplored topics. Based on previous works, multichannel FHR estimation is a field that could strongly benefit from such methods. The developed SQI algorithms as well as resulting classifier were made available under a GNU GPL open-source license and contributed to the FECGSYN toolbox.

On the improvement of signal repeatability in laser-induced air plasmas

NASA Astrophysics Data System (ADS)

Zhang, Shuai; Sheta, Sahar; Hou, Zong-Yu; Wang, Zhe

2018-04-01

The relatively low repeatability of laser-induced breakdown spectroscopy (LIBS) severely hinders its wide commercialization. In the present work, we investigate the optimization of LIBS system for repeatability improvement for both signal generation (plasma evolution) and signal collection. Timeintegrated spectra and images were obtained under different laser energies and focal lengths to investigate the optimum configuration for stable plasmas and repeatable signals. Using our experimental setup, the optimum conditions were found to be a laser energy of 250 mJ and a focus length of 100 mm. A stable and homogeneous plasma with the largest hot core area in the optimum condition yielded the most stable LIBS signal. Time-resolved images showed that the rebounding processes through the air plasma evolution caused the relative standard deviation (RSD) to increase with laser energies of > 250 mJ. In addition, the emission collection was improved by using a concave spherical mirror. The line intensities doubled as their RSDs decreased by approximately 25%. When the signal generation and collection were optimized simultaneously, the pulse-to-pulse RSDs were reduced to approximately 3% for O(I), N(I), and H(I) lines, which are better than the RSDs reported for solid samples and showed great potential for LIBS quantitative analysis by gasifying the solid or liquid samples.

Improvement in detection of small wildfires

NASA Astrophysics Data System (ADS)

Sleigh, William J.

1991-12-01

Detecting and imaging small wildfires with an Airborne Scanner is done against generally high background levels. The Airborne Scanner System used is a two-channel thermal IR scanner, with one channel selected for imaging the terrain and the other channel sensitive to hotter targets. If a relationship can be determined between the two channels that quantifies the background signal for hotter targets, then an algorithm can be determined that removes the background signal in that channel leaving only the fire signal. The relationship can be determined anywhere between various points in the signal processing of the radiometric data from the radiometric input to the quantized output of the system. As long as only linear operations are performed on the signal, the relationship will only depend on the system gain and offsets within the range of interest. The algorithm can be implemented either by using a look-up table or performing the calculation in the system computer. The current presentation will describe the algorithm, its derivation, and its implementation in the Firefly Wildfire Detection System by means of an off-the-shelf commercial scanner. Improvement over the previous algorithm used and the margin gained for improving the imaging of the terrain will be demonstrated.

Improvement in detection of small wildfires

NASA Technical Reports Server (NTRS)

Sleigh, William J.

1991-01-01

Detecting and imaging small wildfires with an Airborne Scanner is done against generally high background levels. The Airborne Scanner System used is a two-channel thermal IR scanner, with one channel selected for imaging the terrain and the other channel sensitive to hotter targets. If a relationship can be determined between the two channels that quantifies the background signal for hotter targets, then an algorithm can be determined that removes the background signal in that channel leaving only the fire signal. The relationship can be determined anywhere between various points in the signal processing of the radiometric data from the radiometric input to the quantized output of the system. As long as only linear operations are performed on the signal, the relationship will only depend on the system gain and offsets within the range of interest. The algorithm can be implemented either by using a look-up table or performing the calculation in the system computer. The current presentation will describe the algorithm, its derivation, and its implementation in the Firefly Wildfire Detection System by means of an off-the-shelf commercial scanner. Improvement over the previous algorithm used and the margin gained for improving the imaging of the terrain will be demonstrated.

A Novel Multilayer Correlation Maximization Model for Improving CCA-Based Frequency Recognition in SSVEP Brain-Computer Interface.

PubMed

Jiao, Yong; Zhang, Yu; Wang, Yu; Wang, Bei; Jin, Jing; Wang, Xingyu

2018-05-01

Multiset canonical correlation analysis (MsetCCA) has been successfully applied to optimize the reference signals by extracting common features from multiple sets of electroencephalogram (EEG) for steady-state visual evoked potential (SSVEP) recognition in brain-computer interface application. To avoid extracting the possible noise components as common features, this study proposes a sophisticated extension of MsetCCA, called multilayer correlation maximization (MCM) model for further improving SSVEP recognition accuracy. MCM combines advantages of both CCA and MsetCCA by carrying out three layers of correlation maximization processes. The first layer is to extract the stimulus frequency-related information in using CCA between EEG samples and sine-cosine reference signals. The second layer is to learn reference signals by extracting the common features with MsetCCA. The third layer is to re-optimize the reference signals set in using CCA with sine-cosine reference signals again. Experimental study is implemented to validate effectiveness of the proposed MCM model in comparison with the standard CCA and MsetCCA algorithms. Superior performance of MCM demonstrates its promising potential for the development of an improved SSVEP-based brain-computer interface.

Improvement of the Laser-Induced Breakdown Spectroscopy method sensitivity by the usage of combination of Ag-nanoparticles and vacuum conditions

NASA Astrophysics Data System (ADS)

Sládková, Lucia; Prochazka, David; Pořízka, Pavel; Škarková, Pavlína; Remešová, Michaela; Hrdlička, Aleš; Novotný, Karel; Čelko, Ladislav; Kaiser, Jozef

2017-01-01

In this work we studied the effect of vacuum (low pressure) conditions on the behavior of laser-induced plasma (LIP) created on a sample surface covered with silver nanoparticles (Ag-NPs), i.e. Nanoparticles-Enhanced Laser-Induced Breakdown Spectroscopy (NELIBS) experiment in a vacuum. The focus was put on the step by step optimization of the measurement parameters, such as energy of the laser pulse, temporally resolved detection, ambient pressure, and different content of Ag-NPs applied on the sample surface. The measurement parameters were optimized in order to achieve the greatest enhancement represented as the signal-to-noise ratio (SNR) of NELIBS signal to the SNR of LIBS signal. The presence of NPs involved in the ablation process enhances LIP intensity; hence the improvement in the analytical sensitivity was yielded. A leaded brass standard was analyzed with the emphasis on the signal enhancement of Pb traces. We gained enhancement by a factor of four. Although the low pressure had no significant influence on the LIP signal enhancement compared to that under ambient conditions, the SNR values were noticeably improved with the implementation of the NPs.

An Ultra-Wideband Cross-Correlation Radiometer for Mesoscopic Experiments

NASA Astrophysics Data System (ADS)

Toonen, Ryan; Haselby, Cyrus; Qin, Hua; Eriksson, Mark; Blick, Robert

2007-03-01

We have designed, built and tested a cross-correlation radiometer for detecting statistical order in the quantum fluctuations of mesoscopic experiments at sub-Kelvin temperatures. Our system utilizes a fully analog front-end--operating over the X- and Ku-bands (8 to 18 GHz)--for computing the cross-correlation function. Digital signal processing techniques are used to provide robustness against instrumentation drifts and offsets. The economized version of our instrument can measure, with sufficient correlation efficiency, noise signals having power levels as low as 10 fW. We show that, if desired, we can improve this performance by including cryogenic preamplifiers which boost the signal-to-noise ratio near the signal source. By adding a few extra components, we can measure both the real and imaginary parts of the cross-correlation function--improving the overall signal-to-noise ratio by a factor of sqrt[2]. We demonstrate the utility of our cross-correlator with noise power measurements from a quantum point contact.

Masking Level Difference Response Norms from Learning Disabled Individuals.

ERIC Educational Resources Information Center

Waryas, Paul A.; Battin, R. Ray

1985-01-01

The study presents normative data on Masking Level Difference (an improvement of the auditory processing of interaural time/intensity differences between signals and masking noises) for 90 learning disabled persons (4-35 years old). It was concluded that the MLD may quickly screen for auditory processing problems. (CL)

Promising evidence of impact on road safety by changing at-risk behavior process at Union Pacific

DOT National Transportation Integrated Search

2008-06-01

Changing At-risk Behavior (CAB) is a safety process that is being conducted at Union Pacifics San Antonio Service Unit with the aim of improving locomotive cab safety related to constraining signals. CAB is an example of a risk reduction method th...

Method to improve the blade tip-timing accuracy of fiber bundle sensor under varying tip clearance

NASA Astrophysics Data System (ADS)

Duan, Fajie; Zhang, Jilong; Jiang, Jiajia; Guo, Haotian; Ye, Dechao

2016-01-01

Blade vibration measurement based on the blade tip-timing method has become an industry-standard procedure. Fiber bundle sensors are widely used for tip-timing measurement. However, the variation of clearance between the sensor and the blade will bring a tip-timing error to fiber bundle sensors due to the change in signal amplitude. This article presents methods based on software and hardware to reduce the error caused by the tip clearance change. The software method utilizes both the rising and falling edges of the tip-timing signal to determine the blade arrival time, and a calibration process suitable for asymmetric tip-timing signals is presented. The hardware method uses an automatic gain control circuit to stabilize the signal amplitude. Experiments are conducted and the results prove that both methods can effectively reduce the impact of tip clearance variation on the blade tip-timing and improve the accuracy of measurements.

Achieving high spatial resolution using a microchannel plate detector with an economic and scalable approach

NASA Astrophysics Data System (ADS)

Wiggins, B. B.; deSouza, Z. O.; Vadas, J.; Alexander, A.; Hudan, S.; deSouza, R. T.

2017-11-01

A second generation position-sensitive microchannel plate detector using the induced signal approach has been realized. This detector is presently capable of measuring the incident position of electrons, photons, or ions. To assess the spatial resolution, the masked detector was illuminated by electrons. The initial, measured spatial resolution of 276 μm FWHM was improved by requiring a minimum signal amplitude on the anode and by employing digital signal processing techniques. The resulting measured spatial resolution of 119 μm FWHM corresponds to an intrinsic resolution of 98 μm FWHM when the effect of the finite slit width is de-convoluted. This measurement is a substantial improvement from the last reported spatial resolution of 466 μm FWHM using the induced signal approach. To understand the factors that limit the measured resolution, the performance of the detector is simulated.

Channel modeling, signal processing and coding for perpendicular magnetic recording

NASA Astrophysics Data System (ADS)

Wu, Zheng

With the increasing areal density in magnetic recording systems, perpendicular recording has replaced longitudinal recording to overcome the superparamagnetic limit. Studies on perpendicular recording channels including aspects of channel modeling, signal processing and coding techniques are presented in this dissertation. To optimize a high density perpendicular magnetic recording system, one needs to know the tradeoffs between various components of the system including the read/write transducers, the magnetic medium, and the read channel. We extend the work by Chaichanavong on the parameter optimization for systems via design curves. Different signal processing and coding techniques are studied. Information-theoretic tools are utilized to determine the acceptable region for the channel parameters when optimal detection and linear coding techniques are used. Our results show that a considerable gain can be achieved by the optimal detection and coding techniques. The read-write process in perpendicular magnetic recording channels includes a number of nonlinear effects. Nonlinear transition shift (NLTS) is one of them. The signal distortion induced by NLTS can be reduced by write precompensation during data recording. We numerically evaluate the effect of NLTS on the read-back signal and examine the effectiveness of several write precompensation schemes in combating NLTS in a channel characterized by both transition jitter noise and additive white Gaussian electronics noise. We also present an analytical method to estimate the bit-error-rate and use it to help determine the optimal write precompensation values in multi-level precompensation schemes. We propose a mean-adjusted pattern-dependent noise predictive (PDNP) detection algorithm for use on the channel with NLTS. We show that this detector can offer significant improvements in bit-error-rate (BER) compared to conventional Viterbi and PDNP detectors. Moreover, the system performance can be further improved by combining the new detector with a simple write precompensation scheme. Soft-decision decoding for algebraic codes can improve performance for magnetic recording systems. In this dissertation, we propose two soft-decision decoding methods for tensor-product parity codes. We also present a list decoding algorithm for generalized error locating codes.

Toward high fidelity spectral sensing and RF signal processing in silicon photonic and nano-opto-mechanical platforms

NASA Astrophysics Data System (ADS)

Siddiqui, Aleem; Reinke, Charles; Shin, Heedeuk; Jarecki, Robert L.; Starbuck, Andrew L.; Rakich, Peter

2017-05-01

The performance of electronic systems for radio-frequency (RF) spectrum analysis is critical for agile radar and communications systems, ISR (intelligence, surveillance, and reconnaissance) operations in challenging electromagnetic (EM) environments, and EM-environment situational awareness. While considerable progress has been made in size, weight, and power (SWaP) and performance metrics in conventional RF technology platforms, fundamental limits make continued improvements increasingly difficult. Alternatively, we propose employing cascaded transduction processes in a chip-scale nano-optomechanical system (NOMS) to achieve a spectral sensor with exceptional signal-linearity, high dynamic range, narrow spectral resolution and ultra-fast sweep times. By leveraging the optimal capabilities of photons and phonons, the system we pursue in this work has performance metrics scalable well beyond the fundamental limitations inherent to all electronic systems. In our device architecture, information processing is performed on wide-bandwidth RF-modulated optical signals by photon-mediated phononic transduction of the modulation to the acoustical-domain for narrow-band filtering, and then back to the optical-domain by phonon-mediated phase modulation (the reverse process). Here, we rely on photonics to efficiently distribute signals for parallel processing, and on phononics for effective and flexible RF-frequency manipulation. This technology is used to create RF-filters that are insensitive to the optical wavelength, with wide center frequency bandwidth selectivity (1-100GHz), ultra-narrow filter bandwidth (1-100MHz), and high dynamic range (70dB), which we will present. Additionally, using this filter as a building block, we will discuss current results and progress toward demonstrating a multichannel-filter with a bandwidth of < 10MHz per channel, while minimizing cumulative optical/acoustic/optical transduced insertion-loss to ideally < 10dB. These proposed metric represent significant improvements over RF-platforms.

Improved EEG Event Classification Using Differential Energy.

PubMed

Harati, A; Golmohammadi, M; Lopez, S; Obeid, I; Picone, J

2015-12-01

Feature extraction for automatic classification of EEG signals typically relies on time frequency representations of the signal. Techniques such as cepstral-based filter banks or wavelets are popular analysis techniques in many signal processing applications including EEG classification. In this paper, we present a comparison of a variety of approaches to estimating and postprocessing features. To further aid in discrimination of periodic signals from aperiodic signals, we add a differential energy term. We evaluate our approaches on the TUH EEG Corpus, which is the largest publicly available EEG corpus and an exceedingly challenging task due to the clinical nature of the data. We demonstrate that a variant of a standard filter bank-based approach, coupled with first and second derivatives, provides a substantial reduction in the overall error rate. The combination of differential energy and derivatives produces a 24 % absolute reduction in the error rate and improves our ability to discriminate between signal events and background noise. This relatively simple approach proves to be comparable to other popular feature extraction approaches such as wavelets, but is much more computationally efficient.

Methods to detect, characterize, and remove motion artifact in resting state fMRI

PubMed Central

Power, Jonathan D; Mitra, Anish; Laumann, Timothy O; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

2013-01-01

Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10 seconds after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects. PMID:23994314

The high accuracy data processing system of laser interferometry signals based on MSP430

NASA Astrophysics Data System (ADS)

Qi, Yong-yue; Lin, Yu-chi; Zhao, Mei-rong

2009-07-01

Generally speaking there are two orthogonal signals used in single-frequency laser interferometer for differentiating direction and electronic subdivision. However there usually exist three errors with the interferential signals: zero offsets error, unequal amplitude error and quadrature phase shift error. These three errors have a serious impact on subdivision precision. Based on Heydemann error compensation algorithm, it is proposed to achieve compensation of the three errors. Due to complicated operation of the Heydemann mode, a improved arithmetic is advanced to decrease the calculating time effectively in accordance with the special characteristic that only one item of data will be changed in each fitting algorithm operation. Then a real-time and dynamic compensatory circuit is designed. Taking microchip MSP430 as the core of hardware system, two input signals with the three errors are turned into digital quantity by the AD7862. After data processing in line with improved arithmetic, two ideal signals without errors are output by the AD7225. At the same time two original signals are turned into relevant square wave and imported to the differentiating direction circuit. The impulse exported from the distinguishing direction circuit is counted by the timer of the microchip. According to the number of the pulse and the soft subdivision the final result is showed by LED. The arithmetic and the circuit are adopted to test the capability of a laser interferometer with 8 times optical path difference and the measuring accuracy of 12-14nm is achieved.

Sparse gammatone signal model optimized for English speech does not match the human auditory filters.

PubMed

Strahl, Stefan; Mertins, Alfred

2008-07-18

Evidence that neurosensory systems use sparse signal representations as well as improved performance of signal processing algorithms using sparse signal models raised interest in sparse signal coding in the last years. For natural audio signals like speech and environmental sounds, gammatone atoms have been derived as expansion functions that generate a nearly optimal sparse signal model (Smith, E., Lewicki, M., 2006. Efficient auditory coding. Nature 439, 978-982). Furthermore, gammatone functions are established models for the human auditory filters. Thus far, a practical application of a sparse gammatone signal model has been prevented by the fact that deriving the sparsest representation is, in general, computationally intractable. In this paper, we applied an accelerated version of the matching pursuit algorithm for gammatone dictionaries allowing real-time and large data set applications. We show that a sparse signal model in general has advantages in audio coding and that a sparse gammatone signal model encodes speech more efficiently in terms of sparseness than a sparse modified discrete cosine transform (MDCT) signal model. We also show that the optimal gammatone parameters derived for English speech do not match the human auditory filters, suggesting for signal processing applications to derive the parameters individually for each applied signal class instead of using psychometrically derived parameters. For brain research, it means that care should be taken with directly transferring findings of optimality for technical to biological systems.

Adaptive windowing in contrast-enhanced intravascular ultrasound imaging.

PubMed

Lindsey, Brooks D; Martin, K Heath; Jiang, Xiaoning; Dayton, Paul A

2016-08-01

Intravascular ultrasound (IVUS) is one of the most commonly-used interventional imaging techniques and has seen recent innovations which attempt to characterize the risk posed by atherosclerotic plaques. One such development is the use of microbubble contrast agents to image vasa vasorum, fine vessels which supply oxygen and nutrients to the walls of coronary arteries and typically have diameters less than 200μm. The degree of vasa vasorum neovascularization within plaques is positively correlated with plaque vulnerability. Having recently presented a prototype dual-frequency transducer for contrast agent-specific intravascular imaging, here we describe signal processing approaches based on minimum variance (MV) beamforming and the phase coherence factor (PCF) for improving the spatial resolution and contrast-to-tissue ratio (CTR) in IVUS imaging. These approaches are examined through simulations, phantom studies, ex vivo studies in porcine arteries, and in vivo studies in chicken embryos. In phantom studies, PCF processing improved CTR by a mean of 4.2dB, while combined MV and PCF processing improved spatial resolution by 41.7%. Improvements of 2.2dB in CTR and 37.2% in resolution were observed in vivo. Applying these processing strategies can enhance image quality in conventional B-mode IVUS or in contrast-enhanced IVUS, where signal-to-noise ratio is relatively low and resolution is at a premium. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

A Modified Subpulse SAR Processing Procedure Based on the Range-Doppler Algorithm for Synthetic Wideband Waveforms

PubMed Central

Lim, Byoung-Gyun; Woo, Jea-Choon; Lee, Hee-Young; Kim, Young-Soo

2008-01-01

Synthetic wideband waveforms (SWW) combine a stepped frequency CW waveform and a chirp signal waveform to achieve high range resolution without requiring a large bandwidth or the consequent very high sampling rate. If an efficient algorithm like the range-Doppler algorithm (RDA) is used to acquire the SAR images for synthetic wideband signals, errors occur due to approximations, so the images may not show the best possible result. This paper proposes a modified subpulse SAR processing algorithm for synthetic wideband signals which is based on RDA. An experiment with an automobile-based SAR system showed that the proposed algorithm is quite accurate with a considerable improvement in resolution and quality of the obtained SAR image. PMID:27873984

Superresolution fluorescence imaging by pump-probe setup using repetitive stimulated transition process

NASA Astrophysics Data System (ADS)

Dake, Fumihiro; Fukutake, Naoki; Hayashi, Seri; Taki, Yusuke

2018-02-01

We proposed superresolution nonlinear fluorescence microscopy with pump-probe setup that utilizes repetitive stimulated absorption and stimulated emission caused by two-color laser beams. The resulting nonlinear fluorescence that undergoes such a repetitive stimulated transition is detectable as a signal via the lock-in technique. As the nonlinear fluorescence signal is produced by the multi-ply combination of incident beams, the optical resolution can be improved. A theoretical model of the nonlinear optical process is provided using rate equations, which offers phenomenological interpretation of nonlinear fluorescence and estimation of the signal properties. The proposed method is demonstrated as having the scalability of optical resolution. Theoretical resolution and bead image are also estimated to validate the experimental result.

The Pseudomonas aeruginosa quorum sensing signal molecule N-(3-oxododecanoyl) homoserine lactone enhances keratinocyte migration and induces Mmp13 gene expression in vitro

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

Paes, Camila, E-mail: camilaquinetti@gmail.com; Nakagami, Gojiro, E-mail: gojiron-tky@umin.ac.jp; Minematsu, Takeo, E-mail: tminematsu-tky@umin.ac.jp

2012-10-19

Highlights: Black-Right-Pointing-Pointer An evidence of the positive effect of AHL on epithelialization process is provided. Black-Right-Pointing-Pointer AHL enhances keratinocyte's ability to migrate in an in vitro scratch wound model. Black-Right-Pointing-Pointer AHL induces the expression of Mmp13. Black-Right-Pointing-Pointer Topical application of AHL represents a possible strategy to treat chronic wounds. -- Abstract: Re-epithelialization is an essential step of wound healing involving three overlapping keratinocyte functions: migration, proliferation and differentiation. While quorum sensing (QS) is a cell density-dependent signaling system that enables bacteria to regulate the expression of certain genes, the QS molecule N-(3-oxododecanoyl) homoserine lactone (AHL) exerts effects also on mammalianmore » cells in a process called inter-kingdom signaling. Recent studies have shown that AHL improves epithelialization in in vivo wound healing models but detailed understanding of the molecular and cellular mechanisms are needed. The present study focused on the AHL as a candidate reagent to improve wound healing through direct modulation of keratinocyte's activity in the re-epithelialization process. Results indicated that AHL enhances the keratinocyte's ability to migrate in an in vitro scratch wound healing model probably due to the high Mmp13 gene expression analysis after AHL treatment that was revealed by real-time RT-PCR. Inhibition of activator protein 1 (AP-1) signaling pathway completely prevented the migration of keratinocytes, and also resulted in a diminished Mmp13 gene expression, suggesting that AP-1 might be essential in the AHL-induced migration. Taken together, these results imply that AHL is a promising candidate molecule to improve re-epithelialization through the induction of migration of keratinocytes. Further investigation is needed to clarify the mechanism of action and molecular pathway of AHL on the keratinocyte migration process.« less

Signal processing for distributed sensor concept: DISCO

NASA Astrophysics Data System (ADS)

Rafailov, Michael K.

2007-04-01

Distributed Sensor concept - DISCO proposed for multiplication of individual sensor capabilities through cooperative target engagement. DISCO relies on ability of signal processing software to format, to process and to transmit and receive sensor data and to exploit those data in signal synthesis process. Each sensor data is synchronized formatted, Signal-to-Noise Ration (SNR) enhanced and distributed inside of the sensor network. Signal processing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique that was initially proposed [1] as a way to improve the SNR, reduce data rate and mitigate FPA correlated noise of an individual sensor digital video-signal processing. In Distributed Sensor Concept RAFIL technique is used in segmented way, when constituencies of the technique are spatially and/or temporally separated between transmitters and receivers. Those constituencies include though not limited to two thresholds - one is tuned for optimum probability of detection, the other - to manage required false alarm rate, and limited frame integration placed somewhere between the thresholds as well as formatters, conventional integrators and more. RAFIL allows a non-linear integration that, along with SNR gain, provides system designers more capability where cost, weight, or power considerations limit system data rate, processing, or memory capability [2]. DISCO architecture allows flexible optimization of SNR gain, data rates and noise suppression on sensor's side and limited integration, re-formatting and final threshold on node's side. DISCO with Recursive Adaptive Frame Integration of Limited data may have flexible architecture that allows segmenting the hardware and software to be best suitable for specific DISCO applications and sensing needs - whatever it is air-or-space platforms, ground terminals or integration of sensors network.

An improved car-following model with two preceding cars' average speed

NASA Astrophysics Data System (ADS)

Yu, Shao-Wei; Shi, Zhong-Ke

2015-01-01

To better describe cooperative car-following behaviors under intelligent transportation circumstances and increase roadway traffic mobility, the data of three successive following cars at a signalized intersection of Jinan in China were obtained and employed to explore the linkage between two preceding cars' average speed and car-following behaviors. The results indicate that two preceding cars' average velocity has significant effects on the following car's motion. Then an improved car-following model considering two preceding cars' average velocity was proposed and calibrated based on full velocity difference model and some numerical simulations were carried out to study how two preceding cars' average speed affected the starting process and the traffic flow evolution process with an initial small disturbance, the results indicate that the improved car-following model can qualitatively describe the impacts of two preceding cars' average velocity on traffic flow and that taking two preceding cars' average velocity into account in designing the control strategy for the cooperative adaptive cruise control system can improve the stability of traffic flow, suppress the appearance of traffic jams and increase the capacity of signalized intersections.

Short-Circuit Fault Detection and Classification Using Empirical Wavelet Transform and Local Energy for Electric Transmission Line.

PubMed

Huang, Nantian; Qi, Jiajin; Li, Fuqing; Yang, Dongfeng; Cai, Guowei; Huang, Guilin; Zheng, Jian; Li, Zhenxin

2017-09-16

In order to improve the classification accuracy of recognizing short-circuit faults in electric transmission lines, a novel detection and diagnosis method based on empirical wavelet transform (EWT) and local energy (LE) is proposed. First, EWT is used to deal with the original short-circuit fault signals from photoelectric voltage transformers, before the amplitude modulated-frequency modulated (AM-FM) mode with a compactly supported Fourier spectrum is extracted. Subsequently, the fault occurrence time is detected according to the modulus maxima of intrinsic mode function (IMF₂) from three-phase voltage signals processed by EWT. After this process, the feature vectors are constructed by calculating the LE of the fundamental frequency based on the three-phase voltage signals of one period after the fault occurred. Finally, the classifier based on support vector machine (SVM) which was constructed with the LE feature vectors is used to classify 10 types of short-circuit fault signals. Compared with complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved CEEMDAN methods, the new method using EWT has a better ability to present the frequency in time. The difference in the characteristics of the energy distribution in the time domain between different types of short-circuit faults can be presented by the feature vectors of LE. Together, simulation and real signals experiment demonstrate the validity and effectiveness of the new approach.

Short-Circuit Fault Detection and Classification Using Empirical Wavelet Transform and Local Energy for Electric Transmission Line

PubMed Central

Huang, Nantian; Qi, Jiajin; Li, Fuqing; Yang, Dongfeng; Cai, Guowei; Huang, Guilin; Zheng, Jian; Li, Zhenxin

2017-01-01

In order to improve the classification accuracy of recognizing short-circuit faults in electric transmission lines, a novel detection and diagnosis method based on empirical wavelet transform (EWT) and local energy (LE) is proposed. First, EWT is used to deal with the original short-circuit fault signals from photoelectric voltage transformers, before the amplitude modulated-frequency modulated (AM-FM) mode with a compactly supported Fourier spectrum is extracted. Subsequently, the fault occurrence time is detected according to the modulus maxima of intrinsic mode function (IMF2) from three-phase voltage signals processed by EWT. After this process, the feature vectors are constructed by calculating the LE of the fundamental frequency based on the three-phase voltage signals of one period after the fault occurred. Finally, the classifier based on support vector machine (SVM) which was constructed with the LE feature vectors is used to classify 10 types of short-circuit fault signals. Compared with complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved CEEMDAN methods, the new method using EWT has a better ability to present the frequency in time. The difference in the characteristics of the energy distribution in the time domain between different types of short-circuit faults can be presented by the feature vectors of LE. Together, simulation and real signals experiment demonstrate the validity and effectiveness of the new approach. PMID:28926953

Development of Advanced Signal Processing and Source Imaging Methods for Superparamagnetic Relaxometry

PubMed Central

Huang, Ming-Xiong; Anderson, Bill; Huang, Charles W.; Kunde, Gerd J.; Vreeland, Erika C.; Huang, Jeffrey W.; Matlashov, Andrei N.; Karaulanov, Todor; Nettles, Christopher P.; Gomez, Andrew; Minser, Kayla; Weldon, Caroline; Paciotti, Giulio; Harsh, Michael; Lee, Roland R.; Flynn, Edward R.

2017-01-01

Superparamagnetic Relaxometry (SPMR) is a highly sensitive technique for the in vivo detection of tumor cells and may improve early stage detection of cancers. SPMR employs superparamagnetic iron oxide nanoparticles (SPION). After a brief magnetizing pulse is used to align the SPION, SPMR measures the time decay of SPION using Super-conducting Quantum Interference Device (SQUID) sensors. Substantial research has been carried out in developing the SQUID hardware and in improving the properties of the SPION. However, little research has been done in the pre-processing of sensor signals and post-processing source modeling in SPMR. In the present study, we illustrate new pre-processing tools that were developed to: 1) remove trials contaminated with artifacts, 2) evaluate and ensure that a single decay process associated with bounded SPION exists in the data, 3) automatically detect and correct flux jumps, and 4) accurately fit the sensor signals with different decay models. Furthermore, we developed an automated approach based on multi-start dipole imaging technique to obtain the locations and magnitudes of multiple magnetic sources, without initial guesses from the users. A regularization process was implemented to solve the ambiguity issue related to the SPMR source variables. A procedure based on reduced chi-square cost-function was introduced to objectively obtain the adequate number of dipoles that describe the data. The new pre-processing tools and multi-start source imaging approach have been successfully evaluated using phantom data. In conclusion, these tools and multi-start source modeling approach substantially enhance the accuracy and sensitivity in detecting and localizing sources from the SPMR signals. Furthermore, multi-start approach with regularization provided robust and accurate solutions for a poor SNR condition similar to the SPMR detection sensitivity in the order of 1000 cells. We believe such algorithms will help establishing the industrial standards for SPMR when applying the technique in pre-clinical and clinical settings. PMID:28072579

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.

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.

Processing of pulse oximeter signals using adaptive filtering and autocorrelation to isolate perfusion and oxygenation components

NASA Astrophysics Data System (ADS)

Ibey, Bennett; Subramanian, Hariharan; Ericson, Nance; Xu, Weijian; Wilson, Mark; Cote, Gerard L.

2005-03-01

A blood perfusion and oxygenation sensor has been developed for in situ monitoring of transplanted organs. In processing in situ data, motion artifacts due to increased perfusion can create invalid oxygenation saturation values. In order to remove the unwanted artifacts from the pulsatile signal, adaptive filtering was employed using a third wavelength source centered at 810nm as a reference signal. The 810 nm source resides approximately at the isosbestic point in the hemoglobin absorption curve where the absorbance of light is nearly equal for oxygenated and deoxygenated hemoglobin. Using an autocorrelation based algorithm oxygenation saturation values can be obtained without the need for large sampling data sets allowing for near real-time processing. This technique has been shown to be more reliable than traditional techniques and proven to adequately improve the measurement of oxygenation values in varying perfusion states.

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

NASA Technical Reports Server (NTRS)

Downie, John D.; Tucker, Deanne (Technical Monitor)

1994-01-01

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Study of sensor spectral responses and data processing algorithms and architectures for onboard feature identification

NASA Technical Reports Server (NTRS)

Huck, F. O.; Davis, R. E.; Fales, C. L.; Aherron, R. M.

1982-01-01

A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.

Design of a Continuous Blood Pressure Measurement System Based on Pulse Wave and ECG Signals.

PubMed

Li, Jian-Qiang; Li, Rui; Chen, Zhuang-Zhuang; Deng, Gen-Qiang; Wang, Huihui; Mavromoustakis, Constandinos X; Song, Houbing; Ming, Zhong

2018-01-01

With increasingly fierce competition for jobs, the pressures on people have risen in recent years, leading to lifestyle and diet disorders that result in significantly higher risks of cardiovascular disease. Hypertension is one of the common chronic cardiovascular diseases; however, mainstream blood pressure measurement devices are relatively heavy. When multiple measurements are required, the user experience and the measurement results may be unsatisfactory. In this paper, we describe the design of a signal collection module that collects pulse waves and electrocardiograph (ECG) signals. The collected signals are input into a signal processing module to filter the noise and amplify the useful physiological signals. Then, we use a wavelet transform to eliminate baseline drift noise and detect the feature points of the pulse waves and ECG signals. We propose the concept of detecting the wave shape associated with an instance, an approach that minimizes the impact of atypical pulse waves on blood pressure measurements. Finally, we propose an improved method for measuring blood pressure based on pulse wave velocity that improves the accuracy of blood pressure measurements by 58%. Moreover, the results meet the american medical instrument promotion association standards, which demonstrate the feasibility of our measurement system.

Design of a Continuous Blood Pressure Measurement System Based on Pulse Wave and ECG Signals

PubMed Central

Li, Jian-Qiang; Li, Rui; Chen, Zhuang-Zhuang; Deng, Gen-Qiang; Wang, Huihui; Mavromoustakis, Constandinos X.; Ming, Zhong

2018-01-01

With increasingly fierce competition for jobs, the pressures on people have risen in recent years, leading to lifestyle and diet disorders that result in significantly higher risks of cardiovascular disease. Hypertension is one of the common chronic cardiovascular diseases; however, mainstream blood pressure measurement devices are relatively heavy. When multiple measurements are required, the user experience and the measurement results may be unsatisfactory. In this paper, we describe the design of a signal collection module that collects pulse waves and electrocardiograph (ECG) signals. The collected signals are input into a signal processing module to filter the noise and amplify the useful physiological signals. Then, we use a wavelet transform to eliminate baseline drift noise and detect the feature points of the pulse waves and ECG signals. We propose the concept of detecting the wave shape associated with an instance, an approach that minimizes the impact of atypical pulse waves on blood pressure measurements. Finally, we propose an improved method for measuring blood pressure based on pulse wave velocity that improves the accuracy of blood pressure measurements by 58%. Moreover, the results meet the american medical instrument promotion association standards, which demonstrate the feasibility of our measurement system. PMID:29541556

An Internet of Things based physiological signal monitoring and receiving system for virtual enhanced health care network.

PubMed

Rajan, J Pandia; Rajan, S Edward

2018-01-01

Wireless physiological signal monitoring system designing with secured data communication in the health care system is an important and dynamic process. We propose a signal monitoring system using NI myRIO connected with the wireless body sensor network through multi-channel signal acquisition method. Based on the server side validation of the signal, the data connected to the local server is updated in the cloud. The Internet of Things (IoT) architecture is used to get the mobility and fast access of patient data to healthcare service providers. This research work proposes a novel architecture for wireless physiological signal monitoring system using ubiquitous healthcare services by virtual Internet of Things. We showed an improvement in method of access and real time dynamic monitoring of physiological signal of this remote monitoring system using virtual Internet of thing approach. This remote monitoring and access system is evaluated in conventional value. This proposed system is envisioned to modern smart health care system by high utility and user friendly in clinical applications. We claim that the proposed scheme significantly improves the accuracy of the remote monitoring system compared to the other wireless communication methods in clinical system.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

NASA Astrophysics Data System (ADS)

Kora, Padmavathi; Sri Rama Krishna, K.

2016-12-01

Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

High dynamic range hyperspectral imaging for camouflage performance test and evaluation

NASA Astrophysics Data System (ADS)

Pearce, D.; Feenan, J.

2016-10-01

This paper demonstrates the use of high dynamic range processing applied to the specific technique of hyper-spectral imaging with linescan spectrometers. The technique provides an improvement in signal to noise for reflectance estimation. This is demonstrated for field measurements of rural imagery collected from a ground-based linescan spectrometer of rural scenes. Once fully developed, the specific application is expected to improve the colour estimation approaches and consequently the test and evaluation accuracy of camouflage performance tests. Data are presented on both field and laboratory experiments that have been used to evaluate the improvements granted by the adoption of high dynamic range data acquisition in the field of hyperspectral imaging. High dynamic ranging imaging is well suited to the hyperspectral domain due to the large variation in solar irradiance across the visible and short wave infra-red (SWIR) spectrum coupled with the wavelength dependence of the nominal silicon detector response. Under field measurement conditions it is generally impractical to provide artificial illumination; consequently, an adaptation of the hyperspectral imaging and re ectance estimation process has been developed to accommodate the solar spectrum. This is shown to improve the signal to noise ratio for the re ectance estimation process of scene materials in the 400-500 nm and 700-900 nm regions.

The recognition of extraterrestrial artificial signals

NASA Technical Reports Server (NTRS)

Seeger, C. L.

1980-01-01

Considerations in the design of receivers for the detection and recognition of artificial microwave signals of extraterrestrial origin are discussed. Following a review of the objectives of SETI and the probable reception and detection characteristics of extraterrestrial signals, means for the improvement of the sensitivity, signal-to-noise ratios and on-line data processing capabilities of SETI receivers are indicated. The characteristics of the signals likely to be present at the output of an ultra-low-noise microwave receiver are then examined, including the system background noise, terrestrial radiations, astrophysical radiations, accidental artificial radiations of terrestrial origin, and intentional radiations produced by humans and by extraterrestrial intelligence. The classes of extraterrestrial signals likely to be detected, beacons and leakage signals, are considered, and options in the specification of gating and thresholding for a high-spectral resolution, high-time-resolution signal discriminator are indicated. Possible tests for the nonhuman origin of a received signal are also pointed out.

Ecological prediction with nonlinear multivariate time-frequency functional data models

USGS Publications Warehouse

Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.

2013-01-01

Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

New detection system and signal processing for the tokamak ISTTOK heavy ion beam diagnostic.

PubMed

Henriques, R B; Nedzelskiy, I S; Malaquias, A; Fernandes, H

2012-10-01

The tokamak ISTTOK havy ion beam diagnostic (HIBD) operates with a multiple cell array detector (MCAD) that allows for the plasma density and the plasma density fluctuations measurements simultaneously at different sampling volumes across the plasma. To improve the capability of the plasma density fluctuations investigations, a new detection system and new signal conditioning amplifier have been designed and tested. The improvements in MCAD design are presented which allow for nearly complete suppression of the spurious plasma background signal by applying a biasing potential onto special electrodes incorporated into MCAD. The new low cost and small size transimpedance amplifiers are described with the parameters of 400 kHz, 10(7) V/A, 0.4 nA of RMS noise, adequate for the plasma density fluctuations measurements.

Multivariate analysis techniques

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

Bendavid, Josh; Fisher, Wade C.; Junk, Thomas R.

2016-01-01

The end products of experimental data analysis are designed to be simple and easy to understand: hypothesis tests and measurements of parameters. But, the experimental data themselves are voluminous and complex. Furthermore, in modern collider experiments, many petabytes of data must be processed in search of rare new processes which occur together with much more copious background processes that are of less interest to the task at hand. The systematic uncertainties on the background may be larger than the expected signal in many cases. The statistical power of an analysis and its sensitivity to systematic uncertainty can therefore usually bothmore » be improved by separating signal events from background events with higher efficiency and purity.« less

[Signaling pathways mTOR and AKT in epilepsy].

PubMed

Romero-Leguizamon, C R; Ramirez-Latorre, J A; Mora-Munoz, L; Guerrero-Naranjo, A

2016-07-01

The signaling pathway AKT/mTOR is a central axis in regulating cellular processes, particularly in neurological diseases. In the case of epilepsy, it has been observed alteration in the pathophysiological process of the same. However, they have not described all the mechanisms of these signaling pathways that could open the opportunity to new research and therapeutic strategies. To review existing partnerships between intracellular signaling pathways AKT and mTOR in the pathophysiology of epilepsy. Epilepsy is a disease with a high epidemiological impact globally, so it is widely investigated regarding the pathophysiological components thereof. In that search they have been involved different intracellular signaling pathways in neurons, as determinants epileptogenic. Advances in this field have even allowed the successful implementation of new therapeutic strategies and to open the way to new research in the field. Improving knowledge about the pathophysiological role of the signaling pathway mTOR/AKT in epilepsy can raise new investigations regarding therapeutic alternatives. The use of mTOR inhibitors, has emerged in recent years as effective in treating this disease entity alternative however is clear the necessity of continue the research for new drug therapies.

Dual signal amplification for highly sensitive electrochemical detection of uropathogens via enzyme-based catalytic target recycling.

PubMed

Su, Jiao; Zhang, Haijie; Jiang, Bingying; Zheng, Huzhi; Chai, Yaqin; Yuan, Ruo; Xiang, Yun

2011-11-15

We report an ultrasensitive electrochemical approach for the detection of uropathogen sequence-specific DNA target. The sensing strategy involves a dual signal amplification process, which combines the signal enhancement by the enzymatic target recycling technique with the sensitivity improvement by the quantum dot (QD) layer-by-layer (LBL) assembled labels. The enzyme-based catalytic target DNA recycling process results in the use of each target DNA sequence for multiple times and leads to direct amplification of the analytical signal. Moreover, the LBL assembled QD labels can further enhance the sensitivity of the sensing system. The coupling of these two effective signal amplification strategies thus leads to low femtomolar (5fM) detection of the target DNA sequences. The proposed strategy also shows excellent discrimination between the target DNA and the single-base mismatch sequences. The advantageous intrinsic sequence-independent property of exonuclease III over other sequence-dependent enzymes makes our new dual signal amplification system a general sensing platform for monitoring ultralow level of various types of target DNA sequences. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Neural Networks For Demodulation Of Phase-Modulated Signals

NASA Technical Reports Server (NTRS)

Altes, Richard A.

1995-01-01

Hopfield neural networks proposed for demodulating quadrature phase-shift-keyed (QPSK) signals carrying digital information. Networks solve nonlinear integral equations prior demodulation circuits cannot solve. Consists of set of N operational amplifiers connected in parallel, with weighted feedback from output terminal of each amplifier to input terminals of other amplifiers. Used to solve signal processing problems. Implemented as analog very-large-scale integrated circuit that achieves rapid convergence. Alternatively, implemented as digital simulation of such circuit. Also used to improve phase estimation performance over that of phase-locked loop.

Electrochemical processes and mechanistic aspects of field-effect sensors for biomolecules

PubMed Central

Huang, Weiguo; Diallo, Abdou Karim; Dailey, Jennifer L.; Besar, Kalpana

2017-01-01

Electronic biosensing is a leading technology for determining concentrations of biomolecules. In some cases, the presence of an analyte molecule induces a measured change in current flow, while in other cases, a new potential difference is established. In the particular case of a field effect biosensor, the potential difference is monitored as a change in conductance elsewhere in the device, such as across a film of an underlying semiconductor. Often, the mechanisms that lead to these responses are not specifically determined. Because improved understanding of these mechanisms will lead to improved performance, it is important to highlight those studies where various mechanistic possibilities are investigated. This review explores a range of possible mechanistic contributions to field-effect biosensor signals. First, we define the field-effect biosensor and the chemical interactions that lead to the field effect, followed by a section on theoretical and mechanistic background. We then discuss materials used in field-effect biosensors and approaches to improving signals from field-effect biosensors. We specifically cover the biomolecule interactions that produce local electric fields, structures and processes at interfaces between bioanalyte solutions and electronic materials, semiconductors used in biochemical sensors, dielectric layers used in top-gated sensors, and mechanisms for converting the surface voltage change to higher signal/noise outputs in circuits. PMID:29238595

Automated filtering of common-mode artifacts in multichannel physiological recordings.

PubMed

Kelly, John W; Siewiorek, Daniel P; Smailagic, Asim; Wang, Wei

2013-10-01

The removal of spatially correlated noise is an important step in processing multichannel recordings. Here, a technique termed the adaptive common average reference (ACAR) is presented as an effective and simple method for removing this noise. The ACAR is based on a combination of the well-known common average reference (CAR) and an adaptive noise canceling (ANC) filter. In a convergent process, the CAR provides a reference to an ANC filter, which in turn provides feedback to enhance the CAR. This method was effective on both simulated and real data, outperforming the standard CAR when the amplitude or polarity of the noise changes across channels. In many cases, the ACAR even outperformed independent component analysis. On 16 channels of simulated data, the ACAR was able to attenuate up to approximately 290 dB of noise and could improve signal quality if the original SNR was as high as 5 dB. With an original SNR of 0 dB, the ACAR improved signal quality with only two data channels and performance improved as the number of channels increased. It also performed well under many different conditions for the structure of the noise and signals. Analysis of contaminated electrocorticographic recordings further showed the effectiveness of the ACAR.

Automated Filtering of Common Mode Artifacts in Multi-Channel Physiological Recordings

PubMed Central

Kelly, John W.; Siewiorek, Daniel P.; Smailagic, Asim; Wang, Wei

2014-01-01

The removal of spatially correlated noise is an important step in processing multi-channel recordings. Here, a technique termed the adaptive common average reference (ACAR) is presented as an effective and simple method for removing this noise. The ACAR is based on a combination of the well-known common average reference (CAR) and an adaptive noise canceling (ANC) filter. In a convergent process, the CAR provides a reference to an ANC filter, which in turn provides feedback to enhance the CAR. This method was effective on both simulated and real data, outperforming the standard CAR when the amplitude or polarity of the noise changes across channels. In many cases the ACAR even outperformed independent component analysis (ICA). On 16 channels of simulated data the ACAR was able to attenuate up to approximately 290 dB of noise and could improve signal quality if the original SNR was as high as 5 dB. With an original SNR of 0 dB, the ACAR improved signal quality with only two data channels and performance improved as the number of channels increased. It also performed well under many different conditions for the structure of the noise and signals. Analysis of contaminated electrocorticographic (ECoG) recordings further showed the effectiveness of the ACAR. PMID:23708770

Electromagnetic Test-Facility characterization: an identification approach

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

Zicker, J.E.; Candy, J.V.

The response of an object subjected to high energy, transient electromagnetic (EM) fields sometimes called electromagnetic pulses (EMP), is an important issue in the survivability of electronic systems (e.g., aircraft), especially when the field has been generated by a high altitude nuclear burst. The characterization of transient response information is a matter of national concern. In this report we discuss techniques to: (1) improve signal processing at a test facility; and (2) parameterize a particular object response. First, we discuss the application of identification-based signal processing techniques to improve signal levels at the Lawrence Livermore National Laboratory (LLNL) EM Transientmore » Test Facility. We identify models of test equipment and then use these models to deconvolve the input/output sequences for the object under test. A parametric model of the object is identified from this data. The model can be used to extrapolate the response to these threat level EMP. Also discussed is the development of a facility simulator (EMSIM) useful for experimental design and calibration and a deconvolution algorithm (DECONV) useful for removing probe effects from the measured data.« less

Enhanced performance for differential detection in coherent Brillouin optical time-domain analysis sensors

NASA Astrophysics Data System (ADS)

Shao, Liyang; Zhang, Yunpeng; Li, Zonglei; Zhang, Zhiyong; Zou, Xihua; Luo, Bin; Pan, Wei; Yan, Lianshan

2016-11-01

Logarithmic detectors (LogDs) have been used in coherent Brillouin optical time-domain analysis (BOTDA) sensors to reduce the effect of phase fluctuation, demodulation complexities, and measurement time. However, because of the inherent properties of LogDs, a DC component at the level of hundreds of millivolts that prohibits high-gain signal amplification (SA) could be generated, resulting in unacceptable data acquisition (DAQ) inaccuracies and decoding errors in the process of prototype integration. By generating a reference light at a level similar to the probe light, differential detection can be applied to remove the DC component automatically using a differential amplifier before the DAQ process. Therefore, high-gain SA can be employed to reduce quantization errors. The signal-to-noise ratio of the weak Brillouin gain signal is improved from ˜11.5 to ˜21.8 dB. A BOTDA prototype is implemented based on the proposed scheme. The experimental results show that the measurement accuracy of the Brillouin frequency shift (BFS) is improved from ±1.9 to ±0.8 MHz at the end of a 40-km sensing fiber.

Split-spectrum processing technique for SNR enhancement of ultrasonic guided wave.

PubMed

Pedram, Seyed Kamran; Fateri, Sina; Gan, Lu; Haig, Alex; Thornicroft, Keith

2018-02-01

Ultrasonic guided wave (UGW) systems are broadly used in several branches of industry where the structural integrity is of concern. In those systems, signal interpretation can often be challenging due to the multi-modal and dispersive propagation of UGWs. This results in degradation of the signals in terms of signal-to-noise ratio (SNR) and spatial resolution. This paper employs the split-spectrum processing (SSP) technique in order to enhance the SNR and spatial resolution of UGW signals using the optimized filter bank parameters in real time scenario for pipe inspection. SSP technique has already been developed for other applications such as conventional ultrasonic testing for SNR enhancement. In this work, an investigation is provided to clarify the sensitivity of SSP performance to the filter bank parameter values for UGWs such as processing bandwidth, filter bandwidth, filter separation and a number of filters. As a result, the optimum values are estimated to significantly improve the SNR and spatial resolution of UGWs. The proposed method is synthetically and experimentally compared with conventional approaches employing different SSP recombination algorithms. The Polarity Thresholding (PT) and PT with Minimization (PTM) algorithms were found to be the best recombination algorithms. They substantially improved the SNR up to 36.9dB and 38.9dB respectively. The outcome of the work presented in this paper paves the way to enhance the reliability of UGW inspections. Copyright © 2017 Elsevier B.V. All rights reserved.

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

The effect of Chinese Jinzhida recipe on the hippocampus in a rat model of diabetes-associated cognitive decline

PubMed Central

2013-01-01

Background To investigate the effects of treatment with Multi component Chinese Medicine Jinzhida (JZD) on behavioral deficits in diabetes-associated cognitive decline (DACD) rats and verify our hypothesis that JZD treatment improves cognitive function by suppressing the endoplasmic reticulum stress (ERS) and improving insulin signaling transduction in the rats’ hippocampus. Methods A rat model of type 2 diabetes mellitus (T2DM) was established using high fat diet and streptozotocin (30 mg/kg, ip). Insulin sensitivity was evaluated by the oral glucose tolerance test and the insulin tolerance test. After 7 weeks, the T2DM rats were treated with JZD. The step-down test and Morris water maze were used to evaluate behavior in T2DM rats after 5 weeks of treatment with JZD. Levels of phosphorylated proteins involved in the ERS and in insulin signaling transduction pathways were assessed by Western blot for T2DM rats’ hippocampus. Results Compared to healthy control rats, T2DM rats initially showed insulin resistance and had declines in acquisition and retrieval processes in the step-down test and in spatial memory in the Morris water maze after 12 weeks. Performance on both the step-down test and Morris water maze tasks improved after JZD treatment. In T2DM rats, the ERS was activated, and then inhibited the insulin signal transduction pathways through the Jun NH2-terminal kinases (JNK) mediated. JZD treatment suppressed the ERS, increased insulin signal transduction, and improved insulin resistance in the rats’ hippocampus. Conclusions Treatment with JZD improved cognitive function in the T2DM rat model. The possible mechanism for DACD was related with ERS inducing the insulin signal transduction dysfunction in T2DM rats’ hippocampus. The JZD could reduce ERS and improve insulin signal transduction and insulin resistance in T2DM rats’ hippocampus and as a result improved the cognitive function. PMID:23829668

An Application of Reassigned Time-Frequency Representations for Seismic Noise/Signal Decomposition

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Langston, C. A.

2016-12-01

Seismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. An automatic method for seismic noise/signal decomposition is presented based upon an enhanced time-frequency representation. Synchrosqueezing is a time-frequency reassignment method aimed at sharpening a time-frequency picture. Noise can be distinguished from the signal and suppressed more easily in this reassigned domain. The threshold level is estimated using a general cross validation approach that does not rely on any prior knowledge about the noise level. Efficiency of thresholding has been improved by adding a pre-processing step based on higher order statistics and a post-processing step based on adaptive hard-thresholding. In doing so, both accuracy and speed of the denoising have been improved compared to our previous algorithms (Mousavi and Langston, 2016a, 2016b; Mousavi et al., 2016). The proposed algorithm can either kill the noise (either white or colored) and keep the signal or kill the signal and keep the noise. Hence, It can be used in either normal denoising applications or in ambient noise studies. Application of the proposed method on synthetic and real seismic data shows the effectiveness of the method for denoising/designaling of local microseismic, and ocean bottom seismic data. References: Mousavi, S.M., C. A. Langston., and S. P. Horton (2016), Automatic Microseismic Denoising and Onset Detection Using the Synchrosqueezed-Continuous Wavelet Transform. Geophysics. 81, V341-V355, doi: 10.1190/GEO2015-0598.1. Mousavi, S.M., and C. A. Langston (2016a), Hybrid Seismic Denoising Using Higher-Order Statistics and Improved Wavelet Block Thresholding. Bull. Seismol. Soc. Am., 106, doi: 10.1785/0120150345. Mousavi, S.M., and C.A. Langston (2016b), Adaptive noise estimation and suppression for improving microseismic event detection, Journal of Applied Geophysics., doi: http://dx.doi.org/10.1016/j.jappgeo.2016.06.008.

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

Adaptive EMG noise reduction in ECG signals using noise level approximation

NASA Astrophysics Data System (ADS)

Marouf, Mohamed; Saranovac, Lazar

2017-12-01

In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.

Identifying and quantifying main components of physiological noise in functional near infrared spectroscopy on the prefrontal cortex.

PubMed

Kirilina, Evgeniya; Yu, Na; Jelzow, Alexander; Wabnitz, Heidrun; Jacobs, Arthur M; Tachtsidis, Ilias

2013-01-01

Functional Near-Infrared Spectroscopy (fNIRS) is a promising method to study functional organization of the prefrontal cortex. However, in order to realize the high potential of fNIRS, effective discrimination between physiological noise originating from forehead skin haemodynamic and cerebral signals is required. Main sources of physiological noise are global and local blood flow regulation processes on multiple time scales. The goal of the present study was to identify the main physiological noise contributions in fNIRS forehead signals and to develop a method for physiological de-noising of fNIRS data. To achieve this goal we combined concurrent time-domain fNIRS and peripheral physiology recordings with wavelet coherence analysis (WCA). Depth selectivity was achieved by analyzing moments of photon time-of-flight distributions provided by time-domain fNIRS. Simultaneously, mean arterial blood pressure (MAP), heart rate (HR), and skin blood flow (SBF) on the forehead were recorded. WCA was employed to quantify the impact of physiological processes on fNIRS signals separately for different time scales. We identified three main processes contributing to physiological noise in fNIRS signals on the forehead. The first process with the period of about 3 s is induced by respiration. The second process is highly correlated with time lagged MAP and HR fluctuations with a period of about 10 s often referred as Mayer waves. The third process is local regulation of the facial SBF time locked to the task-evoked fNIRS signals. All processes affect oxygenated haemoglobin concentration more strongly than that of deoxygenated haemoglobin. Based on these results we developed a set of physiological regressors, which were used for physiological de-noising of fNIRS signals. Our results demonstrate that proposed de-noising method can significantly improve the sensitivity of fNIRS to cerebral signals.

Tevatron beam position monitor upgrade

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

Wolbers, Stephen; Banerjee, B.; Barker, B.

2005-05-01

The Tevatron Beam Position Monitor (BPM) readout electronics and software have been upgraded to improve measurement precision, functionality and reliability. The original system, designed and built in the early 1980's, became inadequate for current and future operations of the Tevatron. The upgraded system consists of 960 channels of new electronics to process analog signals from 240 BPMs, new front-end software, new online and controls software, and modified applications to take advantage of the improved measurements and support the new functionality. The new system reads signals from both ends of the existing directional stripline pickups to provide simultaneous proton and antiprotonmore » position measurements. Measurements using the new system are presented that demonstrate its improved resolution and overall performance.« less

A novel approach for the elimination of artefacts from EEG signals employing an improved Artificial Immune System algorithm

NASA Astrophysics Data System (ADS)

Suja Priyadharsini, S.; Edward Rajan, S.; Femilin Sheniha, S.

2016-03-01

Electroencephalogram (EEG) is the recording of electrical activities of the brain. It is contaminated by other biological signals, such as cardiac signal (electrocardiogram), signals generated by eye movement/eye blinks (electrooculogram) and muscular artefact signal (electromyogram), called artefacts. Optimisation is an important tool for solving many real-world problems. In the proposed work, artefact removal, based on the adaptive neuro-fuzzy inference system (ANFIS) is employed, by optimising the parameters of ANFIS. Artificial Immune System (AIS) algorithm is used to optimise the parameters of ANFIS (ANFIS-AIS). Implementation results depict that ANFIS-AIS is effective in removing artefacts from EEG signal than ANFIS. Furthermore, in the proposed work, improved AIS (IAIS) is developed by including suitable selection processes in the AIS algorithm. The performance of the proposed method IAIS is compared with AIS and with genetic algorithm (GA). Measures such as signal-to-noise ratio, mean square error (MSE) value, correlation coefficient, power spectrum density plot and convergence time are used for analysing the performance of the proposed method. From the results, it is found that the IAIS algorithm converges faster than the AIS and performs better than the AIS and GA. Hence, IAIS tuned ANFIS (ANFIS-IAIS) is effective in removing artefacts from EEG signals.

High-Frequency Spin-Based Devices for Nanoscale Signal Processing

DTIC Science & Technology

2009-01-20

feedback on the devices in order to improve their spectral properties . Deliverable: Microwave signals without an Applied Field. We have successfully...additionally have the advantage of higher operating frequencies than the more conventional devices based on NiFe alloys. By combining several of...Output from a Co/Ni based STNO. Corresponds to approximately 20 nW, about 10 times larger than typical NiFe .device. 6 High-Frequency Spin-Based

Extraction of fetal ECG signal by an improved method using extended Kalman smoother framework from single channel abdominal ECG signal.

PubMed

Panigrahy, D; Sahu, P K

2017-03-01

This paper proposes a five-stage based methodology to extract the fetal electrocardiogram (FECG) from the single channel abdominal ECG using differential evolution (DE) algorithm, extended Kalman smoother (EKS) and adaptive neuro fuzzy inference system (ANFIS) framework. The heart rate of the fetus can easily be detected after estimation of the fetal ECG signal. The abdominal ECG signal contains fetal ECG signal, maternal ECG component, and noise. To estimate the fetal ECG signal from the abdominal ECG signal, removal of the noise and the maternal ECG component presented in it is necessary. The pre-processing stage is used to remove the noise from the abdominal ECG signal. The EKS framework is used to estimate the maternal ECG signal from the abdominal ECG signal. The optimized parameters of the maternal ECG components are required to develop the state and measurement equation of the EKS framework. These optimized maternal ECG parameters are selected by the differential evolution algorithm. The relationship between the maternal ECG signal and the available maternal ECG component in the abdominal ECG signal is nonlinear. To estimate the actual maternal ECG component present in the abdominal ECG signal and also to recognize this nonlinear relationship the ANFIS is used. Inputs to the ANFIS framework are the output of EKS and the pre-processed abdominal ECG signal. The fetal ECG signal is computed by subtracting the output of ANFIS from the pre-processed abdominal ECG signal. Non-invasive fetal ECG database and set A of 2013 physionet/computing in cardiology challenge database (PCDB) are used for validation of the proposed methodology. The proposed methodology shows a sensitivity of 94.21%, accuracy of 90.66%, and positive predictive value of 96.05% from the non-invasive fetal ECG database. The proposed methodology also shows a sensitivity of 91.47%, accuracy of 84.89%, and positive predictive value of 92.18% from the set A of PCDB.

Reactive Oxygen Species Generation-Scavenging and Signaling during Plant-Arbuscular Mycorrhizal and Piriformospora indica Interaction under Stress Condition.

PubMed

Nath, Manoj; Bhatt, Deepesh; Prasad, Ram; Gill, Sarvajeet S; Anjum, Naser A; Tuteja, Narendra

2016-01-01

A defined balance between the generation and scavenging of reactive oxygen species (ROS) is essential to utilize ROS as an adaptive defense response of plants under biotic and abiotic stress conditions. Moreover, ROS are not only a major determinant of stress response but also act as signaling molecule that regulates various cellular processes including plant-microbe interaction. In particular, rhizosphere constitutes the biologically dynamic zone for plant-microbe interactions which forms a mutual link leading to reciprocal signaling in both the partners. Among plant-microbe interactions, symbiotic associations of arbuscular mycorrhizal fungi (AMF) and arbuscular mycorrhizal-like fungus especially Piriformospora indica with plants are well known to improve plant growth by alleviating the stress-impacts and consequently enhance the plant fitness. AMF and P. indica colonization mainly enhances ROS-metabolism, maintains ROS-homeostasis, and thereby averts higher ROS-level accrued inhibition in plant cellular processes and plant growth and survival under stressful environments. This article summarizes the major outcomes of the recent reports on the ROS-generation, scavenging and signaling in biotic-abiotic stressed plants with AMF and P. indica colonization. Overall, a detailed exploration of ROS-signature kinetics during plant-AMF/ P. indica interaction can help in designing innovative strategies for improving plant health and productivity under stress conditions.

Optical Vector Receiver Operating Near the Quantum Limit

NASA Astrophysics Data System (ADS)

Vilnrotter, V. A.; Lau, C.-W.

2005-05-01

An optical receiver concept for binary signals with performance approaching the quantum limit at low average-signal energies is developed and analyzed. A conditionally nulling receiver that reaches the quantum limit in the absence of background photons has been devised by Dolinar. However, this receiver requires ideal optical combining and complicated real-time shaping of the local field; hence, it tends to be difficult to implement at high data rates. A simpler nulling receiver that approaches the quantum limit without complex optical processing, suitable for high-rate operation, had been suggested earlier by Kennedy. Here we formulate a vector receiver concept that incorporates the Kennedy receiver with a physical beamsplitter, but it also utilizes the reflected signal component to improve signal detection. It is found that augmenting the Kennedy receiver with classical coherent detection at the auxiliary beamsplitter output, and optimally processing the vector observations, always improves on the performance of the Kennedy receiver alone, significantly so at low average-photon rates. This is precisely the region of operation where modern codes approach channel capacity. It is also shown that the addition of background radiation has little effect on the performance of the coherent receiver component, suggesting a viable approach for near-quantum-limited performance in high background environments.

Signal analysis and radioholographic methods for airborne radio occultations

NASA Astrophysics Data System (ADS)

Wang, Kuo-Nung

Global Positioning System (GPS) radio occultation (RO) is an atmospheric sounding technique utilizing the change in propagation direction and delay of the GPS signal to measure refractivity, which provides information on temperature and humidity. The GPS-RO technique is now operational on several Low Earth Orbiting (LEO) satellite missions. Nevertheless, when observing localized transient events, such as tropical storms, current LEO satellite systems cannot provide sufficiently high temporal and spatial resolution soundings. An airborne RO (ARO) system has therefore been developed for localized GPS-RO campaigns. The open-loop (OL) tracking in post-processing is used to cross-correlates the received Global Navigation Satellite System (GNSS) signal with an internally generated local carrier signal predicted from a Doppler model and extract the atmospheric refractivity information. OL tracking also allows robust processing of rising GPS signals using backward tracking, which will double the observed occultation event numbers. RO signals in the lower troposphere are adversely affected by rapid phase accelerations and severe signal power fading, however. The negative bias caused by low signal-to-noise ratio (SNR) and multipath ray propagation limits the depth of tracking in the atmosphere. Therefore, we developed a model relating the SNR to the variance in the residual phase of the observed signal produced from OL tracking, and its applicability to airborne data is demonstrated. We then apply this model to set a threshold on refractivity retrieval, based upon the cumulative unwrapping error bias, to determine the altitude limit for reliable signal tracking. To enhance the SNR and decrease the unwrapping error rate, the CIRA-Q climatological model and signal residual phase pre-filtering are utilized to process the ARO residual phase. This more accurately modeled phase and less noisy received signal are shown to greatly reduce the bias caused by unwrapping error at lower altitude. On the other hand, to process the superimposed signal in the lower troposphere with its highly variable moisture distribution, Radio-Holographic (RH) methods such as Phase Matching (PM) have been adapted for ARO platforms to untangle the bending angle of each signal path. Under the assumption of spherically symmetric atmosphere, ARO PM can identify different subsignals using the Method of the Stationary Phase (MSP) and determine the arrival angle for each impact parameter. As a result, each subsignal can be distinguished and its corresponding bending angle can be retrieved without producing a negative bias. The refractivity retrieval results using ARO PM are compared to those using the traditional Geometrical Optics (GO) method. The improvements are shown and discussed in the dissertation. We applied these new methods to the received ARO data collected by the GNSS instrument system for multistatic and occultation sensing (GISMOS) in the 2010 PREDepression Investigation of Cloud systems (PREDICT) campaign. A data set of 5 research flights with 57 occultation events during the formation stage of the Hurricane Karl are processed and analyzed. In this research, the refractivity fractional difference with ERA-I model can be maintained at an average 2% above a height of 2km with a climatological model and ARO PM. Compared to the traditional geometrical optics (GO) method without climatological method assistance, the new ARO processing can effectively decrease the refractivity negative bias and significantly improve the retrieval depth of ARO.

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

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.

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

PubMed Central

2018-01-01

Objective To study the performance of multifocal-visual-evoked-potential (mfVEP) signals filtered using empirical mode decomposition (EMD) in discriminating, based on amplitude, between control and multiple sclerosis (MS) patient groups, and to reduce variability in interocular latency in control subjects. Methods MfVEP signals were obtained from controls, clinically definitive MS and MS-risk progression patients (radiologically isolated syndrome (RIS) and clinically isolated syndrome (CIS)). The conventional method of processing mfVEPs consists of using a 1–35 Hz bandpass frequency filter (XDFT). The EMD algorithm was used to decompose the XDFT signals into several intrinsic mode functions (IMFs). This signal processing was assessed by computing the amplitudes and latencies of the XDFT and IMF signals (XEMD). The amplitudes from the full visual field and from ring 5 (9.8–15° eccentricity) were studied. The discrimination index was calculated between controls and patients. Interocular latency values were computed from the XDFT and XEMD signals in a control database to study variability. Results Using the amplitude of the mfVEP signals filtered with EMD (XEMD) obtains higher discrimination index values than the conventional method when control, MS-risk progression (RIS and CIS) and MS subjects are studied. The lowest variability in interocular latency computations from the control patient database was obtained by comparing the XEMD signals with the XDFT signals. Even better results (amplitude discrimination and latency variability) were obtained in ring 5 (9.8–15° eccentricity of the visual field). Conclusions Filtering mfVEP signals using the EMD algorithm will result in better identification of subjects at risk of developing MS and better accuracy in latency studies. This could be applied to assess visual cortex activity in MS diagnosis and evolution studies. PMID:29677200

Estimation of source location and ground impedance using a hybrid multiple signal classification and Levenberg-Marquardt approach

NASA Astrophysics Data System (ADS)

Tam, Kai-Chung; Lau, Siu-Kit; Tang, Shiu-Keung

2016-07-01

A microphone array signal processing method for locating a stationary point source over a locally reactive ground and for estimating ground impedance is examined in detail in the present study. A non-linear least square approach using the Levenberg-Marquardt method is proposed to overcome the problem of unknown ground impedance. The multiple signal classification method (MUSIC) is used to give the initial estimation of the source location, while the technique of forward backward spatial smoothing is adopted as a pre-processer of the source localization to minimize the effects of source coherence. The accuracy and robustness of the proposed signal processing method are examined. Results show that source localization in the horizontal direction by MUSIC is satisfactory. However, source coherence reduces drastically the accuracy in estimating the source height. The further application of Levenberg-Marquardt method with the results from MUSIC as the initial inputs improves significantly the accuracy of source height estimation. The present proposed method provides effective and robust estimation of the ground surface impedance.

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).

PKD signaling and pancreatitis

PubMed Central

Yuan, Jingzhen; Pandol, Stephen J.

2016-01-01

Background Acute pancreatitis is a serious medical disorder with no current therapies directed to the molecular pathogenesis of the disorder. Inflammation, inappropriate intracellular activation of digestive enzymes, and parenchymal acinar cell death by necrosis are the critical pathophysiologic processes of acute pancreatitis. Thus, it is necessary to elucidate the key molecular signals that mediate these pathobiologic processes and develop new therapeutic strategies to attenuate the appropriate signaling pathways in order to improve outcomes for this disease. A novel serine/threonine protein kinase D (PKD) family has emerged as key participants in signal transduction, and this family is increasingly being implicated in the regulation of multiple cellular functions and diseases. Methods This review summarizes recent findings of our group and others regarding the signaling pathway and the biological roles of the PKD family in pancreatic acinar cells. In particular, we highlight our studies of the functions of PKD in several key pathobiologic processes associated with acute pancreatitis in experimental models. Results Our findings reveal that PKD signaling is required for NF-κB activation/inflammation, intracellular zymogen activation, and acinar cell necrosis in rodent experimental pancreatitis. Novel small-molecule PKD inhibitors attenuate the severity of pancreatitis in both in vitro and in vivo experimental models. Further, this review emphasizes our latest advances in the therapeutic application of PKD inhibitors to experimental pancreatitis after the initiation of pancreatitis. Conclusions These novel findings suggest that PKD signaling is a necessary modulator in key initiating pathobiologic processes of pancreatitis, and that it constitutes a novel therapeutic target for treatments of this disorder. PMID:26879861

Affective e-Learning: Using "Emotional" Data to Improve Learning in Pervasive Learning Environment

ERIC Educational Resources Information Center

Shen, Liping; Wang, Minjuan; Shen, Ruimin

2009-01-01

Using emotion detection technologies from biophysical signals, this study explored how emotion evolves during learning process and how emotion feedback could be used to improve learning experiences. This article also described a cutting-edge pervasive e-Learning platform used in a Shanghai online college and proposed an affective e-Learning model,…

High-speed digital signal normalization for feature identification

NASA Technical Reports Server (NTRS)

Ortiz, J. A.; Meredith, B. D.

1983-01-01

A design approach for high speed normalization of digital signals was developed. A reciprocal look up table technique is employed, where a digital value is mapped to its reciprocal via a high speed memory. This reciprocal is then multiplied with an input signal to obtain the normalized result. Normalization improves considerably the accuracy of certain feature identification algorithms. By using the concept of pipelining the multispectral sensor data processing rate is limited only by the speed of the multiplier. The breadboard system was found to operate at an execution rate of five million normalizations per second. This design features high precision, a reduced hardware complexity, high flexibility, and expandability which are very important considerations for spaceborne applications. It also accomplishes a high speed normalization rate essential for real time data processing.

High resolution signal-processing method for extrinsic Fabry-Perot interferometric sensors

NASA Astrophysics Data System (ADS)

Xie, Jiehui; Wang, Fuyin; Pan, Yao; Wang, Junjie; Hu, Zhengliang; Hu, Yongming

2015-03-01

In this paper, a signal-processing method for optical fiber extrinsic Fabry-Perot interferometric sensors is presented. It achieves both high resolution and absolute measurement of the dynamic change of cavity length with low sampling points in wavelength domain. In order to improve the demodulation accuracy, the reflected interference spectrum is cleared by Discrete Wavelet Transform and adjusted by the Hilbert transform. Then the cavity length is interrogated by the cross correlation algorithm. The continuous tests show the resolution of cavity length is only 36.7 pm. Moreover, the corresponding resolution of cavity length is only 1 pm on the low frequency range below 420 Hz, and the corresponding power spectrum shows the possibility of detecting the ultra-low frequency signals based on spectra detection.

14- by 22-Foot Subsonic Tunnel Laser Velocimeter Upgrade

NASA Technical Reports Server (NTRS)

Meyers, James F.; Lee, Joseph W.; Cavone, Angelo A.; Fletcher, Mark T.

2012-01-01

A long-focal length laser velocimeter constructed in the early 1980's was upgraded using current technology to improve usability, reliability and future serviceability. The original, free-space optics were replaced with a state-of-the-art fiber-optic subsystem which allowed most of the optics, including the laser, to be remote from the harsh tunnel environment. General purpose high-speed digitizers were incorporated in a standard modular data acquisition system, along with custom signal processing software executed on a desktop computer, served as the replacement for the signal processors. The resulting system increased optical sensitivity with real-time signal/data processing that produced measurement precisions exceeding those of the original system. Monte Carlo simulations, along with laboratory and wind tunnel investigations were used to determine system characteristics and measurement precision.

The Modernization of a Long-Focal Length Fringe-Type Laser Velocimeter

NASA Technical Reports Server (NTRS)

Meyers, James F.; Lee, Joseph W.; Cavone, Angelo A.; Fletcher, Mark T.

2012-01-01

A long-focal length laser velocimeter constructed in the early 1980's was upgraded using current technology to improve usability, reliability and future serviceability. The original, free-space optics were replaced with a state-of-the-art fiber-optic subsystem which allowed most of the optics, including the laser, to be remote from the harsh tunnel environment. General purpose high-speed digitizers were incorporated in a standard modular data acquisition system, along with custom signal processing software executed on a desktop computer, served as the replacement for the signal processors. The resulting system increased optical sensitivity with real-time signal/data processing that produced measurement precisions exceeding those of the original system. Monte Carlo simulations, along with laboratory and wind tunnel investigations were used to determine system characteristics and measurement precision.

Optical amplifiers for coherent lidar

NASA Technical Reports Server (NTRS)

Fork, Richard

1996-01-01

We examine application of optical amplification to coherent lidar for the case of a weak return signal (a number of quanta of the return optical field close to unity). We consider the option that has been explored to date, namely, incorporation of an optical amplifier operated in a linear manner located after reception of the signal and immediately prior to heterodyning and photodetection. We also consider alternative strategies where the coherent interaction, the nonlinear processes, and the amplification are not necessarily constrained to occur in the manner investigated to date. We include the complications that occur because of mechanisms that occur at the level of a few, or one, quantum excitation. Two factors combine in the work to date that limit the value of the approach. These are: (1) the weak signal tends to require operation of the amplifier in the linear regime where the important advantages of nonlinear optical processing are not accessed, (2) the linear optical amplifier has a -3dB noise figure (SN(out)/SN(in)) that necessarily degrades the signal. Some improvement is gained because the gain provided by the optical amplifier can be used to overcome losses in the heterodyned process and photodetection. The result, however, is that introduction of an optical amplifier in a well optimized coherent lidar system results in, at best, a modest improvement in signal to noise. Some improvement may also be realized on incorporating more optical components in a coherent lidar system for purely practical reasons. For example, more compact, lighter weight, components, more robust alignment, or more rapid processing may be gained. We further find that there remain a number of potentially valuable, but unexplored options offered both by the rapidly expanding base of optical technology and the recent investigation of novel nonlinear coherent interference phenomena occurring at the single quantum excitation level. Key findings are: (1) insertion of linear optical amplifiers in well optimized conventional lidar systems offers modest improvements, at best, (2) the practical advantages of optical amplifiers, especially fiber amplifiers, such as ease of alignment, compactness, efficiency, lightweight, etc., warrant further investigation for coherent lidar, (3) the possibility of more fully optical lidar systems should be explored, (4) advantages gained by use of coherent interference of optical fields at the level of one, or a few, signal quanta should be explored, (5) amplification without inversion, population trapping, and use of electromagnetic induced transparency warrant investigation in connection with coherent lidar, (6) these new findings are probably more applicable to earth related NASA work, although applications to deep space should not be excluded, and (7) our own work in the Ultrafast Laboratory at UAH along some of the above lines of investigation, may be useful.

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

NASA Technical Reports Server (NTRS)

Jong, Jen-Yi

1997-01-01

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Laser Welding Process Monitoring Systems: Advanced Signal Analysis for Quality Assurance

NASA Astrophysics Data System (ADS)

D'Angelo, Giuseppe

Laser material processing today is widely used in industry. Especially laser welding became one of the key-technologies, e. g., for the automotive sector. This is due to the improvement and development of new laser sources and the increasing knowledge gained at countless scientific research projects. Nevertheless, it is still not possible to use the full potential of this technology. Therefore, the introduction and application of quality-assuring systems is required. For a long time, the statement "the best sensor is no sensor" was often heard. Today, a change of paradigm can be observed. On the one hand, ISO 9000 and other by law enforced regulations have led to the understanding that quality monitoring is an essential tool in modern manufacturing and necessary in order to keep production results in deterministic boundaries. On the other hand, rising quality requirements not only set higher and higher requirements for the process technology but also demand qualityassurance measures which ensure the reliable recognition of process faults. As a result, there is a need for reliable online detection and correction of welding faults by means of an in-process monitoring. The chapter describes an advanced signals analysis technique to extract information from signals detected, during the laser welding process, by optical sensors. The technique is based on the method of reassignment which was first applied to the spectrogram by Kodera, Gendrin and de Villedary22,23 and later generalized to any bilinear time-frequency representation by Auger and Flandrin.24 Key to the method is a nonlinear convolution where the value of the convolution is not placed at the center of the convolution kernel but rather reassigned to the center of mass of the function within the kernel. The resulting reassigned representation yields significantly improved components localization. We compare the proposed time-frequency distributions by analyzing signals detected during the laser welding of tailored blanks, demonstrating the advantages of the reassigned representation, giving practical applicability to the proposed method.

Optimizing Waveform Maximum Determination for Specular Point Tracking in Airborne GNSS-R.

PubMed

Motte, Erwan; Zribi, Mehrez

2017-08-16

Airborne GNSS-R campaigns are crucial to the understanding of signal interactions with the Earth's surface. As a consequence of the specific geometric configurations arising during measurements from aircraft, the reflected signals can be difficult to interpret under certain conditions like over strongly attenuating media such as forests, or when the reflected signal is contaminated by the direct signal. For these reasons, there are many cases where the reflectivity is overestimated, or a portion of the dataset has to be flagged as unusable. In this study we present techniques that have been developed to optimize the processing of airborne GNSS-R data, with the goal of improving its accuracy and robustness under non-optimal conditions. This approach is based on the detailed analysis of data produced by the instrument GLORI, which was recorded during an airborne campaign in the south west of France in June 2015. Our technique relies on the improved determination of reflected waveform peaks in the delay dimension, which is related to the loci of the signals contributed by the zone surrounding the specular point. It is shown that when developing techniques for the correct localization of waveform maxima under conditions of surfaces of low reflectivity, and/or contamination from the direct signal, it is possible to correct and extract values corresponding to the real reflectivity of the zone in the neighborhood of the specular point. This algorithm was applied to a reanalysis of the complete campaign dataset, following which the accuracy and sensitivity improved, and the usability of the dataset was improved by 30%.

Differential pulse amplitude modulation for multiple-input single-output OWVLC

NASA Astrophysics Data System (ADS)

Yang, S. H.; Kwon, D. H.; Kim, S. J.; Son, Y. H.; Han, S. K.

2015-01-01

White light-emitting diodes (LEDs) are widely used for lighting due to their energy efficiency, eco-friendly, and small size than previously light sources such as incandescent, fluorescent bulbs and so on. Optical wireless visible light communication (OWVLC) based on LED merges lighting and communications in applications such as indoor lighting, traffic signals, vehicles, and underwater communications because LED can be easily modulated. However, physical bandwidth of LED is limited about several MHz by slow time constant of the phosphor and characteristics of device. Therefore, using the simplest modulation format which is non-return-zero on-off-keying (NRZ-OOK), the data rate reaches only to dozens Mbit/s. Thus, to improve the transmission capacity, optical filtering and pre-, post-equalizer are adapted. Also, high-speed wireless connectivity is implemented using spectrally efficient modulation methods: orthogonal frequency division multiplexing (OFDM) or discrete multi-tone (DMT). However, these modulation methods need additional digital signal processing such as FFT and IFFT, thus complexity of transmitter and receiver is increasing. To reduce the complexity of transmitter and receiver, we proposed a novel modulation scheme which is named differential pulse amplitude modulation. The proposed modulation scheme transmits different NRZ-OOK signals with same amplitude and unit time delay using each LED chip, respectively. The `N' parallel signals from LEDs are overlapped and directly detected at optical receiver. Received signal is demodulated by power difference between unit time slots. The proposed scheme can overcome the bandwidth limitation of LEDs and data rate can be improved according to number of LEDs without complex digital signal processing.

Research to Operations of Ionospheric Scintillation Detection and Forecasting

NASA Astrophysics Data System (ADS)

Jones, J.; Scro, K.; Payne, D.; Ruhge, R.; Erickson, B.; Andorka, S.; Ludwig, C.; Karmann, J.; Ebelhar, D.

Ionospheric Scintillation refers to random fluctuations in phase and amplitude of electromagnetic waves caused by a rapidly varying refractive index due to turbulent features in the ionosphere. Scintillation of transionospheric UHF and L-Band radio frequency signals is particularly troublesome since this phenomenon can lead to degradation of signal strength and integrity that can negatively impact satellite communications and navigation, radar, or radio signals from other systems that traverse or interact with the ionosphere. Although ionospheric scintillation occurs in both the equatorial and polar regions of the Earth, the focus of this modeling effort is on equatorial scintillation. The ionospheric scintillation model is data-driven in a sense that scintillation observations are used to perform detection and characterization of scintillation structures. These structures are then propagated to future times using drift and decay models to represent the natural evolution of ionospheric scintillation. The impact on radio signals is also determined by the model and represented in graphical format to the user. A frequency scaling algorithm allows for impact analysis on frequencies other than the observation frequencies. The project began with lab-grade software and through a tailored Agile development process, deployed operational-grade code to a DoD operational center. The Agile development process promotes adaptive promote adaptive planning, evolutionary development, early delivery, continuous improvement, regular collaboration with the customer, and encourage rapid and flexible response to customer-driven changes. The Agile philosophy values individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a rigid plan. The end result was an operational capability that met customer expectations. Details of the model and the process of operational integration are discussed as well as lessons learned to improve performance on future projects.

Decodability of Reward Learning Signals Predicts Mood Fluctuations.

PubMed

Eldar, Eran; Roth, Charlotte; Dayan, Peter; Dolan, Raymond J

2018-05-07

Our mood often fluctuates without warning. Recent accounts propose that these fluctuations might be preceded by changes in how we process reward. According to this view, the degree to which reward improves our mood reflects not only characteristics of the reward itself (e.g., its magnitude) but also how receptive to reward we happen to be. Differences in receptivity to reward have been suggested to play an important role in the emergence of mood episodes in psychiatric disorders [1-16]. However, despite substantial theory, the relationship between reward processing and daily fluctuations of mood has yet to be tested directly. In particular, it is unclear whether the extent to which people respond to reward changes from day to day and whether such changes are followed by corresponding shifts in mood. Here, we use a novel mobile-phone platform with dense data sampling and wearable heart-rate and electroencephalographic sensors to examine mood and reward processing over an extended period of one week. Subjects regularly performed a trial-and-error choice task in which different choices were probabilistically rewarded. Subjects' choices revealed two complementary learning processes, one fast and one slow. Reward prediction errors [17, 18] indicative of these two processes were decodable from subjects' physiological responses. Strikingly, more accurate decodability of prediction-error signals reflective of the fast process predicted improvement in subjects' mood several hours later, whereas more accurate decodability of the slow process' signals predicted better mood a whole day later. We conclude that real-life mood fluctuations follow changes in responsivity to reward at multiple timescales. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

MULTI-CHANNEL PULSE HEIGHT ANALYZER

DOEpatents

Boyer, K.; Johnstone, C.W.

1958-11-25

An improved multi-channel pulse height analyzer of the type where the device translates the amplitude of each pulse into a time duration electrical quantity which is utilized to control the length of a train of pulses forwarded to a scaler is described. The final state of the scaler for any one train of pulses selects the appropriate channel in a magnetic memory in which an additional count of one is placed. The improvement consists of a storage feature for storing a signal pulse so that in many instances when two signal pulses occur in rapid succession, the second pulse is preserved and processed at a later time.

The technology on noise reduction of the APD detection circuit

NASA Astrophysics Data System (ADS)

Wu, Xue-ying; Zheng, Yong-chao; Cui, Jian-yong

2013-09-01

The laser pulse detection is widely used in the field of laser range finders, laser communications, laser radar, laser Identification Friend or Foe, et al, for the laser pulse detection has the advantage of high accuracy, high sensitivity and strong anti-interference. The avalanche photodiodes (APD) has the advantage of high quantum efficiency, high response speed and huge gain. The APD is particularly suitable for weak signal detection. The technology that APD acts as the photodetector for weak signal reception and amplification is widely used in laser pulse detection. The APD will convert the laser signal to weak electrical signal. The weak signal is amplified, processed and exported by the circuit. In the circuit design, the optimal signal detection is one key point in photoelectric detection system. The issue discusses how to reduce the noise of the photoelectric signal detection circuit and how to improve the signal-to-noise ratio, related analysis and practice included. The essay analyzes the mathematical model of the signal-to-noise ratio for photoelectric conversion and the noise of the APD photoelectric detection system. By analysis the bandwidth of the detection system is determined, and the circuit devices are selected that match the APD. In the circuit design separated devices with low noise are combined with integrated operational amplifier for the purpose of noise reduction. The methods can effectively suppress the noise, and improve the detection sensitivity.

Proposal and performance analysis on the PDM microwave photonic link for the mm-wave signal with hybrid QAM-MPPM-RZ modulation

NASA Astrophysics Data System (ADS)

Tian, Bo; Zhang, Qi; Ma, Jianxin; Tao, Ying; Shen, Yufei; Wang, Yang; Zhang, Geng; Zhou, Wenmao; Zhao, Yi; Pan, Xiaolong

2018-07-01

A polarization division multiplexed (PDM) microwave photonic link for the millimeter (MM)-wave signal with hybrid modulation scheme is proposed in this paper, which is based on the combination of quadrature amplitude modulation, multi-pulse pulse-position modulation and return to zero modulation (QAM-MPPM-RZ). In this scheme, the two orthogonal polarization states enable simultaneous transmission of four data flows, which can provide different services for users according to the data rate requirement. To generate hybrid QAM-MPPM-RZ mm-wave signal, the QAM mm-wave signal is directly modulated by MPPM-RZ signal without using digital signal processing (DSP) devices, which reduces the overhead of the encoding process. Then, the generated QAM-MPPM-RZ mm-wave signal is transmitted in PDM microwave photonic link based on SSB modulation. The sparsity characteristic of QAM-MPPM-RZ not only improves the power efficiency, but also decreases the degradation caused by the fiber chromatic dispersion. The simulation results show that, under the constraint of the same transmitted data rate, the PDM microwave photonic link with 50 GHz QAM-MPPM-RZ mm-wave signal achieves much lower levels of bit-error rate than ordinary 32-QAM. In addition, the increase of laser linewidth brings no additional impact to the proposed scheme.

Optical signal processing techniques and applications of optical phase modulation in high-speed communication systems

NASA Astrophysics Data System (ADS)

Deng, Ning

In recent years, optical phase modulation has attracted much research attention in the field of fiber optic communications. Compared with the traditional optical intensity-modulated signal, one of the main merits of the optical phase-modulated signal is the better transmission performance. For optical phase modulation, in spite of the comprehensive study of its transmission performance, only a little research has been carried out in terms of its functions, applications and signal processing for future optical networks. These issues are systematically investigated in this thesis. The research findings suggest that optical phase modulation and its signal processing can greatly facilitate flexible network functions and high bandwidth which can be enjoyed by end users. In the thesis, the most important physical-layer technology, signal processing and multiplexing, are investigated with optical phase-modulated signals. Novel and advantageous signal processing and multiplexing approaches are proposed and studied. Experimental investigations are also reported and discussed in the thesis. Optical time-division multiplexing and demultiplexing. With the ever-increasing demand on communication bandwidth, optical time division multiplexing (OTDM) is an effective approach to upgrade the capacity of each wavelength channel in current optical systems. OTDM multiplexing can be simply realized, however, the demultiplexing requires relatively complicated signal processing and stringent timing control, and thus hinders its practicability. To tackle this problem, in this thesis a new OTDM scheme with hybrid DPSK and OOK signals is proposed. Experimental investigation shows this scheme can greatly enhance the demultiplexing timing misalignment and improve the demultiplexing performance, and thus make OTDM more practical and cost effective. All-optical signal processing. In current and future optical communication systems and networks, the data rate per wavelength has been approaching the speed limitation of electronics. Thus, all-optical signal processing techniques are highly desirable to support the necessary optical switching functionalities in future ultrahigh-speed optical packet-switching networks. To cope with the wide use of optical phase-modulated signals, in the thesis, an all-optical logic for DPSK or PSK input signals is developed, for the first time. Based on four-wave mixing in semiconductor optical amplifier, the structure of the logic gate is simple, compact, and capable of supporting ultrafast operation. In addition to the general logic processing, a simple label recognition scheme, as a specific signal processing function, is proposed for phase-modulated label signals. The proposed scheme can recognize any incoming label pattern according to the local pattern, and is potentially capable of handling variable-length label patterns. Optical access network with multicast overlay and centralized light sources. In the arena of optical access networks, wavelength division multiplexing passive optical network (WDM-PON) is a promising technology to deliver high-speed data traffic. However, most of proposed WDM-PONs only support conventional point-to-point service, and cannot meet the requirement of increasing demand on broadcast and multicast service. In this thesis, a simple network upgrade is proposed based on the traditional PON architecture to support both point-to-point and multicast service. In addition, the two service signals are modulated on the same lightwave carrier. The upstream signal is also remodulated on the same carrier at the optical network unit, which can significantly relax the requirement on wavelength management at the network unit.

Impact of VLSI/VHSIC on satellite on-board signal processing

NASA Astrophysics Data System (ADS)

Aanstoos, J. V.; Ruedger, W. H.; Snyder, W. E.; Kelly, W. L.

Forecasted improvements in IC fabrication techniques, such as the use of X-ray lithography, are expected to yield submicron circuit feature sizes within the decade of the 1980s. As dimensions decrease, reliability, cost, speed, power consumption and density improvements will be realized which have a significant impact on the capabilities of onboard spacecraft signal processing functions. This will in turn result in increases of the intelligence that may be deployed on spaceborne remote sensing platforms. Among programs oriented toward such goals are the silicon-based Very High Speed Integrated Circuit (VHSIC) researches sponsored by the U.S. Department of Defense, and efforts toward the development of GaAs devices which will compete with silicon VLSI technology for future applications. GaAs has an electron mobility which is five to six times that of silicon, and promises commensurate computation speed increases under low field conditions.

Speckle reduction in echocardiography by temporal compounding and anisotropic diffusion filtering

NASA Astrophysics Data System (ADS)

Giraldo-Guzmán, Jader; Porto-Solano, Oscar; Cadena-Bonfanti, Alberto; Contreras-Ortiz, Sonia H.

2015-01-01

Echocardiography is a medical imaging technique based on ultrasound signals that is used to evaluate heart anatomy and physiology. Echocardiographic images are affected by speckle, a type of multiplicative noise that obscures details of the structures, and reduces the overall image quality. This paper shows an approach to enhance echocardiography using two processing techniques: temporal compounding and anisotropic diffusion filtering. We used twenty echocardiographic videos that include one or three cardiac cycles to test the algorithms. Two images from each cycle were aligned in space and averaged to obtain the compound images. These images were then processed using anisotropic diffusion filters to further improve their quality. Resultant images were evaluated using quality metrics and visual assessment by two medical doctors. The average total improvement on signal-to-noise ratio was up to 100.29% for videos with three cycles, and up to 32.57% for videos with one cycle.

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.

A new FPGA architecture suitable for DSP applications

NASA Astrophysics Data System (ADS)

Liyun, Wang; Jinmei, Lai; Jiarong, Tong; Pushan, Tang; Xing, Chen; Xueyan, Duan; Liguang, Chen; Jian, Wang; Yuan, Wang

2011-05-01

A new FPGA architecture suitable for digital signal processing applications is presented. DSP modules can be inserted into FPGA conveniently with the proposed architecture, which is much faster when used in the field of digital signal processing compared with traditional FPGAs. An advanced 2-level MUX (multiplexer) is also proposed. With the added SLEEP MODE PASS to traditional 2-level MUX, static leakage is reduced. Furthermore, buffers are inserted at early returns of long lines. With this kind of buffer, the delay of the long line is improved by 9.8% while the area increases by 4.37%. The layout of this architecture has been taped out in standard 0.13 μm CMOS technology successfully. The die size is 6.3 × 4.5 mm2 with the QFP208 package. Test results show that performances of presented classical DSP cases are improved by 28.6%-302% compared with traditional FPGAs.

Visualizing Time: How Linguistic Metaphors Are Incorporated into Displaying Instruments in the Process of Interpreting Time-Varying Signals

ERIC Educational Resources Information Center

Garcia-Belmonte, Germà

2017-01-01

Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static…

Restoring auditory cortex plasticity in adult mice by restricting thalamic adenosine signaling

DOE PAGES

Blundon, Jay A.; Roy, Noah C.; Teubner, Brett J. W.; ...

2017-06-30

Circuits in the auditory cortex are highly susceptible to acoustic influences during an early postnatal critical period. The auditory cortex selectively expands neural representations of enriched acoustic stimuli, a process important for human language acquisition. Adults lack this plasticity. We show in the murine auditory cortex that juvenile plasticity can be reestablished in adulthood if acoustic stimuli are paired with disruption of ecto-5'-nucleotidase–dependent adenosine production or A1–adenosine receptor signaling in the auditory thalamus. This plasticity occurs at the level of cortical maps and individual neurons in the auditory cortex of awake adult mice and is associated with long-term improvement ofmore » tone-discrimination abilities. We determined that, in adult mice, disrupting adenosine signaling in the thalamus rejuvenates plasticity in the auditory cortex and improves auditory perception.« less

Restoring auditory cortex plasticity in adult mice by restricting thalamic adenosine signaling

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

Blundon, Jay A.; Roy, Noah C.; Teubner, Brett J. W.

Circuits in the auditory cortex are highly susceptible to acoustic influences during an early postnatal critical period. The auditory cortex selectively expands neural representations of enriched acoustic stimuli, a process important for human language acquisition. Adults lack this plasticity. We show in the murine auditory cortex that juvenile plasticity can be reestablished in adulthood if acoustic stimuli are paired with disruption of ecto-5'-nucleotidase–dependent adenosine production or A1–adenosine receptor signaling in the auditory thalamus. This plasticity occurs at the level of cortical maps and individual neurons in the auditory cortex of awake adult mice and is associated with long-term improvement ofmore » tone-discrimination abilities. We determined that, in adult mice, disrupting adenosine signaling in the thalamus rejuvenates plasticity in the auditory cortex and improves auditory perception.« less

Stochastic resonance in an underdamped system with FitzHug-Nagumo potential for weak signal detection

NASA Astrophysics Data System (ADS)

López, Cristian; Zhong, Wei; Lu, Siliang; Cong, Feiyun; Cortese, Ignacio

2017-12-01

Vibration signals are widely used for bearing fault detection and diagnosis. When signals are acquired in the field, usually, the faulty periodic signal is weak and is concealed by noise. Various de-noising methods have been developed to extract the target signal from the raw signal. Stochastic resonance (SR) is a technique that changed the traditional denoising process, in which the weak periodic fault signal can be identified by adding an expression, the potential, to the raw signal and solving a differential equation problem. However, current SR methods have some deficiencies such us limited filtering performance, low frequency input signal and sequential search for optimum parameters. Consequently, in this study, we explore the application of SR based on the FitzHug-Nagumo (FHN) potential in rolling bearing vibration signals. Besides, we improve the search of the SR optimum parameters by the use of particle swarm optimization (PSO). The effectiveness of the proposed method is verified by using both simulated and real bearing data sets.

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.

Super-resolution imaging using multi- electrode CMUTs: theoretical design and simulation using point targets.

PubMed

You, Wei; Cretu, Edmond; Rohling, Robert

2013-11-01

This paper investigates a low computational cost, super-resolution ultrasound imaging method that leverages the asymmetric vibration mode of CMUTs. Instead of focusing on the broadband received signal on the entire CMUT membrane, we utilize the differential signal received on the left and right part of the membrane obtained by a multi-electrode CMUT structure. The differential signal reflects the asymmetric vibration mode of the CMUT cell excited by the nonuniform acoustic pressure field impinging on the membrane, and has a resonant component in immersion. To improve the resolution, we propose an imaging method as follows: a set of manifold matrices of CMUT responses for multiple focal directions are constructed off-line with a grid of hypothetical point targets. During the subsequent imaging process, the array sequentially steers to multiple angles, and the amplitudes (weights) of all hypothetical targets at each angle are estimated in a maximum a posteriori (MAP) process with the manifold matrix corresponding to that angle. Then, the weight vector undergoes a directional pruning process to remove the false estimation at other angles caused by the side lobe energy. Ultrasound imaging simulation is performed on ring and linear arrays with a simulation program adapted with a multi-electrode CMUT structure capable of obtaining both average and differential received signals. Because the differential signals from all receiving channels form a more distinctive temporal pattern than the average signals, better MAP estimation results are expected than using the average signals. The imaging simulation shows that using differential signals alone or in combination with the average signals produces better lateral resolution than the traditional phased array or using the average signals alone. This study is an exploration into the potential benefits of asymmetric CMUT responses for super-resolution imaging.

Automated wavelet denoising of photoacoustic signals for circulating melanoma cell detection and burn image reconstruction.

PubMed

Holan, Scott H; Viator, John A

2008-06-21

Photoacoustic image reconstruction may involve hundreds of point measurements, each of which contributes unique information about the subsurface absorbing structures under study. For backprojection imaging, two or more point measurements of photoacoustic waves induced by irradiating a biological sample with laser light are used to produce an image of the acoustic source. Each of these measurements must undergo some signal processing, such as denoising or system deconvolution. In order to process the numerous signals, we have developed an automated wavelet algorithm for denoising signals. We appeal to the discrete wavelet transform for denoising photoacoustic signals generated in a dilute melanoma cell suspension and in thermally coagulated blood. We used 5, 9, 45 and 270 melanoma cells in the laser beam path as test concentrations. For the burn phantom, we used coagulated blood in 1.6 mm silicon tube submerged in Intralipid. Although these two targets were chosen as typical applications for photoacoustic detection and imaging, they are of independent interest. The denoising employs level-independent universal thresholding. In order to accommodate nonradix-2 signals, we considered a maximal overlap discrete wavelet transform (MODWT). For the lower melanoma cell concentrations, as the signal-to-noise ratio approached 1, denoising allowed better peak finding. For coagulated blood, the signals were denoised to yield a clean photoacoustic resulting in an improvement of 22% in the reconstructed image. The entire signal processing technique was automated so that minimal user intervention was needed to reconstruct the images. Such an algorithm may be used for image reconstruction and signal extraction for applications such as burn depth imaging, depth profiling of vascular lesions in skin and the detection of single cancer cells in blood samples.

Instantaneous and Frequency-Warped Signal Processing Techniques for Auditory Source Separation.

NASA Astrophysics Data System (ADS)

Wang, Avery Li-Chun

This thesis summarizes several contributions to the areas of signal processing and auditory source separation. The philosophy of Frequency-Warped Signal Processing is introduced as a means for separating the AM and FM contributions to the bandwidth of a complex-valued, frequency-varying sinusoid p (n), transforming it into a signal with slowly-varying parameters. This transformation facilitates the removal of p (n) from an additive mixture while minimizing the amount of damage done to other signal components. The average winding rate of a complex-valued phasor is explored as an estimate of the instantaneous frequency. Theorems are provided showing the robustness of this measure. To implement frequency tracking, a Frequency-Locked Loop algorithm is introduced which uses the complex winding error to update its frequency estimate. The input signal is dynamically demodulated and filtered to extract the envelope. This envelope may then be remodulated to reconstruct the target partial, which may be subtracted from the original signal mixture to yield a new, quickly-adapting form of notch filtering. Enhancements to the basic tracker are made which, under certain conditions, attain the Cramer -Rao bound for the instantaneous frequency estimate. To improve tracking, the novel idea of Harmonic -Locked Loop tracking, using N harmonically constrained trackers, is introduced for tracking signals, such as voices and certain musical instruments. The estimated fundamental frequency is computed from a maximum-likelihood weighting of the N tracking estimates, making it highly robust. The result is that harmonic signals, such as voices, can be isolated from complex mixtures in the presence of other spectrally overlapping signals. Additionally, since phase information is preserved, the resynthesized harmonic signals may be removed from the original mixtures with relatively little damage to the residual signal. Finally, a new methodology is given for designing linear-phase FIR filters which require a small fraction of the computational power of conventional FIR implementations. This design strategy is based on truncated and stabilized IIR filters. These signal-processing methods have been applied to the problem of auditory source separation, resulting in voice separation from complex music that is significantly better than previous results at far lower computational cost.

Aligning a Receiving Antenna Array to Reduce Interference

NASA Technical Reports Server (NTRS)

Jongeling, Andre P.; Rogstad, David H.

2009-01-01

A digital signal-processing algorithm has been devised as a means of aligning (as defined below) the outputs of multiple receiving radio antennas in a large array for the purpose of receiving a desired weak signal transmitted by a single distant source in the presence of an interfering signal that (1) originates at another source lying within the antenna beam and (2) occupies a frequency band significantly wider than that of the desired signal. In the original intended application of the algorithm, the desired weak signal is a spacecraft telemetry signal, the antennas are spacecraft-tracking antennas in NASA s Deep Space Network, and the source of the wide-band interfering signal is typically a radio galaxy or a planet that lies along or near the line of sight to the spacecraft. The algorithm could also afford the ability to discriminate between desired narrow-band and nearby undesired wide-band sources in related applications that include satellite and terrestrial radio communications and radio astronomy. The development of the present algorithm involved modification of a prior algorithm called SUMPLE and a predecessor called SIMPLE. SUMPLE was described in Algorithm for Aligning an Array of Receiving Radio Antennas (NPO-40574), NASA Tech Briefs Vol. 30, No. 4 (April 2006), page 54. To recapitulate: As used here, aligning signifies adjusting the delays and phases of the outputs from the various antennas so that their relatively weak replicas of the desired signal can be added coherently to increase the signal-to-noise ratio (SNR) for improved reception, as though one had a single larger antenna. Prior to the development of SUMPLE, it was common practice to effect alignment by means of a process that involves correlation of signals in pairs. SIMPLE is an example of an algorithm that effects such a process. SUMPLE also involves correlations, but the correlations are not performed in pairs. Instead, in a partly iterative process, each signal is appropriately weighted and then correlated with a composite signal equal to the sum of the other signals.

Active elimination of radio frequency interference for improved signal-to-noise ratio for in-situ NMR experiments in strong magnetic field gradients

NASA Astrophysics Data System (ADS)

Ibrahim, M.; Pardi, C. I.; Brown, T. W. C.; McDonald, P. J.

2018-02-01

Improvement in the signal-to-noise ratio of Nuclear Magnetic Resonance (NMR) systems may be achieved either by increasing the signal amplitude or by decreasing the noise. The noise has multiple origins - not all of which are strictly "noise": incoherent thermal noise originating in the probe and pre-amplifiers, probe ring down or acoustic noise and coherent externally broadcast radio frequency transmissions. The last cannot always be shielded in open access experiments. In this paper, we show that pulsed, low radio-frequency data communications are a significant source of broadcast interference. We explore two signal processing methods of de-noising short T2∗ NMR experiments corrupted by these communications: Linear Predictive Coding (LPC) and the Discrete Wavelet Transform (DWT). Results are shown for numerical simulations and experiments conducted under controlled conditions with pseudo radio frequency interference. We show that both the LPC and DWT methods have merit.

Comparing Binaural Pre-processing Strategies II: Speech Intelligibility of Bilateral Cochlear Implant Users.

PubMed

Baumgärtel, Regina M; Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-12-30

Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. © The Author(s) 2015.

Comparing Binaural Pre-processing Strategies II

PubMed Central

Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-01-01

Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. PMID:26721921

Gas ultrasonic flow rate measurement through genetic-ant colony optimization based on the ultrasonic pulse received signal model

NASA Astrophysics Data System (ADS)

Hou, Huirang; Zheng, Dandan; Nie, Laixiao

2015-04-01

For gas ultrasonic flowmeters, the signals received by ultrasonic sensors are susceptible to noise interference. If signals are mingled with noise, a large error in flow measurement can be caused by triggering mistakenly using the traditional double-threshold method. To solve this problem, genetic-ant colony optimization (GACO) based on the ultrasonic pulse received signal model is proposed. Furthermore, in consideration of the real-time performance of the flow measurement system, the improvement of processing only the first three cycles of the received signals rather than the whole signal is proposed. Simulation results show that the GACO algorithm has the best estimation accuracy and ant-noise ability compared with the genetic algorithm, ant colony optimization, double-threshold and enveloped zero-crossing. Local convergence doesn’t appear with the GACO algorithm until -10 dB. For the GACO algorithm, the converging accuracy and converging speed and the amount of computation are further improved when using the first three cycles (called GACO-3cycles). Experimental results involving actual received signals show that the accuracy of single-gas ultrasonic flow rate measurement can reach 0.5% with GACO-3 cycles, which is better than with the double-threshold method.

Linear friction weld process monitoring of fixture cassette deformations using empirical mode decomposition

NASA Astrophysics Data System (ADS)

Bakker, O. J.; Gibson, C.; Wilson, P.; Lohse, N.; Popov, A. A.

2015-10-01

Due to its inherent advantages, linear friction welding is a solid-state joining process of increasing importance to the aerospace, automotive, medical and power generation equipment industries. Tangential oscillations and forge stroke during the burn-off phase of the joining process introduce essential dynamic forces, which can also be detrimental to the welding process. Since burn-off is a critical phase in the manufacturing stage, process monitoring is fundamental for quality and stability control purposes. This study aims to improve workholding stability through the analysis of fixture cassette deformations. Methods and procedures for process monitoring are developed and implemented in a fail-or-pass assessment system for fixture cassette deformations during the burn-off phase. Additionally, the de-noised signals are compared to results from previous production runs. The observed deformations as a consequence of the forces acting on the fixture cassette are measured directly during the welding process. Data on the linear friction-welding machine are acquired and de-noised using empirical mode decomposition, before the burn-off phase is extracted. This approach enables a direct, objective comparison of the signal features with trends from previous successful welds. The capacity of the whole process monitoring system is validated and demonstrated through the analysis of a large number of signals obtained from welding experiments.

Signal enhancement based on complex curvelet transform and complementary ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Dong, Lieqian; Wang, Deying; Zhang, Yimeng; Zhou, Datong

2017-09-01

Signal enhancement is a necessary step in seismic data processing. In this paper we utilize the complementary ensemble empirical mode decomposition (CEEMD) and complex curvelet transform (CCT) methods to separate signal from random noise further to improve the signal to noise (S/N) ratio. Firstly, the original data with noise is decomposed into a series of intrinsic mode function (IMF) profiles with the aid of CEEMD. Then the IMFs with noise are transformed into CCT domain. By choosing different thresholds which are based on the noise level difference of each IMF profile, the noise in original data can be suppressed. Finally, we illustrate the effectiveness of the approach by simulated and field datasets.

Complex Signal Kurtosis and Independent Component Analysis for Wideband Radio Frequency Interference Detection

NASA Technical Reports Server (NTRS)

Schoenwald, Adam; Mohammed, Priscilla; Bradley, Damon; Piepmeier, Jeffrey; Wong, Englin; Gholian, Armen

2016-01-01

Radio-frequency interference (RFI) has negatively implicated scientific measurements across a wide variation passive remote sensing satellites. This has been observed in the L-band radiometers SMOS, Aquarius and more recently, SMAP [1, 2]. RFI has also been observed at higher frequencies such as K band [3]. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements [4]. This work explores the use of ICA (Independent Component Analysis) as a blind source separation technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

Range Measurement as Practiced in the Deep Space Network

NASA Technical Reports Server (NTRS)

Berner, Jeff B.; Bryant, Scott H.; Kinman, Peter W.

2007-01-01

Range measurements are used to improve the trajectory models of spacecraft tracked by the Deep Space Network. The unique challenge of deep-space ranging is that the two-way delay is long, typically many minutes, and the signal-to-noise ratio is small. Accurate measurements are made under these circumstances by means of long correlations that incorporate Doppler rate-aiding. This processing is done with commercial digital signal processors, providing a flexibility in signal design that can accommodate both the traditional sequential ranging signal and pseudonoise range codes. Accurate range determination requires the calibration of the delay within the tracking station. Measurements with a standard deviation of 1 m have been made.

Secure chaotic transmission of electrocardiography signals with acousto-optic modulation under profiled beam propagation.

PubMed

Almehmadi, Fares S; Chatterjee, Monish R

2015-01-10

Electrocardiography (ECG) signals are used for both medical purposes and identifying individuals. It is often necessary to encrypt this highly sensitive information before it is transmitted over any channel. A closed-loop acousto-optic hybrid device acting as a chaotic modulator is applied to ECG signals to achieve this encryption. Recently improved modeling of this approach using profiled optical beams has shown it to be very sensitive to key parameters that characterize the encryption and decryption process, exhibiting its potential for secure transmission of analog and digital signals. Here the encryption and decryption is demonstrated for ECG signals, both analog and digital versions, illustrating strong encryption without significant distortion. Performance analysis pertinent to both analog and digital transmission of the ECG waveform is also carried out using output signal-to-noise, signal-to-distortion, and bit-error-rate measures relative to the key parameters and presence of channel noise in the system.

A digital strategy for manometer dynamic enhancement. [for wind tunnel monitoring

NASA Technical Reports Server (NTRS)

Stoughton, J. W.

1978-01-01

Application of digital signal processing techniques to improve the non-linear dynamic characteristics of a sonar-type mercury manometer is described. The dynamic enhancement strategy quasi-linearizes the manometer characteristics and improves the effective bandwidth in the context of a wind-tunnel pressure regulation system. Model identification data and real-time hybrid simulation data demonstrate feasibility of approach.

A source number estimation method for single optical fiber sensor

NASA Astrophysics Data System (ADS)

Hu, Junpeng; Huang, Zhiping; Su, Shaojing; Zhang, Yimeng; Liu, Chunwu

2015-10-01

The single-channel blind source separation (SCBSS) technique makes great significance in many fields, such as optical fiber communication, sensor detection, image processing and so on. It is a wide range application to realize blind source separation (BSS) from a single optical fiber sensor received data. The performance of many BSS algorithms and signal process methods will be worsened with inaccurate source number estimation. Many excellent algorithms have been proposed to deal with the source number estimation in array signal process which consists of multiple sensors, but they can not be applied directly to the single sensor condition. This paper presents a source number estimation method dealing with the single optical fiber sensor received data. By delay process, this paper converts the single sensor received data to multi-dimension form. And the data covariance matrix is constructed. Then the estimation algorithms used in array signal processing can be utilized. The information theoretic criteria (ITC) based methods, presented by AIC and MDL, Gerschgorin's disk estimation (GDE) are introduced to estimate the source number of the single optical fiber sensor's received signal. To improve the performance of these estimation methods at low signal noise ratio (SNR), this paper make a smooth process to the data covariance matrix. By the smooth process, the fluctuation and uncertainty of the eigenvalues of the covariance matrix are reduced. Simulation results prove that ITC base methods can not estimate the source number effectively under colored noise. The GDE method, although gets a poor performance at low SNR, but it is able to accurately estimate the number of sources with colored noise. The experiments also show that the proposed method can be applied to estimate the source number of single sensor received data.

Mössbauer spectra linearity improvement by sine velocity waveform followed by linearization process

NASA Astrophysics Data System (ADS)

Kohout, Pavel; Frank, Tomas; Pechousek, Jiri; Kouril, Lukas

2018-05-01

This note reports the development of a new method for linearizing the Mössbauer spectra recorded with a sine drive velocity signal. Mössbauer spectra linearity is a critical parameter to determine Mössbauer spectrometer accuracy. Measuring spectra with a sine velocity axis and consecutive linearization increases the linearity of spectra in a wider frequency range of a drive signal, as generally harmonic movement is natural for velocity transducers. The obtained data demonstrate that linearized sine spectra have lower nonlinearity and line width parameters in comparison with those measured using a traditional triangle velocity signal.

DNA Damage Signalling and Repair Inhibitors: The Long-Sought-After Achilles’ Heel of Cancer

PubMed Central

Velic, Denis; Couturier, Anthony M.; Ferreira, Maria Tedim; Rodrigue, Amélie; Poirier, Guy G.; Fleury, Fabrice; Masson, Jean-Yves

2015-01-01

For decades, radiotherapy and chemotherapy were the two only approaches exploiting DNA repair processes to fight against cancer. Nowadays, cancer therapeutics can be a major challenge when it comes to seeking personalized targeted medicine that is both effective and selective to the malignancy. Over the last decade, the discovery of new targeted therapies against DNA damage signalling and repair has offered the possibility of therapeutic improvements in oncology. In this review, we summarize the current knowledge of DNA damage signalling and repair inhibitors, their molecular and cellular effects, and future therapeutic use. PMID:26610585

Model-Based Fault Diagnosis for Turboshaft Engines

NASA Technical Reports Server (NTRS)

Green, Michael D.; Duyar, Ahmet; Litt, Jonathan S.

1998-01-01

Tests are described which, when used to augment the existing periodic maintenance and pre-flight checks of T700 engines, can greatly improve the chances of uncovering a problem compared to the current practice. These test signals can be used to expose and differentiate between faults in various components by comparing the responses of particular engine variables to the expected. The responses can be processed on-line in a variety of ways which have been shown to reveal and identify faults. The combination of specific test signals and on-line processing methods provides an ad hoc approach to the isolation of faults which might not otherwise be detected during pre-flight checkout.

RHIC BPM SYSTEM MODIFICATIONS AND PERFORMANCE.

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

SATOGATA, T.; CALAGA, R.; CAMERON, P.

2005-05-16

The RHIC beam position monitor (BPM) system provides independent average orbit and turn-by-turn (TBT) position measurements. In each ring, there are 162 measurement locations per plane (horizontal and vertical) for a total of 648 BPM planes in the RHIC machine. During 2003 and 2004 shutdowns, BPM processing electronics were moved from the RHIC tunnel to controls alcoves to reduce radiation impact, and the analog signal paths of several dozen modules were modified to eliminate gain-switching relays and improve signal stability. This paper presents results of improved system performance, including stability for interaction region beam-based alignment efforts. We also summarize performancemore » of recently-added DSP profile scan capability, and improved million-turn TBT acquisition channels for 10 Hz triplet vibration, nonlinear dynamics, and echo studies.« less

Optically modulated fluorescence bioimaging: visualizing obscured fluorophores in high background.

PubMed

Hsiang, Jung-Cheng; Jablonski, Amy E; Dickson, Robert M

2014-05-20

Fluorescence microscopy and detection have become indispensible for understanding organization and dynamics in biological systems. Novel fluorophores with improved brightness, photostability, and biocompatibility continue to fuel further advances but often rely on having minimal background. The visualization of interactions in very high biological background, especially for proteins or bound complexes at very low copy numbers, remains a primary challenge. Instead of focusing on molecular brightness of fluorophores, we have adapted the principles of high-sensitivity absorption spectroscopy to improve the sensitivity and signal discrimination in fluorescence bioimaging. Utilizing very long wavelength transient absorptions of kinetically trapped dark states, we employ molecular modulation schemes that do not simultaneously modulate the background fluorescence. This improves the sensitivity and ease of implementation over high-energy photoswitch-based recovery schemes, as no internal dye reference or nanoparticle-based fluorophores are needed to separate the desired signals from background. In this Account, we describe the selection process for and identification of fluorophores that enable optically modulated fluorescence to decrease obscuring background. Differing from thermally stable photoswitches using higher-energy secondary lasers, coillumination at very low energies depopulates transient dark states, dynamically altering the fluorescence and giving characteristic modulation time scales for each modulatable emitter. This process is termed synchronously amplified fluorescence image recovery (SAFIRe) microscopy. By understanding and optically controlling the dye photophysics, we selectively modulate desired fluorophore signals independent of all autofluorescent background. This shifts the fluorescence of interest to unique detection frequencies with nearly shot-noise-limited detection, as no background signals are collected. Although the fluorescence brightness is improved slightly, SAFIRe yields up to 100-fold improved signal visibility by essentially removing obscuring, unmodulated background (Richards, C. I.; J. Am. Chem. Soc. 2009, 131, 4619). While SAFIRe exhibits a wide, linear dynamic range, we have demonstrated single-molecule signal recovery buried within 200 nM obscuring dye. In addition to enabling signal recovery through background reduction, each dye exhibits a characteristic modulation frequency indicative of its photophysical dynamics. Thus, these characteristic time scales offer opportunities not only to expand the dimensionality of fluorescence imaging by using dark-state lifetimes but also to distinguish the dynamics of subpopulations on the basis of photophysical versus diffusional time scales, even within modulatable populations. The continued development of modulation for signal recovery and observation of biological dynamics holds great promise for studying a range of transient biological phenomena in natural environments. Through the development of a wide range of fluorescent proteins, organic dyes, and inorganic emitters that exhibit significant dark-state populations under steady-state illumination, we can drastically expand the applicability of fluorescence imaging to probe lower-abundance complexes and their dynamics.

Programmable noise bandwidth reduction by means of digital averaging

NASA Technical Reports Server (NTRS)

Poklemba, John J. (Inventor)

1993-01-01

Predetection noise bandwidth reduction is effected by a pre-averager capable of digitally averaging the samples of an input data signal over two or more symbols, the averaging interval being defined by the input sampling rate divided by the output sampling rate. As the averaged sample is clocked to a suitable detector at a much slower rate than the input signal sampling rate the noise bandwidth at the input to the detector is reduced, the input to the detector having an improved signal to noise ratio as a result of the averaging process, and the rate at which such subsequent processing must operate is correspondingly reduced. The pre-averager forms a data filter having an output sampling rate of one sample per symbol of received data. More specifically, selected ones of a plurality of samples accumulated over two or more symbol intervals are output in response to clock signals at a rate of one sample per symbol interval. The pre-averager includes circuitry for weighting digitized signal samples using stored finite impulse response (FIR) filter coefficients. A method according to the present invention is also disclosed.

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.

Transformation of safety culture on the San Antonio service unit of Union Pacific Railroad

DOT National Transportation Integrated Search

2012-10-31

The Federal Railroad Administration conducted a pilot demonstration of Clear Signal for Action (CSA), a risk reduction process : that combines peer-to-peer feedback, continuous improvement, and safety leadership development. An independent formative ...

Effect of Energy Equalization on the Intelligibility of Speech in Fluctuating Background Interference for Listeners With Hearing Impairment

PubMed Central

D’Aquila, Laura A.; Desloge, Joseph G.; Braida, Louis D.

2017-01-01

The masking release (MR; i.e., better speech recognition in fluctuating compared with continuous noise backgrounds) that is evident for listeners with normal hearing (NH) is generally reduced or absent for listeners with sensorineural hearing impairment (HI). In this study, a real-time signal-processing technique was developed to improve MR in listeners with HI and offer insight into the mechanisms influencing the size of MR. This technique compares short-term and long-term estimates of energy, increases the level of short-term segments whose energy is below the average energy, and normalizes the overall energy of the processed signal to be equivalent to that of the original long-term estimate. This signal-processing algorithm was used to create two types of energy-equalized (EEQ) signals: EEQ1, which operated on the wideband speech plus noise signal, and EEQ4, which operated independently on each of four bands with equal logarithmic width. Consonant identification was tested in backgrounds of continuous and various types of fluctuating speech-shaped Gaussian noise including those with both regularly and irregularly spaced temporal fluctuations. Listeners with HI achieved similar scores for EEQ and the original (unprocessed) stimuli in continuous-noise backgrounds, while superior performance was obtained for the EEQ signals in fluctuating background noises that had regular temporal gaps but not for those with irregularly spaced fluctuations. Thus, in noise backgrounds with regularly spaced temporal fluctuations, the energy-normalized signals led to larger values of MR and higher intelligibility than obtained with unprocessed signals. PMID:28602128

Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

NASA Astrophysics Data System (ADS)

Feng, Zhipeng; Chu, Fulei; Zuo, Ming J.

2011-03-01

Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.

Fallon, Nevada FORGE Seismic Reflection Profiles

DOE Data Explorer

Blankenship, Doug; Faulds, James; Queen, John; Fortuna, Mark

2018-02-01

Newly reprocessed Naval Air Station Fallon (1994) seismic lines: pre-stack depth migrations, with interpretations to support the Fallon FORGE (Phase 2B) 3D Geologic model. Data along seven profiles (>100 km of total profile length) through and adjacent to the Fallon site were re-processed. The most up-to-date, industry-tested seismic processing techniques were utilized to improve the signal strength and coherency in the sedimentary, volcanic, and Mesozoic crystalline basement sections, in conjunction with fault diffractions in order to improve the identification and definition of faults within the study area.

Multi-step EMG Classification Algorithm for Human-Computer Interaction

NASA Astrophysics Data System (ADS)

Ren, Peng; Barreto, Armando; Adjouadi, Malek

A three-electrode human-computer interaction system, based on digital processing of the Electromyogram (EMG) signal, is presented. This system can effectively help disabled individuals paralyzed from the neck down to interact with computers or communicate with people through computers using point-and-click graphic interfaces. The three electrodes are placed on the right frontalis, the left temporalis and the right temporalis muscles in the head, respectively. The signal processing algorithm used translates the EMG signals during five kinds of facial movements (left jaw clenching, right jaw clenching, eyebrows up, eyebrows down, simultaneous left & right jaw clenching) into five corresponding types of cursor movements (left, right, up, down and left-click), to provide basic mouse control. The classification strategy is based on three principles: the EMG energy of one channel is typically larger than the others during one specific muscle contraction; the spectral characteristics of the EMG signals produced by the frontalis and temporalis muscles during different movements are different; the EMG signals from adjacent channels typically have correlated energy profiles. The algorithm is evaluated on 20 pre-recorded EMG signal sets, using Matlab simulations. The results show that this method provides improvements and is more robust than other previous approaches.

Dark matter RNA: an intelligent scaffold for the dynamic regulation of the nuclear information landscape

PubMed Central

St. Laurent, Georges; Savva, Yiannis A.; Kapranov, Philipp

2012-01-01

Perhaps no other topic in contemporary genomics has inspired such diverse viewpoints as the 95+% of the genome, previously known as “junk DNA,” that does not code for proteins. Here, we present a theory in which dark matter RNA plays a role in the generation of a landscape of spatial micro-domains coupled to the information signaling matrix of the nuclear landscape. Within and between these micro-domains, dark matter RNAs additionally function to tether RNA interacting proteins and complexes of many different types, and by doing so, allow for a higher performance of the various processes requiring them at ultra-fast rates. This improves signal to noise characteristics of RNA processing, trafficking, and epigenetic signaling, where competition and differential RNA binding among proteins drives the computational decisions inherent in regulatory events. PMID:22539933

Remote sensing of the energetic status of plants and ecosystems: optical and odorous signals

NASA Astrophysics Data System (ADS)

Penuelas, J.; Bartrons, M.; Llusia, J.; Filella, I.

2016-12-01

The optical and odorous signals emitted by plants and ecosystems present consistent relationships. They offer promising prospects for continuous local and global monitoring of the energetic status of plants and ecosystems, and therefore of their processing of energy and matter. We will discuss how the energetic status of plants (and ecosystems) resulting from the balance between the supply and demand of reducing power can be assessed biochemically, by the cellular NADPH/NADP ratio, optically, by using the photochemical reflectance index and sun-induced fluorescence as indicators of the dissipation of excess energy and associated physiological processes, and "odorously", by the emission of volatile organic compounds such as isoprenoids, as indicators of an excess of reducing equivalents and also of enhancement of protective converging physiological processes. These signals thus provide information on the energetic status, associated health status, and the functioning of plants and ecosystems. We will present the links among the three signals and will especially discuss the possibility of remotely sense the optical signals linked to carbon uptake and VOCs exchange by plants and ecosystems. These signals and their integration may have multiple applications for environmental and agricultural monitoring, for example, by extending the spatial coverage of carbon-flux and VOCs emission observations to most places and times, and/or for improving the process-based modeling of carbon fixation and isoprenoid emissions from terrestrial vegetation on plant, ecosystemic and global scales. Considerable challenges remain for a wide-scale and routine implementation of these biochemical, optical, and odorous signals for ecosystemic and/or agronomic monitoring and modeling, but its interest for making further steps forward in global ecology, agricultural applications, global carbon cycle, atmospheric science, and earth science warrants further research efforts in this line.

Note: An improved calibration system with phase correction for electronic transformers with digital output.

PubMed

Cheng, Han-miao; Li, Hong-bin

2015-08-01

The existing electronic transformer calibration systems employing data acquisition cards cannot satisfy some practical applications, because the calibration systems have phase measurement errors when they work in the mode of receiving external synchronization signals. This paper proposes an improved calibration system scheme with phase correction to improve the phase measurement accuracy. We employ NI PCI-4474 to design a calibration system, and the system has the potential to receive external synchronization signals and reach extremely high accuracy classes. Accuracy verification has been carried out in the China Electric Power Research Institute, and results demonstrate that the system surpasses the accuracy class 0.05. Furthermore, this system has been used to test the harmonics measurement accuracy of all-fiber optical current transformers. In the same process, we have used an existing calibration system, and a comparison of the test results is presented. The system after improvement is suitable for the intended applications.

Refinement and application of acoustic impulse technique to study nozzle transmission characteristics

NASA Technical Reports Server (NTRS)

Salikuddin, M.; Brown, W. H.; Ramakrishnan, R.; Tanna, H. K.

1983-01-01

An improved acoustic impulse technique was developed and was used to study the transmission characteristics of duct/nozzle systems. To accomplish the above objective, various problems associated with the existing spark-discharge impulse technique were first studied. These included (1) the nonlinear behavior of high intensity pulses, (2) the contamination of the signal with flow noise, (3) low signal-to-noise ratio at high exhaust velocities, and (4) the inability to control or shape the signal generated by the source, specially when multiple spark points were used as the source. The first step to resolve these problems was the replacement of the spark-discharge source with electroacoustic driver(s). These included (1) synthesizing on acoustic impulse with acoustic driver(s) to control and shape the output signal, (2) time domain signal averaging to remove flow noise from the contaminated signal, (3) signal editing to remove unwanted portions of the time history, (4) spectral averaging, and (5) numerical smoothing. The acoustic power measurement technique was improved by taking multiple induct measurements and by a modal decomposition process to account for the contribution of higher order modes in the power computation. The improved acoustic impulse technique was then validated by comparing the results derived by an impedance tube method. The mechanism of acoustic power loss, that occurs when sound is transmitted through nozzle terminations, was investigated. Finally, the refined impulse technique was applied to obtain more accurate results for the acoustic transmission characteristics of a conical nozzle and a multi-lobe multi-tube supressor nozzle.

Software-Reconfigurable Processors for Spacecraft

NASA Technical Reports Server (NTRS)

Farrington, Allen; Gray, Andrew; Bell, Bryan; Stanton, Valerie; Chong, Yong; Peters, Kenneth; Lee, Clement; Srinivasan, Jeffrey

2005-01-01

A report presents an overview of an architecture for a software-reconfigurable network data processor for a spacecraft engaged in scientific exploration. When executed on suitable electronic hardware, the software performs the functions of a physical layer (in effect, acts as a software radio in that it performs modulation, demodulation, pulse-shaping, error correction, coding, and decoding), a data-link layer, a network layer, a transport layer, and application-layer processing of scientific data. The software-reconfigurable network processor is undergoing development to enable rapid prototyping and rapid implementation of communication, navigation, and scientific signal-processing functions; to provide a long-lived communication infrastructure; and to provide greatly improved scientific-instrumentation and scientific-data-processing functions by enabling science-driven in-flight reconfiguration of computing resources devoted to these functions. This development is an extension of terrestrial radio and network developments (e.g., in the cellular-telephone industry) implemented in software running on such hardware as field-programmable gate arrays, digital signal processors, traditional digital circuits, and mixed-signal application-specific integrated circuits (ASICs).

SVD and Hankel matrix based de-noising approach for ball bearing fault detection and its assessment using artificial faults

NASA Astrophysics Data System (ADS)

Golafshan, Reza; Yuce Sanliturk, Kenan

2016-03-01

Ball bearings remain one of the most crucial components in industrial machines and due to their critical role, it is of great importance to monitor their conditions under operation. However, due to the background noise in acquired signals, it is not always possible to identify probable faults. This incapability in identifying the faults makes the de-noising process one of the most essential steps in the field of Condition Monitoring (CM) and fault detection. In the present study, Singular Value Decomposition (SVD) and Hankel matrix based de-noising process is successfully applied to the ball bearing time domain vibration signals as well as to their spectrums for the elimination of the background noise and the improvement the reliability of the fault detection process. The test cases conducted using experimental as well as the simulated vibration signals demonstrate the effectiveness of the proposed de-noising approach for the ball bearing fault detection.

Improving Robot Motor Learning with Negatively Valenced Reinforcement Signals

PubMed Central

Navarro-Guerrero, Nicolás; Lowe, Robert J.; Wermter, Stefan

2017-01-01

Both nociception and punishment signals have been used in robotics. However, the potential for using these negatively valenced types of reinforcement learning signals for robot learning has not been exploited in detail yet. Nociceptive signals are primarily used as triggers of preprogrammed action sequences. Punishment signals are typically disembodied, i.e., with no or little relation to the agent-intrinsic limitations, and they are often used to impose behavioral constraints. Here, we provide an alternative approach for nociceptive signals as drivers of learning rather than simple triggers of preprogrammed behavior. Explicitly, we use nociception to expand the state space while we use punishment as a negative reinforcement learning signal. We compare the performance—in terms of task error, the amount of perceived nociception, and length of learned action sequences—of different neural networks imbued with punishment-based reinforcement signals for inverse kinematic learning. We contrast the performance of a version of the neural network that receives nociceptive inputs to that without such a process. Furthermore, we provide evidence that nociception can improve learning—making the algorithm more robust against network initializations—as well as behavioral performance by reducing the task error, perceived nociception, and length of learned action sequences. Moreover, we provide evidence that punishment, at least as typically used within reinforcement learning applications, may be detrimental in all relevant metrics. PMID:28420976

Coil-to-coil physiological noise correlations and their impact on functional MRI time-series signal-to-noise ratio.

PubMed

Triantafyllou, Christina; Polimeni, Jonathan R; Keil, Boris; Wald, Lawrence L

2016-12-01

Physiological nuisance fluctuations ("physiological noise") are a major contribution to the time-series signal-to-noise ratio (tSNR) of functional imaging. While thermal noise correlations between array coil elements have a well-characterized effect on the image Signal to Noise Ratio (SNR 0 ), the element-to-element covariance matrix of the time-series fluctuations has not yet been analyzed. We examine this effect with a goal of ultimately improving the combination of multichannel array data. We extend the theoretical relationship between tSNR and SNR 0 to include a time-series noise covariance matrix Ψ t , distinct from the thermal noise covariance matrix Ψ 0 , and compare its structure to Ψ 0 and the signal coupling matrix SS H formed from the signal intensity vectors S. Inclusion of the measured time-series noise covariance matrix into the model relating tSNR and SNR 0 improves the fit of experimental multichannel data and is shown to be distinct from Ψ 0 or SS H . Time-series noise covariances in array coils are found to differ from Ψ 0 and more surprisingly, from the signal coupling matrix SS H . Correct characterization of the time-series noise has implications for the analysis of time-series data and for improving the coil element combination process. Magn Reson Med 76:1708-1719, 2016. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Fiber fault location utilizing traffic signal in optical network.

PubMed

Zhao, Tong; Wang, Anbang; Wang, Yuncai; Zhang, Mingjiang; Chang, Xiaoming; Xiong, Lijuan; Hao, Yi

2013-10-07

We propose and experimentally demonstrate a method for fault location in optical communication network. This method utilizes the traffic signal transmitted across the network as probe signal, and then locates the fault by correlation technique. Compared with conventional techniques, our method has a simple structure and low operation expenditure, because no additional device is used, such as light source, modulator and signal generator. The correlation detection in this method overcomes the tradeoff between spatial resolution and measurement range in pulse ranging technique. Moreover, signal extraction process can improve the location result considerably. Experimental results show that we achieve a spatial resolution of 8 cm and detection range of over 23 km with -8-dBm mean launched power in optical network based on synchronous digital hierarchy protocols.

Full-duplex bidirectional transmission of 10-Gb/s millimeter-wave QPSK signal in E-band optical wireless link.

PubMed

Fang, Yuan; Yu, Jianjun; Chi, Nan; Xiao, Jiangnan

2014-01-27

We experimentally demonstrated full-duplex bidirectional transmission of 10-Gb/s millimeter-wave (mm-wave) quadrature phase shift keying (QPSK) signal in E-band (71-76 GHz and 81-86 GHz) optical wireless link. Single-mode fibers (SMF) are connected at both sides of the antenna for uplink and downlink which realize 40-km SMF and 2-m wireless link for bidirectional transmission simultaneously. We utilized multi-level modulation format and coherent detection in such E-band optical wireless link for the first time. Mm-wave QPSK signal is generated by photonic technique to increase spectrum efficiency and received signal is coherently detected to improve receiver sensitivity. After the coherent detection, digital signal processing is utilized to compensate impairments of devices and transmission link.

Noise facilitates transcriptional control under dynamic inputs.

PubMed

Kellogg, Ryan A; Tay, Savaş

2015-01-29

Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments. Copyright © 2015 Elsevier Inc. All rights reserved.

Noncausal telemetry data recovery techniques

NASA Technical Reports Server (NTRS)

Tsou, H.; Lee, R.; Mileant, A.; Hinedi, S.

1995-01-01

Cost efficiency is becoming a major driver in future space missions. Because of the constraints on total cost, including design, implementation, and operation, future spacecraft are limited in terms of their size power and complexity. Consequently, it is expected that future missions will operate on marginal space-to-ground communication links that, in turn, can pose an additional risk on the successful scientific data return of these missions. For low data-rate and low downlink-margin missions, the buffering of the telemetry signal for further signal processing to improve data return is a possible strategy; it has been adopted for the Galileo S-band mission. This article describes techniques used for postprocessing of buffered telemetry signal segments (called gaps) to recover data lost during acquisition and resynchronization. Two methods, one for a closed-loop and the other one for an open-loop configuration, are discussed in this article. Both of them can be used in either forward or backward processing of signal segments, depending on where a gap is specifically situated in a pass.

A Doppler centroid estimation algorithm for SAR systems optimized for the quasi-homogeneous source

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1989-01-01

Radar signal processing applications frequently require an estimate of the Doppler centroid of a received signal. The Doppler centroid estimate is required for synthetic aperture radar (SAR) processing. It is also required for some applications involving target motion estimation and antenna pointing direction estimation. In some cases, the Doppler centroid can be accurately estimated based on available information regarding the terrain topography, the relative motion between the sensor and the terrain, and the antenna pointing direction. Often, the accuracy of the Doppler centroid estimate can be improved by analyzing the characteristics of the received SAR signal. This kind of signal processing is also referred to as clutterlock processing. A Doppler centroid estimation (DCE) algorithm is described which contains a linear estimator optimized for the type of terrain surface that can be modeled by a quasi-homogeneous source (QHS). Information on the following topics is presented: (1) an introduction to the theory of Doppler centroid estimation; (2) analysis of the performance characteristics of previously reported DCE algorithms; (3) comparison of these analysis results with experimental results; (4) a description and performance analysis of a Doppler centroid estimator which is optimized for a QHS; and (5) comparison of the performance of the optimal QHS Doppler centroid estimator with that of previously reported methods.

Performance analysis of gamma ray spectrometric parameters on digital signal and analog signal processing based MCA systems using NaI(Tl) detector.

PubMed

Kukreti, B M; Sharma, G K

2012-05-01

Accurate and speedy estimations of ppm range uranium and thorium in the geological and rock samples are most useful towards ongoing uranium investigations and identification of favorable radioactive zones in the exploration field areas. In this study with the existing 5 in. × 4 in. NaI(Tl) detector setup, prevailing background and time constraints, an enhanced geometrical setup has been worked out to improve the minimum detection limits for primordial radioelements K(40), U(238) and Th(232). This geometrical setup has been integrated with the newly introduced, digital signal processing based MCA system for the routine spectrometric analysis of low concentration rock samples. Stability performance, during the long counting hours, for digital signal processing MCA system and its predecessor NIM bin based MCA system has been monitored, using the concept of statistical process control. Monitored results, over a time span of few months, have been quantified in terms of spectrometer's parameters such as Compton striping constants and Channel sensitivities, used for evaluating primordial radio element concentrations (K(40), U(238) and Th(232)) in geological samples. Results indicate stable dMCA performance, with a tendency of higher relative variance, about mean, particularly for Compton stripping constants. Copyright © 2012 Elsevier Ltd. All rights reserved.

Vestibular Stochastic Resonance as a Method to Improve Balance Function: Optimization of Stimulus Characteristics

NASA Technical Reports Server (NTRS)

Mulavara, Ajitkumar; Fiedler, Matthew; Kofman, Igor; Peters, Brian; Wood, Scott; Serrador, Jorge; Cohen, Helen; Reschke, Millard; Bloomberg, Jacob

2010-01-01

Stochastic resonance (SR) is a mechanism by which noise can assist and enhance the response of neural systems to relevant sensory signals. Application of imperceptible SR noise coupled with sensory input through the proprioceptive, visual, or vestibular sensory systems has been shown to improve motor function. Specifically, studies have shown that that vestibular electrical stimulation by imperceptible stochastic noise, when applied to normal young and elderly subjects, significantly improved their ocular stabilization reflexes in response to whole-body tilt as well as balance performance during postural disturbances. The goal of this study was to optimize the characteristics of the stochastic vestibular signals for balance performance during standing on an unstable surface. Subjects performed a standardized balance task of standing on a block of 10 cm thick medium density foam with their eyes closed for a total of 40 seconds. Stochastic electrical stimulation was applied to the vestibular system through electrodes placed over the mastoid process behind the ears during the last 20 seconds of the test period. A custom built constant current stimulator with subject isolation delivered the stimulus. Stimulation signals were generated with frequencies in the bandwidth of 1-2 Hz and 0.01-30 Hz. Amplitude of the signals were varied in the range of 0- +/-700 micro amperes with the RMS of the signal increased by 30 micro amperes for each 100 micro amperes increase in the current range. Balance performance was measured using a force plate under the foam block and inertial motion sensors placed on the torso and head segments. Preliminary results indicate that balance performance is improved in the range of 10-25% compared to no stimulation conditions. Subjects improved their performance consistently across the blocks of stimulation. Further the signal amplitude at which the performance was maximized was different in the two frequency ranges. Optimization of the frequency and amplitude of the signal characteristics of the stochastic noise signals on maximizing balance performance will have a significant impact in its development as a unique system to aid recovery of function in astronauts after long duration space flight or for people with balance disorders.

A review of channel selection algorithms for EEG signal processing

NASA Astrophysics Data System (ADS)

Alotaiby, Turky; El-Samie, Fathi E. Abd; Alshebeili, Saleh A.; Ahmad, Ishtiaq

2015-12-01

Digital processing of electroencephalography (EEG) signals has now been popularly used in a wide variety of applications such as seizure detection/prediction, motor imagery classification, mental task classification, emotion classification, sleep state classification, and drug effects diagnosis. With the large number of EEG channels acquired, it has become apparent that efficient channel selection algorithms are needed with varying importance from one application to another. The main purpose of the channel selection process is threefold: (i) to reduce the computational complexity of any processing task performed on EEG signals by selecting the relevant channels and hence extracting the features of major importance, (ii) to reduce the amount of overfitting that may arise due to the utilization of unnecessary channels, for the purpose of improving the performance, and (iii) to reduce the setup time in some applications. Signal processing tools such as time-domain analysis, power spectral estimation, and wavelet transform have been used for feature extraction and hence for channel selection in most of channel selection algorithms. In addition, different evaluation approaches such as filtering, wrapper, embedded, hybrid, and human-based techniques have been widely used for the evaluation of the selected subset of channels. In this paper, we survey the recent developments in the field of EEG channel selection methods along with their applications and classify these methods according to the evaluation approach.

On the importance of preserving the harmonics and neighboring partials prior to vocoder processing: implications for cochlear implants.

PubMed

Hu, Yi; Loizou, Philipos C

2010-01-01

Pre-processing based noise-reduction algorithms used for cochlear implants (CIs) can sometimes introduce distortions which are carried through the vocoder stages of CI processing. While the background noise may be notably suppressed, the harmonic structure and/or spectral envelope of the signal may be distorted. The present study investigates the potential of preserving the signal's harmonic structure in voiced segments (e.g., vowels) as a means of alleviating the negative effects of pre-processing. The hypothesis tested is that preserving the harmonic structure of the signal is crucial for subsequent vocoder processing. The implications of preserving either the main harmonic components occurring at multiples of F0 or the main harmonics along with adjacent partials are investigated. This is done by first pre-processing noisy speech with a conventional noise-reduction algorithm, regenerating the harmonics, and vocoder processing the stimuli with eight channels of stimulation in steady speech-shaped noise. Results indicated that preserving the main low-frequency harmonics (spanning 1 or 3 kHz) alone was not beneficial. Preserving, however, the harmonic structure of the stimulus, i.e., the main harmonics along with the adjacent partials, was found to be critically important and provided substantial improvements (41 percentage points) in intelligibility.

Ghost image in enhanced self-heterodyne synthetic aperture imaging ladar

NASA Astrophysics Data System (ADS)

Zhang, Guo; Sun, Jianfeng; Zhou, Yu; Lu, Zhiyong; Li, Guangyuan; Xu, Mengmeng; Zhang, Bo; Lao, Chenzhe; He, Hongyu

2018-03-01

The enhanced self-heterodyne synthetic aperture imaging ladar (SAIL) self-heterodynes two polarization-orthogonal echo signals to eliminate the phase disturbance caused by atmospheric turbulence and mechanical trembling, uses heterodyne receiver instead of self-heterodyne receiver to improve signal-to-noise ratio. The principle and structure of the enhanced self-heterodyne SAIL are presented. The imaging process of enhanced self-heterodyne SAIL for distributed target is also analyzed. In enhanced self-heterodyne SAIL, the phases of two orthogonal-polarization beams are modulated by four cylindrical lenses in transmitter to improve resolutions in orthogonal direction and travel direction, which will generate ghost image. The generation process of ghost image in enhanced self-heterodyne SAIL is mathematically detailed, and a method of eliminating ghost image is also presented, which is significant for far-distance imaging. A number of experiments of enhanced self-heterodyne SAIL for distributed target are presented, these experimental results verify the theoretical analysis of enhanced self-heterodyne SAIL. The enhanced self-heterodyne SAIL has the capability to eliminate the influence from the atmospheric turbulence and mechanical trembling, has high advantage in detecting weak signals, and has promising application for far-distance ladar imaging.

Affective Aspects of Perceived Loss of Control and Potential Implications for Brain-Computer Interfaces.

PubMed

Grissmann, Sebastian; Zander, Thorsten O; Faller, Josef; Brönstrup, Jonas; Kelava, Augustin; Gramann, Klaus; Gerjets, Peter

2017-01-01

Most brain-computer interfaces (BCIs) focus on detecting single aspects of user states (e.g., motor imagery) in the electroencephalogram (EEG) in order to use these aspects as control input for external systems. This communication can be effective, but unaccounted mental processes can interfere with signals used for classification and thereby introduce changes in the signal properties which could potentially impede BCI classification performance. To improve BCI performance, we propose deploying an approach that potentially allows to describe different mental states that could influence BCI performance. To test this approach, we analyzed neural signatures of potential affective states in data collected in a paradigm where the complex user state of perceived loss of control (LOC) was induced. In this article, source localization methods were used to identify brain dynamics with source located outside but affecting the signal of interest originating from the primary motor areas, pointing to interfering processes in the brain during natural human-machine interaction. In particular, we found affective correlates which were related to perceived LOC. We conclude that additional context information about the ongoing user state might help to improve the applicability of BCIs to real-world scenarios.

Affective Aspects of Perceived Loss of Control and Potential Implications for Brain-Computer Interfaces

PubMed Central

Grissmann, Sebastian; Zander, Thorsten O.; Faller, Josef; Brönstrup, Jonas; Kelava, Augustin; Gramann, Klaus; Gerjets, Peter

2017-01-01

Most brain-computer interfaces (BCIs) focus on detecting single aspects of user states (e.g., motor imagery) in the electroencephalogram (EEG) in order to use these aspects as control input for external systems. This communication can be effective, but unaccounted mental processes can interfere with signals used for classification and thereby introduce changes in the signal properties which could potentially impede BCI classification performance. To improve BCI performance, we propose deploying an approach that potentially allows to describe different mental states that could influence BCI performance. To test this approach, we analyzed neural signatures of potential affective states in data collected in a paradigm where the complex user state of perceived loss of control (LOC) was induced. In this article, source localization methods were used to identify brain dynamics with source located outside but affecting the signal of interest originating from the primary motor areas, pointing to interfering processes in the brain during natural human-machine interaction. In particular, we found affective correlates which were related to perceived LOC. We conclude that additional context information about the ongoing user state might help to improve the applicability of BCIs to real-world scenarios. PMID:28769776

USDA Forest Service mobile satellite communications applications

NASA Technical Reports Server (NTRS)

Warren, John R.

1990-01-01

The airborne IR signal processing system being developed will require the use of mobile satellite communications to achieve its full capability and improvement in delivery timeliness of processed IR data to the Fire Staff. There are numerous other beneficial uses, both during wildland fire management operations or in daily routine tasks, which will also benefit from the availability of reliable communications from remote areas.

Capillary Electrophoresis Sensitivity Enhancement Based on Adaptive Moving Average Method.

PubMed

Drevinskas, Tomas; Telksnys, Laimutis; Maruška, Audrius; Gorbatsova, Jelena; Kaljurand, Mihkel

2018-06-05

In the present work, we demonstrate a novel approach to improve the sensitivity of the "out of lab" portable capillary electrophoretic measurements. Nowadays, many signal enhancement methods are (i) underused (nonoptimal), (ii) overused (distorts the data), or (iii) inapplicable in field-portable instrumentation because of a lack of computational power. The described innovative migration velocity-adaptive moving average method uses an optimal averaging window size and can be easily implemented with a microcontroller. The contactless conductivity detection was used as a model for the development of a signal processing method and the demonstration of its impact on the sensitivity. The frequency characteristics of the recorded electropherograms and peaks were clarified. Higher electrophoretic mobility analytes exhibit higher-frequency peaks, whereas lower electrophoretic mobility analytes exhibit lower-frequency peaks. On the basis of the obtained data, a migration velocity-adaptive moving average algorithm was created, adapted, and programmed into capillary electrophoresis data-processing software. Employing the developed algorithm, each data point is processed depending on a certain migration time of the analyte. Because of the implemented migration velocity-adaptive moving average method, the signal-to-noise ratio improved up to 11 times for sampling frequency of 4.6 Hz and up to 22 times for sampling frequency of 25 Hz. This paper could potentially be used as a methodological guideline for the development of new smoothing algorithms that require adaptive conditions in capillary electrophoresis and other separation methods.

Evaluation of Speech Intelligibility and Sound Localization Abilities with Hearing Aids Using Binaural Wireless Technology.

PubMed

Ibrahim, Iman; Parsa, Vijay; Macpherson, Ewan; Cheesman, Margaret

2013-01-02

Wireless synchronization of the digital signal processing (DSP) features between two hearing aids in a bilateral hearing aid fitting is a fairly new technology. This technology is expected to preserve the differences in time and intensity between the two ears by co-ordinating the bilateral DSP features such as multichannel compression, noise reduction, and adaptive directionality. The purpose of this study was to evaluate the benefits of wireless communication as implemented in two commercially available hearing aids. More specifically, this study measured speech intelligibility and sound localization abilities of normal hearing and hearing impaired listeners using bilateral hearing aids with wireless synchronization of multichannel Wide Dynamic Range Compression (WDRC). Twenty subjects participated; 8 had normal hearing and 12 had bilaterally symmetrical sensorineural hearing loss. Each individual completed the Hearing in Noise Test (HINT) and a sound localization test with two types of stimuli. No specific benefit from wireless WDRC synchronization was observed for the HINT; however, hearing impaired listeners had better localization with the wireless synchronization. Binaural wireless technology in hearing aids may improve localization abilities although the possible effect appears to be small at the initial fitting. With adaptation, the hearing aids with synchronized signal processing may lead to an improvement in localization and speech intelligibility. Further research is required to demonstrate the effect of adaptation to the hearing aids with synchronized signal processing on different aspects of auditory performance.

Under-sampling in a Multiple-Channel Laser Vibrometry System

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

Corey, Jordan

2007-03-01

Laser vibrometry is a technique used to detect vibrations on objects using the interference of coherent light with itself. Most vibrometry systems process only one target location at a time, but processing multiple locations simultaneously provides improved detection capabilities. Traditional laser vibrometry systems employ oversampling to sample the incoming modulated-light signal, however as the number of channels increases in these systems, certain issues arise such a higher computational cost, excessive heat, increased power requirements, and increased component cost. This thesis describes a novel approach to laser vibrometry that utilizes undersampling to control the undesirable issues associated with over-sampled systems. Undersamplingmore » allows for significantly less samples to represent the modulated-light signals, which offers several advantages in the overall system design. These advantages include an improvement in thermal efficiency, lower processing requirements, and a higher immunity to the relative intensity noise inherent in laser vibrometry applications. A unique feature of this implementation is the use of a parallel architecture to increase the overall system throughput. This parallelism is realized using a hierarchical multi-channel architecture based on off-the-shelf programmable logic devices (PLDs).« less

Automated tetraploid genotype calling by hierarchical clustering

USDA-ARS?s Scientific Manuscript database

SNP arrays are transforming breeding and genetics research for autotetraploids. To fully utilize these arrays, however, the relationship between signal intensity and allele dosage must be inferred independently for each marker. We developed an improved computational method to automate this process, ...

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

Ectopic expression of phosphoenolpyruvate carboxylase in Vicia narbonensis seeds: effects of improved nutrient status on seed maturation and transcriptional regulatory networks.

PubMed

Radchuk, Ruslana; Radchuk, Volodymyr; Götz, Klaus-Peter; Weichert, Heiko; Richter, Andreas; Emery, R J Neil; Weschke, Winfriede; Weber, Hans

2007-09-01

Seed maturation responds to endogenous and exogenous signals like nutrient status, energy and hormones. We recently showed that phosphoenolpyruvate carboxylase (PEPC) overexpression in Vicia narbonensis seeds alters seed metabolism and channels carbon into organic acids, resulting in greater seed storage capacity and increased protein content. Thus, these lines represent models with altered sink strength and improved nutrient status. Here we analyse seed developmental and metabolic parameters, and C/N partitioning in these seeds. Transgenic embryos take up more carbon and nitrogen. Changes in dry to FW ratio, seed fill duration and major seed components indicate altered seed development. Array-based gene expression analysis of embryos reveals upregulation of seed metabolism, especially during the transition phase and at late maturation, in terms of protein storage and processing, amino acid metabolism, primary metabolism and transport, energy and mitochondrial activity, transcriptional and translational activity, stress tolerance, photosynthesis, cell proliferation and elongation, signalling and hormone action and regulated protein degradation. Stimulated cell elongation is in accordance with upregulated signalling pathways related to gibberellic acid/brassinosteroids. We discuss that activated organic and amino acid production leads to a wide-range activation of nitrogen metabolism, including the machinery of storage protein synthesis, amino acid synthesis, protein processing and deposition, translational activity and the methylation cycle. We suggest that alpha-ketoglutarate (alpha-KG) and/or oxalacetate provide signals for coordinate upregulation of amino acid biosynthesis. Activation of stress tolerance genes indicates partial overlap between nutrient, stress and abscisic acid (ABA) signals, indicating a common interacting or regulatory mechanism between nutrients, stress and ABA. In conclusion, analysis of PEPC overexpressing seeds identified pathways responsive to metabolic and nutrient control on the transcriptional level and its underlying signalling mechanisms.

Coil-to-coil physiological noise correlations and their impact on fMRI time-series SNR

PubMed Central

Triantafyllou, C.; Polimeni, J. R.; Keil, B.; Wald, L. L.

2017-01-01

Purpose Physiological nuisance fluctuations (“physiological noise”) are a major contribution to the time-series Signal to Noise Ratio (tSNR) of functional imaging. While thermal noise correlations between array coil elements have a well-characterized effect on the image Signal to Noise Ratio (SNR0), the element-to-element covariance matrix of the time-series fluctuations has not yet been analyzed. We examine this effect with a goal of ultimately improving the combination of multichannel array data. Theory and Methods We extend the theoretical relationship between tSNR and SNR0 to include a time-series noise covariance matrix Ψt, distinct from the thermal noise covariance matrix Ψ0, and compare its structure to Ψ0 and the signal coupling matrix SSH formed from the signal intensity vectors S. Results Inclusion of the measured time-series noise covariance matrix into the model relating tSNR and SNR0 improves the fit of experimental multichannel data and is shown to be distinct from Ψ0 or SSH. Conclusion Time-series noise covariances in array coils are found to differ from Ψ0 and more surprisingly, from the signal coupling matrix SSH. Correct characterization of the time-series noise has implications for the analysis of time-series data and for improving the coil element combination process. PMID:26756964

Tailoring noise frequency spectrum between two consecutive second derivative filtering procedures to improve liquid chromatography-mass spectrometry determinations.

PubMed

Wang, Shau-Chun; Lin, Chiao-Juan; Chiang, Shu-Min; Yu, Sung-Nien

2008-03-15

This paper reports a simple chemometric technique to alter the noise spectrum of a liquid chromatography-mass spectrometry (LC-MS) chromatogram between two consecutive second-derivative filter procedures to improve the peak signal-to-noise (S/N) ratio enhancement. This technique is to multiply one second-derivative filtered LC-MS chromatogram with another artificial chromatogram added with thermal noises prior to the other second-derivative filter. Because the second-derivative filter cannot eliminate frequency components within its own filter bandwidth, more efficient peak S/N ratio improvement cannot be accomplished using consecutive second-derivative filter procedures to process LC-MS chromatograms. In contrast, when the second-derivative filtered LC-MS chromatogram is conditioned with the multiplication alteration prior to the other second-derivative filter, much better ratio improvement is achieved. The noise frequency spectrum of the second-derivative filtered chromatogram, which originally contains frequency components within the filter bandwidth, is altered to span a broader range with multiplication operation. When the frequency range of this modified noise spectrum shifts toward the other regimes, the other second-derivative filter, working as a band-pass filter, is able to provide better filtering efficiency to obtain higher peak S/N ratios. Real LC-MS chromatograms, of which 5-fold peak S/N ratio improvement achieved with two consecutive second-derivative filters remains the same S/N ratio improvement using a one-step second-derivative filter, are improved to accomplish much better ratio enhancement, approximately 25-fold or higher when the noise frequency spectrum is modified between two matched filters. The linear standard curve using the filtered LC-MS signals is validated. The filtered LC-MS signals are also more reproducible. The more accurate determinations of very low-concentration samples (S/N ratio about 5-7) are obtained via standard addition procedures using the filtered signals rather than the determinations using the original signals.

Digital multi-channel stabilization of four-mode phase-sensitive parametric multicasting.

PubMed

Liu, Lan; Tong, Zhi; Wiberg, Andreas O J; Kuo, Bill P P; Myslivets, Evgeny; Alic, Nikola; Radic, Stojan

2014-07-28

Stable four-mode phase-sensitive (4MPS) process was investigated as a means to enhance two-pump driven parametric multicasting conversion efficiency (CE) and signal to noise ratio (SNR). Instability of multi-beam, phase sensitive (PS) device that inherently behaves as an interferometer, with output subject to ambient induced fluctuations, was addressed theoretically and experimentally. A new stabilization technique that controls phases of three input waves of the 4MPS multicaster and maximizes CE was developed and described. Stabilization relies on digital phase-locked loop (DPLL) specifically was developed to control pump phases to guarantee stable 4MPS operation that is independent of environmental fluctuations. The technique also controls a single (signal) input phase to optimize the PS-induced improvement of the CE and SNR. The new, continuous-operation DPLL has allowed for fully stabilized PS parametric broadband multicasting, demonstrating CE improvement over 20 signal copies in excess of 10 dB.

Detecting modulated signals in modulated noise: (II) neural thresholds in the songbird forebrain.

PubMed

Bee, Mark A; Buschermöhle, Michael; Klump, Georg M

2007-10-01

Sounds in the real world fluctuate in amplitude. The vertebrate auditory system exploits patterns of amplitude fluctuations to improve signal detection in noise. One experimental paradigm demonstrating these general effects has been used in psychophysical studies of 'comodulation detection difference' (CDD). The CDD effect refers to the fact that thresholds for detecting a modulated, narrowband noise signal are lower when the envelopes of flanking bands of modulated noise are comodulated with each other, but fluctuate independently of the signal compared with conditions in which the envelopes of the signal and flanking bands are all comodulated. Here, we report results from a study of the neural correlates of CDD in European starlings (Sturnus vulgaris). We manipulated: (i) the envelope correlations between a narrowband noise signal and a masker comprised of six flanking bands of noise; (ii) the signal onset delay relative to masker onset; (iii) signal duration; and (iv) masker spectrum level. Masked detection thresholds were determined from neural responses using signal detection theory. Across conditions, the magnitude of neural CDD ranged between 2 and 8 dB, which is similar to that reported in a companion psychophysical study of starlings [U. Langemann & G.M. Klump (2007) Eur. J. Neurosci., 26, 1969-1978]. We found little evidence to suggest that neural CDD resulted from the across-channel processing of auditory grouping cues related to common envelope fluctuations and synchronous onsets between the signal and flanking bands. We discuss a within-channel model of peripheral processing that explains many of our results.

Processing Techniques for Intelligibility Improvement to Speech with Co-Channel Interference.

DTIC Science & Technology

1983-09-01

processing was found to be always less than in the original unprocessed co-channel sig- nali also as the length of the comb filter increased, the...7 D- i35 702 PROCESSING TECHNIQUES FOR INTELLIGIBILITY IMPRO EMENT 1𔃼.TO SPEECH WITH CO-C..(U) SIGNAL TECHNOLOGY INC GOLETACA B A HANSON ET AL SEP...11111111122 11111.25 1111 .4 111.6 MICROCOPY RESOLUTION TEST CHART NATIONAL BUREAU Of STANDARDS- 1963-A RA R.83-225 Set ,’ember 1983 PROCESSING

Being watched: the effect of social self-focus on interoceptive and exteroceptive somatosensory perception.

PubMed

Durlik, Caroline; Cardini, Flavia; Tsakiris, Manos

2014-04-01

We become aware of our bodies interoceptively, by processing signals arising from within the body, and exteroceptively, by processing signals arising on or outside the body. Recent research highlights the importance of the interaction of exteroceptive and interoceptive signals in modulating bodily self-consciousness. The current study investigated the effect of social self-focus, manipulated via a video camera that was facing the participants and that was either switched on or off, on interoceptive sensitivity (using a heartbeat perception task) and on tactile perception (using the Somatic Signal Detection Task (SSDT)). The results indicated a significant effect of self-focus on SSDT performance, but not on interoception. SSDT performance was not moderated by interoceptive sensitivity, although interoceptive sensitivity scores were positively correlated with false alarms, independently of self-focus. Together with previous research, our results suggest that self-focus may exert different effects on body perception depending on its mode (private versus social). While interoception has been previously shown to be enhanced by private self-focus, the current study failed to find an effect of social self-focus on interoceptive sensitivity, instead demonstrating that social self-focus improves exteroceptive somatosensory processing. Copyright © 2014 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

Improvement of the energy resolution via an optimized digital signal processing in GERDA Phase I

DOE PAGES

Agostini, M.; Allardt, M.; Bakalyarov, A. M.; ...

2015-06-09

An optimized digital shaping filter has been developed for the Gerda experiment which searches for neutrinoless double beta decay inmore » $$^{76}$$Ge. The Gerda Phase I energy calibration data have been reprocessed and an average improvement of 0.3 keV in energy resolution (FWHM) corresponding to 10% at the $Q$ value for $$0\

Design and DSP implementation of star image acquisition and star point fast acquiring and tracking

NASA Astrophysics Data System (ADS)

Zhou, Guohui; Wang, Xiaodong; Hao, Zhihang

2006-02-01

Star sensor is a special high accuracy photoelectric sensor. Attitude acquisition time is an important function index of star sensor. In this paper, the design target is to acquire 10 samples per second dynamic performance. On the basis of analyzing CCD signals timing and star image processing, a new design and a special parallel architecture for improving star image processing are presented in this paper. In the design, the operation moving the data in expanded windows including the star to the on-chip memory of DSP is arranged in the invalid period of CCD frame signal. During the CCD saving the star image to memory, DSP processes the data in the on-chip memory. This parallelism greatly improves the efficiency of processing. The scheme proposed here results in enormous savings of memory normally required. In the scheme, DSP HOLD mode and CPLD technology are used to make a shared memory between CCD and DSP. The efficiency of processing is discussed in numerical tests. Only in 3.5ms is acquired the five lightest stars in the star acquisition stage. In 43us, the data in five expanded windows including stars are moved into the internal memory of DSP, and in 1.6ms, five star coordinates are achieved in the star tracking stage.

Optimized signal detection and analysis methods for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Qiyan; Zhou, Quanyu; Yang, Ping; Wang, Xiaoling; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2017-02-01

Melanoma is known as a malignant tumor of melanocytes, which usually appear in the blood circulation at the metastasis stage of cancer. Thus the detection of circulating melanoma cells is useful for early diagnosis and therapy of cancer. Here we have developed an in vivo photoacoustic flow cytometry (PAFC) based on the photoacoustic effect to detect melanoma cells. However, the raw signals we obtain from the target cells contain noises such as environmental sonic noises and electronic noises. Therefore we apply correlation comparison and feature separation methods to the detection and verification of the in vivo signals. Due to similar shape and structure of cells, the photoacoustic signals usually have similar vibration mode. By analyzing the correlations and the signal features in time domain and frequency domain, we are able to provide a method for separating photoacoustic signals generated by target cells from background noises. The method introduced here has proved to optimize the signal acquisition and signal processing, which can improve the detection accuracy in PAFC.

EMD self-adaptive selecting relevant modes algorithm for FBG spectrum signal

NASA Astrophysics Data System (ADS)

Chen, Yong; Wu, Chun-ting; Liu, Huan-lin

2017-07-01

Noise may reduce the demodulation accuracy of fiber Bragg grating (FBG) sensing signal so as to affect the quality of sensing detection. Thus, the recovery of a signal from observed noisy data is necessary. In this paper, a precise self-adaptive algorithm of selecting relevant modes is proposed to remove the noise of signal. Empirical mode decomposition (EMD) is first used to decompose a signal into a set of modes. The pseudo modes cancellation is introduced to identify and eliminate false modes, and then the Mutual Information (MI) of partial modes is calculated. MI is used to estimate the critical point of high and low frequency components. Simulation results show that the proposed algorithm estimates the critical point more accurately than the traditional algorithms for FBG spectral signal. While, compared to the similar algorithms, the signal noise ratio of the signal can be improved more than 10 dB after processing by the proposed algorithm, and correlation coefficient can be increased by 0.5, so it demonstrates better de-noising effect.

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce.

PubMed

Jayapandian, Catherine; Wei, Annan; Ramesh, Priya; Zonjy, Bilal; Lhatoo, Samden D; Loparo, Kenneth; Zhang, Guo-Qiang; Sahoo, Satya S

2015-01-01

Data-driven neuroscience research is providing new insights in progression of neurological disorders and supporting the development of improved treatment approaches. However, the volume, velocity, and variety of neuroscience data generated from sophisticated recording instruments and acquisition methods have exacerbated the limited scalability of existing neuroinformatics tools. This makes it difficult for neuroscience researchers to effectively leverage the growing multi-modal neuroscience data to advance research in serious neurological disorders, such as epilepsy. We describe the development of the Cloudwave data flow that uses new data partitioning techniques to store and analyze electrophysiological signal in distributed computing infrastructure. The Cloudwave data flow uses MapReduce parallel programming algorithm to implement an integrated signal data processing pipeline that scales with large volume of data generated at high velocity. Using an epilepsy domain ontology together with an epilepsy focused extensible data representation format called Cloudwave Signal Format (CSF), the data flow addresses the challenge of data heterogeneity and is interoperable with existing neuroinformatics data representation formats, such as HDF5. The scalability of the Cloudwave data flow is evaluated using a 30-node cluster installed with the open source Hadoop software stack. The results demonstrate that the Cloudwave data flow can process increasing volume of signal data by leveraging Hadoop Data Nodes to reduce the total data processing time. The Cloudwave data flow is a template for developing highly scalable neuroscience data processing pipelines using MapReduce algorithms to support a variety of user applications.

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce

PubMed Central

Jayapandian, Catherine; Wei, Annan; Ramesh, Priya; Zonjy, Bilal; Lhatoo, Samden D.; Loparo, Kenneth; Zhang, Guo-Qiang; Sahoo, Satya S.

2015-01-01

Data-driven neuroscience research is providing new insights in progression of neurological disorders and supporting the development of improved treatment approaches. However, the volume, velocity, and variety of neuroscience data generated from sophisticated recording instruments and acquisition methods have exacerbated the limited scalability of existing neuroinformatics tools. This makes it difficult for neuroscience researchers to effectively leverage the growing multi-modal neuroscience data to advance research in serious neurological disorders, such as epilepsy. We describe the development of the Cloudwave data flow that uses new data partitioning techniques to store and analyze electrophysiological signal in distributed computing infrastructure. The Cloudwave data flow uses MapReduce parallel programming algorithm to implement an integrated signal data processing pipeline that scales with large volume of data generated at high velocity. Using an epilepsy domain ontology together with an epilepsy focused extensible data representation format called Cloudwave Signal Format (CSF), the data flow addresses the challenge of data heterogeneity and is interoperable with existing neuroinformatics data representation formats, such as HDF5. The scalability of the Cloudwave data flow is evaluated using a 30-node cluster installed with the open source Hadoop software stack. The results demonstrate that the Cloudwave data flow can process increasing volume of signal data by leveraging Hadoop Data Nodes to reduce the total data processing time. The Cloudwave data flow is a template for developing highly scalable neuroscience data processing pipelines using MapReduce algorithms to support a variety of user applications. PMID:25852536

P-code enhanced method for processing encrypted GPS signals without knowledge of the encryption code

NASA Technical Reports Server (NTRS)

Young, Lawrence E. (Inventor); Meehan, Thomas K. (Inventor); Thomas, Jr., Jess Brooks (Inventor)

2000-01-01

In the preferred embodiment, an encrypted GPS signal is down-converted from RF to baseband to generate two quadrature components for each RF signal (L1 and L2). Separately and independently for each RF signal and each quadrature component, the four down-converted signals are counter-rotated with a respective model phase, correlated with a respective model P code, and then successively summed and dumped over presum intervals substantially coincident with chips of the respective encryption code. Without knowledge of the encryption-code signs, the effect of encryption-code sign flips is then substantially reduced by selected combinations of the resulting presums between associated quadrature components for each RF signal, separately and independently for the L1 and L2 signals. The resulting combined presums are then summed and dumped over longer intervals and further processed to extract amplitude, phase and delay for each RF signal. Precision of the resulting phase and delay values is approximately four times better than that obtained from straight cross-correlation of L1 and L2. This improved method provides the following options: separate and independent tracking of the L1-Y and L2-Y channels; separate and independent measurement of amplitude, phase and delay L1-Y channel; and removal of the half-cycle ambiguity in L1-Y and L2-Y carrier phase.

Review of Sparse Representation-Based Classification Methods on EEG Signal Processing for Epilepsy Detection, Brain-Computer Interface and Cognitive Impairment

PubMed Central

Wen, Dong; Jia, Peilei; Lian, Qiusheng; Zhou, Yanhong; Lu, Chengbiao

2016-01-01

At present, the sparse representation-based classification (SRC) has become an important approach in electroencephalograph (EEG) signal analysis, by which the data is sparsely represented on the basis of a fixed dictionary or learned dictionary and classified based on the reconstruction criteria. SRC methods have been used to analyze the EEG signals of epilepsy, cognitive impairment and brain computer interface (BCI), which made rapid progress including the improvement in computational accuracy, efficiency and robustness. However, these methods have deficiencies in real-time performance, generalization ability and the dependence of labeled sample in the analysis of the EEG signals. This mini review described the advantages and disadvantages of the SRC methods in the EEG signal analysis with the expectation that these methods can provide the better tools for analyzing EEG signals. PMID:27458376

High-speed spectral domain optical coherence tomography using non-uniform fast Fourier transform

PubMed Central

Chan, Kenny K. H.; Tang, Shuo

2010-01-01

The useful imaging range in spectral domain optical coherence tomography (SD-OCT) is often limited by the depth dependent sensitivity fall-off. Processing SD-OCT data with the non-uniform fast Fourier transform (NFFT) can improve the sensitivity fall-off at maximum depth by greater than 5dB concurrently with a 30 fold decrease in processing time compared to the fast Fourier transform with cubic spline interpolation method. NFFT can also improve local signal to noise ratio (SNR) and reduce image artifacts introduced in post-processing. Combined with parallel processing, NFFT is shown to have the ability to process up to 90k A-lines per second. High-speed SD-OCT imaging is demonstrated at camera-limited 100 frames per second on an ex-vivo squid eye. PMID:21258551

Robust high-resolution quantification of time signals encoded by in vivo magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Belkić, Dževad; Belkić, Karen

2018-01-01

This paper on molecular imaging emphasizes improving specificity of magnetic resonance spectroscopy (MRS) for early cancer diagnostics by high-resolution data analysis. Sensitivity of magnetic resonance imaging (MRI) is excellent, but specificity is insufficient. Specificity is improved with MRS by going beyond morphology to assess the biochemical content of tissue. This is contingent upon accurate data quantification of diagnostically relevant biomolecules. Quantification is spectral analysis which reconstructs chemical shifts, amplitudes and relaxation times of metabolites. Chemical shifts inform on electronic shielding of resonating nuclei bound to different molecular compounds. Oscillation amplitudes in time signals retrieve the abundance of MR sensitive nuclei whose number is proportional to metabolite concentrations. Transverse relaxation times, the reciprocal of decay probabilities of resonances, arise from spin-spin coupling and reflect local field inhomogeneities. In MRS single voxels are used. For volumetric coverage, multi-voxels are employed within a hybrid of MRS and MRI called magnetic resonance spectroscopic imaging (MRSI). Common to MRS and MRSI is encoding of time signals and subsequent spectral analysis. Encoded data do not provide direct clinical information. Spectral analysis of time signals can yield the quantitative information, of which metabolite concentrations are the most clinically important. This information is equivocal with standard data analysis through the non-parametric, low-resolution fast Fourier transform and post-processing via fitting. By applying the fast Padé transform (FPT) with high-resolution, noise suppression and exact quantification via quantum mechanical signal processing, advances are made, presented herein, focusing on four areas of critical public health importance: brain, prostate, breast and ovarian cancers.

A hybrid method based on Band Pass Filter and Correlation Algorithm to improve debris sensor capacity

NASA Astrophysics Data System (ADS)

Hong, Wei; Wang, Shaoping; Liu, Haokuo; Tomovic, Mileta M.; Chao, Zhang

2017-01-01

The inductive debris detection is an effective method for monitoring mechanical wear, and could be used to prevent serious accidents. However, debris detection during early phase of mechanical wear, when small debris (<100 um) is generated, requires that the sensor has high sensitivity with respect to background noise. In order to detect smaller debris by existing sensors, this paper presents a hybrid method which combines Band Pass Filter and Correlation Algorithm to improve sensor signal-to-noise ratio (SNR). The simulation results indicate that the SNR will be improved at least 2.67 times after signal processing. In other words, this method ensures debris identification when the sensor's SNR is bigger than -3 dB. Thus, smaller debris will be detected in the same SNR. Finally, effectiveness of the proposed method is experimentally validated.

Improving MEG source localizations: an automated method for complete artifact removal based on independent component analysis.

PubMed

Mantini, D; Franciotti, R; Romani, G L; Pizzella, V

2008-03-01

The major limitation for the acquisition of high-quality magnetoencephalography (MEG) recordings is the presence of disturbances of physiological and technical origins: eye movements, cardiac signals, muscular contractions, and environmental noise are serious problems for MEG signal analysis. In the last years, multi-channel MEG systems have undergone rapid technological developments in terms of noise reduction, and many processing methods have been proposed for artifact rejection. Independent component analysis (ICA) has already shown to be an effective and generally applicable technique for concurrently removing artifacts and noise from the MEG recordings. However, no standardized automated system based on ICA has become available so far, because of the intrinsic difficulty in the reliable categorization of the source signals obtained with this technique. In this work, approximate entropy (ApEn), a measure of data regularity, is successfully used for the classification of the signals produced by ICA, allowing for an automated artifact rejection. The proposed method has been tested using MEG data sets collected during somatosensory, auditory and visual stimulation. It was demonstrated to be effective in attenuating both biological artifacts and environmental noise, in order to reconstruct clear signals that can be used for improving brain source localizations.

Firmware Development Improves System Efficiency

NASA Technical Reports Server (NTRS)

Chern, E. James; Butler, David W.

1993-01-01

Most manufacturing processes require physical pointwise positioning of the components or tools from one location to another. Typical mechanical systems utilize either stop-and-go or fixed feed-rate procession to accomplish the task. The first approach achieves positional accuracy but prolongs overall time and increases wear on the mechanical system. The second approach sustains the throughput but compromises positional accuracy. A computer firmware approach has been developed to optimize this point wise mechanism by utilizing programmable interrupt controls to synchronize engineering processes 'on the fly'. This principle has been implemented in an eddy current imaging system to demonstrate the improvement. Software programs were developed that enable a mechanical controller card to transmit interrupts to a system controller as a trigger signal to initiate an eddy current data acquisition routine. The advantages are: (1) optimized manufacturing processes, (2) increased throughput of the system, (3) improved positional accuracy, and (4) reduced wear and tear on the mechanical system.

Relationship Among Signal Fidelity, Hearing Loss, and Working Memory for Digital Noise Suppression.

PubMed

Arehart, Kathryn; Souza, Pamela; Kates, James; Lunner, Thomas; Pedersen, Michael Syskind

2015-01-01

This study considered speech modified by additive babble combined with noise-suppression processing. The purpose was to determine the relative importance of the signal modifications, individual peripheral hearing loss, and individual cognitive capacity on speech intelligibility and speech quality. The participant group consisted of 31 individuals with moderate high-frequency hearing loss ranging in age from 51 to 89 years (mean = 69.6 years). Speech intelligibility and speech quality were measured using low-context sentences presented in babble at several signal-to-noise ratios. Speech stimuli were processed with a binary mask noise-suppression strategy with systematic manipulations of two parameters (error rate and attenuation values). The cumulative effects of signal modification produced by babble and signal processing were quantified using an envelope-distortion metric. Working memory capacity was assessed with a reading span test. Analysis of variance was used to determine the effects of signal processing parameters on perceptual scores. Hierarchical linear modeling was used to determine the role of degree of hearing loss and working memory capacity in individual listener response to the processed noisy speech. The model also considered improvements in envelope fidelity caused by the binary mask and the degradations to envelope caused by error and noise. The participants showed significant benefits in terms of intelligibility scores and quality ratings for noisy speech processed by the ideal binary mask noise-suppression strategy. This benefit was observed across a range of signal-to-noise ratios and persisted when up to a 30% error rate was introduced into the processing. Average intelligibility scores and average quality ratings were well predicted by an objective metric of envelope fidelity. Degree of hearing loss and working memory capacity were significant factors in explaining individual listener's intelligibility scores for binary mask processing applied to speech in babble. Degree of hearing loss and working memory capacity did not predict listeners' quality ratings. The results indicate that envelope fidelity is a primary factor in determining the combined effects of noise and binary mask processing for intelligibility and quality of speech presented in babble noise. Degree of hearing loss and working memory capacity are significant factors in explaining variability in listeners' speech intelligibility scores but not in quality ratings.

Sensor, signal, and image informatics - state of the art and current topics.

PubMed

Lehmann, T M; Aach, T; Witte, H

2006-01-01

The number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments. Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CT-based diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ. The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered. Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.

Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation.

PubMed

Baumgärtel, Regina M; Krawczyk-Becker, Martin; Marquardt, Daniel; Völker, Christoph; Hu, Hongmei; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Ernst, Stephan M A; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-12-30

In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibility. Four distinct, reverberant scenarios were created to reflect everyday listening situations: a stationary speech-shaped noise, a multitalker babble noise, a single interfering talker, and a realistic cafeteria noise. Three instrumental measures were employed to assess predicted speech intelligibility and predicted sound quality: the intelligibility-weighted signal-to-noise ratio, the short-time objective intelligibility measure, and the perceptual evaluation of speech quality. The results show substantial improvements in predicted speech intelligibility as well as sound quality for the proposed algorithms. The evaluated coherence-based noise reduction algorithm was able to provide improvements in predicted audio signal quality. For the tested single-channel noise reduction algorithm, improvements in intelligibility-weighted signal-to-noise ratio were observed in all but the nonstationary cafeteria ambient noise scenario. Binaural minimum variance distortionless response beamforming algorithms performed particularly well in all noise scenarios. © The Author(s) 2015.

Comparing Binaural Pre-processing Strategies I

PubMed Central

Krawczyk-Becker, Martin; Marquardt, Daniel; Völker, Christoph; Hu, Hongmei; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Ernst, Stephan M. A.; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-01-01

In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibility. Four distinct, reverberant scenarios were created to reflect everyday listening situations: a stationary speech-shaped noise, a multitalker babble noise, a single interfering talker, and a realistic cafeteria noise. Three instrumental measures were employed to assess predicted speech intelligibility and predicted sound quality: the intelligibility-weighted signal-to-noise ratio, the short-time objective intelligibility measure, and the perceptual evaluation of speech quality. The results show substantial improvements in predicted speech intelligibility as well as sound quality for the proposed algorithms. The evaluated coherence-based noise reduction algorithm was able to provide improvements in predicted audio signal quality. For the tested single-channel noise reduction algorithm, improvements in intelligibility-weighted signal-to-noise ratio were observed in all but the nonstationary cafeteria ambient noise scenario. Binaural minimum variance distortionless response beamforming algorithms performed particularly well in all noise scenarios. PMID:26721920

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.

Integrated CMOS photodetectors and signal processing for very low-level chemical sensing with the bioluminescent bioreporter integrated circuit

NASA Technical Reports Server (NTRS)

Bolton, Eric K.; Sayler, Gary S.; Nivens, David E.; Rochelle, James M.; Ripp, Steven; Simpson, Michael L.

2002-01-01

We report an integrated CMOS microluminometer optimized for the detection of low-level bioluminescence as part of the bioluminescent bioreporter integrated circuit (BBIC). This microluminometer improves on previous devices through careful management of the sub-femtoampere currents, both signal and leakage, that flow in the front-end processing circuitry. In particular, the photodiode is operated with a reverse bias of only a few mV, requiring special attention to the reset circuitry of the current-to-frequency converter (CFC) that forms the front-end circuit. We report a sub-femtoampere leakage current and a minimum detectable signal (MDS) of 0.15 fA (1510 s integration time) using a room temperature 1.47 mm2 CMOS photodiode. This microluminometer can detect luminescence from as few as 5000 fully induced Pseudomonas fluorescens 5RL bacterial cells. c2002 Elsevier Science B.V. All rights reserved.

Advanced linear and nonlinear compensations for 16QAM SC-400G unrepeatered transmission system

NASA Astrophysics Data System (ADS)

Zhang, Junwen; Yu, Jianjun; Chien, Hung-Chang

2018-02-01

Digital signal processing (DSP) with both linear equalization and nonlinear compensations are studied in this paper for the single-carrier 400G system based on 65-GBaud 16-quadrature amplitude modulation (QAM) signals. The 16-QAM signals are generated and pre-processed with pre-equalization (Pre-EQ) and Look-up-Table (LUT) based pre-distortion (Pre-DT) at the transmitter (Tx)-side. The implementation principle of training-based equalization and pre-distortion are presented here in this paper with experimental studies. At the receiver (Rx)-side, fiber-nonlinearity compensation based on digital backward propagation (DBP) are also utilized to further improve the transmission performances. With joint LUT-based Pre-DT and DBP-based post-compensation to mitigate the opto-electronic components and fiber nonlinearity impairments, we demonstrate the unrepeatered transmission of 1.6Tb/s based on 4-lane 400G single-carrier PDM-16QAM over 205-km SSMF without distributed amplifier.

Laser Calibration of an Impact Disdrometer

NASA Technical Reports Server (NTRS)

Lane, John E.; Kasparis, Takis; Metzger, Philip T.; Jones, W. Linwood

2014-01-01

A practical approach to developing an operational low-cost disdrometer hinges on implementing an effective in situ adaptive calibration strategy. This calibration strategy lowers the cost of the device and provides a method to guarantee continued automatic calibration. In previous work, a collocated tipping bucket rain gauge was utilized to provide a calibration signal to the disdrometer's digital signal processing software. Rainfall rate is proportional to the 11/3 moment of the drop size distribution (a 7/2 moment can also be assumed, depending on the choice of terminal velocity relationship). In the previous case, the disdrometer calibration was characterized and weighted to the 11/3 moment of the drop size distribution (DSD). Optical extinction by rainfall is proportional to the 2nd moment of the DSD. Using visible laser light as a means to focus and generate an auxiliary calibration signal, the adaptive calibration processing is significantly improved.

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.

A new methodology for vibration error compensation of optical encoders.

PubMed

Lopez, Jesus; Artes, Mariano

2012-01-01

Optical encoders are sensors based on grating interference patterns. Tolerances inherent to the manufacturing process can induce errors in the position accuracy as the measurement signals stand apart from the ideal conditions. In case the encoder is working under vibrations, the oscillating movement of the scanning head is registered by the encoder system as a displacement, introducing an error into the counter to be added up to graduation, system and installation errors. Behavior improvement can be based on different techniques trying to compensate the error from measurement signals processing. In this work a new "ad hoc" methodology is presented to compensate the error of the encoder when is working under the influence of vibration. The methodology is based on fitting techniques to the Lissajous figure of the deteriorated measurement signals and the use of a look up table, giving as a result a compensation procedure in which a higher accuracy of the sensor is obtained.

Implantable electronics: emerging design issues and an ultra light-weight security solution.

PubMed

Narasimhan, Seetharam; Wang, Xinmu; Bhunia, Swarup

2010-01-01

Implantable systems that monitor biological signals require increasingly complex digital signal processing (DSP) electronics for real-time in-situ analysis and compression of the recorded signals. While it is well-known that such signal processing hardware needs to be implemented under tight area and power constraints, new design requirements emerge with their increasing complexity. Use of nanoscale technology shows tremendous benefits in implementing these advanced circuits due to dramatic improvement in integration density and power dissipation per operation. However, it also brings in new challenges such as reliability and large idle power (due to higher leakage current). Besides, programmability of the device as well as security of the recorded information are rapidly becoming major design considerations of such systems. In this paper, we analyze the emerging issues associated with the design of the DSP unit in an implantable system. Next, we propose a novel ultra light-weight solution to address the information security issue. Unlike the conventional information security approaches like data encryption, which come at large area and power overhead and hence are not amenable for resource-constrained implantable systems, we propose a multilevel key-based scrambling algorithm, which exploits the nature of the biological signal to effectively obfuscate it. Analysis of the proposed algorithm in the context of neural signal processing and its hardware implementation shows that we can achieve high level of security with ∼ 13X lower power and ∼ 5X lower area overhead than conventional cryptographic solutions.

SPEECH PERCEPTION AS A TALKER-CONTINGENT PROCESS

PubMed Central

Nygaard, Lynne C.; Sommers, Mitchell S.; Pisoni, David B.

2011-01-01

To determine how familiarity with a talker’s voice affects perception of spoken words, we trained two groups of subjects to recognize a set of voices over a 9-day period. One group then identified novel words produced by the same set of talkers at four signal-to-noise ratios. Control subjects identified the same words produced by a different set of talkers. The results showed that the ability to identify a talker’s voice improved intelligibility of novel words produced by that talker. The results suggest that speech perception may involve talker-contingent processes whereby perceptual learning of aspects of the vocal source facilitates the subsequent phonetic analysis of the acoustic signal. PMID:21526138

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.

Creative reflections-the strategic use of reflections in multitrack music production

NASA Astrophysics Data System (ADS)

Case, Alexander

2005-09-01

There is a long tradition of deliberately capturing and even synthesizing early reflections to enhance the music intended for loudspeaker playback. The desire to improve or at least alter the quality, audibility, intelligibility, stereo width, and/or uniqueness of the audio signal guides the recording engineer's use of the recording space, influences their microphone selection and placement, and inspires countless signal-processing approaches. This paper reviews contemporary multitrack production techniques that specifically take advantage of reflected sound energy for musical benefit.

Two-Dimensional Signal Processing and Storage and Theory and Applications of Electromagnetic Measurements.

DTIC Science & Technology

1984-06-01

and shift varying deblurring of images. mui W AcCOan~MP ins Several of the techniques which have been investigated under this work unit are based upon...concern with the use of these iterative algorithms for deconvolution is the effect of noise on the restoration. In the absence of constraints on the...perform badly in the presence of broadband noise . An ad A hoc procedure which improves performance is to prefilter the data to enhance the signal-to

Detecting the crankshaft torsional vibration of diesel engines for combustion related diagnosis

NASA Astrophysics Data System (ADS)

Charles, P.; Sinha, Jyoti K.; Gu, F.; Lidstone, L.; Ball, A. D.

2009-04-01

Early fault detection and diagnosis for medium-speed diesel engines is important to ensure reliable operation throughout the course of their service. This work presents an investigation of the diesel engine combustion related fault detection capability of crankshaft torsional vibration. The encoder signal, often used for shaft speed measurement, has been used to construct the instantaneous angular speed (IAS) waveform, which actually represents the signature of the torsional vibration. Earlier studies have shown that the IAS signal and its fast Fourier transform (FFT) analysis are effective for monitoring engines with less than eight cylinders. The applicability to medium-speed engines, however, is strongly contested due to the high number of cylinders and large moment of inertia. Therefore the effectiveness of the FFT-based approach has further been enhanced by improving the signal processing to determine the IAS signal and subsequently tested on a 16-cylinder engine. In addition, a novel method of presentation, based on the polar coordinate system of the IAS signal, has also been introduced; to improve the discrimination features of the faults compared to the FFT-based approach of the IAS signal. The paper discusses two typical experimental studies on 16- and 20-cylinder engines, with and without faults, and the diagnosis results by the proposed polar presentation method. The results were also compared with the earlier FFT-based method of the IAS signal.

Compensated individually addressable array technology for human breast imaging

DOEpatents

Lewis, D. Kent

2003-01-01

A method of forming broad bandwidth acoustic or microwave beams which encompass array design, array excitation, source signal preprocessing, and received signal postprocessing. This technique uses several different methods to achieve improvement over conventional array systems. These methods are: 1) individually addressable array elements; 2) digital-to-analog converters for the source signals; 3) inverse filtering from source precompensation; and 4) spectral extrapolation to expand the bandwidth of the received signals. The components of the system will be used as follows: 1) The individually addressable array allows scanning around and over an object, such as a human breast, without any moving parts. The elements of the array are broad bandwidth elements and efficient radiators, as well as detectors. 2) Digital-to-analog converters as the source signal generators allow virtually any radiated field to be created in the half-space in front of the array. 3) Preprocessing allows for corrections in the system, most notably in the response of the individual elements and in the ability to increase contrast and resolution of signal propagating through the medium under investigation. 4) Postprocessing allows the received broad bandwidth signals to be expanded in a process similar to analytic continuation. Used together, the system allows for compensation to create beams of any desired shape, control the wave fields generated to correct for medium differences, and improve contract and resolution in and through the medium.

Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes.

PubMed

Foo, Mathias; Kim, Jongrae; Sawlekar, Rucha; Bates, Declan G

2017-04-06

Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a 'subtractor' that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a biomolecular controller that allows tracking of required changes in the outputs of enzymatic reaction processes can be designed and implemented within the framework of chemical reaction network theory. The controller architecture employs an inversion-based feedforward controller that compensates for the limitations of the one-sided subtractor that generates the error signals for a feedback controller. The proposed approach requires significantly fewer chemical reactions to implement than alternative designs, and should have wide applicability throughout the fields of synthetic biology and biological engineering.

Using Seismic and Infrasonic Data to Identify Persistent Sources

NASA Astrophysics Data System (ADS)

Nava, S.; Brogan, R.

2014-12-01

Data from seismic and infrasound sensors were combined to aid in the identification of persistent sources such as mining-related explosions. It is of interest to operators of seismic networks to identify these signals in their event catalogs. Acoustic signals below the threshold of human hearing, in the frequency range of ~0.01 to 20 Hz are classified as infrasound. Persistent signal sources are useful as ground truth data for the study of atmospheric infrasound signal propagation, identification of manmade versus naturally occurring seismic sources, and other studies. By using signals emanating from the same location, propagation studies, for example, can be conducted using a variety of atmospheric conditions, leading to improvements to the modeling process for eventual use where the source is not known. We present results from several studies to identify ground truth sources using both seismic and infrasound data.

New Insight into the Role of Reactive Oxygen Species (ROS) in Cellular Signal-Transduction Processes.

PubMed

Russell, Eileen G; Cotter, Thomas G

2015-01-01

Reactive oxygen species (ROS) were once considered to be deleterious agents, contributing to a vast range of pathologies. But, now their protective effects are being appreciated. Both their damaging and beneficial effects are initiated when they target distinct molecules and consequently begin functioning as part of complex signal-transduction pathways. The recognition of ROS as signaling mediators has driven a wealth of research into their roles in both normal and pathophysiological states. The present review assesses the relevant recent literature to outline the current perspectives on redox-signaling mechanisms, physiological implications, and therapeutic strategies. This study highlights that a more fundamental knowledge about many aspects of redox signaling will allow better targeting of ROS, which would in turn improve prophylactic and pharmacotherapy for redox-associated diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar

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

Sen, Satyabrata

We propose a peak-to-average power ratio (PAPR) constrained Pareto-optimal waveform design approach for an orthogonal frequency division multiplexing (OFDM) radar signal to detect a target using the space-time adaptive processing (STAP) technique. The use of an OFDM signal does not only increase the frequency diversity of our system, but also enables us to adaptively design the OFDM coefficients in order to further improve the system performance. First, we develop a parametric OFDM-STAP measurement model by considering the effects of signaldependent clutter and colored noise. Then, we observe that the resulting STAP-performance can be improved by maximizing the output signal-to-interference-plus-noise ratiomore » (SINR) with respect to the signal parameters. However, in practical scenarios, the computation of output SINR depends on the estimated values of the spatial and temporal frequencies and target scattering responses. Therefore, we formulate a PAPR-constrained multi-objective optimization (MOO) problem to design the OFDM spectral parameters by simultaneously optimizing four objective functions: maximizing the output SINR, minimizing two separate Cramer-Rao bounds (CRBs) on the normalized spatial and temporal frequencies, and minimizing the trace of CRB matrix on the target scattering coefficients estimations. We present several numerical examples to demonstrate the achieved performance improvement due to the adaptive waveform design.« less

Method and apparatus for optical encoding with compressible imaging

NASA Technical Reports Server (NTRS)

Leviton, Douglas B. (Inventor)

2006-01-01

The present invention presents an optical encoder with increased conversion rates. Improvement in the conversion rate is a result of combining changes in the pattern recognition encoder's scale pattern with an image sensor readout technique which takes full advantage of those changes, and lends itself to operation by modern, high-speed, ultra-compact microprocessors and digital signal processors (DSP) or field programmable gate array (FPGA) logic elements which can process encoder scale images at the highest speeds. Through these improvements, all three components of conversion time (reciprocal conversion rate)--namely exposure time, image readout time, and image processing time--are minimized.

Method For Enhanced Gas Monitoring In High Density Flow Streams

DOEpatents

Von Drasek, William A.; Mulderink, Kenneth A.; Marin, Ovidiu

2005-09-13

A method for conducting laser absorption measurements in high temperature process streams having high levels of particulate matter is disclosed. An impinger is positioned substantially parallel to a laser beam propagation path and at upstream position relative to the laser beam. Beam shielding pipes shield the beam from the surrounding environment. Measurement is conducted only in the gap between the two shielding pipes where the beam propagates through the process gas. The impinger facilitates reduced particle presence in the measurement beam, resulting in improved SNR (signal-to-noise) and improved sensitivity and dynamic range of the measurement.

Biological Signal Processing with a Genetic Toggle Switch

PubMed Central

Hillenbrand, Patrick; Fritz, Georg; Gerland, Ulrich

2013-01-01

Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems. PMID:23874595

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.

Aquifers as indicators of volcanic unrest - models of hydrological responses to magmatic activity and their geophysical signals

NASA Astrophysics Data System (ADS)

Strehlow, Karen; Gottsmann, Jo

2014-05-01

Aquifers respond to and modify the surface expressions of magmatic activity, and they can also become agents of unrest themselves. Therefore, monitoring the hydrology can provide a valuable window into subsurface processes in volcanic areas. Interpretations of unrest signals as groundwater responses to changes in the magmatic system can be found for many volcanoes. Changes in temperature and strain conditions, seismic excitation or the injection of magmatic fluids into hydrothermal systems are just a few of the proposed processes induced by magmatic activity that affect the local hydrology. Aquifer responses are described to include changes in water table levels, changes in temperature or composition of hydrothermal waters and pore pressure-induced ground deformation. We can observe these effects at the surface via geophysical and geochemical signals. To fully to utilise these indicators as monitoring and forecasting tools, however, it is necessary to improve our still poor understanding of the ongoing mechanisms in the interactions of hydrological and magmatic systems. An extensive literature research provided an overview on reported effects, which we investigate in detail using numerical modelling. The hydrogeophysical study uses finite element analysis to quantitatively test proposed mechanisms of aquifer excitation and the resultant geophysical signals. We present a set of generic models for two typical volcanic landforms - a stratovolcano and a caldera - that simulate the interaction between deeper magmatic systems with shallow-seated aquifers, focusing on strain and temperature effects. They predict pore pressure induced hydraulic head changes in the aquifer as well as changing groundwater temperatures and strain induced fluid migration. Volcano observatories can track these hydrological effects for example with potential field investigations or the monitoring of wells. The models allow us to explore the parameter space, contributing to a better understanding of the coupling of these two highly complex systems. Our results provide further insight into the subsurface processes at volcanic systems and will aid the evaluation of unrest signals with potential for improved eruption forecasting.

Enhanced Positioning Algorithm of ARPS for Improving Accuracy and Expanding Service Coverage

PubMed Central

Lee, Kyuman; Baek, Hoki; Lim, Jaesung

2016-01-01

The airborne relay-based positioning system (ARPS), which employs the relaying of navigation signals, was proposed as an alternative positioning system. However, the ARPS has limitations, such as relatively large vertical error and service restrictions, because firstly, the user position is estimated based on airborne relays that are located in one direction, and secondly, the positioning is processed using only relayed navigation signals. In this paper, we propose an enhanced positioning algorithm to improve the performance of the ARPS. The main idea of the enhanced algorithm is the adaptable use of either virtual or direct measurements of reference stations in the calculation process based on the structural features of the ARPS. Unlike the existing two-step algorithm for airborne relay and user positioning, the enhanced algorithm is divided into two cases based on whether the required number of navigation signals for user positioning is met. In the first case, where the number of signals is greater than four, the user first estimates the positions of the airborne relays and its own initial position. Then, the user position is re-estimated by integrating a virtual measurement of a reference station that is calculated using the initial estimated user position and known reference positions. To prevent performance degradation, the re-estimation is performed after determining its requirement through comparing the expected position errors. If the navigation signals are insufficient, such as when the user is outside of airborne relay coverage, the user position is estimated by additionally using direct signal measurements of the reference stations in place of absent relayed signals. The simulation results demonstrate that a higher accuracy level can be achieved because the user position is estimated based on the measurements of airborne relays and a ground station. Furthermore, the service coverage is expanded by using direct measurements of reference stations for user positioning. PMID:27529252

Enhanced Positioning Algorithm of ARPS for Improving Accuracy and Expanding Service Coverage.

PubMed

Lee, Kyuman; Baek, Hoki; Lim, Jaesung

2016-08-12

The airborne relay-based positioning system (ARPS), which employs the relaying of navigation signals, was proposed as an alternative positioning system. However, the ARPS has limitations, such as relatively large vertical error and service restrictions, because firstly, the user position is estimated based on airborne relays that are located in one direction, and secondly, the positioning is processed using only relayed navigation signals. In this paper, we propose an enhanced positioning algorithm to improve the performance of the ARPS. The main idea of the enhanced algorithm is the adaptable use of either virtual or direct measurements of reference stations in the calculation process based on the structural features of the ARPS. Unlike the existing two-step algorithm for airborne relay and user positioning, the enhanced algorithm is divided into two cases based on whether the required number of navigation signals for user positioning is met. In the first case, where the number of signals is greater than four, the user first estimates the positions of the airborne relays and its own initial position. Then, the user position is re-estimated by integrating a virtual measurement of a reference station that is calculated using the initial estimated user position and known reference positions. To prevent performance degradation, the re-estimation is performed after determining its requirement through comparing the expected position errors. If the navigation signals are insufficient, such as when the user is outside of airborne relay coverage, the user position is estimated by additionally using direct signal measurements of the reference stations in place of absent relayed signals. The simulation results demonstrate that a higher accuracy level can be achieved because the user position is estimated based on the measurements of airborne relays and a ground station. Furthermore, the service coverage is expanded by using direct measurements of reference stations for user positioning.

Background noise exerts diverse effects on the cortical encoding of foreground sounds.

PubMed

Malone, B J; Heiser, Marc A; Beitel, Ralph E; Schreiner, Christoph E

2017-08-01

In natural listening conditions, many sounds must be detected and identified in the context of competing sound sources, which function as background noise. Traditionally, noise is thought to degrade the cortical representation of sounds by suppressing responses and increasing response variability. However, recent studies of neural network models and brain slices have shown that background synaptic noise can improve the detection of signals. Because acoustic noise affects the synaptic background activity of cortical networks, it may improve the cortical responses to signals. We used spike train decoding techniques to determine the functional effects of a continuous white noise background on the responses of clusters of neurons in auditory cortex to foreground signals, specifically frequency-modulated sweeps (FMs) of different velocities, directions, and amplitudes. Whereas the addition of noise progressively suppressed the FM responses of some cortical sites in the core fields with decreasing signal-to-noise ratios (SNRs), the stimulus representation remained robust or was even significantly enhanced at specific SNRs in many others. Even though the background noise level was typically not explicitly encoded in cortical responses, significant information about noise context could be decoded from cortical responses on the basis of how the neural representation of the foreground sweeps was affected. These findings demonstrate significant diversity in signal in noise processing even within the core auditory fields that could support noise-robust hearing across a wide range of listening conditions. NEW & NOTEWORTHY The ability to detect and discriminate sounds in background noise is critical for our ability to communicate. The neural basis of robust perceptual performance in noise is not well understood. We identified neuronal populations in core auditory cortex of squirrel monkeys that differ in how they process foreground signals in background noise and that may contribute to robust signal representation and discrimination in acoustic environments with prominent background noise. Copyright © 2017 the American Physiological Society.

Reliability improvement methods for sapphire fiber temperature sensors

NASA Astrophysics Data System (ADS)

Schietinger, C.; Adams, B.

1991-08-01

Mechanical, optical, electrical, and software design improvements can be brought to bear in the enhancement of fiber-optic sapphire-fiber temperature measurement tool reliability in harsh environments. The optical fiber thermometry (OFT) equipment discussed is used in numerous process industries and generally involves a sapphire sensor, an optical transmission cable, and a microprocessor-based signal analyzer. OFT technology incorporating sensors for corrosive environments, hybrid sensors, and two-wavelength measurements, are discussed.

Estimation of continuous multi-DOF finger joint kinematics from surface EMG using a multi-output Gaussian Process.

PubMed

Ngeo, Jimson; Tamei, Tomoya; Shibata, Tomohiro

2014-01-01

Surface electromyographic (EMG) signals have often been used in estimating upper and lower limb dynamics and kinematics for the purpose of controlling robotic devices such as robot prosthesis and finger exoskeletons. However, in estimating multiple and a high number of degrees-of-freedom (DOF) kinematics from EMG, output DOFs are usually estimated independently. In this study, we estimate finger joint kinematics from EMG signals using a multi-output convolved Gaussian Process (Multi-output Full GP) that considers dependencies between outputs. We show that estimation of finger joints from muscle activation inputs can be improved by using a regression model that considers inherent coupling or correlation within the hand and finger joints. We also provide a comparison of estimation performance between different regression methods, such as Artificial Neural Networks (ANN) which is used by many of the related studies. We show that using a multi-output GP gives improved estimation compared to multi-output ANN and even dedicated or independent regression models.

Improved Tracking of an Atomic-Clock Resonance Transition

NASA Technical Reports Server (NTRS)

Prestage, John D.; Chung, Sang K.; Tu, Meirong

2010-01-01

An improved method of making an electronic oscillator track the frequency of an atomic-clock resonance transition is based on fitting a theoretical nonlinear curve to measurements at three oscillator frequencies within the operational frequency band of the transition (in other words, at three points within the resonance peak). In the measurement process, the frequency of a microwave oscillator is repeatedly set at various offsets from the nominal resonance frequency, the oscillator signal is applied in a square pulse of the oscillator signal having a suitable duration (typically, of the order of a second), and, for each pulse at each frequency offset, fluorescence photons of the transition in question are counted. As described below, the counts are used to determine a new nominal resonance frequency. Thereafter, offsets are determined with respect to the new resonance frequency. The process as described thus far is repeated so as to repeatedly adjust the oscillator to track the most recent estimate of the nominal resonance frequency.

Few-Flakes Reduced Graphene Oxide Sensors for Organic Vapors with a High Signal-to-Noise Ratio

PubMed Central

Hasan, Nowzesh; Zhang, Wenli

2017-01-01

This paper reports our findings on how to prepare a graphene oxide-based gas sensor for sensing fast pulses of volatile organic compounds with a better signal-to-noise ratio. We use rapid acetone pulses of varying concentrations to test the sensors. First, we compare the effect of graphene oxide deposition method (dielectrophoresis versus solvent evaporation) on the sensor’s response. We find that dielectrophoresis yields films with uniform coverage and better sensor response. Second, we examine the effect of chemical reduction. Contrary to prior reports, we find that graphene oxide reduction leads to a reduction in sensor response and current noise, thus keeping the signal-to-noise ratio the same. We found that if we sonicated the sensor in acetone, we created a sensor with a few flakes of reduced graphene oxide. Such sensors provided a higher signal-to-noise ratio that could be correlated to the vapor concentration of acetone with better repeatability. Modeling shows that the sensor’s response is due to one-site Langmuir adsorption or an overall single exponent process. Further, the desorption of acetone as deduced from the sensor recovery signal follows a single exponent process. Thus, we show a simple way to improve the signal-to-noise ratio in reduced graphene oxide sensors. PMID:29065488

Synchronous acquisition of multi-channel signals by single-channel ADC based on square wave modulation

NASA Astrophysics Data System (ADS)

Yi, Xiaoqing; Hao, Liling; Jiang, Fangfang; Xu, Lisheng; Song, Shaoxiu; Li, Gang; Lin, Ling

2017-08-01

Synchronous acquisition of multi-channel biopotential signals, such as electrocardiograph (ECG) and electroencephalograph, has vital significance in health care and clinical diagnosis. In this paper, we proposed a new method which is using single channel ADC to acquire multi-channel biopotential signals modulated by square waves synchronously. In this method, a specific modulate and demodulate method has been investigated without complex signal processing schemes. For each channel, the sampling rate would not decline with the increase of the number of signal channels. More specifically, the signal-to-noise ratio of each channel is n times of the time-division method or an improvement of 3.01 ×log2n dB, where n represents the number of the signal channels. A numerical simulation shows the feasibility and validity of this method. Besides, a newly developed 8-lead ECG based on the new method has been introduced. These experiments illustrate that the method is practicable and thus is potential for low-cost medical monitors.

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

Pierre, John W.; Wies, Richard; Trudnowski, Daniel

Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacificmore » Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing techniques. Bootstrap techniques have been developed to estimate confidence intervals for the electromechanical modes from field measured data. Results were obtained using injected signal data provided by BPA. A new probing signal was designed that puts more strength into the signal for a given maximum peak to peak swing. Further simulations were conducted on a model based on measured data and with the modifications of the 19-machine simulation model. Montana Tech researchers participated in two primary activities: (1) continued development of the 19-machine simulation test system to include a DC line; and (2) extensive simulation analysis of the various system identification algorithms and bootstrap techniques using the 19 machine model. Researchers at the University of Alaska-Fairbanks focused on the development and testing of adaptive filter algorithms for mode estimation using data generated from simulation models and on data provided in collaboration with BPA and PNNL. There efforts consist of pre-processing field data, testing and refining adaptive filter techniques (specifically the Least Mean Squares (LMS), the Adaptive Step-size LMS (ASLMS), and Error Tracking (ET) algorithms). They also improved convergence of the adaptive algorithms by using an initial estimate from block processing AR method to initialize the weight vector for LMS. Extensive testing was performed on simulated data from the 19 machine model. This project was also extensively involved in the WECC (Western Electricity Coordinating Council) system wide tests carried out in 2005 and 2006. These tests involved injecting known probing signals into the western power grid. One of the primary goals of these tests was the reliable estimation of electromechanical mode properties from measured PMU data. Applied to the system were three types of probing inputs: (1) activation of the Chief Joseph Dynamic Brake, (2) mid-level probing at the Pacific DC Intertie (PDCI), and (3) low-level probing on the PDCI. The Chief Joseph Dynamic Brake is a 1400 MW disturbance to the system and is injected for a half of a second. For the mid and low-level probing, the Celilo terminal of the PDCI is modulated with a known probing signal. Similar but less extensive tests were conducted in June of 2000. The low-level probing signals were designed at the University of Wyoming. A number of important design factors are considered. The designed low-level probing signal used in the tests is a multi-sine signal. Its frequency content is focused in the range of the inter-area electromechanical modes. The most frequently used of these low-level multi-sine signals had a period of over two minutes, a root-mean-square (rms) value of 14 MW, and a peak magnitude of 20 MW. Up to 15 cycles of this probing signal were injected into the system resulting in a processing gain of 15. The resulting measured response at points throughout the system was not much larger than the ambient noise present in the measurements.« less

Hierarchical classification strategy for Phenotype extraction from epidermal growth factor receptor endocytosis screening.

PubMed

Cao, Lu; Graauw, Marjo de; Yan, Kuan; Winkel, Leah; Verbeek, Fons J

2016-05-03

Endocytosis is regarded as a mechanism of attenuating the epidermal growth factor receptor (EGFR) signaling and of receptor degradation. There is increasing evidence becoming available showing that breast cancer progression is associated with a defect in EGFR endocytosis. In order to find related Ribonucleic acid (RNA) regulators in this process, high-throughput imaging with fluorescent markers is used to visualize the complex EGFR endocytosis process. Subsequently a dedicated automatic image and data analysis system is developed and applied to extract the phenotype measurement and distinguish different developmental episodes from a huge amount of images acquired through high-throughput imaging. For the image analysis, a phenotype measurement quantifies the important image information into distinct features or measurements. Therefore, the manner in which prominent measurements are chosen to represent the dynamics of the EGFR process becomes a crucial step for the identification of the phenotype. In the subsequent data analysis, classification is used to categorize each observation by making use of all prominent measurements obtained from image analysis. Therefore, a better construction for a classification strategy will support to raise the performance level in our image and data analysis system. In this paper, we illustrate an integrated analysis method for EGFR signalling through image analysis of microscopy images. Sophisticated wavelet-based texture measurements are used to obtain a good description of the characteristic stages in the EGFR signalling. A hierarchical classification strategy is designed to improve the recognition of phenotypic episodes of EGFR during endocytosis. Different strategies for normalization, feature selection and classification are evaluated. The results of performance assessment clearly demonstrate that our hierarchical classification scheme combined with a selected set of features provides a notable improvement in the temporal analysis of EGFR endocytosis. Moreover, it is shown that the addition of the wavelet-based texture features contributes to this improvement. Our workflow can be applied to drug discovery to analyze defected EGFR endocytosis processes.

Neural correlates of training and transfer effects in working memory in older adults.

PubMed

Heinzel, Stephan; Lorenz, Robert C; Pelz, Patricia; Heinz, Andreas; Walter, Henrik; Kathmann, Norbert; Rapp, Michael A; Stelzel, Christine

2016-07-01

As indicated by previous research, aging is associated with a decline in working memory (WM) functioning, related to alterations in fronto-parietal neural activations. At the same time, previous studies showed that WM training in older adults may improve the performance in the trained task (training effect), and more importantly, also in untrained WM tasks (transfer effects). However, neural correlates of these transfer effects that would improve understanding of its underlying mechanisms, have not been shown in older participants as yet. In this study, we investigated blood-oxygen-level-dependent (BOLD) signal changes during n-back performance and an untrained delayed recognition (Sternberg) task following 12sessions (45min each) of adaptive n-back training in older adults. The Sternberg task used in this study allowed to test for neural training effects independent of specific task affordances of the trained task and to separate maintenance from updating processes. Thirty-two healthy older participants (60-75years) were assigned either to an n-back training or a no-contact control group. Before (t1) and after (t2) training/waiting period, both the n-back task and the Sternberg task were conducted while BOLD signal was measured using functional Magnetic Resonance Imaging (fMRI) in all participants. In addition, neuropsychological tests were performed outside the scanner. WM performance improved with training and behavioral transfer to tests measuring executive functions, processing speed, and fluid intelligence was found. In the training group, BOLD signal in the right lateral middle frontal gyrus/caudal superior frontal sulcus (Brodmann area, BA 6/8) decreased in both the trained n-back and the updating condition of the untrained Sternberg task at t2, compared to the control group. fMRI findings indicate a training-related increase in processing efficiency of WM networks, potentially related to the process of WM updating. Performance gains in untrained tasks suggest that transfer to other cognitive tasks remains possible in aging. Copyright © 2016 Elsevier Inc. All rights reserved.

Investigation on the generation characteristic of pressure pulse wave signal during the measurement-while-drilling process

NASA Astrophysics Data System (ADS)

Changqing, Zhao; Kai, Liu; Tong, Zhao; Takei, Masahiro; Weian, Ren

2014-04-01

The mud-pulse logging instrument is an advanced measurement-while-drilling (MWD) tool and widely used by the industry in the world. In order to improve the signal transmission rate, ensure the accurate transmission of information and address the issue of the weak signal on the ground of oil and gas wells, the signal generator should send out the strong mud-pulse signals with the maximum amplitude. With the rotary valve pulse generator as the study object, the three-dimensional Reynolds NS equations and standard k - ɛ turbulent model were used as a mathematical model. The speed and pressure coupling calculation was done by simple algorithms to get the amplitudes of different rates of flow and axial clearances. Tests were done to verify the characteristics of the pressure signals. The pressure signal was captured by the standpiece pressure monitoring system. The study showed that the axial clearances grew bigger as the pressure wave amplitude value decreased and caused the weakening of the pulse signal. As the rate of flow got larger, the pressure wave amplitude would increase and the signal would be enhanced.

Using dark current data to estimate AVIRIS noise covariance and improve spectral analyses

NASA Technical Reports Server (NTRS)

Boardman, Joseph W.

1995-01-01

Starting in 1994, all AVIRIS data distributions include a new product useful for quantification and modeling of the noise in the reported radiance data. The 'postcal' file contains approximately 100 lines of dark current data collected at the end of each data acquisition run. In essence this is a regular spectral-image cube, with 614 samples, 100 lines and 224 channels, collected with a closed shutter. Since there is no incident radiance signal, the recorded DN measure only the DC signal level and the noise in the system. Similar dark current measurements, made at the end of each line are used, with a 100 line moving average, to remove the DC signal offset. Therefore, the pixel-by-pixel fluctuations about the mean of this dark current image provide an excellent model for the additive noise that is present in AVIRIS reported radiance data. The 61,400 dark current spectra can be used to calculate the noise levels in each channel and the noise covariance matrix. Both of these noise parameters should be used to improve spectral processing techniques. Some processing techniques, such as spectral curve fitting, will benefit from a robust estimate of the channel-dependent noise levels. Other techniques, such as automated unmixing and classification, will be improved by the stable and scene-independence noise covariance estimate. Future imaging spectrometry systems should have a similar ability to record dark current data, permitting this noise characterization and modeling.

Improving the detection of tectonic transients in Japan by accounting for Earth's deformation response to surface mass loading

NASA Astrophysics Data System (ADS)

Martens, H. R.; Simons, M.; Moore, A. W.; Owen, S. E.; Rivera, L. A.

2016-12-01

We explore the contributions of oceanic, atmospheric, and hydrologic mass loading to Global Navigation Satellite System (GNSS)-inferred observations of surface displacements in Japan. Surface mass loading (SML) generates mm- to cm-level deformation of the solid Earth on time scales of hours to years, which exceeds the measurement uncertainties of most GNSS position estimates. By improving the efficiency and accuracy of the prediction and empirical estimation of SML response, we aim to reduce the variance of GNSS time series and therefore enhance the ability to resolve subtle tectonic signals, such as aseismic transients associated with subduction zone processes. Using the GIPSY software in precise point positioning mode, we estimate time series of sub-daily receiver positions for the GNSS Earth Observation Network System (GEONET) in Japan. We also model the Earth's elastic deformation response to a variety of surface mass loads, including loads of atmospheric (e.g., ECMWF) and oceanic (e.g., TPXO8-Atlas, ECCO2) origin. We extract periodic signals, such as the ocean tides and seasonal variations in hydrological loading, using harmonic analysis. Deformation caused by non-periodic loads, such as non-tidal oceanic and atmospheric loads, can be predicted and removed to further reduce the variance. We seek to streamline the workflow for estimating SML-induced surface displacements from a variety of sources in order to account for loading signals in routine GNSS data processing, thereby improving the ability to assess the mechanics of plate boundaries.

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

Monitoring Streambed Scour/Deposition Under Nonideal Temperature Signal and Flood Conditions

NASA Astrophysics Data System (ADS)

DeWeese, Timothy; Tonina, Daniele; Luce, Charles

2017-12-01

Streambed erosion and deposition are fundamental geomorphic processes in riverbeds, and monitoring their evolution is important for ecological system management and in-stream infrastructure stability. Previous research showed proof of concept that analysis of paired temperature signals of stream and pore waters can simultaneously provide monitoring scour and deposition, stream sediment thermal regime, and seepage velocity information. However, it did not address challenges often associated with natural systems, including nonideal temperature variations (low-amplitude, nonsinusoidal signal, and vertical thermal gradients) and natural flooding conditions on monitoring scour and deposition processes over time. Here we addressed this knowledge gap by testing the proposed thermal scour-deposition chain (TSDC) methodology, with laboratory experiments to test the impact of nonideal temperature signals under a range of seepage velocities and with a field application during a pulse flood. Both analyses showed excellent match between surveyed and temperature-derived bed elevation changes even under very low temperature signal amplitudes (less than 1°C), nonideal signal shape (sawtooth shape), and strong and changing vertical thermal gradients (4°C/m). Root-mean-square errors on predicting the change in streambed elevations were comparable with the median grain size of the streambed sediment. Future research should focus on improved techniques for temperature signal phase and amplitude extractions, as well as TSDC applications over long periods spanning entire hydrographs.

A computer controlled signal preprocessor for laser fringe anemometer applications

NASA Technical Reports Server (NTRS)

Oberle, Lawrence G.

1987-01-01

The operation of most commercially available laser fringe anemometer (LFA) counter-processors assumes that adjustments are made to the signal processing independent of the computer used for reducing the data acquired. Not only does the researcher desire a record of these parameters attached to the data acquired, but changes in flow conditions generally require that these settings be changed to improve data quality. Because of this limitation, on-line modification of the data acquisition parameters can be difficult and time consuming. A computer-controlled signal preprocessor has been developed which makes possible this optimization of the photomultiplier signal as a normal part of the data acquisition process. It allows computer control of the filter selection, signal gain, and photo-multiplier voltage. The raw signal from the photomultiplier tube is input to the preprocessor which, under the control of a digital computer, filters the signal and amplifies it to an acceptable level. The counter-processor used at Lewis Research Center generates the particle interarrival times, as well as the time-of-flight of the particle through the probe volume. The signal preprocessor allows computer control of the acquisition of these data.Through the preprocessor, the computer also can control the hand shaking signals for the interface between itself and the counter-processor. Finally, the signal preprocessor splits the pedestal from the signal before filtering, and monitors the photo-multiplier dc current, sends a signal proportional to this current to the computer through an analog to digital converter, and provides an alarm if the current exceeds a predefined maximum. Complete drawings and explanations are provided in the text as well as a sample interface program for use with the data acquisition software.

PAM-4 delivery based on pre-distortion and CMMA equalization in a ROF system at 40 GHz

NASA Astrophysics Data System (ADS)

Zhou, Wen; Zhang, Jiao; Han, Xifeng; Kong, Miao; Gou, Pengqi

2018-06-01

In this paper, we proposed a PAM-4 delivery in a ROF system at 40-GHz. PAM-4 transmission data can be generated via look-up table (LUT) pre-distortion, then delivered over 25km single-mode fiber and 0.5m wireless link. At the receiver side, the received signal can be processed with cascaded multi-module algorithm (CMMA) equalization to improve the decision precision. Our measured results show that 10Gbaud PAM-4 transmission in a ROF system at 40-GHz can be achieved with BER of 1.6 × 10-3. To our knowledge, this is the first time to introduce LUT pre-distortion and CMMA equalization in a ROF system to improve signal performance.

Ultrasonic guided wave tomography of pipes: A development of new techniques for the nondestructive evaluation of cylindrical geometries and guided wave multi-mode analysis

NASA Astrophysics Data System (ADS)

Leonard, Kevin Raymond

This dissertation concentrates on the development of two new tomographic techniques that enable wide-area inspection of pipe-like structures. By envisioning a pipe as a plate wrapped around upon itself, the previous Lamb Wave Tomography (LWT) techniques are adapted to cylindrical structures. Helical Ultrasound Tomography (HUT) uses Lamb-like guided wave modes transmitted and received by two circumferential arrays in a single crosshole geometry. Meridional Ultrasound Tomography (MUT) creates the same crosshole geometry with a linear array of transducers along the axis of the cylinder. However, even though these new scanning geometries are similar to plates, additional complexities arise because they are cylindrical structures. First, because it is a single crosshole geometry, the wave vector coverage is poorer than in the full LWT system. Second, since waves can travel in both directions around the circumference of the pipe, modes can also constructively and destructively interfere with each other. These complexities necessitate improved signal processing algorithms to produce accurate and unambiguous tomographic reconstructions. Consequently, this work also describes a new algorithm for improving the extraction of multi-mode arrivals from guided wave signals. Previous work has relied solely on the first arriving mode for the time-of-flight measurements. In order to improve the LWT, HUT and MUT systems reconstructions, improved signal processing methods are needed to extract information about the arrival times of the later arriving modes. Because each mode has different through-thickness displacement values, they are sensitive to different types of flaws, and the information gained from the multi-mode analysis improves understanding of the structural integrity of the inspected material. Both tomographic frequency compounding and mode sorting algorithms are introduced. It is also shown that each of these methods improve the reconstructed images both qualitatively and quantitatively.

A Subsystem Test Bed for Chinese Spectral Radioheliograph

NASA Astrophysics Data System (ADS)

Zhao, An; Yan, Yihua; Wang, Wei

2014-11-01

The Chinese Spectral Radioheliograph is a solar dedicated radio interferometric array that will produce high spatial resolution, high temporal resolution, and high spectral resolution images of the Sun simultaneously in decimetre and centimetre wave range. Digital processing of intermediate frequency signal is an important part in a radio telescope. This paper describes a flexible and high-speed digital down conversion system for the CSRH by applying complex mixing, parallel filtering, and extracting algorithms to process IF signal at the time of being designed and incorporates canonic-signed digit coding and bit-plane method to improve program efficiency. The DDC system is intended to be a subsystem test bed for simulation and testing for CSRH. Software algorithms for simulation and hardware language algorithms based on FPGA are written which use less hardware resources and at the same time achieve high performances such as processing high-speed data flow (1 GHz) with 10 MHz spectral resolution. An experiment with the test bed is illustrated by using geostationary satellite data observed on March 20, 2014. Due to the easy alterability of the algorithms on FPGA, the data can be recomputed with different digital signal processing algorithms for selecting optimum algorithm.

EARLINET Single Calculus Chain - technical - Part 1: Pre-processing of raw lidar data

NASA Astrophysics Data System (ADS)

D'Amico, Giuseppe; Amodeo, Aldo; Mattis, Ina; Freudenthaler, Volker; Pappalardo, Gelsomina

2016-02-01

In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.

A novel speech-processing strategy incorporating tonal information for cochlear implants.

PubMed

Lan, N; Nie, K B; Gao, S K; Zeng, F G

2004-05-01

Good performance in cochlear implant users depends in large part on the ability of a speech processor to effectively decompose speech signals into multiple channels of narrow-band electrical pulses for stimulation of the auditory nerve. Speech processors that extract only envelopes of the narrow-band signals (e.g., the continuous interleaved sampling (CIS) processor) may not provide sufficient information to encode the tonal cues in languages such as Chinese. To improve the performance in cochlear implant users who speak tonal language, we proposed and developed a novel speech-processing strategy, which extracted both the envelopes of the narrow-band signals and the fundamental frequency (F0) of the speech signal, and used them to modulate both the amplitude and the frequency of the electrical pulses delivered to stimulation electrodes. We developed an algorithm to extract the fundatmental frequency and identified the general patterns of pitch variations of four typical tones in Chinese speech. The effectiveness of the extraction algorithm was verified with an artificial neural network that recognized the tonal patterns from the extracted F0 information. We then compared the novel strategy with the envelope-extraction CIS strategy in human subjects with normal hearing. The novel strategy produced significant improvement in perception of Chinese tones, phrases, and sentences. This novel processor with dynamic modulation of both frequency and amplitude is encouraging for the design of a cochlear implant device for sensorineurally deaf patients who speak tonal languages.

Damage localization in aluminum plate with compact rectangular phased piezoelectric transducer array

NASA Astrophysics Data System (ADS)

Liu, Zenghua; Sun, Kunming; Song, Guorong; He, Cunfu; Wu, Bin

2016-03-01

In this work, a detection method for the damage in plate-like structure with a compact rectangular phased piezoelectric transducer array of 16 piezoelectric elements was presented. This compact array can not only detect and locate a single defect (through hole) in plate, but also identify multi-defects (through holes and surface defect simulated by an iron pillar glued to the plate). The experiments proved that the compact rectangular phased transducer array could detect the full range of plate structures and implement multiple-defect detection simultaneously. The processing algorithm proposed in this paper contains two parts: signal filtering and damage imaging. The former part was used to remove noise from signals. Continuous wavelet transform was applicable to signal filtering. Continuous wavelet transform can provide a plot of wavelet coefficients and the signal with narrow frequency band can be easily extracted from the plot. The latter part of processing algorithm was to implement damage detection and localization. In order to accurately locate defects and improve the imaging quality, two images were obtained from amplitude and phase information. One image was obtained with the Total Focusing Method (TFM) and another phase image was obtained with the Sign Coherence Factor (SCF). Furthermore, an image compounding technique for compact rectangular phased piezoelectric transducer array was proposed in this paper. With the proposed technique, the compounded image can be obtained by combining TFM image with SCF image, thus greatly improving the resolution and contrast of image.

Improving the signal subtle feature extraction performance based on dual improved fractal box dimension eigenvectors

NASA Astrophysics Data System (ADS)

Chen, Xiang; Li, Jingchao; Han, Hui; Ying, Yulong

2018-05-01

Because of the limitations of the traditional fractal box-counting dimension algorithm in subtle feature extraction of radiation source signals, a dual improved generalized fractal box-counting dimension eigenvector algorithm is proposed. First, the radiation source signal was preprocessed, and a Hilbert transform was performed to obtain the instantaneous amplitude of the signal. Then, the improved fractal box-counting dimension of the signal instantaneous amplitude was extracted as the first eigenvector. At the same time, the improved fractal box-counting dimension of the signal without the Hilbert transform was extracted as the second eigenvector. Finally, the dual improved fractal box-counting dimension eigenvectors formed the multi-dimensional eigenvectors as signal subtle features, which were used for radiation source signal recognition by the grey relation algorithm. The experimental results show that, compared with the traditional fractal box-counting dimension algorithm and the single improved fractal box-counting dimension algorithm, the proposed dual improved fractal box-counting dimension algorithm can better extract the signal subtle distribution characteristics under different reconstruction phase space, and has a better recognition effect with good real-time performance.

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing.

PubMed

Li, Jun; Lin, Qiu-Hua; Kang, Chun-Yu; Wang, Kai; Yang, Xiu-Ting

2018-03-18

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets.

Design and Analysis of a Neuromemristive Reservoir Computing Architecture for Biosignal Processing

PubMed Central

Kudithipudi, Dhireesha; Saleh, Qutaiba; Merkel, Cory; Thesing, James; Wysocki, Bryant

2016-01-01

Reservoir computing (RC) is gaining traction in several signal processing domains, owing to its non-linear stateful computation, spatiotemporal encoding, and reduced training complexity over recurrent neural networks (RNNs). Previous studies have shown the effectiveness of software-based RCs for a wide spectrum of applications. A parallel body of work indicates that realizing RNN architectures using custom integrated circuits and reconfigurable hardware platforms yields significant improvements in power and latency. In this research, we propose a neuromemristive RC architecture, with doubly twisted toroidal structure, that is validated for biosignal processing applications. We exploit the device mismatch to implement the random weight distributions within the reservoir and propose mixed-signal subthreshold circuits for energy efficiency. A comprehensive analysis is performed to compare the efficiency of the neuromemristive RC architecture in both digital(reconfigurable) and subthreshold mixed-signal realizations. Both Electroencephalogram (EEG) and Electromyogram (EMG) biosignal benchmarks are used for validating the RC designs. The proposed RC architecture demonstrated an accuracy of 90 and 84% for epileptic seizure detection and EMG prosthetic finger control, respectively. PMID:26869876

An improved human anxiety process biomarker: characterization of frequency band, personality and pharmacology

PubMed Central

Shadli, S M; Glue, P; McIntosh, J; McNaughton, N

2015-01-01

Anxiety disorders are among the most common mental illness in the western world with a major impact on disability. But their diagnosis has lacked objective biomarkers. We previously demonstrated a human anxiety process biomarker, goal-conflict-specific electroencephalography (EEG) rhythmicity (GCSR) in the stop-signal task (SST). Here we have developed and characterized an improved test appropriate for clinical group testing. We modified the SST to produce balanced numbers of trials in clearly separated stop-signal delay groups. As previously, right frontal (F8) GCSR was extracted as the difference in EEG log Fourier power between matching stop and go trials (that is, stop-signal-specific power) of a quadratic contrast of the three delay values (that is, power when stopping and going are in balanced conflict compared with the average of when stopping or going is greater). Separate experiments assessed drug sensitivity (n=34) and personality relations (n=59). GCSR in this new SST was reduced by three chemically distinct anxiolytic drugs (administered double-blind): buspirone (10 mg), triazolam (0.25 mg) and pregabalin (75 mg); had a frequency range (4–12 Hz) consistent with rodent model data; and positively correlated significantly with neuroticism and nonsignificantly with trait anxiety scores. GCSR, measured in our new form of the SST, should be suitable as a biomarker for one specific anxiety process in the testing of clinical groups and novel drugs and in the development of measures suitable for individual diagnosis. PMID:26670284

Evaluation of Speech Intelligibility and Sound Localization Abilities with Hearing Aids Using Binaural Wireless Technology

PubMed Central

Ibrahim, Iman; Parsa, Vijay; Macpherson, Ewan; Cheesman, Margaret

2012-01-01

Wireless synchronization of the digital signal processing (DSP) features between two hearing aids in a bilateral hearing aid fitting is a fairly new technology. This technology is expected to preserve the differences in time and intensity between the two ears by co-ordinating the bilateral DSP features such as multichannel compression, noise reduction, and adaptive directionality. The purpose of this study was to evaluate the benefits of wireless communication as implemented in two commercially available hearing aids. More specifically, this study measured speech intelligibility and sound localization abilities of normal hearing and hearing impaired listeners using bilateral hearing aids with wireless synchronization of multichannel Wide Dynamic Range Compression (WDRC). Twenty subjects participated; 8 had normal hearing and 12 had bilaterally symmetrical sensorineural hearing loss. Each individual completed the Hearing in Noise Test (HINT) and a sound localization test with two types of stimuli. No specific benefit from wireless WDRC synchronization was observed for the HINT; however, hearing impaired listeners had better localization with the wireless synchronization. Binaural wireless technology in hearing aids may improve localization abilities although the possible effect appears to be small at the initial fitting. With adaptation, the hearing aids with synchronized signal processing may lead to an improvement in localization and speech intelligibility. Further research is required to demonstrate the effect of adaptation to the hearing aids with synchronized signal processing on different aspects of auditory performance. PMID:26557339

Enhanced automatic artifact detection based on independent component analysis and Renyi's entropy.

PubMed

Mammone, Nadia; Morabito, Francesco Carlo

2008-09-01

Artifacts are disturbances that may occur during signal acquisition and may affect their processing. The aim of this paper is to propose a technique for automatically detecting artifacts from the electroencephalographic (EEG) recordings. In particular, a technique based on both Independent Component Analysis (ICA) to extract artifactual signals and on Renyi's entropy to automatically detect them is presented. This technique is compared to the widely known approach based on ICA and the joint use of kurtosis and Shannon's entropy. The novel processing technique is shown to detect on average 92.6% of the artifactual signals against the average 68.7% of the previous technique on the studied available database. Moreover, Renyi's entropy is shown to be able to detect muscle and very low frequency activity as well as to discriminate them from other kinds of artifacts. In order to achieve an efficient rejection of the artifacts while minimizing the information loss, future efforts will be devoted to the improvement of blind artifact separation from EEG in order to ensure a very efficient isolation of the artifactual activity from any signals deriving from other brain tasks.

Autocorrelation-based time synchronous averaging for condition monitoring of planetary gearboxes in wind turbines

NASA Astrophysics Data System (ADS)

Ha, Jong M.; Youn, Byeng D.; Oh, Hyunseok; Han, Bongtae; Jung, Yoongho; Park, Jungho

2016-03-01

We propose autocorrelation-based time synchronous averaging (ATSA) to cope with the challenges associated with the current practice of time synchronous averaging (TSA) for planet gears in planetary gearboxes of wind turbine (WT). An autocorrelation function that represents physical interactions between the ring, sun, and planet gears in the gearbox is utilized to define the optimal shape and range of the window function for TSA using actual kinetic responses. The proposed ATSA offers two distinctive features: (1) data-efficient TSA processing and (2) prevention of signal distortion during the TSA process. It is thus expected that an order analysis with the ATSA signals significantly improves the efficiency and accuracy in fault diagnostics of planet gears in planetary gearboxes. Two case studies are presented to demonstrate the effectiveness of the proposed method: an analytical signal from a simulation and a signal measured from a 2 kW WT testbed. It can be concluded from the results that the proposed method outperforms conventional TSA methods in condition monitoring of the planetary gearbox when the amount of available stationary data is limited.

Eddy current testing for blade edge micro cracks of aircraft engine

NASA Astrophysics Data System (ADS)

Zhang, Wei-min; Xu, Min-dong; Gao, Xuan-yi; Jin, Xin; Qin, Feng

2017-10-01

Based on the problems of low detection efficiency in the micro cracks detection of aircraft engine blades, a differential excitation eddy current testing system was designed and developed. The function and the working principle of the system were described, the problems which contained the manufacture method of simulated cracks, signal generating, signal processing and the signal display method were described. The detection test was carried out by taking a certain model aircraft engine blade with simulated cracks as a tested specimen. The test data was processed by digital low-pass filter in the computer and the crack signals of time domain display and Lissajous figure display were acquired. By comparing the test results, it is verified that Lissajous figure display shows better performance compared to time domain display when the crack angle is small. The test results show that the eddy current testing system designed in this paper is feasible to detect the micro cracks on the aeroengine blade and can effectively improve the detection efficiency of micro cracks in the practical detection work.

Improving the All-Hazards Homeland Security Enterprise Through the Use of an Emergency Management Intelligence Model

DTIC Science & Technology

2013-09-01

Office of the Inspector General OSINT Open Source Intelligence PPD Presidential Policy Directive SIGINT Signals Intelligence SLFC State/Local Fusion...Geospatial Intelligence (GEOINT) from Geographic Information Systems (GIS), and Open Source Intelligence ( OSINT ) from Social Media. GIS is widely...and monitor make it a feasible tool to capitalize on for OSINT . A formalized EM intelligence process would help expedite the processing of such

Improvement in the amine glass platform by bubbling method for a DNA microarray

PubMed Central

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool. PMID:26468293

Improvement in the amine glass platform by bubbling method for a DNA microarray.

PubMed

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool.

Improved measurement of vibration amplitude in dynamic optical coherence elastography

PubMed Central

Kennedy, Brendan F.; Wojtkowski, Maciej; Szkulmowski, Maciej; Kennedy, Kelsey M.; Karnowski, Karol; Sampson, David D.

2012-01-01

Abstract: Optical coherence elastography employs optical coherence tomography (OCT) to measure the displacement of tissues under load and, thus, maps the resulting strain into an image, known as an elastogram. We present a new improved method to measure vibration amplitude in dynamic optical coherence elastography. The tissue vibration amplitude caused by sinusoidal loading is measured from the spread of the Doppler spectrum, which is extracted using joint spectral and time domain signal processing. At low OCT signal-to-noise ratio (SNR), the method provides more accurate vibration amplitude measurements than the currently used phase-sensitive method. For measurements performed on a mirror at OCT SNR = 5 dB, our method introduces <3% error, compared to >20% using the phase-sensitive method. We present elastograms of a tissue-mimicking phantom and excised porcine tissue that demonstrate improvements, including a 50% increase in the depth range of reliable vibration amplitude measurement. PMID:23243565

On Limitations of the Ultrasonic Characterization of Pieces Manufactured with Highly Attenuating Materials

NASA Astrophysics Data System (ADS)

Ramos, A.; Moreno, E.; Rubio, B.; Calas, H.; Galarza, N.; Rubio, J.; Diez, L.; Castellanos, L.; Gómez, T.

Some technical aspects of two Spanish cooperation projects, funded by DPI and Innpacto Programs of the R&D National Plan, are discussed. The objective is to analyze the common belief about than the ultrasonic testing in MHz range is not a tool utilizable to detect internal flaws in highly attenuating pieces made of coarse-grained steel. In fact high-strength steels, used in some safe industrial infrastructures of energy & transport sectors, are difficult to be inspected using the conventional "state of the art" in ultrasonic technology, due to their internal microstructures are very attenuating and coarse-grained. It is studied if this inspection difficulty could be overcome by finding intense interrogating pulses and advanced signal processing of the acquired echoes. A possible solution would depend on drastically improving signal-to-noise-ratios, by applying new advances on: ultrasonic transduction, HV electronics for intense pulsed driving of the testing probes, and an "ad-hoc" digital processing or focusing of the received noisy signals, in function of each material to be inspected. To attain this challenging aim on robust steel pieces would open the possibility of obtaining improvements in inspecting critical industrial components made of highly attenuating & dispersive materials, as new composites in aeronautic and motorway bridges, or new metallic alloys in nuclear area, where additional testing limitations often appear.

Scalable Indoor Localization via Mobile Crowdsourcing and Gaussian Process

PubMed Central

Chang, Qiang; Li, Qun; Shi, Zesen; Chen, Wei; Wang, Weiping

2016-01-01

Indoor localization using Received Signal Strength Indication (RSSI) fingerprinting has been extensively studied for decades. The positioning accuracy is highly dependent on the density of the signal database. In areas without calibration data, however, this algorithm breaks down. Building and updating a dense signal database is labor intensive, expensive, and even impossible in some areas. Researchers are continually searching for better algorithms to create and update dense databases more efficiently. In this paper, we propose a scalable indoor positioning algorithm that works both in surveyed and unsurveyed areas. We first propose Minimum Inverse Distance (MID) algorithm to build a virtual database with uniformly distributed virtual Reference Points (RP). The area covered by the virtual RPs can be larger than the surveyed area. A Local Gaussian Process (LGP) is then applied to estimate the virtual RPs’ RSSI values based on the crowdsourced training data. Finally, we improve the Bayesian algorithm to estimate the user’s location using the virtual database. All the parameters are optimized by simulations, and the new algorithm is tested on real-case scenarios. The results show that the new algorithm improves the accuracy by 25.5% in the surveyed area, with an average positioning error below 2.2 m for 80% of the cases. Moreover, the proposed algorithm can localize the users in the neighboring unsurveyed area. PMID:26999139

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

Olama, Mohammed M; Matalgah, Mustafa M; Bobrek, Miljko

Traditional encryption techniques require packet overhead, produce processing time delay, and suffer from severe quality of service deterioration due to fades and interference in wireless channels. These issues reduce the effective transmission data rate (throughput) considerably in wireless communications, where data rate with limited bandwidth is the main constraint. In this paper, performance evaluation analyses are conducted for an integrated signaling-encryption mechanism that is secure and enables improved throughput and probability of bit-error in wireless channels. This mechanism eliminates the drawbacks stated herein by encrypting only a small portion of an entire transmitted frame, while the rest is not subjectmore » to traditional encryption but goes through a signaling process (designed transformation) with the plaintext of the portion selected for encryption. We also propose to incorporate error correction coding solely on the small encrypted portion of the data to drastically improve the overall bit-error rate performance while not noticeably increasing the required bit-rate. We focus on validating the signaling-encryption mechanism utilizing Hamming and convolutional error correction coding by conducting an end-to-end system-level simulation-based study. The average probability of bit-error and throughput of the encryption mechanism are evaluated over standard Gaussian and Rayleigh fading-type channels and compared to the ones of the conventional advanced encryption standard (AES).« less

New Perspectives on Assessing Amplification Effects

PubMed Central

Souza, Pamela E.; Tremblay, Kelly L.

2006-01-01

Clinicians have long been aware of the range of performance variability with hearing aids. Despite improvements in technology, there remain many instances of well-selected and appropriately fitted hearing aids whereby the user reports minimal improvement in speech understanding. This review presents a multistage framework for understanding how a hearing aid affects performance. Six stages are considered: (1) acoustic content of the signal, (2) modification of the signal by the hearing aid, (3) interaction between sound at the output of the hearing aid and the listener's ear, (4) integrity of the auditory system, (5) coding of available acoustic cues by the listener's auditory system, and (6) correct identification of the speech sound. Within this framework, this review describes methodology and research on 2 new assessment techniques: acoustic analysis of speech measured at the output of the hearing aid and auditory evoked potentials recorded while the listener wears hearing aids. Acoustic analysis topics include the relationship between conventional probe microphone tests and probe microphone measurements using speech, appropriate procedures for such tests, and assessment of signal-processing effects on speech acoustics and recognition. Auditory evoked potential topics include an overview of physiologic measures of speech processing and the effect of hearing loss and hearing aids on cortical auditory evoked potential measurements in response to speech. Finally, the clinical utility of these procedures is discussed. PMID:16959734

Brain signal variability as a window into the bidirectionality between music and language processing: moving from a linear to a nonlinear model

PubMed Central

Hutka, Stefanie; Bidelman, Gavin M.; Moreno, Sylvain

2013-01-01

There is convincing empirical evidence for bidirectional transfer between music and language, such that experience in either domain can improve mental processes required by the other. This music-language relationship has been studied using linear models (e.g., comparing mean neural activity) that conceptualize brain activity as a static entity. The linear approach limits how we can understand the brain’s processing of music and language because the brain is a nonlinear system. Furthermore, there is evidence that the networks supporting music and language processing interact in a nonlinear manner. We therefore posit that the neural processing and transfer between the domains of language and music are best viewed through the lens of a nonlinear framework. Nonlinear analysis of neurophysiological activity may yield new insight into the commonalities, differences, and bidirectionality between these two cognitive domains not measurable in the local output of a cortical patch. We thus propose a novel application of brain signal variability (BSV) analysis, based on mutual information and signal entropy, to better understand the bidirectionality of music-to-language transfer in the context of a nonlinear framework. This approach will extend current methods by offering a nuanced, network-level understanding of the brain complexity involved in music-language transfer. PMID:24454295

Brain signal variability as a window into the bidirectionality between music and language processing: moving from a linear to a nonlinear model.

PubMed

Hutka, Stefanie; Bidelman, Gavin M; Moreno, Sylvain

2013-12-30

There is convincing empirical evidence for bidirectional transfer between music and language, such that experience in either domain can improve mental processes required by the other. This music-language relationship has been studied using linear models (e.g., comparing mean neural activity) that conceptualize brain activity as a static entity. The linear approach limits how we can understand the brain's processing of music and language because the brain is a nonlinear system. Furthermore, there is evidence that the networks supporting music and language processing interact in a nonlinear manner. We therefore posit that the neural processing and transfer between the domains of language and music are best viewed through the lens of a nonlinear framework. Nonlinear analysis of neurophysiological activity may yield new insight into the commonalities, differences, and bidirectionality between these two cognitive domains not measurable in the local output of a cortical patch. We thus propose a novel application of brain signal variability (BSV) analysis, based on mutual information and signal entropy, to better understand the bidirectionality of music-to-language transfer in the context of a nonlinear framework. This approach will extend current methods by offering a nuanced, network-level understanding of the brain complexity involved in music-language transfer.

Analysis on accuracy improvement of rotor-stator rubbing localization based on acoustic emission beamforming method.

PubMed

He, Tian; Xiao, Denghong; Pan, Qiang; Liu, Xiandong; Shan, Yingchun

2014-01-01

This paper attempts to introduce an improved acoustic emission (AE) beamforming method to localize rotor-stator rubbing fault in rotating machinery. To investigate the propagation characteristics of acoustic emission signals in casing shell plate of rotating machinery, the plate wave theory is used in a thin plate. A simulation is conducted and its result shows the localization accuracy of beamforming depends on multi-mode, dispersion, velocity and array dimension. In order to reduce the effect of propagation characteristics on the source localization, an AE signal pre-process method is introduced by combining plate wave theory and wavelet packet transform. And the revised localization velocity to reduce effect of array size is presented. The accuracy of rubbing localization based on beamforming and the improved method of present paper are compared by the rubbing test carried on a test table of rotating machinery. The results indicate that the improved method can localize rub fault effectively. Copyright © 2013 Elsevier B.V. All rights reserved.

Note: An improved calibration system with phase correction for electronic transformers with digital output

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

Cheng, Han-miao, E-mail: chenghanmiao@hust.edu.cn; Li, Hong-bin, E-mail: lihongbin@hust.edu.cn; State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Wuhan 430074

The existing electronic transformer calibration systems employing data acquisition cards cannot satisfy some practical applications, because the calibration systems have phase measurement errors when they work in the mode of receiving external synchronization signals. This paper proposes an improved calibration system scheme with phase correction to improve the phase measurement accuracy. We employ NI PCI-4474 to design a calibration system, and the system has the potential to receive external synchronization signals and reach extremely high accuracy classes. Accuracy verification has been carried out in the China Electric Power Research Institute, and results demonstrate that the system surpasses the accuracy classmore » 0.05. Furthermore, this system has been used to test the harmonics measurement accuracy of all-fiber optical current transformers. In the same process, we have used an existing calibration system, and a comparison of the test results is presented. The system after improvement is suitable for the intended applications.« less

Effects of High-Rate Pulse Trains on Electrode Discrimination in Cochlear Implant Users

PubMed Central

Runge-Samuelson, Christina L.

2009-01-01

Overcoming issues related to abnormally high neural synchrony in response to electrical stimulation is one aspect in improving hearing with a cochlear implant. Desynchronization of electrical stimuli have shown benefits in neural encoding of electrical signals and improvements in psychophysical tasks. In the present study, 10 participants with either CII or HiRes 90k Advanced Bionics devices were tested for the effects of desynchronizing constant-amplitude high-rate (5,000 Hz) pulse trains on electrode discrimination of sinusoidal stimuli (1,000 Hz). When averaged across the sinusoidal dynamic range, overall improvements in electrode discrimination with high-rate pulses were found for 8 of 10 participants. This effect was significant for the group (p = .003). Nonmonotonic patterns of electrode discrimination as a function of sinusoidal stimulation level were observed. By providing additional spectral channels, it is possible that clinical implementation of constant-amplitude high-rate pulse trains in a signal processing strategy may improve performance with the device. PMID:19447763

Improvement of the energetic properties of the GPR

NASA Astrophysics Data System (ADS)

Pochanin, Gennadiy P.; Ruban, Vadim P.; Kholod, Pavlo V.; Shuba, Alexander A.; Pochanin, Alexander G.; Orlenko, Alexander A.

2014-05-01

The necessary condition for the expansion of the impulse Ground Penetrating Radar (GPR) applications is to improve the GPR energy performance for the detection of signals on the background of noise. Digital signal processing techniques allow suppressing the noise largely, but they work only when the GPR is able to register the reflected signals. The majority of the modern GPRs use sampling receivers. They allow recording signals of a very short du- ration. However, very large energy losses are inherent to this method. To improve the signal to noise ratio it is possible to increase the power of the probing signal and to de- crease the noise level of the receiver. In GPR, the transmitting and receiving antennas are usually electrodynamically coupled because they are situated quite close to each other. The sensitive input circuit of the receiver does not allow the excess of the signal amplitude typically more than 1 V. Thus, the increase of the intensity of the probing signal is possible only up to a certain level. To overcome this limitation, it was proposed to design an antenna in such a way that the coupling between the transmitting and receiving sections was absent or minimal. A special method that provided the decoupling below -64 dB was invented (theoretically the isolation is absolute and frequency independent). In order to register as short as possible signals, researchers strive to make sample duration of the sampling converter as short as possible. However, the shorter the sample duration, the smaller the energy of the signal that can be received and the larger the noise. Due to the dispersive absorption of electromagnetic waves in the ground, the high-frequency part of the signal spectrum is attenuated faster than the low-frequency part. It makes no sense to expect the arrival of very short pulses from deep reflectors. Thus, it is possible to increase the duration of the samples at reception of the signals from the deep objects. The authors proposed to increase the duration of the samples with the distance. In this way, a smoothing of the noise and an increase of the recorded energy at each subsequent sampling were achieved. The next opportunity to improve the signal to noise ratio is the coherent accumulation of the signal that can be carried out both in digital and analog forms. Due to the fast ADC, it became possible to accumulate a large number of signals in an acceptable survey period. In practice, the amount of accumulated signals is limited by jitter. Thus, to achieve accumulation and re- ception of signals without distortion the authors have suggested and implemented GPR improvements allowing to get the instability of sampling below 3.5 ps. Owing to increase of the pulse-repetition frequency up to 1 MHz and data transmission via Ethernet, it was also possible to provide a fast GPR survey. ----------------------------------------------------------------------------------------- This research has been performed partly owing to EU 7th Framework Marie Curie Actions IRSES project (PIRSES-GA-2010-269157) "Active and Passive Microwaves for Security and Subsurface imaging (AMISS)." The Authors thank COST Action TU1208 "Civil Engineering Applications of Ground Penetrating Radar" for its networking activities.

Use of polarization to improve signal to clutter ratio in an outdoor active imaging system

NASA Astrophysics Data System (ADS)

Fontoura, Patrick F.; Giles, Michael K.; Padilla, Denise D.

2005-08-01

This paper describes the methodology and presents the results of the design of a polarization-sensitive system used to increase the signal-to-clutter ratio in a robust outdoor structured lighting sensor that uses standard CCD camera technology. This lighting sensor is intended to be used on an autonomous vehicle, looking down to the ground and horizontal to obstacles in an 8 foot range. The kinds of surfaces to be imaged are natural and man-made, such as asphalt, concrete, dirt and grass. The main problem for an outdoor eye-safe laser imaging system is that the reflected energy from background clutter tends to be brighter than the reflected laser energy. A narrow-band optical filter does not reduce significantly the background clutter in bright sunlight, and problems also occur when the surface is highly absorptive, like asphalt. Therefore, most of applications are limited to indoor and controlled outdoor conditions. A series of measurements was made for each of the materials studied in order to find the best configuration for the polarizing system and also to find out the potential improvement in the signal-to-clutter ratio (STC). This process was divided into three parts: characterization of the reflected sunlight, characterization of the reflected laser light, and measurement of the improvement in the STC. The results show that by using polarization properties it is possible to design an optical system that is able to increase the signal-to-clutter ratio from approximately 30% to 100% in the imaging system, depending on the kind of surface and on the incidence angle of the sunlight. The technique was also analyzed for indoor use, with the background clutter being the room illumination. For this specific case, polarization did not improve the signal-to-clutter ratio.

Applying emerging digital video interface standards to airborne avionics sensor and digital map integrations: benefits outweigh the initial costs

NASA Astrophysics Data System (ADS)

Kuehl, C. Stephen

1996-06-01

Video signal system performance can be compromised in a military aircraft cockpit management system (CMS) with the tailoring of vintage Electronics Industries Association (EIA) RS170 and RS343A video interface standards. Video analog interfaces degrade when induced system noise is present. Further signal degradation has been traditionally associated with signal data conversions between avionics sensor outputs and the cockpit display system. If the CMS engineering process is not carefully applied during the avionics video and computing architecture development, extensive and costly redesign will occur when visual sensor technology upgrades are incorporated. Close monitoring and technical involvement in video standards groups provides the knowledge-base necessary for avionic systems engineering organizations to architect adaptable and extendible cockpit management systems. With the Federal Communications Commission (FCC) in the process of adopting the Digital HDTV Grand Alliance System standard proposed by the Advanced Television Systems Committee (ATSC), the entertainment and telecommunications industries are adopting and supporting the emergence of new serial/parallel digital video interfaces and data compression standards that will drastically alter present NTSC-M video processing architectures. The re-engineering of the U.S. Broadcasting system must initially preserve the electronic equipment wiring networks within broadcast facilities to make the transition to HDTV affordable. International committee activities in technical forums like ITU-R (former CCIR), ANSI/SMPTE, IEEE, and ISO/IEC are establishing global consensus on video signal parameterizations that support a smooth transition from existing analog based broadcasting facilities to fully digital computerized systems. An opportunity exists for implementing these new video interface standards over existing video coax/triax cabling in military aircraft cockpit management systems. Reductions in signal conversion processing steps, major improvement in video noise reduction, and an added capability to pass audio/embedded digital data within the digital video signal stream are the significant performance increases associated with the incorporation of digital video interface standards. By analyzing the historical progression of military CMS developments, establishing a systems engineering process for CMS design, tracing the commercial evolution of video signal standardization, adopting commercial video signal terminology/definitions, and comparing/contrasting CMS architecture modifications using digital video interfaces; this paper provides a technical explanation on how a systems engineering process approach to video interface standardization can result in extendible and affordable cockpit management systems.

Research on detecting spot selection and signal pretreatment of four-quadrant detector

NASA Astrophysics Data System (ADS)

Liu, Wenli; Han, Shaokun

2018-01-01

The four-quadrant detector is a photoelectric position sensor based on the photovoltaic effect. It is widely used in many fields such as target azimuth measurement, end-guided weapon and so on. The selection of the spot and the calculation of the center position are one of the main factors that affect the accuracy of the position measurement of the fourquadrant detector. In order to improve the positioning accuracy of the four-quadrant detector, the method of determining the best spot size is obtained from the theoretical research. The output signal of the four-quadrant detector is a weak narrow pulse signal, which needs to be magnified and widened at high magnitudes. The signal preprocessing method is simulated and experimentally studied. Detecting the spot and the signal processing is realized by the four-quadrant detector, which is important for the use of quadrant detectors for high-precision position measurements.

Gradient-based multiresolution image fusion.

PubMed

Petrović, Valdimir S; Xydeas, Costas S

2004-02-01

A novel approach to multiresolution signal-level image fusion is presented for accurately transferring visual information from any number of input image signals, into a single fused image without loss of information or the introduction of distortion. The proposed system uses a "fuse-then-decompose" technique realized through a novel, fusion/decomposition system architecture. In particular, information fusion is performed on a multiresolution gradient map representation domain of image signal information. At each resolution, input images are represented as gradient maps and combined to produce new, fused gradient maps. Fused gradient map signals are processed, using gradient filters derived from high-pass quadrature mirror filters to yield a fused multiresolution pyramid representation. The fused output image is obtained by applying, on the fused pyramid, a reconstruction process that is analogous to that of conventional discrete wavelet transform. This new gradient fusion significantly reduces the amount of distortion artefacts and the loss of contrast information usually observed in fused images obtained from conventional multiresolution fusion schemes. This is because fusion in the gradient map domain significantly improves the reliability of the feature selection and information fusion processes. Fusion performance is evaluated through informal visual inspection and subjective psychometric preference tests, as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional fusion systems.

Onboard Autonomous Corrections for Accurate IRF Pointing.

NASA Astrophysics Data System (ADS)

Jorgensen, J. L.; Betto, M.; Denver, T.

2002-05-01

Over the past decade, the Noise Equivalent Angle (NEA) of onboard attitude reference instruments, has decreased from tens-of-arcseconds to the sub-arcsecond level. This improved performance is partly due to improved sensor-technology with enhanced signal to noise ratios, partly due to improved processing electronics which allows for more sophisticated and faster signal processing. However, the main reason for the increased precision, is the application of onboard autonomy, which apart from simple outlier rejection also allows for removal of "false positive" answers, and other "unexpected" noise sources, that otherwise would degrade the quality of the measurements (e.g. discrimination between signals caused by starlight and ionizing radiation). The utilization of autonomous signal processing has also provided the means for another onboard processing step, namely the autonomous recovery from lost in space, where the attitude instrument without a priori knowledge derive the absolute attitude, i.e. in IRF coordinates, within fractions of a second. Combined with precise orbital state or position data, the absolute attitude information opens for multiple ways to improve the mission performance, either by reducing operations costs, by increasing pointing accuracy, by reducing mission expendables, or by providing backup decision information in case of anomalies. The Advanced Stellar Compass's (ASC) is a miniature, high accuracy, attitude instrument which features fully autonomous operations. The autonomy encompass all direct steps from automatic health checkout at power-on, over fully automatic SEU and SEL handling and proton induced sparkle removal, to recovery from "lost in space", and optical disturbance detection and handling. But apart from these more obvious autonomy functions, the ASC also features functions to handle and remove the aforementioned residuals. These functions encompass diverse operators such as a full orbital state vector model with automatic cloud filtered GPS updates, a world time clock, astrometric correction tables, and a attitude output transform system, that allow the ASC to deliver the spacecraft attitude relative to the Inertial Reference Frame (IRF) in realtime. This paper describes the operations of the onboard autonomy of the ASC, which in realtime removes the residuals from the attitude measurements, whereby a timely IRF attitude at arcsecond level, is delivered to the AOCS (or sent to ground). A discussion about achievable robustness and accuracy is given, and compared to inflight results from the operations of the two Advanced Stellar Compass's (ASC), which are flying in LEO onboard the German geo-potential research satellite CHAMP. The ASC's onboard CHAMP are dual head versions, i.e. each processing unit is attached to two star camera heads. The dual head configuration is primarily employed to achieve a carefree AOCS control with respect to the Sun, Moon and Earth, and to increase the attitude accuracy, but it also enables onboard estimation and removal of thermal generated biases.

Effect of Processing and Storage on RBC function in vivo

PubMed Central

Doctor, Allan; Spinella, Phil

2012-01-01

Red Blood Cell (RBC) transfusion is indicated to improve oxygen delivery to tissue, and for no other purpose. We have come to appreciate that donor RBCs are fundamentally altered during processing and storage, in a fashion that both impairs oxygen transport efficacy and introduces additional risk by perturbing both immune and coagulation systems. The protean biophysical and physiologic changes in RBC function arising from storage are termed the ‘storage lesion’; many have been understood for some time; for example, we know that the oxygen affinity of stored blood rises during the storage period1 and that intracellular allosteric regulators, notably 2,3-bisphosphoglyceric acid (DPG) and ATP, are depleted during storage. Our appreciation of other storage lesion features has emerged with improved understanding of coagulation, immune and vascular signaling systems. Herein we review key features of the ‘storage lesion’. Additionally, we call particular attention to the newly appreciated role of RBCs in regulating linkage between regional blood flow and regional O2 consumption by regulating the bioavailability of key vasoactive mediators in plasma, as well as discuss how processing and storage disturbs this key signaling function and impairs transfusion efficacy. PMID:22818545

Application of an improved maximum correlated kurtosis deconvolution method for fault diagnosis of rolling element bearings

NASA Astrophysics Data System (ADS)

Miao, Yonghao; Zhao, Ming; Lin, Jing; Lei, Yaguo

2017-08-01

The extraction of periodic impulses, which are the important indicators of rolling bearing faults, from vibration signals is considerably significance for fault diagnosis. Maximum correlated kurtosis deconvolution (MCKD) developed from minimum entropy deconvolution (MED) has been proven as an efficient tool for enhancing the periodic impulses in the diagnosis of rolling element bearings and gearboxes. However, challenges still exist when MCKD is applied to the bearings operating under harsh working conditions. The difficulties mainly come from the rigorous requires for the multi-input parameters and the complicated resampling process. To overcome these limitations, an improved MCKD (IMCKD) is presented in this paper. The new method estimates the iterative period by calculating the autocorrelation of the envelope signal rather than relies on the provided prior period. Moreover, the iterative period will gradually approach to the true fault period through updating the iterative period after every iterative step. Since IMCKD is unaffected by the impulse signals with the high kurtosis value, the new method selects the maximum kurtosis filtered signal as the final choice from all candidates in the assigned iterative counts. Compared with MCKD, IMCKD has three advantages. First, without considering prior period and the choice of the order of shift, IMCKD is more efficient and has higher robustness. Second, the resampling process is not necessary for IMCKD, which is greatly convenient for the subsequent frequency spectrum analysis and envelope spectrum analysis without resetting the sampling rate. Third, IMCKD has a significant performance advantage in diagnosing the bearing compound-fault which expands the application range. Finally, the effectiveness and superiority of IMCKD are validated by a number of simulated bearing fault signals and applying to compound faults and single fault diagnosis of a locomotive bearing.

Losartan Restores Skeletal Muscle Remodeling and Protects Against Disuse Atrophy in Sarcopenia

PubMed Central

Burks, Tyesha N.; Andres-Mateos, Eva; Marx, Ruth; Mejias, Rebeca; Van Erp, Christel; Simmers, Jessica L.; Walston, Jeremy D.; Ward, Christopher W.; Cohn, Ronald D.

2011-01-01

Sarcopenia, a critical loss of muscle mass and function because of the physiological process of aging, contributes to disability and mortality in older adults. It increases the incidence of pathologic fractures, causing prolonged periods of hospitalization and rehabilitation. The molecular mechanisms underlying sarcopenia are poorly understood, but recent evidence suggests that increased transforming growth factor–β (TGF-β) signaling contributes to impaired satellite cell function and muscle repair in aged skeletal muscle. We therefore evaluated whether antagonism of TGF-β signaling via losartan, an angiotensin II receptor antagonist commonly used to treat high blood pressure, had a beneficial impact on the muscle remodeling process of sarcopenic mice. We demonstrated that mice treated with losartan developed significantly less fibrosis and exhibited improved in vivo muscle function after cardiotoxin-induced injury. We found that losartan not only blunted the canonical TGF-β signaling cascade but also modulated the noncanonical TGF-β mitogen-activated protein kinase pathway. We next assessed whether losartan was able to combat disuse atrophy in aged mice that were subjected to hindlimb immobilization. We showed that immobilized mice treated with losartan were protected against loss of muscle mass. Unexpectedly, this protective mechanism was not mediated by TGF-β signaling but was due to an increased activation of the insulin-like growth factor 1 (IGF-1)/Akt/mammalian target of rapamycin (mTOR) pathway. Thus, blockade of the AT1 (angiotensin II type I) receptor improved muscle remodeling and protected against disuse atrophy by differentially regulating the TGF-β and IGF-1/Akt/mTOR signaling cascades, two pathways critical for skeletal muscle homeostasis. Thus, losartan, a Food and Drug Administration–approved drug, may prove to have clinical benefits to combat injury-related muscle remodeling and provide protection against disuse atrophy in humans with sarcopenia. PMID:21562229

Intensity-based masking: A tool to improve functional connectivity results of resting-state fMRI.

PubMed

Peer, Michael; Abboud, Sami; Hertz, Uri; Amedi, Amir; Arzy, Shahar

2016-07-01

Seed-based functional connectivity (FC) of resting-state functional MRI data is a widely used methodology, enabling the identification of functional brain networks in health and disease. Based on signal correlations across the brain, FC measures are highly sensitive to noise. A somewhat neglected source of noise is the fMRI signal attenuation found in cortical regions in close vicinity to sinuses and air cavities, mainly in the orbitofrontal, anterior frontal and inferior temporal cortices. BOLD signal recorded at these regions suffers from dropout due to susceptibility artifacts, resulting in an attenuated signal with reduced signal-to-noise ratio in as many as 10% of cortical voxels. Nevertheless, signal attenuation is largely overlooked during FC analysis. Here we first demonstrate that signal attenuation can significantly influence FC measures by introducing false functional correlations and diminishing existing correlations between brain regions. We then propose a method for the detection and removal of the attenuated signal ("intensity-based masking") by fitting a Gaussian-based model to the signal intensity distribution and calculating an intensity threshold tailored per subject. Finally, we apply our method on real-world data, showing that it diminishes false correlations caused by signal dropout, and significantly improves the ability to detect functional networks in single subjects. Furthermore, we show that our method increases inter-subject similarity in FC, enabling reliable distinction of different functional networks. We propose to include the intensity-based masking method as a common practice in the pre-processing of seed-based functional connectivity analysis, and provide software tools for the computation of intensity-based masks on fMRI data. Hum Brain Mapp 37:2407-2418, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Clinical evaluation of the effects of signal integrity and saturation on data availability and accuracy of Masimo SE and Nellcor N-395 oximeters in children.

PubMed

Robertson, Frederick A; Hoffman, George M

2004-03-01

Pulse oximetry manufacturers have introduced technologies that claim improved detection of hypoxemic events. Because improvements in signal processing and data rejection algorithms may differentially affect data reporting, we compared the data reporting and signal heuristic performance and agreement among the Nellcor N-395, Masimo SET, and GE Solar 8000 oximeters under a spectrum of conditions of signal integrity and arterial oxygen saturations. A blinded side-by-side comparison of technologies was performed in 27 patients, and data were analyzed for time of data availability, measures of agreement and signal heuristics, and warnings stratified by signal integrity and SpO(2). The Solar 8000 had less total data dropout than either of the new technologies. Masimo's LoSIQ (signal quality) heuristic rejected less data than Nellcor's MOT/PS (motion/pulse search) flag. When no signal heuristic was displayed, there was little difference in precision and bias between the two newer technologies; however, agreement between devices deteriorated in the presence of SIQ, MOT, or hypoxemia. Both newer devices flagged questionable data, but their use of different rejection algorithms resulted in different probabilities of presenting data. Therefore, with poor SIQ or during hypoxemia, the Nellcor N-395 and Masimo oximeters are not clinically equivalent to each other or to the older Solar 8000 oximeter. We compared new pulse oximeters from Nellcor and Masimo and found that, with good signal conditions, both new devices performed similarly to older technology. Overall, Masimo reported less data as questionable than Nellcor. With poor signal conditions or during hypoxemia, the new devices are not clinically equivalent to each other or to the older technology.

Simple simulation training system for short-wave radio station

NASA Astrophysics Data System (ADS)

Tan, Xianglin; Shao, Zhichao; Tu, Jianhua; Qu, Fuqi

2018-04-01

The short-wave radio station is a most important transmission equipment of our signal corps, but in the actual teaching process, which exist the phenomenon of fewer equipment and more students, making the students' short-wave radio operation and practice time is very limited. In order to solve the above problems, to carry out shortwave radio simple simulation training system development is very necessary. This project is developed by combining hardware and software to simulate the voice communication operation and signal principle of shortwave radio station, and can test the signal flow of shortwave radio station. The test results indicate that this system is simple operation, human-machine interface friendly and can improve teaching more efficiency.

RFI Detection and Mitigation using Independent Component Analysis as a Pre-Processor

NASA Technical Reports Server (NTRS)

Schoenwald, Adam J.; Gholian, Armen; Bradley, Damon C.; Wong, Mark; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.

2016-01-01

Radio-frequency interference (RFI) has negatively impacted scientific measurements of passive remote sensing satellites. This has been observed in the L-band radiometers Soil Moisture and Ocean Salinity (SMOS), Aquarius and more recently, Soil Moisture Active Passive (SMAP). RFI has also been observed at higher frequencies such as K band. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements. This work explores the use of Independent Component Analysis (ICA) as a blind source separation (BSS) technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

Sound vibration signal processing for detection and identification detonation (knock) to optimize performance Otto engine

NASA Astrophysics Data System (ADS)

Sujono, A.; Santoso, B.; Juwana, W. E.

2016-03-01

Problems of detonation (knock) on Otto engine (petrol engine) is completely unresolved problem until now, especially if want to improve the performance. This research did sound vibration signal processing engine with a microphone sensor, for the detection and identification of detonation. A microphone that can be mounted is not attached to the cylinder block, that's high temperature, so that its performance will be more stable, durable and inexpensive. However, the method of analysis is not very easy, because a lot of noise (interference). Therefore the use of new methods of pattern recognition, through filtration, and the regression function normalized envelope. The result is quite good, can achieve a success rate of about 95%.

[Situational awareness: you won't see it unless you understand it].

PubMed

Graafland, Maurits; Schijven, Marlies P

2015-01-01

In dynamic, high-risk environments such as the modern operating theatre, healthcare providers are required to identify a multitude of signals correctly and in time. Errors resulting from failure to identify or interpret signals correctly lead to calamities. Medical training curricula focus largely on teaching technical skills and knowledge, not on the cognitive skills needed to interact appropriately with fast-changing, complex environments in practice. The term 'situational awareness' describes the dynamic process of receiving, interpreting and processing information in such dynamic environments. Improving situational awareness in high-risk environments should be part of medical curricula. In addition, the flood of information in high-risk environments should be presented more clearly and effectively. It is important that physicians become more involved in this regard.

Bioactive Molecules in Soil Ecosystems: Masters of the Underground

PubMed Central

Zhuang, Xuliang; Gao, Jie; Ma, Anzhou; Fu, Shenglei; Zhuang, Guoqiang

2013-01-01

Complex biological and ecological processes occur in the rhizosphere through ecosystem-level interactions between roots, microorganisms and soil fauna. Over the past decade, studies of the rhizosphere have revealed that when roots, microorganisms and soil fauna physically contact one another, bioactive molecular exchanges often mediate these interactions as intercellular signal, which prepare the partners for successful interactions. Despite the importance of bioactive molecules in sustainable agriculture, little is known of their numerous functions, and improving plant health and productivity by altering ecological processes remains difficult. In this review, we describe the major bioactive molecules present in below-ground ecosystems (i.e., flavonoids, exopolysaccharides, antibiotics and quorum-sensing signals), and we discuss how these molecules affect microbial communities, nutrient availability and plant defense responses. PMID:23615474

SEMICONDUCTOR TECHNOLOGY A signal processing method for the friction-based endpoint detection system of a CMP process

NASA Astrophysics Data System (ADS)

Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang

2010-12-01

A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.

Advanced Quantitative Measurement Methodology in Physics Education Research

ERIC Educational Resources Information Center

Wang, Jing

2009-01-01

The ultimate goal of physics education research (PER) is to develop a theoretical framework to understand and improve the learning process. In this journey of discovery, assessment serves as our headlamp and alpenstock. It sometimes detects signals in student mental structures, and sometimes presents the difference between expert understanding and…

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

PubMed Central

Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong

2016-01-01

Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267

Preservation of Cognitive Function by Lepidium meyenii (Maca) Is Associated with Improvement of Mitochondrial Activity and Upregulation of Autophagy-Related Proteins in Middle-Aged Mouse Cortex

PubMed Central

Guo, Shan-Shan; Gao, Xiao-Fang; Gu, Yan-Rong

2016-01-01

Maca has been used as a foodstuff and a traditional medicine in the Andean region for over 2,000 years. Recently the neuroprotective effects of maca also arouse interest of researchers. Decrease in mitochondrial function and decline in autophagy signaling may participate in the process of age-related cognitive decline. This study aimed to investigate if maca could improve cognitive function of middle-aged mice and if this effect was associated with improvement of mitochondrial activity and modulation of autophagy signaling in mouse cortex. Fourteen-month-old male ICR mice received maca powder administered by gavage for five weeks. Maca improved cognitive function, motor coordination, and endurance capacity in middle-aged mice, accompanied by increased mitochondrial respiratory function and upregulation of autophagy-related proteins in cortex. Our findings suggest that maca is a newly defined nutritional plant which can improve mitochondrial function and upregulate autophagy-related proteins and may be an effective functional food for slowing down age-related cognitive decline. PMID:27648102

Preservation of Cognitive Function by Lepidium meyenii (Maca) Is Associated with Improvement of Mitochondrial Activity and Upregulation of Autophagy-Related Proteins in Middle-Aged Mouse Cortex.

PubMed

Guo, Shan-Shan; Gao, Xiao-Fang; Gu, Yan-Rong; Wan, Zhong-Xiao; Lu, A-Ming; Qin, Zheng-Hong; Luo, Li

2016-01-01

Maca has been used as a foodstuff and a traditional medicine in the Andean region for over 2,000 years. Recently the neuroprotective effects of maca also arouse interest of researchers. Decrease in mitochondrial function and decline in autophagy signaling may participate in the process of age-related cognitive decline. This study aimed to investigate if maca could improve cognitive function of middle-aged mice and if this effect was associated with improvement of mitochondrial activity and modulation of autophagy signaling in mouse cortex. Fourteen-month-old male ICR mice received maca powder administered by gavage for five weeks. Maca improved cognitive function, motor coordination, and endurance capacity in middle-aged mice, accompanied by increased mitochondrial respiratory function and upregulation of autophagy-related proteins in cortex. Our findings suggest that maca is a newly defined nutritional plant which can improve mitochondrial function and upregulate autophagy-related proteins and may be an effective functional food for slowing down age-related cognitive decline.

Combination of process and vibration data for improved condition monitoring of industrial systems working under variable operating conditions

NASA Astrophysics Data System (ADS)

Ruiz-Cárcel, C.; Jaramillo, V. H.; Mba, D.; Ottewill, J. R.; Cao, Y.

2016-01-01

The detection and diagnosis of faults in industrial processes is a very active field of research due to the reduction in maintenance costs achieved by the implementation of process monitoring algorithms such as Principal Component Analysis, Partial Least Squares or more recently Canonical Variate Analysis (CVA). Typically the condition of rotating machinery is monitored separately using vibration analysis or other specific techniques. Conventional vibration-based condition monitoring techniques are based on the tracking of key features observed in the measured signal. Typically steady-state loading conditions are required to ensure consistency between measurements. In this paper, a technique based on merging process and vibration data is proposed with the objective of improving the detection of mechanical faults in industrial systems working under variable operating conditions. The capabilities of CVA for detection and diagnosis of faults were tested using experimental data acquired from a compressor test rig where different process faults were introduced. Results suggest that the combination of process and vibration data can effectively improve the detectability of mechanical faults in systems working under variable operating conditions.

Engineering information on an Analog Signal to Discrete Time Interval Converter (ASDT-IC)

NASA Technical Reports Server (NTRS)

Schwarz, F. C.

1974-01-01

An electronic control system for nondissipative dc power converters is presented which improves (1) the routinely attainable static output voltage accuracy to the order of + or - 1% for ambient temperatures from -55 to 100 C and (2) the dynamic stability by utilizing approximately one tenth of the feedback gain needed otherwise. Performance is due to a functional philosophy of deterministic pulse modulation based on pulse area control and to an autocompensated signal processing principle. The system can be implemented with commercially available unselected components.

Methods for increasing noise immunity of radio electronic systems with redundancy

NASA Astrophysics Data System (ADS)

Orlov, P. E.; Medvedev, A. V.; Sharafutdinov, V. R.; Gazizov, T. R.; Ubaichin, A. V.

2018-05-01

The idea of increasing the noise immunity of radioelectronic systems with redundancy is presented. Specific technical solutions based on this idea of modal redundancy are described. An estimation of noise immunity improvement was performed by the example of implementation of modal redundancy with the broad-side electromagnetic coupling for a printed circuit board of the digital signal processing unit for an autonomous navigation system of a spacecraft. It is shown that the implementation of modal redundancy can provide an attenuation coefficient for the interference signal up to 12 dB.

Research on wheelchair robot control system based on EOG

NASA Astrophysics Data System (ADS)

Xu, Wang; Chen, Naijian; Han, Xiangdong; Sun, Jianbo

2018-04-01

The paper describes an intelligent wheelchair control system based on EOG. It can help disabled people improve their living ability. The system can acquire EOG signal from the user, detect the number of blink and the direction of glancing, and then send commands to the wheelchair robot via RS-232 to achieve the control of wheelchair robot. Wheelchair robot control system based on EOG is composed of processing EOG signal and human-computer interactive technology, which achieves a purpose of using conscious eye movement to control wheelchair robot.

High-speed event detector for embedded nanopore bio-systems.

PubMed

Huang, Yiyun; Magierowski, Sebastian; Ghafar-Zadeh, Ebrahim; Wang, Chengjie

2015-08-01

Biological measurements of microscopic phenomena often deal with discrete-event signals. The ability to automatically carry out such measurements at high-speed in a miniature embedded system is desirable but compromised by high-frequency noise along with practical constraints on filter quality and sampler resolution. This paper presents a real-time event-detection method in the context of nanopore sensing that helps to mitigate these drawbacks and allows accurate signal processing in an embedded system. Simulations show at least a 10× improvement over existing on-line detection methods.

A multi-channel instrumentation system for biosignal recording.

PubMed

Yu, Hong; Li, Pengfei; Xiao, Zhiming; Peng, Chung-Ching; Bashirullah, Rizwan

2008-01-01

This paper reports a highly integrated battery operated multi-channel instrumentation system intended for physiological signal recording. The mixed signal IC has been fabricated in standard 0.5microm 5V 3M-2P CMOS process and features 32 instrumentation amplifiers, four 8b SAR ADCs, a wireless power interface with Li-ion battery charger, low power bidirectional telemetry and FSM controller with power gating control for improved energy efficiency. The chip measures 3.2mm by 4.8mm and dissipates approximately 2.1mW when fully operational.

Comparison of digital signal-signal beat interference compensation techniques in direct-detection subcarrier modulation systems.

PubMed

Li, Zhe; Erkilinc, M Sezer; Galdino, Lidia; Shi, Kai; Thomsen, Benn C; Bayvel, Polina; Killey, Robert I

2016-12-12

Single-polarization direct-detection transceivers may offer advantages compared to digital coherent technology for some metro, back-haul, access and inter-data center applications since they offer low-cost and complexity solutions. However, a direct-detection receiver introduces nonlinearity upon photo detection, since it is a square-law device, which results in signal distortion due to signal-signal beat interference (SSBI). Consequently, it is desirable to develop effective and low-cost SSBI compensation techniques to improve the performance of such transceivers. In this paper, we compare the performance of a number of recently proposed digital signal processing-based SSBI compensation schemes, including the use of single- and two-stage linearization filters, an iterative linearization filter and a SSBI estimation and cancellation technique. Their performance is assessed experimentally using a 7 × 25 Gb/s wavelength division multiplexed (WDM) single-sideband 16-QAM Nyquist-subcarrier modulation system operating at a net information spectral density of 2.3 (b/s)/Hz.

Cardiac arrhythmia beat classification using DOST and PSO tuned SVM.

PubMed

Raj, Sandeep; Ray, Kailash Chandra; Shankar, Om

2016-11-01

The increase in the number of deaths due to cardiovascular diseases (CVDs) has gained significant attention from the study of electrocardiogram (ECG) signals. These ECG signals are studied by the experienced cardiologist for accurate and proper diagnosis, but it becomes difficult and time-consuming for long-term recordings. Various signal processing techniques are studied to analyze the ECG signal, but they bear limitations due to the non-stationary behavior of ECG signals. Hence, this study aims to improve the classification accuracy rate and provide an automated diagnostic solution for the detection of cardiac arrhythmias. The proposed methodology consists of four stages, i.e. filtering, R-peak detection, feature extraction and classification stages. In this study, Wavelet based approach is used to filter the raw ECG signal, whereas Pan-Tompkins algorithm is used for detecting the R-peak inside the ECG signal. In the feature extraction stage, discrete orthogonal Stockwell transform (DOST) approach is presented for an efficient time-frequency representation (i.e. morphological descriptors) of a time domain signal and retains the absolute phase information to distinguish the various non-stationary behavior ECG signals. Moreover, these morphological descriptors are further reduced in lower dimensional space by using principal component analysis and combined with the dynamic features (i.e based on RR-interval of the ECG signals) of the input signal. This combination of two different kinds of descriptors represents each feature set of an input signal that is utilized for classification into subsequent categories by employing PSO tuned support vector machines (SVM). The proposed methodology is validated on the baseline MIT-BIH arrhythmia database and evaluated under two assessment schemes, yielding an improved overall accuracy of 99.18% for sixteen classes in the category-based and 89.10% for five classes (mapped according to AAMI standard) in the patient-based assessment scheme respectively to the state-of-art diagnosis. The results reported are further compared to the existing methodologies in literature. The proposed feature representation of cardiac signals based on symmetrical features along with PSO based optimization technique for the SVM classifier reported an improved classification accuracy in both the assessment schemes evaluated on the benchmark MIT-BIH arrhythmia database and hence can be utilized for automated computer-aided diagnosis of cardiac arrhythmia beats. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

PubMed Central

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-01-01

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective. PMID:25207870

Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

PubMed

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-09-09

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective.

Complex inhibitory microcircuitry regulates retinal signaling near visual threshold

PubMed Central

Grimes, William N.; Zhang, Jun; Tian, Hua; Graydon, Cole W.; Hoon, Mrinalini; Rieke, Fred

2015-01-01

Neuronal microcircuits, small, localized signaling motifs involving two or more neurons, underlie signal processing and computation in the brain. Compartmentalized signaling within a neuron may enable it to participate in multiple, independent microcircuits. Each A17 amacrine cell in the mammalian retina contains within its dendrites hundreds of synaptic feedback microcircuits that operate independently to modulate feedforward signaling in the inner retina. Each of these microcircuits comprises a small (<1 μm) synaptic varicosity that typically receives one excitatory synapse from a presynaptic rod bipolar cell (RBC) and returns two reciprocal inhibitory synapses back onto the same RBC terminal. Feedback inhibition from the A17 sculpts the feedforward signal from the RBC to the AII, a critical component of the circuitry mediating night vision. Here, we show that the two inhibitory synapses from the A17 to the RBC express kinetically distinct populations of GABA receptors: rapidly activating GABAARs are enriched at one synapse while more slowly activating GABACRs are enriched at the other. Anatomical and electrophysiological data suggest that macromolecular complexes of voltage-gated (Cav) channels and Ca2+-activated K+ channels help to regulate GABA release from A17 varicosities and limit GABACR activation under certain conditions. Finally, we find that selective elimination of A17-mediated feedback inhibition reduces the signal to noise ratio of responses to dim flashes recorded in the feedforward pathway (i.e., the AII amacrine cell). We conclude that A17-mediated feedback inhibition improves the signal to noise ratio of RBC-AII transmission near visual threshold, thereby improving visual sensitivity at night. PMID:25972578

Visual Perceptual Learning and Models.

PubMed

Dosher, Barbara; Lu, Zhong-Lin

2017-09-15

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.