Comparison of formant detection methods used in speech processing applications

NASA Astrophysics Data System (ADS)

Belean, Bogdan

2013-11-01

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

Preface to the special issue on "Integrated Microwave Photonic Signal Processing"

NASA Astrophysics Data System (ADS)

Azaña, José; Yao, Jianping

2016-08-01

As Guest Editors, we are pleased to introduce this special issue on ;Integrated Microwave Photonic Signal Processing; published by the Elsevier journal Optics Communications. Microwave photonics is a field of growing importance from both scientific and practical application perspectives. The field of microwave photonics is devoted to the study, development and application of optics-based techniques and technologies aimed to the generation, processing, control, characterization and/or distribution of microwave signals, including signals well into the millimeter-wave frequency range. The use of photonic technologies for these microwave applications translates into a number of key advantages, such as the possibility of dealing with high-frequency, wide bandwidth signals with minimal losses and reduced electromagnetic interferences, and the potential for enhanced reconfigurability. The central purpose of this special issue is to provide an overview of the state of the art of generation, processing and characterization technologies for high-frequency microwave signals. It is now widely accepted that the practical success of microwave photonics at a large scale will essentially depend on the realization of high-performance microwave-photonic signal-processing engines in compact and integrated formats, preferably on a chip. Thus, the focus of the issue is on techniques implemented using integrated photonic technologies, with the goal of providing an update of the most recent advances toward realization of this vision.

UCMS - A new signal parameter measurement system using digital signal processing techniques. [User Constraint Measurement System

NASA Technical Reports Server (NTRS)

Choi, H. J.; Su, Y. T.

1986-01-01

The User Constraint Measurement System (UCMS) is a hardware/software package developed by NASA Goddard to measure the signal parameter constraints of the user transponder in the TDRSS environment by means of an all-digital signal sampling technique. An account is presently given of the features of UCMS design and of its performance capabilities and applications; attention is given to such important aspects of the system as RF interface parameter definitions, hardware minimization, the emphasis on offline software signal processing, and end-to-end link performance. Applications to the measurement of other signal parameters are also discussed.

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

Sensitivity Analysis in RIPless Compressed Sensing

DTIC Science & Technology

2014-10-01

SECURITY CLASSIFICATION OF: The compressive sensing framework finds a wide range of applications in signal processing and analysis. Within this...Analysis of Compressive Sensing Solutions Report Title The compressive sensing framework finds a wide range of applications in signal processing and...compressed sensing. More specifically, we show that in a noiseless and RIP-less setting [11], the recovery process of a compressed sensing framework is

Wavelet transform: fundamentals, applications, and implementation using acousto-optic correlators

NASA Astrophysics Data System (ADS)

DeCusatis, Casimer M.; Koay, J.; Litynski, Daniel M.; Das, Pankaj K.

1995-10-01

In recent years there has been a great deal of interest in the use of wavelets to supplement or replace conventional Fourier transform signal processing. This paper provides a review of wavelet transforms for signal processing applications, and discusses several emerging applications which benefit from the advantages of wavelets. The wavelet transform can be implemented as an acousto-optic correlator; perfect reconstruction of digital signals may also be achieved using acousto-optic finite impulse response filter banks. Acousto-optic image correlators are discussed as a potential implementation of the wavelet transform, since a 1D wavelet filter bank may be encoded as a 2D image. We discuss applications of the wavelet transform including nondestructive testing of materials, biomedical applications in the analysis of EEG signals, and interference excision in spread spectrum communication systems. Computer simulations and experimental results for these applications are also provided.

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

NASA Astrophysics Data System (ADS)

Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor

2004-07-01

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

Designer cell signal processing circuits for biotechnology

PubMed Central

Bradley, Robert W.; Wang, Baojun

2015-01-01

Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field. PMID:25579192

Signal processing methods for MFE plasma diagnostics

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

Candy, J.V.; Casper, T.; Kane, R.

1985-02-01

The application of various signal processing methods to extract energy storage information from plasma diamagnetism sensors occurring during physics experiments on the Tandom Mirror Experiment-Upgrade (TMX-U) is discussed. We show how these processing techniques can be used to decrease the uncertainty in the corresponding sensor measurements. The algorithms suggested are implemented using SIG, an interactive signal processing package developed at LLNL.

Aerospace Applications Conference, Steamboat Springs, CO, Feb. 1-8, 1986, Digest

NASA Astrophysics Data System (ADS)

The present conference considers topics concerning the projected NASA Space Station's systems, digital signal and data processing applications, and space science and microwave applications. Attention is given to Space Station video and audio subsystems design, clock error, jitter, phase error and differential time-of-arrival in satellite communications, automation and robotics in space applications, target insertion into synthetic background scenes, and a novel scheme for the computation of the discrete Fourier transform on a systolic processor. Also discussed are a novel signal parameter measurement system employing digital signal processing, EEPROMS for spacecraft applications, a unique concurrent processor architecture for high speed simulation of dynamic systems, a dual polarization flat plate antenna, Fresnel diffraction, and ultralinear TWTs for high efficiency satellite communications.

Applications of ICA and fractal dimension in sEMG signal processing for subtle movement analysis: a review.

PubMed

Naik, Ganesh R; Arjunan, Sridhar; Kumar, Dinesh

2011-06-01

The surface electromyography (sEMG) signal separation and decphompositions has always been an interesting research topic in the field of rehabilitation and medical research. Subtle myoelectric control is an advanced technique concerned with the detection, processing, classification, and application of myoelectric signals to control human-assisting robots or rehabilitation devices. This paper reviews recent research and development in independent component analysis and Fractal dimensional analysis for sEMG pattern recognition, and presents state-of-the-art achievements in terms of their type, structure, and potential application. Directions for future research are also briefly outlined.

Adaptive filtering in biological signal processing.

PubMed

Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

1990-01-01

The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

Signal existence verification (SEV) for GPS low received power signal detection using the time-frequency approach.

PubMed

Jan, Shau-Shiun; Sun, Chih-Cheng

2010-01-01

The detection of low received power of global positioning system (GPS) signals in the signal acquisition process is an important issue for GPS applications. Improving the miss-detection problem of low received power signal is crucial, especially for urban or indoor environments. This paper proposes a signal existence verification (SEV) process to detect and subsequently verify low received power GPS signals. The SEV process is based on the time-frequency representation of GPS signal, and it can capture the characteristic of GPS signal in the time-frequency plane to enhance the GPS signal acquisition performance. Several simulations and experiments are conducted to show the effectiveness of the proposed method for low received power signal detection. The contribution of this work is that the SEV process is an additional scheme to assist the GPS signal acquisition process in low received power signal detection, without changing the original signal acquisition or tracking algorithms.

Remote diagnosis server

NASA Technical Reports Server (NTRS)

Deb, Somnath (Inventor); Ghoshal, Sudipto (Inventor); Malepati, Venkata N. (Inventor); Kleinman, David L. (Inventor); Cavanaugh, Kevin F. (Inventor)

2004-01-01

A network-based diagnosis server for monitoring and diagnosing a system, the server being remote from the system it is observing, comprises a sensor for generating signals indicative of a characteristic of a component of the system, a network-interfaced sensor agent coupled to the sensor for receiving signals therefrom, a broker module coupled to the network for sending signals to and receiving signals from the sensor agent, a handler application connected to the broker module for transmitting signals to and receiving signals therefrom, a reasoner application in communication with the handler application for processing, and responding to signals received from the handler application, wherein the sensor agent, broker module, handler application, and reasoner applications operate simultaneously relative to each other, such that the present invention diagnosis server performs continuous monitoring and diagnosing of said components of the system in real time. The diagnosis server is readily adaptable to various different systems.

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

PubMed

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

2014-04-01

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

Optical signal processing of spatially distributed sensor data in smart structures

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

EMG amplifier with wireless data transmission

NASA Astrophysics Data System (ADS)

Kowalski, Grzegorz; Wildner, Krzysztof

2017-08-01

Wireless medical diagnostics is a trend in modern technology used in medicine. This paper presents a concept of realization, architecture of hardware and software implementation of an elecromyography signal (EMG) amplifier with wireless data transmission. This amplifier consists of three components: analogue processing of bioelectric signal module, micro-controller circuit and an application enabling data acquisition via a personal computer. The analogue bioelectric signal processing circuit receives electromyography signals from the skin surface, followed by initial analogue processing and preparation of the signals for further digital processing. The second module is a micro-controller circuit designed to wirelessly transmit the electromyography signals from the analogue signal converter to a personal computer. Its purpose is to eliminate the need for wired connections between the patient and the data logging device. The third block is a computer application designed to display the transmitted electromyography signals, as well as data capture and analysis. Its purpose is to provide a graphical representation of the collected data. The entire device has been thoroughly tested to ensure proper functioning. In use, the device displayed the captured electromyography signal from the arm of the patient. Amplitude- frequency characteristics were set in order to investigate the bandwidth and the overall gain of the device.

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

NASA Technical Reports Server (NTRS)

Halverson, Peter G.; Loya, Frank M.

2004-01-01

This paper describes heterodyne displacement metrology gauge signal processing methods that achieve satisfactory robustness against low signal strength and spurious signals, and good long-term stability. We have a proven displacement-measuring approach that is useful not only to space-optical projects at JPL, but also to the wider field of distance measurements.

Digital Signal Processing Methods for Ultrasonic Echoes.

PubMed

Sinding, Kyle; Drapaca, Corina; Tittmann, Bernhard

2016-04-28

Digital signal processing has become an important component of data analysis needed in industrial applications. In particular, for ultrasonic thickness measurements the signal to noise ratio plays a major role in the accurate calculation of the arrival time. For this application a band pass filter is not sufficient since the noise level cannot be significantly decreased such that a reliable thickness measurement can be performed. This paper demonstrates the abilities of two regularization methods - total variation and Tikhonov - to filter acoustic and ultrasonic signals. Both of these methods are compared to a frequency based filtering for digitally produced signals as well as signals produced by ultrasonic transducers. This paper demonstrates the ability of the total variation and Tikhonov filters to accurately recover signals from noisy acoustic signals faster than a band pass filter. Furthermore, the total variation filter has been shown to reduce the noise of a signal significantly for signals with clear ultrasonic echoes. Signal to noise ratios have been increased over 400% by using a simple parameter optimization. While frequency based filtering is efficient for specific applications, this paper shows that the reduction of noise in ultrasonic systems can be much more efficient with regularization methods.

Transit signal priority systems application and technology investigation : final report, March 2009.

DOT National Transportation Integrated Search

2009-03-01

This report describes the process and results of research to develop an evaluation process that will : assist NJ Transit in quickly determining which intersections are good candidates for Transit Signal : Priority (TSP). This evaluation process is ap...

A bunch to bucket phase detector for the RHIC LLRF upgrade platform

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

Smith, K.S.; Harvey, M.; Hayes, T.

2011-03-28

As part of the overall development effort for the RHIC LLRF Upgrade Platform [1,2,3], a generic four channel 16 bit Analog-to-Digital Converter (ADC) daughter module was developed to provide high speed, wide dynamic range digitizing and processing of signals from DC to several hundred megahertz. The first operational use of this card was to implement the bunch to bucket phase detector for the RHIC LLRF beam control feedback loops. This paper will describe the design and performance features of this daughter module as a bunch to bucket phase detector, and also provide an overview of its place within the overallmore » LLRF platform architecture as a high performance digitizer and signal processing module suitable to a variety of applications. In modern digital control and signal processing systems, ADCs provide the interface between the analog and digital signal domains. Once digitized, signals are then typically processed using algorithms implemented in field programmable gate array (FPGA) logic, general purpose processors (GPPs), digital signal processors (DSPs) or a combination of these. For the recently developed and commissioned RHIC LLRF Upgrade Platform, we've developed a four channel ADC daughter module based on the Linear Technology LTC2209 16 bit, 160 MSPS ADC and the Xilinx V5FX70T FPGA. The module is designed to be relatively generic in application, and with minimal analog filtering on board, is capable of processing signals from DC to 500 MHz or more. The module's first application was to implement the bunch to bucket phase detector (BTB-PD) for the RHIC LLRF system. The same module also provides DC digitizing of analog processed BPM signals used by the LLRF system for radial feedback.« less

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

PubMed

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

2016-01-01

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

Digital Signal Processing Based Biotelemetry Receivers

NASA Technical Reports Server (NTRS)

Singh, Avtar; Hines, John; Somps, Chris

1997-01-01

This is an attempt to develop a biotelemetry receiver using digital signal processing technology and techniques. The receiver developed in this work is based on recovering signals that have been encoded using either Pulse Position Modulation (PPM) or Pulse Code Modulation (PCM) technique. A prototype has been developed using state-of-the-art digital signal processing technology. A Printed Circuit Board (PCB) is being developed based on the technique and technology described here. This board is intended to be used in the UCSF Fetal Monitoring system developed at NASA. The board is capable of handling a variety of PPM and PCM signals encoding signals such as ECG, temperature, and pressure. A signal processing program has also been developed to analyze the received ECG signal to determine heart rate. This system provides a base for using digital signal processing in biotelemetry receivers and other similar applications.

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.

Analog integrated circuits design for processing physiological signals.

PubMed

Li, Yan; Poon, Carmen C Y; Zhang, Yuan-Ting

2010-01-01

Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this paper, techniques for designing the analog front-end circuits with these three characteristics will be reviewed, including subthreshold circuits, bulk-driven MOSFETs, floating gate MOSFETs, and log-domain circuits to reduce power consumption; methods for designing fully integrated low cutoff frequency circuits; as well as chopper stabilization (CHS) and other techniques that can be used to achieve a high signal-to-noise performance. Novel applications using these techniques will also be discussed.

Orthogonal transform feasibility study

NASA Technical Reports Server (NTRS)

Robinson, G. S.

1971-01-01

The application of various orthogonal transformations to communication was investigated, with particular emphasis placed on speech and visual signal processing. The fundamentals of the one- and two-dimensional orthogonal transforms and their application to speech and visual signals are treated in detail.

siGnum: graphical user interface for EMG signal analysis.

PubMed

Kaur, Manvinder; Mathur, Shilpi; Bhatia, Dinesh; Verma, Suresh

2015-01-01

Electromyography (EMG) signals that represent the electrical activity of muscles can be used for various clinical and biomedical applications. These are complicated and highly varying signals that are dependent on anatomical location and physiological properties of the muscles. EMG signals acquired from the muscles require advanced methods for detection, decomposition and processing. This paper proposes a novel Graphical User Interface (GUI) siGnum developed in MATLAB that will apply efficient and effective techniques on processing of the raw EMG signals and decompose it in a simpler manner. It could be used independent of MATLAB software by employing a deploy tool. This would enable researcher's to gain good understanding of EMG signal and its analysis procedures that can be utilized for more powerful, flexible and efficient applications in near future.

Materials, devices, techniques, and applications for Z-plane focal plane array technology II; Proceedings of the Meeting, San Diego, CA, July 12, 13, 1990

NASA Astrophysics Data System (ADS)

Carson, John C.

1990-11-01

Various papers on materials, devices, techniques, and applications for X-plane focal plane array technology are presented. Individual topics addressed include: application of Z-plane technology to the remote sensing of the earth from GEO, applications of smart neuromorphic focal planes, image-processing of Z-plane technology, neural network Z-plane implementation with very high interconnection rates, using a small IR surveillance satellite for tactical applications, establishing requirements for homing applications, Z-plane technology. Also discussed are: on-array spike suppression signal processing, algorithms for on-focal-plane gamma circumvention and time-delay integration, current HYMOSS Z-technology, packaging of electrons for on- and off-FPA signal processing, space/performance qualification of tape automated bonded devices, automation in tape automated bonding, high-speed/high-volume radiometric testing of Z-technology focal planes, 128-layer HYMOSS-module fabrication issues, automation of IRFPA production processes.

Multi-Dimensional Signal Processing Research Program

DTIC Science & Technology

1981-09-30

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

Hot topics: Signal processing in acoustics

NASA Astrophysics Data System (ADS)

Gaumond, Charles F.

2005-09-01

Signal processing in acoustics is a multidisciplinary group of people that work in many areas of acoustics. We have chosen two areas that have shown exciting new applications of signal processing to acoustics or have shown exciting and important results from the use of signal processing. In this session, two hot topics are shown: the use of noiselike acoustic fields to determine sound propagation structure and the use of localization to determine animal behaviors. The first topic shows the application of correlation on geo-acoustic fields to determine the Greens function for propagation through the Earth. These results can then be further used to solve geo-acoustic inverse problems. The first topic also shows the application of correlation using oceanic noise fields to determine the Greens function through the ocean. These results also have utility for oceanic inverse problems. The second topic shows exciting results from the detection, localization, and tracking of marine mammals by two different groups. Results from detection and localization of bullfrogs are shown, too. Each of these studies contributed to the knowledge of animal behavior. [Work supported by ONR.

Properties of an improved Gabor wavelet transform and its applications to seismic signal processing and interpretation

NASA Astrophysics Data System (ADS)

Ji, Zhan-Huai; Yan, Sheng-Gang

2017-12-01

This paper presents an analytical study of the complete transform of improved Gabor wavelets (IGWs), and discusses its application to the processing and interpretation of seismic signals. The complete Gabor wavelet transform has the following properties. First, unlike the conventional transform, the improved Gabor wavelet transform (IGWT) maps time domain signals to the time-frequency domain instead of the time-scale domain. Second, the IGW's dominant frequency is fixed, so the transform can perform signal frequency division, where the dominant frequency components of the extracted sub-band signal carry essentially the same information as the corresponding components of the original signal, and the subband signal bandwidth can be regulated effectively by the transform's resolution factor. Third, a time-frequency filter consisting of an IGWT and its inverse transform can accurately locate target areas in the time-frequency field and perform filtering in a given time-frequency range. The complete IGW transform's properties are investigated using simulation experiments and test cases, showing positive results for seismic signal processing and interpretation, such as enhancing seismic signal resolution, permitting signal frequency division, and allowing small faults to be identified.

Digital communications study

NASA Technical Reports Server (NTRS)

Boorstyn, R. R.

1973-01-01

Research is reported dealing with problems of digital data transmission and computer communications networks. The results of four individual studies are presented which include: (1) signal processing with finite state machines, (2) signal parameter estimation from discrete-time observations, (3) digital filtering for radar signal processing applications, and (4) multiple server queues where all servers are not identical.

Parallel Processing with Digital Signal Processing Hardware and Software

NASA Technical Reports Server (NTRS)

Swenson, Cory V.

1995-01-01

The assembling and testing of a parallel processing system is described which will allow a user to move a Digital Signal Processing (DSP) application from the design stage to the execution/analysis stage through the use of several software tools and hardware devices. The system will be used to demonstrate the feasibility of the Algorithm To Architecture Mapping Model (ATAMM) dataflow paradigm for static multiprocessor solutions of DSP applications. The individual components comprising the system are described followed by the installation procedure, research topics, and initial program development.

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

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.

Advanced digital signal processing for short haul optical fiber transmission beyond 100G

NASA Astrophysics Data System (ADS)

Kikuchi, Nobuhiko

2017-01-01

Significant increase of intra and inter data center traffic has been expected by the rapid spread of various network applications like SNS, IoT, mobile and cloud computing, and the needs for ultra-high speed and cost-effective short- to medium-reach optical fiber links beyond 100-Gbit/s is becoming larger and larger. Such high-speed links typically use multilevel modulation to lower signaling speed, which in turn face serious challenges in limited loss budget and waveform distortion tolerance. One of the promising techniques to overcome them is the use of advanced digital signal processing (DSP) and we review various DSP applications for short-to-medium reach applications.

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.

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

NASA Technical Reports Server (NTRS)

Huang, Norden E.

2003-01-01

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

Sensors, Volume 1, Fundamentals and General Aspects

NASA Astrophysics Data System (ADS)

Grandke, Thomas; Ko, Wen H.

1996-12-01

'Sensors' is the first self-contained series to deal with the whole area of sensors. It describes general aspects, technical and physical fundamentals, construction, function, applications and developments of the various types of sensors. This volume deals with the fundamentals and common principles of sensors and covers the wide areas of principles, technologies, signal processing, and applications. Contents include: Sensor Fundamentals, e.g. Sensor Parameters, Modeling, Design and Packaging; Basic Sensor Technologies, e.g. Thin and Thick Films, Integrated Magnetic Sensors, Optical Fibres and Intergrated Optics, Ceramics and Oxides; Sensor Interfaces, e.g. Signal Processing, Multisensor Signal Processing, Smart Sensors, Interface Systems; Sensor Applications, e.g. Automotive: On-board Sensors, Traffic Surveillance and Control, Home Appliances, Environmental Monitoring, etc. This volume is an indispensable reference work and text book for both specialits and newcomers, researchers and developers.

Applications of digital processing for noise removal from plasma diagnostics

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

Kane, R.J.; Candy, J.V.; Casper, T.A.

1985-11-11

The use of digital signal techniques for removal of noise components present in plasma diagnostic signals is discussed, particularly with reference to diamagnetic loop signals. These signals contain noise due to power supply ripple in addition to plasma characteristics. The application of noise canceling techniques, such as adaptive noise canceling and model-based estimation, will be discussed. The use of computer codes such as SIG is described. 19 refs., 5 figs.

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.

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.

Spiked Models of Large Dimensional Random Matrices Applied to Wireless Communications and Array Signal Processing

DTIC Science & Technology

2013-12-14

population covariance matrix with application to array signal processing; and 5) a sample covariance matrix for which a CLT is studied on linear...Applications , (01 2012): 1150004. doi: Walid Hachem, Malika Kharouf, Jamal Najim, Jack W. Silverstein. A CLT FOR INFORMATION- THEORETIC STATISTICS...for Multi-source Power Estimation, (04 2010) Malika Kharouf, Jamal Najim, Jack W. Silverstein, Walid Hachem. A CLT FOR INFORMATION- THEORETIC

A dynamic multi-channel speech enhancement system for distributed microphones in a car environment

NASA Astrophysics Data System (ADS)

Matheja, Timo; Buck, Markus; Fingscheidt, Tim

2013-12-01

Supporting multiple active speakers in automotive hands-free or speech dialog applications is an interesting issue not least due to comfort reasons. Therefore, a multi-channel system for enhancement of speech signals captured by distributed distant microphones in a car environment is presented. Each of the potential speakers in the car has a dedicated directional microphone close to his position that captures the corresponding speech signal. The aim of the resulting overall system is twofold: On the one hand, a combination of an arbitrary pre-defined subset of speakers' signals can be performed, e.g., to create an output signal in a hands-free telephone conference call for a far-end communication partner. On the other hand, annoying cross-talk components from interfering sound sources occurring in multiple different mixed output signals are to be eliminated, motivated by the possibility of other hands-free applications being active in parallel. The system includes several signal processing stages. A dedicated signal processing block for interfering speaker cancellation attenuates the cross-talk components of undesired speech. Further signal enhancement comprises the reduction of residual cross-talk and background noise. Subsequently, a dynamic signal combination stage merges the processed single-microphone signals to obtain appropriate mixed signals at the system output that may be passed to applications such as telephony or a speech dialog system. Based on signal power ratios between the particular microphone signals, an appropriate speaker activity detection and therewith a robust control mechanism of the whole system is presented. The proposed system may be dynamically configured and has been evaluated for a car setup with four speakers sitting in the car cabin disturbed in various noise conditions.

See-through Detection and 3D Reconstruction Using Terahertz Leaky-Wave Radar Based on Sparse Signal Processing

NASA Astrophysics Data System (ADS)

Murata, Koji; Murano, Kosuke; Watanabe, Issei; Kasamatsu, Akifumi; Tanaka, Toshiyuki; Monnai, Yasuaki

2018-02-01

We experimentally demonstrate see-through detection and 3D reconstruction using terahertz leaky-wave radar based on sparse signal processing. The application of terahertz waves to radar has received increasing attention in recent years for its potential to high-resolution and see-through detection. Among others, the implementation using a leaky-wave antenna is promising for compact system integration with beam steering capability based on frequency sweep. However, the use of a leaky-wave antenna poses a challenge on signal processing. Since a leaky-wave antenna combines the entire signal captured by each part of the aperture into a single output, the conventional array signal processing assuming access to a respective antenna element is not applicable. In this paper, we apply an iterative recovery algorithm "CoSaMP" to signals acquired with terahertz leaky-wave radar for clutter mitigation and aperture synthesis. We firstly demonstrate see-through detection of target location even when the radar is covered with an opaque screen, and therefore, the radar signal is disturbed by clutter. Furthermore, leveraging the robustness of the algorithm against noise, we also demonstrate 3D reconstruction of distributed targets by synthesizing signals collected from different orientations. The proposed approach will contribute to the smart implementation of terahertz leaky-wave radar.

A Cochlear Implant Signal Processing Lab: Exploration of a Problem-Based Learning Exercise

ERIC Educational Resources Information Center

Bhatti, P. T.; McClellan, J. H.

2011-01-01

This paper presents an introductory signal processing laboratory and examines this laboratory exercise in the context of problem-based learning (PBL). Centered in a real-world application, a cochlear implant, the exercise challenged students to demonstrate a working software-based signal processor. Partnering in groups of two or three, second-year…

Department of Cybernetic Acoustics

NASA Astrophysics Data System (ADS)

The development of the theory, instrumentation and applications of methods and systems for the measurement, analysis, processing and synthesis of acoustic signals within the audio frequency range, particularly of the speech signal and the vibro-acoustic signal emitted by technical and industrial equipments treated as noise and vibration sources was discussed. The research work, both theoretical and experimental, aims at applications in various branches of science, and medicine, such as: acoustical diagnostics and phoniatric rehabilitation of pathological and postoperative states of the speech organ; bilateral ""man-machine'' speech communication based on the analysis, recognition and synthesis of the speech signal; vibro-acoustical diagnostics and continuous monitoring of the state of machines, technical equipments and technological processes.

Array signal processing in the NASA Deep Space Network

NASA Technical Reports Server (NTRS)

Pham, Timothy T.; Jongeling, Andre P.

2004-01-01

In this paper, we will describe the benefits of arraying and past as well as expected future use of this application. The signal processing aspects of array system are described. Field measurements via actual tracking spacecraft are also presented.

Application of maximum likelihood methods to laser Thomson scattering measurements of low density plasmas

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

Washeleski, Robert L.; Meyer, Edmond J. IV; King, Lyon B.

2013-10-15

Laser Thomson scattering (LTS) is an established plasma diagnostic technique that has seen recent application to low density plasmas. It is difficult to perform LTS measurements when the scattered signal is weak as a result of low electron number density, poor optical access to the plasma, or both. Photon counting methods are often implemented in order to perform measurements in these low signal conditions. However, photon counting measurements performed with photo-multiplier tubes are time consuming and multi-photon arrivals are incorrectly recorded. In order to overcome these shortcomings a new data analysis method based on maximum likelihood estimation was developed. Themore » key feature of this new data processing method is the inclusion of non-arrival events in determining the scattered Thomson signal. Maximum likelihood estimation and its application to Thomson scattering at low signal levels is presented and application of the new processing method to LTS measurements performed in the plume of a 2-kW Hall-effect thruster is discussed.« less

Application of maximum likelihood methods to laser Thomson scattering measurements of low density plasmas.

PubMed

Washeleski, Robert L; Meyer, Edmond J; King, Lyon B

2013-10-01

Laser Thomson scattering (LTS) is an established plasma diagnostic technique that has seen recent application to low density plasmas. It is difficult to perform LTS measurements when the scattered signal is weak as a result of low electron number density, poor optical access to the plasma, or both. Photon counting methods are often implemented in order to perform measurements in these low signal conditions. However, photon counting measurements performed with photo-multiplier tubes are time consuming and multi-photon arrivals are incorrectly recorded. In order to overcome these shortcomings a new data analysis method based on maximum likelihood estimation was developed. The key feature of this new data processing method is the inclusion of non-arrival events in determining the scattered Thomson signal. Maximum likelihood estimation and its application to Thomson scattering at low signal levels is presented and application of the new processing method to LTS measurements performed in the plume of a 2-kW Hall-effect thruster is discussed.

Biomolecular logic systems: applications to biosensors and bioactuators

NASA Astrophysics Data System (ADS)

Katz, Evgeny

2014-05-01

The paper presents an overview of recent advances in biosensors and bioactuators based on the biocomputing concept. Novel biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce output in the form of YES/NO response. Compared to traditional single-analyte sensing devices, biocomputing approach enables a high-fidelity multi-analyte biosensing, particularly beneficial for biomedical applications. Multi-signal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert to medical emergencies, along with an immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly exemplified for liver injury. Wide-ranging applications of multi-analyte digital biosensors in medicine, environmental monitoring and homeland security are anticipated. "Smart" bioactuators, for example for signal-triggered drug release, were designed by interfacing switchable electrodes and biocomputing systems. Integration of novel biosensing and bioactuating systems with the biomolecular information processing systems keeps promise for further scientific advances and numerous practical applications.

Editorial: Mathematical Methods and Modeling in Machine Fault Diagnosis

DOE PAGES

Yan, Ruqiang; Chen, Xuefeng; Li, Weihua; ...

2014-12-18

Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less

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

Yan, Ruqiang; Chen, Xuefeng; Li, Weihua

Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less

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.

Overview of the DART project

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

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

1992-01-01

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

Overview of the DART project

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

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

1992-01-01

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

Digital signal processing based on inverse scattering transform.

PubMed

Turitsyna, Elena G; Turitsyn, Sergei K

2013-10-15

Through numerical modeling, we illustrate the possibility of a new approach to digital signal processing in coherent optical communications based on the application of the so-called inverse scattering transform. Considering without loss of generality a fiber link with normal dispersion and quadrature phase shift keying signal modulation, we demonstrate how an initial information pattern can be recovered (without direct backward propagation) through the calculation of nonlinear spectral data of the received optical signal.

Bistatic SAR: Signal Processing and Image Formation.

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

Wahl, Daniel E.; Yocky, David A.

This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013more » on Kirtland Air Force Base, New Mexico.« less

Optimization of MLS receivers for multipath environments

NASA Technical Reports Server (NTRS)

Mcalpine, G. A.; Highfill, J. H., III

1976-01-01

The design of a microwave landing system (MLS) aircraft receiver, capable of optimal performance in multipath environments found in air terminal areas, is reported. Special attention was given to the angle tracking problem of the receiver and includes tracking system design considerations, study and application of locally optimum estimation involving multipath adaptive reception and then envelope processing, and microcomputer system design. Results show processing is competitive in this application with i-f signal processing performance-wise and is much more simple and cheaper. A summary of the signal model is given.

Waveguide Studies for Fiber Optics and Optical Signal Processing Applications.

DTIC Science & Technology

1980-04-01

AO-A086 115 UNI!VERtSIT? OF SOUTIUR CALEPCRNA LOS AMUSS / 5 WAVGUIDE STUIES15 FOR FEB53 OpTECS AND OpTICAL SEOSA.o P /0Ksu-y "/6 UNLSIIDAPR N0 E...SAMUE Flola-??-c-sa UNCASZFIORAC-M-8042 U Final Technical Report (1 1April 1950 L V ~ WAVEGUIDE STUDIES FOR FIBER OPTICS AND OPTICAL SIGNAL PROCESSING...and Subtitle) 081 6&4𔃾JODO )EI YAVECUIDESTUDIES FOR JIBER OPTICS ANDL 7 Final ,T/echnical epoErt, OPTICAL SI’tNAL PROCESSING APPLICATIONS.4 11 Se 77

Defense Applications of Signal Processing

DTIC Science & Technology

1999-08-27

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

A mixed signal ECG processing platform with an adaptive sampling ADC for portable monitoring applications.

PubMed

Kim, Hyejung; Van Hoof, Chris; Yazicioglu, Refet Firat

2011-01-01

This paper describes a mixed-signal ECG processing platform with an 12-bit ADC architecture that can adapt its sampling rate according to the input signals rate of change. This enables the sampling of ECG signals with significantly reduced data rate without loss of information. The presented adaptive sampling scheme reduces the ADC power consumption, enables the processing of ECG signals with lower power consumption, and reduces the power consumption of the radio while streaming the ECG signals. The test results show that running a CWT-based R peak detection algorithm using the adaptively sampled ECG signals consumes only 45.6 μW and it leads to 36% less overall system power consumption.

Signal Processing Applications Of Wigner-Ville Analysis

NASA Astrophysics Data System (ADS)

Whitehouse, H. J.; Boashash, B.

1986-04-01

The Wigner-Ville distribution (WVD), a form of time-frequency analysis, is shown to be useful in the analysis of a variety of non-stationary signals both deterministic and stochastic. The properties of the WVD are reviewed and alternative methods of calculating the WVD are discussed. Applications are presented.

All-optical signal processing using dynamic Brillouin gratings

PubMed Central

Santagiustina, Marco; Chin, Sanghoon; Primerov, Nicolay; Ursini, Leonora; Thévenaz, Luc

2013-01-01

The manipulation of dynamic Brillouin gratings in optical fibers is demonstrated to be an extremely flexible technique to achieve, with a single experimental setup, several all-optical signal processing functions. In particular, all-optical time differentiation, time integration and true time reversal are theoretically predicted, and then numerically and experimentally demonstrated. The technique can be exploited to process both photonic and ultra-wide band microwave signals, so enabling many applications in photonics and in radio science. PMID:23549159

Digital Signal Processing by Virtual Instrumentation of a MEMS Magnetic Field Sensor for Biomedical Applications

PubMed Central

Juárez-Aguirre, Raúl; Domínguez-Nicolás, Saúl M.; Manjarrez, Elías; Tapia, Jesús A.; Figueras, Eduard; Vázquez-Leal, Héctor; Aguilera-Cortés, Luz A.; Herrera-May, Agustín L.

2013-01-01

We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing. The virtual instrument includes an algorithm to implement different configurations of infinite impulse response (IIR) filters. The PCB contains a precision instrumentation amplifier, a demodulator, a low-pass filter (LPF) and a buffer with operational amplifier. The proposed prototype is used for real-time non-invasive monitoring of magnetic flux density in the thoracic cage of rats. The response of the rat respiratory magnetogram displays a similar behavior as the rat electromyogram (EMG). PMID:24196434

A fully reconfigurable waveguide Bragg grating for programmable photonic signal processing.

PubMed

Zhang, Weifeng; Yao, Jianping

2018-04-11

Since the discovery of the Bragg's law in 1913, Bragg gratings have become important optical devices and have been extensively used in various systems. In particular, the successful inscription of a Bragg grating in a fiber core has significantly boosted its engineering applications. However, a conventional grating device is usually designed for a particular use, which limits general-purpose applications since its index modulation profile is fixed after fabrication. In this article, we propose to implement a fully reconfigurable grating, which is fast and electrically reconfigurable by field programming. The concept is verified by fabricating an integrated grating on a silicon-on-insulator platform, which is employed as a programmable signal processor to perform multiple signal processing functions including temporal differentiation, microwave time delay, and frequency identification. The availability of ultrafast and reconfigurable gratings opens new avenues for programmable optical signal processing at the speed of light.

Digital signal processing by virtual instrumentation of a MEMS magnetic field sensor for biomedical applications.

PubMed

Juárez-Aguirre, Raúl; Domínguez-Nicolás, Saúl M; Manjarrez, Elías; Tapia, Jesús A; Figueras, Eduard; Vázquez-Leal, Héctor; Aguilera-Cortés, Luz A; Herrera-May, Agustín L

2013-11-05

We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing. The virtual instrument includes an algorithm to implement different configurations of infinite impulse response (IIR) filters. The PCB contains a precision instrumentation amplifier, a demodulator, a low-pass filter (LPF) and a buffer with operational amplifier. The proposed prototype is used for real-time non-invasive monitoring of magnetic flux density in the thoracic cage of rats. The response of the rat respiratory magnetogram displays a similar behavior as the rat electromyogram (EMG).

Data processing with microcode designed with source coding

DOEpatents

McCoy, James A; Morrison, Steven E

2013-05-07

Programming for a data processor to execute a data processing application is provided using microcode source code. The microcode source code is assembled to produce microcode that includes digital microcode instructions with which to signal the data processor to execute the data processing application.

Seismic signal processing on heterogeneous supercomputers

NASA Astrophysics Data System (ADS)

Gokhberg, Alexey; Ermert, Laura; Fichtner, Andreas

2015-04-01

The processing of seismic signals - including the correlation of massive ambient noise data sets - represents an important part of a wide range of seismological applications. It is characterized by large data volumes as well as high computational input/output intensity. Development of efficient approaches towards seismic signal processing on emerging high performance computing systems is therefore essential. Heterogeneous supercomputing systems introduced in the recent years provide numerous computing nodes interconnected via high throughput networks, every node containing a mix of processing elements of different architectures, like several sequential processor cores and one or a few graphical processing units (GPU) serving as accelerators. A typical representative of such computing systems is "Piz Daint", a supercomputer of the Cray XC 30 family operated by the Swiss National Supercomputing Center (CSCS), which we used in this research. Heterogeneous supercomputers provide an opportunity for manifold application performance increase and are more energy-efficient, however they have much higher hardware complexity and are therefore much more difficult to program. The programming effort may be substantially reduced by the introduction of modular libraries of software components that can be reused for a wide class of seismology applications. The ultimate goal of this research is design of a prototype for such library suitable for implementing various seismic signal processing applications on heterogeneous systems. As a representative use case we have chosen an ambient noise correlation application. Ambient noise interferometry has developed into one of the most powerful tools to image and monitor the Earth's interior. Future applications will require the extraction of increasingly small details from noise recordings. To meet this demand, more advanced correlation techniques combined with very large data volumes are needed. This poses new computational problems that require dedicated HPC solutions. The chosen application is using a wide range of common signal processing methods, which include various IIR filter designs, amplitude and phase correlation, computing the analytic signal, and discrete Fourier transforms. Furthermore, various processing methods specific for seismology, like rotation of seismic traces, are used. Efficient implementation of all these methods on the GPU-accelerated systems represents several challenges. In particular, it requires a careful distribution of work between the sequential processors and accelerators. Furthermore, since the application is designed to process very large volumes of data, special attention had to be paid to the efficient use of the available memory and networking hardware resources in order to reduce intensity of data input and output. In our contribution we will explain the software architecture as well as principal engineering decisions used to address these challenges. We will also describe the programming model based on C++ and CUDA that we used to develop the software. Finally, we will demonstrate performance improvements achieved by using the heterogeneous computing architecture. This work was supported by a grant from the Swiss National Supercomputing Centre (CSCS) under project ID d26.

Transient high frequency signal estimation: A model-based processing approach

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

Barnes, F.L.

1985-03-22

By utilizing the superposition property of linear systems a method of estimating the incident signal from reflective nondispersive data is developed. One of the basic merits of this approach is that, the reflections were removed by direct application of a Weiner type estimation algorithm, after the appropriate input was synthesized. The structure of the nondispersive signal model is well documented, and thus its' credence is established. The model is stated and more effort is devoted to practical methods of estimating the model parameters. Though a general approach was developed for obtaining the reflection weights, a simpler approach was employed here,more » since a fairly good reflection model is available. The technique essentially consists of calculating ratios of the autocorrelation function at lag zero and that lag where the incident and first reflection coincide. We initially performed our processing procedure on a measurement of a single signal. Multiple application of the processing procedure was required when we applied the reflection removal technique on a measurement containing information from the interaction of two physical phenomena. All processing was performed using SIG, an interactive signal processing package. One of the many consequences of using SIG was that repetitive operations were, for the most part, automated. A custom menu was designed to perform the deconvolution process.« less

Unveiling the Biometric Potential of Finger-Based ECG Signals

PubMed Central

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications. PMID:21837235

Unveiling the biometric potential of finger-based ECG signals.

PubMed

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

Experiments with Sensor Motes and Java-DSP

ERIC Educational Resources Information Center

Kwon, Homin; Berisha, V.; Atti, V.; Spanias, A.

2009-01-01

Distributed wireless sensor networks (WSNs) are being proposed for various applications including defense, security, and smart stages. The introduction of hardware wireless sensors in a signal processing education setting can serve as a paradigm for data acquisition, collaborative signal processing, or simply as a platform for obtaining,…

Towards a Standard Mixed-Signal Parallel Processing Architecture for Miniature and Microrobotics.

PubMed

Sadler, Brian M; Hoyos, Sebastian

2014-01-01

The conventional analog-to-digital conversion (ADC) and digital signal processing (DSP) architecture has led to major advances in miniature and micro-systems technology over the past several decades. The outlook for these systems is significantly enhanced by advances in sensing, signal processing, communications and control, and the combination of these technologies enables autonomous robotics on the miniature to micro scales. In this article we look at trends in the combination of analog and digital (mixed-signal) processing, and consider a generalized sampling architecture. Employing a parallel analog basis expansion of the input signal, this scalable approach is adaptable and reconfigurable, and is suitable for a large variety of current and future applications in networking, perception, cognition, and control.

Towards a Standard Mixed-Signal Parallel Processing Architecture for Miniature and Microrobotics

PubMed Central

Sadler, Brian M; Hoyos, Sebastian

2014-01-01

The conventional analog-to-digital conversion (ADC) and digital signal processing (DSP) architecture has led to major advances in miniature and micro-systems technology over the past several decades. The outlook for these systems is significantly enhanced by advances in sensing, signal processing, communications and control, and the combination of these technologies enables autonomous robotics on the miniature to micro scales. In this article we look at trends in the combination of analog and digital (mixed-signal) processing, and consider a generalized sampling architecture. Employing a parallel analog basis expansion of the input signal, this scalable approach is adaptable and reconfigurable, and is suitable for a large variety of current and future applications in networking, perception, cognition, and control. PMID:26601042

Real-time optical fiber digital speckle pattern interferometry for industrial applications

NASA Astrophysics Data System (ADS)

Chan, Robert K.; Cheung, Y. M.; Lo, C. H.; Tam, T. K.

1997-03-01

There is current interest, especially in the industrial sector, to use the digital speckle pattern interferometry (DSPI) technique to measure surface stress. Indeed, many publications in the subject are evident of the growing interests in the field. However, to bring the technology to industrial use requires the integration of several emerging technologies, viz. optics, feedback control, electronics, imaging processing and digital signal processing. Due to the highly interdisciplinary nature of the technique, successful implementation and development require expertise in all of the fields. At Baptist University, under the funding of a major industrial grant, we are developing the technology for the industrial sector. Our system fully exploits optical fibers and diode lasers in the design to enable practical and rugged systems suited for industrial applications. Besides the development in optics, we have broken away from the reliance of a microcomputer PC platform for both image capture and processing, and have developed a digital signal processing array system that can handle simultaneous and independent image capture/processing with feedback control. The system, named CASPA for 'cascadable architecture signal processing array,' is a third generation development system that utilizes up to 7 digital signal processors has proved to be a very powerful system. With our CASPA we are now in a better position to developing novel optical measurement systems for industrial application that may require different measurement systems to operate concurrently and requiring information exchange between the systems. Applications in mind such as simultaneous in-plane and out-of-plane DSPI image capture/process, vibrational analysis with interactive DSPI and phase shifting control of optical systems are a few good examples of the potentials.

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

Optical modulation techniques for analog signal processing and CMOS compatible electro-optic modulation

NASA Astrophysics Data System (ADS)

Gill, Douglas M.; Rasras, Mahmoud; Tu, Kun-Yii; Chen, Young-Kai; White, Alice E.; Patel, Sanjay S.; Carothers, Daniel; Pomerene, Andrew; Kamocsai, Robert; Beattie, James; Kopa, Anthony; Apsel, Alyssa; Beals, Mark; Mitchel, Jurgen; Liu, Jifeng; Kimerling, Lionel C.

2008-02-01

Integrating electronic and photonic functions onto a single silicon-based chip using techniques compatible with mass-production CMOS electronics will enable new design paradigms for existing system architectures and open new opportunities for electro-optic applications with the potential to dramatically change the management, cost, footprint, weight, and power consumption of today's communication systems. While broadband analog system applications represent a smaller volume market than that for digital data transmission, there are significant deployments of analog electro-optic systems for commercial and military applications. Broadband linear modulation is a critical building block in optical analog signal processing and also could have significant applications in digital communication systems. Recently, broadband electro-optic modulators on a silicon platform have been demonstrated based on the plasma dispersion effect. The use of the plasma dispersion effect within a CMOS compatible waveguide creates new challenges and opportunities for analog signal processing since the index and propagation loss change within the waveguide during modulation. We will review the current status of silicon-based electrooptic modulators and also linearization techniques for optical modulation.

Integrated nonlinear photonics. Emerging applications and ongoing challenges - A mini review

DOE PAGES

Hendrickson, Scott M.; Foster, Amy C.; Camacho, Ryan M.; ...

2014-11-26

In this paper, we provide a review of recent progress in integrated nonlinear photonics with a focus on emerging applications in all-optical signal processing, ultra-low-power all-optical switching, and quantum information processing.

A Resume of Stochastic, Time-Varying, Linear System Theory with Application to Active-Sonar Signal-Processing Problems

DTIC Science & Technology

1981-06-15

relationships 5 3. Normalized energy in ambiguity function for i = 0 14 k ilI SACLANTCEN SR-50 A RESUME OF STOCHASTIC, TIME-VARYING, LINEAR SYSTEM THEORY WITH...the order in which systems are concatenated is unimportant. These results are exactly analogous to the results of time-invariant linear system theory in...REFERENCES 1. MEIER, L. A rdsum6 of deterministic time-varying linear system theory with application to active sonar signal processing problems, SACLANTCEN

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

PubMed

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

2010-01-01

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

Thermal Radiometer Signal Processing Using Radiation Hard CMOS Application Specific Integrated Circuits for Use in Harsh Planetary Environments

NASA Technical Reports Server (NTRS)

Quilligan, G.; DuMonthier, J.; Aslam, S.; Lakew, B.; Kleyner, I.; Katz, R.

2015-01-01

Thermal radiometers such as proposed for the Europa Clipper flyby mission require low noise signal processing for thermal imaging with immunity to Total Ionizing Dose (TID) and Single Event Latchup (SEL). Described is a second generation Multi- Channel Digitizer (MCD2G) Application Specific Integrated Circuit (ASIC) that accurately digitizes up to 40 thermopile pixels with greater than 50 Mrad (Si) immunity TID and 174 MeV-sq cm/mg SEL. The MCD2G ASIC uses Radiation Hardened By Design (RHBD) techniques with a 180 nm CMOS process node.

Thermal Radiometer Signal Processing using Radiation Hard CMOS Application Specific Integrated Circuits for use in Harsh Planetary Environments

NASA Astrophysics Data System (ADS)

Quilligan, G.; DuMonthier, J.; Aslam, S.; Lakew, B.; Kleyner, I.; Katz, R.

2015-10-01

Thermal radiometers such as proposed for the Europa Clipper flyby mission [1] require low noise signal processing for thermal imaging with immunity to Total Ionizing Dose (TID) and Single Event Latchup (SEL). Described is a second generation Multi- Channel Digitizer (MCD2G) Application Specific Integrated Circuit (ASIC) that accurately digitizes up to 40 thermopile pixels with greater than 50 Mrad (Si) immunity TID and 174 MeV-cm2/mg SEL. The MCD2G ASIC uses Radiation Hardened By Design (RHBD) techniques with a 180 nm CMOS process node.

Controlled membrane translocation provides a mechanism for signal transduction and amplification

NASA Astrophysics Data System (ADS)

Langton, Matthew J.; Keymeulen, Flore; Ciaccia, Maria; Williams, Nicholas H.; Hunter, Christopher A.

2017-05-01

Transmission and amplification of chemical signals across lipid bilayer membranes is of profound significance in many biological processes, from the development of multicellular organisms to information processing in the nervous system. In biology, membrane-spanning proteins are responsible for the transmission of chemical signals across membranes, and signal transduction is often associated with an amplified signalling cascade. The ability to reproduce such processes in artificial systems has potential applications in sensing, controlled drug delivery and communication between compartments in tissue-like constructs of synthetic vesicles. Here we describe a mechanism for transmitting a chemical signal across a membrane based on the controlled translocation of a synthetic molecular transducer from one side of a lipid bilayer membrane to the other. The controlled molecular motion has been coupled to the activation of a catalyst on the inside of a vesicle, which leads to a signal-amplification process analogous to the biological counterpart.

The Brassinosteroid Signaling Pathway—New Key Players and Interconnections with Other Signaling Networks Crucial for Plant Development and Stress Tolerance

PubMed Central

Gruszka, Damian

2013-01-01

Brassinosteroids (BRs) are a class of steroid hormones regulating a wide range of physiological processes during the plant life cycle from seed development to the modulation of flowering and senescence. The last decades, and recent years in particular, have witnessed a significant advance in the elucidation of the molecular mechanisms of BR signaling from perception by the transmembrane receptor complex to the regulation of transcription factors influencing expression of the target genes. Application of the new approaches shed light on the molecular functions of the key players regulating the BR signaling cascade and allowed identification of new factors. Recent studies clearly indicated that some of the components of BR signaling pathway act as multifunctional proteins involved in other signaling networks regulating diverse physiological processes, such as photomorphogenesis, cell death control, stomatal development, flowering, plant immunity to pathogens and metabolic responses to stress conditions, including salinity. Regulation of some of these processes is mediated through a crosstalk between BR signalosome and the signaling cascades of other hormones, including auxin, abscisic acid, ethylene and salicylic acid. Unravelling the complicated mechanisms of BR signaling and its interconnections with other molecular networks may be of great importance for future practical applications in agriculture. PMID:23615468

Method and apparatus for obtaining complete speech signals for speech recognition applications

NASA Technical Reports Server (NTRS)

Abrash, Victor (Inventor); Cesari, Federico (Inventor); Franco, Horacio (Inventor); George, Christopher (Inventor); Zheng, Jing (Inventor)

2009-01-01

The present invention relates to a method and apparatus for obtaining complete speech signals for speech recognition applications. In one embodiment, the method continuously records an audio stream comprising a sequence of frames to a circular buffer. When a user command to commence or terminate speech recognition is received, the method obtains a number of frames of the audio stream occurring before or after the user command in order to identify an augmented audio signal for speech recognition processing. In further embodiments, the method analyzes the augmented audio signal in order to locate starting and ending speech endpoints that bound at least a portion of speech to be processed for recognition. At least one of the speech endpoints is located using a Hidden Markov Model.

An integrated nonlinear optical loop mirror in silicon photonics for all-optical signal processing

NASA Astrophysics Data System (ADS)

Wang, Zifei; Glesk, Ivan; Chen, Lawrence R.

2018-02-01

The nonlinear optical loop mirror (NOLM) has been studied for several decades and has attracted considerable attention for applications in high data rate optical communications and all-optical signal processing. The majority of NOLM research has focused on silica fiber-based implementations. While various fiber designs have been considered to increase the nonlinearity and manage dispersion, several meters to hundreds of meters of fiber are still required. On the other hand, there is increasing interest in developing photonic integrated circuits for realizing signal processing functions. In this paper, we realize the first-ever passive integrated NOLM in silicon photonics and demonstrate its application for all-optical signal processing. In particular, we show wavelength conversion of 10 Gb/s return-to-zero on-off keying (RZ-OOK) signals over a wavelength range of 30 nm with error-free operation and a power penalty of less than 2.5 dB, we achieve error-free nonreturn to zero (NRZ)-to-RZ modulation format conversion at 10 Gb/s also with a power penalty of less than 2.8 dB, and we obtain error-free all-optical time-division demultiplexing of a 40 Gb/s RZ-OOK data signal into its 10 Gb/s tributary channels with a maximum power penalty of 3.5 dB.

47 CFR 76.55 - Definitions applicable to the must-carry rules.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Carriage of Television Broadcast Signals § 76.55... responsible for the costs of delivering to the cable system a signal of good quality or a baseband video... terminals of the signal processing equipment, or a baseband video signal. (e) Television market. (1) Until...

47 CFR 76.55 - Definitions applicable to the must-carry rules.

Code of Federal Regulations, 2014 CFR

2014-10-01

... SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Carriage of Television Broadcast Signals § 76.55... responsible for the costs of delivering to the cable system a signal of good quality or a baseband video... terminals of the signal processing equipment, or a baseband video signal. (e) Television market. (1) Until...

47 CFR 76.55 - Definitions applicable to the must-carry rules.

Code of Federal Regulations, 2012 CFR

2012-10-01

... SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Carriage of Television Broadcast Signals § 76.55... responsible for the costs of delivering to the cable system a signal of good quality or a baseband video... terminals of the signal processing equipment, or a baseband video signal. (e) Television market. (1) Until...

47 CFR 76.55 - Definitions applicable to the must-carry rules.

Code of Federal Regulations, 2013 CFR

2013-10-01

... SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Carriage of Television Broadcast Signals § 76.55... responsible for the costs of delivering to the cable system a signal of good quality or a baseband video... terminals of the signal processing equipment, or a baseband video signal. (e) Television market. (1) Until...

Analysis of the times involved in processing and communication in a lower limb simulation system controlled by SEMG

NASA Astrophysics Data System (ADS)

Profumieri, A.; Bonell, C.; Catalfamo, P.; Cherniz, A.

2016-04-01

Virtual reality has been proposed for different applications, including the evaluation of new control strategies and training protocols for upper limb prostheses and for the study of new rehabilitation programs. In this study, a lower limb simulation environment commanded by surface electromyography signals is evaluated. The time delays generated by the acquisition and processing stages for the signals that would command the knee joint, were measured and different acquisition windows were analysed. The subjective perception of the quality of simulation was also evaluated when extra delays were added to the process. The results showed that the acquisition window is responsible for the longest delay. Also, the basic implemented processes allowed for the acquisition of three signal channels for commanding the simulation. Finally, the communication between different applications is arguably efficient, although it depends on the amount of data to be sent.

Graphical Environment Tools for Application to Gamma-Ray Energy Tracking Arrays

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

Todd, Richard A.; Radford, David C.

2013-12-30

Highly segmented, position-sensitive germanium detector systems are being developed for nuclear physics research where traditional electronic signal processing with mixed analog and digital function blocks would be enormously complex and costly. Future systems will be constructed using pipelined processing of high-speed digitized signals as is done in the telecommunications industry. Techniques which provide rapid algorithm and system development for future systems are desirable. This project has used digital signal processing concepts and existing graphical system design tools to develop a set of re-usable modular functions and libraries targeted for the nuclear physics community. Researchers working with complex nuclear detector arraysmore » such as the Gamma-Ray Energy Tracking Array (GRETA) have been able to construct advanced data processing algorithms for implementation in field programmable gate arrays (FPGAs) through application of these library functions using intuitive graphical interfaces.« less

Spectral imaging applications: Remote sensing, environmental monitoring, medicine, military operations, factory automation and manufacturing

NASA Technical Reports Server (NTRS)

Gat, N.; Subramanian, S.; Barhen, J.; Toomarian, N.

1996-01-01

This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.

A model system for targeted drug release triggered by biomolecular signals logically processed through enzyme logic networks.

PubMed

Mailloux, Shay; Halámek, Jan; Katz, Evgeny

2014-03-07

A new Sense-and-Act system was realized by the integration of a biocomputing system, performing analytical processes, with a signal-responsive electrode. A drug-mimicking release process was triggered by biomolecular signals processed by different logic networks, including three concatenated AND logic gates or a 3-input OR logic gate. Biocatalytically produced NADH, controlled by various combinations of input signals, was used to activate the electrochemical system. A biocatalytic electrode associated with signal-processing "biocomputing" systems was electrically connected to another electrode coated with a polymer film, which was dissolved upon the formation of negative potential releasing entrapped drug-mimicking species, an enzyme-antibody conjugate, operating as a model for targeted immune-delivery and consequent "prodrug" activation. The system offers great versatility for future applications in controlled drug release and personalized medicine.

Developing Signal-Pattern-Recognition Programs

NASA Technical Reports Server (NTRS)

Shelton, Robert O.; Hammen, David

2006-01-01

Pattern Interpretation and Recognition Application Toolkit Environment (PIRATE) is a block-oriented software system that aids the development of application programs that analyze signals in real time in order to recognize signal patterns that are indicative of conditions or events of interest. PIRATE was originally intended for use in writing application programs to recognize patterns in space-shuttle telemetry signals received at Johnson Space Center's Mission Control Center: application programs were sought to (1) monitor electric currents on shuttle ac power busses to recognize activations of specific power-consuming devices, (2) monitor various pressures and infer the states of affected systems by applying a Kalman filter to the pressure signals, (3) determine fuel-leak rates from sensor data, (4) detect faults in gyroscopes through analysis of system measurements in the frequency domain, and (5) determine drift rates in inertial measurement units by regressing measurements against time. PIRATE can also be used to develop signal-pattern-recognition software for different purposes -- for example, to monitor and control manufacturing processes.

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.

Application of laser anemometry in turbine engine research

NASA Technical Reports Server (NTRS)

Seasholtz, R. G.

1983-01-01

The application of laser anemometry to the study of flow fields in turbine engine components is reviewed. Included are discussions of optical configurations, seeding requirements, electronic signal processing, and data processing. Some typical results are presented along with a discussion of ongoing work.

Application of laser anemometry in turbine engine research

NASA Technical Reports Server (NTRS)

Seasholtz, R. G.

1982-01-01

The application of laser anemometry to the study of flow fields in turbine engine components is reviewed. Included are discussions of optical configurations, seeding requirements, electronic signal processing, and data processing. Some typical results are presented along with a discussion of ongoing work.

A fast discrete S-transform for biomedical signal processing.

PubMed

Brown, Robert A; Frayne, Richard

2008-01-01

Determining the frequency content of a signal is a basic operation in signal and image processing. The S-transform provides both the true frequency and globally referenced phase measurements characteristic of the Fourier transform and also generates local spectra, as does the wavelet transform. Due to this combination, the S-transform has been successfully demonstrated in a variety of biomedical signal and image processing tasks. However, the computational demands of the S-transform have limited its application in medicine to this point in time. This abstract introduces the fast S-transform, a more efficient discrete implementation of the classic S-transform with dramatically reduced computational requirements.

Cramer-Rao Bound for Gaussian Random Processes and Applications to Radar Processing of Atmospheric Signals

NASA Technical Reports Server (NTRS)

Frehlich, Rod

1993-01-01

Calculations of the exact Cramer-Rao Bound (CRB) for unbiased estimates of the mean frequency, signal power, and spectral width of Doppler radar/lidar signals (a Gaussian random process) are presented. Approximate CRB's are derived using the Discrete Fourier Transform (DFT). These approximate results are equal to the exact CRB when the DFT coefficients are mutually uncorrelated. Previous high SNR limits for CRB's are shown to be inaccurate because the discrete summations cannot be approximated with integration. The performance of an approximate maximum likelihood estimator for mean frequency approaches the exact CRB for moderate signal to noise ratio and moderate spectral width.

High-performance wavelet engine

NASA Astrophysics Data System (ADS)

Taylor, Fred J.; Mellot, Jonathon D.; Strom, Erik; Koren, Iztok; Lewis, Michael P.

1993-11-01

Wavelet processing has shown great promise for a variety of image and signal processing applications. Wavelets are also among the most computationally expensive techniques in signal processing. It is demonstrated that a wavelet engine constructed with residue number system arithmetic elements offers significant advantages over commercially available wavelet accelerators based upon conventional arithmetic elements. Analysis is presented predicting the dynamic range requirements of the reported residue number system based wavelet accelerator.

Genomic signal processing methods for computation of alignment-free distances from DNA sequences.

PubMed

Borrayo, Ernesto; Mendizabal-Ruiz, E Gerardo; Vélez-Pérez, Hugo; Romo-Vázquez, Rebeca; Mendizabal, Adriana P; Morales, J Alejandro

2014-01-01

Genomic signal processing (GSP) refers to the use of digital signal processing (DSP) tools for analyzing genomic data such as DNA sequences. A possible application of GSP that has not been fully explored is the computation of the distance between a pair of sequences. In this work we present GAFD, a novel GSP alignment-free distance computation method. We introduce a DNA sequence-to-signal mapping function based on the employment of doublet values, which increases the number of possible amplitude values for the generated signal. Additionally, we explore the use of three DSP distance metrics as descriptors for categorizing DNA signal fragments. Our results indicate the feasibility of employing GAFD for computing sequence distances and the use of descriptors for characterizing DNA fragments.

Genomic Signal Processing Methods for Computation of Alignment-Free Distances from DNA Sequences

PubMed Central

Borrayo, Ernesto; Mendizabal-Ruiz, E. Gerardo; Vélez-Pérez, Hugo; Romo-Vázquez, Rebeca; Mendizabal, Adriana P.; Morales, J. Alejandro

2014-01-01

Genomic signal processing (GSP) refers to the use of digital signal processing (DSP) tools for analyzing genomic data such as DNA sequences. A possible application of GSP that has not been fully explored is the computation of the distance between a pair of sequences. In this work we present GAFD, a novel GSP alignment-free distance computation method. We introduce a DNA sequence-to-signal mapping function based on the employment of doublet values, which increases the number of possible amplitude values for the generated signal. Additionally, we explore the use of three DSP distance metrics as descriptors for categorizing DNA signal fragments. Our results indicate the feasibility of employing GAFD for computing sequence distances and the use of descriptors for characterizing DNA fragments. PMID:25393409

Two-dimensional signal processing with application to image restoration

NASA Technical Reports Server (NTRS)

Assefi, T.

1974-01-01

A recursive technique for modeling and estimating a two-dimensional signal contaminated by noise is presented. A two-dimensional signal is assumed to be an undistorted picture, where the noise introduces the distortion. Both the signal and the noise are assumed to be wide-sense stationary processes with known statistics. Thus, to estimate the two-dimensional signal is to enhance the picture. The picture representing the two-dimensional signal is converted to one dimension by scanning the image horizontally one line at a time. The scanner output becomes a nonstationary random process due to the periodic nature of the scanner operation. Procedures to obtain a dynamical model corresponding to the autocorrelation function of the scanner output are derived. Utilizing the model, a discrete Kalman estimator is designed to enhance the image.

Adaptive Signal Processing Testbed: VME-based DSP board market survey

NASA Astrophysics Data System (ADS)

Ingram, Rick E.

1992-04-01

The Adaptive Signal Processing Testbed (ASPT) is a real-time multiprocessor system utilizing digital signal processor technology on VMEbus based printed circuit boards installed on a Sun workstation. The ASPT has specific requirements, particularly as regards to the signal excision application, with respect to interfacing with current and planned data generation equipment, processing of the data, storage to disk of final and intermediate results, and the development tools for applications development and integration into the overall EW/COM computing environment. A prototype ASPT was implemented using three VME-C-30 boards from Applied Silicon. Experience gained during the prototype development led to the conclusions that interprocessor communications capability is the most significant contributor to overall ASPT performance. In addition, the host involvement should be minimized. Boards using different processors were evaluated with respect to the ASPT system requirements, pricing, and availability. Specific recommendations based on various priorities are made as well as recommendations concerning the integration and interaction of various tools developed during the prototype implementation.

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

PubMed

Karagiannis, Alexandros; Constantinou, Philip

2011-01-01

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

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.

Computational Analysis and Simulation of Empathic Behaviors: a Survey of Empathy Modeling with Behavioral Signal Processing Framework.

PubMed

Xiao, Bo; Imel, Zac E; Georgiou, Panayiotis; Atkins, David C; Narayanan, Shrikanth S

2016-05-01

Empathy is an important psychological process that facilitates human communication and interaction. Enhancement of empathy has profound significance in a range of applications. In this paper, we review emerging directions of research on computational analysis of empathy expression and perception as well as empathic interactions, including their simulation. We summarize the work on empathic expression analysis by the targeted signal modalities (e.g., text, audio, and facial expressions). We categorize empathy simulation studies into theory-based emotion space modeling or application-driven user and context modeling. We summarize challenges in computational study of empathy including conceptual framing and understanding of empathy, data availability, appropriate use and validation of machine learning techniques, and behavior signal processing. Finally, we propose a unified view of empathy computation and offer a series of open problems for future research.

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.

Laser doppler blood flow imaging using a CMOS imaging sensor with on-chip signal processing.

PubMed

He, Diwei; Nguyen, Hoang C; Hayes-Gill, Barrie R; Zhu, Yiqun; Crowe, John A; Gill, Cally; Clough, Geraldine F; Morgan, Stephen P

2013-09-18

The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue.

The mathematical theory of signal processing and compression-designs

NASA Astrophysics Data System (ADS)

Feria, Erlan H.

2006-05-01

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

A low-cost 3-D printed stethoscope connected to a smartphone.

PubMed

Aguilera-Astudillo, Carlos; Chavez-Campos, Marx; Gonzalez-Suarez, Alan; Garcia-Cordero, Jose L

2016-08-01

We demonstrate the fabrication of a digital stethoscope using a 3D printer and commercial off-the-shelf electronics. A chestpiece consists of an electret microphone embedded into the drum of a 3D printed chestpiece. An electronic dongle amplifies the signal from the microphone and reduces any external noise. It also adjusts the signal to the voltages accepted by the smartphones headset jack. A graphical user interface programmed in Android displays the signals processed by the dongle. The application also saves the processed signal and sends it to a physician.

Employers' social contacts and their hiring behavior in a factorial survey.

PubMed

Di Stasio, Valentina; Gërxhani, Klarita

2015-05-01

We investigate whether referrals from employers' business and professional contacts matter in the hiring process. Additionally, we examine whether the effect of referrals varies depending on: (1) the signaling role of education during the hiring process, and (2) applicants' level of education. Based on a combination of a factorial survey and an experimental design with a sample of English employers, we measure the effect of referrals on employers' hiring assessments. We find only weak evidence that referred applicants are considered more trainable than otherwise identical applicants that do not have a tie with the employer. More detailed analyses show that referrals do matter for employers who consider education a noisy signal, in line with the argument that informal recruitment can represent a strategy for employers to compensate for poor signaling. Referrals are especially beneficial for highly educated applicants, probably because employers need some guarantee against possible wage or turnover costs. Copyright © 2015 Elsevier Inc. All rights reserved.

47 CFR 73.3700 - Channel sharing.

Code of Federal Regulations, 2014 CFR

2014-10-01

...) of this section will be afforded expedited processing if the application: (A) Does not seek to expand... and expanded facilities applications and specifying appropriate processing guidelines, including the... Channel Reassignment Public Notice; and (ii) MVPDs in order to continue to carry the signal of a full...

System and methods for determining masking signals for applying empirical mode decomposition (EMD) and for demodulating intrinsic mode functions obtained from application of EMD

DOEpatents

Senroy, Nilanjan [New Delhi, IN; Suryanarayanan, Siddharth [Littleton, CO

2011-03-15

A computer-implemented method of signal processing is provided. The method includes generating one or more masking signals based upon a computed Fourier transform of a received signal. The method further includes determining one or more intrinsic mode functions (IMFs) of the received signal by performing a masking-signal-based empirical mode decomposition (EMD) using the at least one masking signal.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Optical signal-processing systems based on anisotropic media

NASA Astrophysics Data System (ADS)

Kiyashko, B. V.

1995-10-01

Partially coherent optical systems for signal processing are considered. The transfer functions are formed in these systems by interference of polarised light transmitted by an anisotropic medium. It is shown that such systems can perform various integral transformations of both optical and electric signals, in particular, two-dimensional Fourier and Fresnel transformations, as well as spectral analysis of weak light sources. It is demonstrated that such systems have the highest luminosity and vibration immunity among the systems with interference formation of transfer functions. An experimental investigation is reported of the application of these systems in the processing of signals from a linear hydroacoustic antenna array, and in measurements of the optical spectrum and of the intrinsic noise.

Interferometric architectures based All-Optical logic design methods and their implementations

NASA Astrophysics Data System (ADS)

Singh, Karamdeep; Kaur, Gurmeet

2015-06-01

All-Optical Signal Processing is an emerging technology which can avoid costly Optical-electronic-optical (O-E-O) conversions which are usually compulsory in traditional Electronic Signal Processing systems, thus greatly enhancing operating bit rate with some added advantages such as electro-magnetic interference immunity and low power consumption etc. In order to implement complex signal processing tasks All-Optical logic gates are required as backbone elements. This review describes the advances in the field of All-Optical logic design methods based on interferometric architectures such as Mach-Zehnder Interferometer (MZI), Sagnac Interferometers and Ultrafast Non-Linear Interferometer (UNI). All-Optical logic implementations for realization of arithmetic and signal processing applications based on each interferometric arrangement are also presented in a categorized manner.

Optical rangefinding applications using communications modulation technique

NASA Astrophysics Data System (ADS)

Caplan, William D.; Morcom, Christopher John

2010-10-01

A novel range detection technique combines optical pulse modulation patterns with signal cross-correlation to produce an accurate range estimate from low power signals. The cross-correlation peak is analyzed by a post-processing algorithm such that the phase delay is proportional to the range to target. This technique produces a stable range estimate from noisy signals. The advantage is higher accuracy obtained with relatively low optical power transmitted. The technique is useful for low cost, low power and low mass sensors suitable for tactical use. The signal coding technique allows applications including IFF and battlefield identification systems.

SAW chirp filter technology for satellite on-board processing applications

NASA Astrophysics Data System (ADS)

Shaw, M. D.; Miller, N. D. J.; Malarky, A. P.; Warne, D. H.

1989-11-01

Market growth in the area of thin route satellite communications services has led to consideration of nontraditional system architectures requiring sophisticated on-board processing functions. Surface acoustic wave (SAW) technology exists today which can provide implementation of key on-board processing subsystems by using multicarrier demodulators. This paper presents a review of this signal processing technology, along with a brief review of dispersive SAW device technology as applied to the implementation of multicarrier demodulators for on-board signal processing.

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

NASA Astrophysics Data System (ADS)

Bayram, Eda; Vural, Elif; Alatan, Aydin

2017-10-01

Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.

BioSig: The Free and Open Source Software Library for Biomedical Signal Processing

PubMed Central

Vidaurre, Carmen; Sander, Tilmann H.; Schlögl, Alois

2011-01-01

BioSig is an open source software library for biomedical signal processing. The aim of the BioSig project is to foster research in biomedical signal processing by providing free and open source software tools for many different application areas. Some of the areas where BioSig can be employed are neuroinformatics, brain-computer interfaces, neurophysiology, psychology, cardiovascular systems, and sleep research. Moreover, the analysis of biosignals such as the electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), or respiration signals is a very relevant element of the BioSig project. Specifically, BioSig provides solutions for data acquisition, artifact processing, quality control, feature extraction, classification, modeling, and data visualization, to name a few. In this paper, we highlight several methods to help students and researchers to work more efficiently with biomedical signals. PMID:21437227

BioSig: the free and open source software library for biomedical signal processing.

PubMed

Vidaurre, Carmen; Sander, Tilmann H; Schlögl, Alois

2011-01-01

BioSig is an open source software library for biomedical signal processing. The aim of the BioSig project is to foster research in biomedical signal processing by providing free and open source software tools for many different application areas. Some of the areas where BioSig can be employed are neuroinformatics, brain-computer interfaces, neurophysiology, psychology, cardiovascular systems, and sleep research. Moreover, the analysis of biosignals such as the electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), or respiration signals is a very relevant element of the BioSig project. Specifically, BioSig provides solutions for data acquisition, artifact processing, quality control, feature extraction, classification, modeling, and data visualization, to name a few. In this paper, we highlight several methods to help students and researchers to work more efficiently with biomedical signals.

Bioinspired Polarization Imaging Sensors: From Circuits and Optics to Signal Processing Algorithms and Biomedical Applications

PubMed Central

York, Timothy; Powell, Samuel B.; Gao, Shengkui; Kahan, Lindsey; Charanya, Tauseef; Saha, Debajit; Roberts, Nicholas W.; Cronin, Thomas W.; Marshall, Justin; Achilefu, Samuel; Lake, Spencer P.; Raman, Baranidharan; Gruev, Viktor

2015-01-01

In this paper, we present recent work on bioinspired polarization imaging sensors and their applications in biomedicine. In particular, we focus on three different aspects of these sensors. First, we describe the electro–optical challenges in realizing a bioinspired polarization imager, and in particular, we provide a detailed description of a recent low-power complementary metal–oxide–semiconductor (CMOS) polarization imager. Second, we focus on signal processing algorithms tailored for this new class of bioinspired polarization imaging sensors, such as calibration and interpolation. Third, the emergence of these sensors has enabled rapid progress in characterizing polarization signals and environmental parameters in nature, as well as several biomedical areas, such as label-free optical neural recording, dynamic tissue strength analysis, and early diagnosis of flat cancerous lesions in a murine colorectal tumor model. We highlight results obtained from these three areas and discuss future applications for these sensors. PMID:26538682

Quantitative evaluation of photoplethysmographic artifact reduction for pulse oximetry

NASA Astrophysics Data System (ADS)

Hayes, Matthew J.; Smith, Peter R.

1999-01-01

Motion artefact corruption of pulse oximeter output, causing both measurement inaccuracies and false alarm conditions, is a primary restriction in the current clinical practice and future applications of this useful technique. Artefact reduction in photoplethysmography (PPG), and therefore by application in pulse oximetry, is demonstrated using a novel non-linear methodology recently proposed by the authors. The significance of these processed PPG signals for pulse oximetry measurement is discussed, with particular attention to the normalization inherent in the artefact reduction process. Quantitative experimental investigation of the performance of PPG artefact reduction is then utilized to evaluate this technology for application to pulse oximetry. While the successfully demonstrated reduction of severe artefacts may widen the applicability of all PPG technologies and decrease the occurrence of pulse oximeter false alarms, the observed reduction of slight artefacts suggests that many such effects may go unnoticed in clinical practice. The signal processing and output averaging used in most commercial oximeters can incorporate these artefact errors into the output, while masking the true PPG signal corruption. It is therefore suggested that PPG artefact reduction should be incorporated into conventional pulse oximetry measurement, even in the absence of end-user artefact problems.

Scalable Multiprocessor for High-Speed Computing in Space

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

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

Application of simulation models for the optimization of business processes

NASA Astrophysics Data System (ADS)

Jašek, Roman; Sedláček, Michal; Chramcov, Bronislav; Dvořák, Jiří

2016-06-01

The paper deals with the applications of modeling and simulation tools in the optimization of business processes, especially in solving an optimization of signal flow in security company. As a modeling tool was selected Simul8 software that is used to process modeling based on discrete event simulation and which enables the creation of a visual model of production and distribution processes.

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.

The application of digital signal processing techniques to a teleoperator radar system

NASA Technical Reports Server (NTRS)

Pujol, A.

1982-01-01

A digital signal processing system was studied for the determination of the spectral frequency distribution of echo signals from a teleoperator radar system. The system consisted of a sample and hold circuit, an analog to digital converter, a digital filter, and a Fast Fourier Transform. The system is interfaced to a 16 bit microprocessor. The microprocessor is programmed to control the complete digital signal processing. The digital filtering and Fast Fourier Transform functions are implemented by a S2815 digital filter/utility peripheral chip and a S2814A Fast Fourier Transform chip. The S2815 initially simulates a low-pass Butterworth filter with later expansion to complete filter circuit (bandpass and highpass) synthesizing.

Conference on Charge-Coupled Device Technology and Applications

NASA Technical Reports Server (NTRS)

1976-01-01

Papers were presented from the conference on charge coupled device technology and applications. The following topics were investigated: data processing; infrared; devices and testing; electron-in, x-ray, radiation; and applications. The emphasis was on the advances of mutual relevance and potential significance both to industry and NASA's current and future requirements in all fields of imaging, signal processing and memory.

Computational Analysis and Simulation of Empathic Behaviors: A Survey of Empathy Modeling with Behavioral Signal Processing Framework

PubMed Central

Xiao, Bo; Imel, Zac E.; Georgiou, Panayiotis; Atkins, David C.; Narayanan, Shrikanth S.

2017-01-01

Empathy is an important psychological process that facilitates human communication and interaction. Enhancement of empathy has profound significance in a range of applications. In this paper, we review emerging directions of research on computational analysis of empathy expression and perception as well as empathic interactions, including their simulation. We summarize the work on empathic expression analysis by the targeted signal modalities (e.g., text, audio, facial expressions). We categorize empathy simulation studies into theory-based emotion space modeling or application-driven user and context modeling. We summarize challenges in computational study of empathy including conceptual framing and understanding of empathy, data availability, appropriate use and validation of machine learning techniques, and behavior signal processing. Finally, we propose a unified view of empathy computation, and offer a series of open problems for future research. PMID:27017830

Genetic Algorithms Evolve Optimized Transforms for Signal Processing Applications

DTIC Science & Technology

2005-04-01

coefficient sets describing inverse transforms and matched forward/ inverse transform pairs that consistently outperform wavelets for image compression and reconstruction applications under conditions subject to quantization error.

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

PubMed

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Test and Evaluation of Neural Network Applications for Seismic Signal Discrimination

DTIC Science & Technology

1992-09-28

IMS) for automated processing and interpretation of regional seismic data. Also reported is the result of a preliminary study on the application of...of analyst-verified events that were missed by the automated processing decreased by more than a factor of 2 (about 10 events/week). The second

Accuracy-energy configurable sensor processor and IoT device for long-term activity monitoring in rare-event sensing applications.

PubMed

Park, Daejin; Cho, Jeonghun

2014-01-01

A specially designed sensor processor used as a main processor in IoT (internet-of-thing) device for the rare-event sensing applications is proposed. The IoT device including the proposed sensor processor performs the event-driven sensor data processing based on an accuracy-energy configurable event-quantization in architectural level. The received sensor signal is converted into a sequence of atomic events, which is extracted by the signal-to-atomic-event generator (AEG). Using an event signal processing unit (EPU) as an accelerator, the extracted atomic events are analyzed to build the final event. Instead of the sampled raw data transmission via internet, the proposed method delays the communication with a host system until a semantic pattern of the signal is identified as a final event. The proposed processor is implemented on a single chip, which is tightly coupled in bus connection level with a microcontroller using a 0.18 μm CMOS embedded-flash process. For experimental results, we evaluated the proposed sensor processor by using an IR- (infrared radio-) based signal reflection and sensor signal acquisition system. We successfully demonstrated that the expected power consumption is in the range of 20% to 50% compared to the result of the basement in case of allowing 10% accuracy error.

Signal Detection with Criterion Noise: Applications to Recognition Memory

ERIC Educational Resources Information Center

Benjamin, Aaron S.; Diaz, Michael; Wee, Serena

2009-01-01

A tacit but fundamental assumption of the theory of signal detection is that criterion placement is a noise-free process. This article challenges that assumption on theoretical and empirical grounds and presents the noisy decision theory of signal detection (ND-TSD). Generalized equations for the isosensitivity function and for measures of…

Signal Processing Methods Monitor Cranial Pressure

NASA Technical Reports Server (NTRS)

2010-01-01

Dr. Norden Huang, of Goddard Space Flight Center, invented a set of algorithms (called the Hilbert-Huang Transform, or HHT) for analyzing nonlinear and nonstationary signals that developed into a user-friendly signal processing technology for analyzing time-varying processes. At an auction managed by Ocean Tomo Federal Services LLC, licenses of 10 U.S. patents and 1 domestic patent application related to HHT were sold to DynaDx Corporation, of Mountain View, California. DynaDx is now using the licensed NASA technology for medical diagnosis and prediction of brain blood flow-related problems, such as stroke, dementia, and traumatic brain injury.

Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar. Thesis Technical Report No. 20

NASA Technical Reports Server (NTRS)

Lai, Jonathan Y.

1994-01-01

This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

Influence of Spectral Transfer Processes in Compressible Low Frequency Plasma Turbulence on Scattering and Refraction of Electromagnetic Signals

DTIC Science & Technology

2015-01-01

AFRL-RY-WP-TR-2014-0230 INFLUENCE OF SPECTRAL TRANSFER PROCESSES IN COMPRESSIBLE LOW FREQUENCY PLASMA TURBULENCE ON SCATTERING AND...INFLUENCE OF SPECTRAL TRANSFER PROCESSES IN COMPRESSIBLE LOW FREQUENCY PLASMA TURBULENCE ON SCATTERING AND REFRACTION OF ELECTROMAGNETIC SIGNALS 5a...research is to analyze influence of plasma turbulence on hypersonic sensor systems and NGOTHR applications and to meet the Air Force’s ever-increasing

Frequency-wavenumber processing for infrasound distributed arrays.

PubMed

Costley, R Daniel; Frazier, W Garth; Dillion, Kevin; Picucci, Jennifer R; Williams, Jay E; McKenna, Mihan H

2013-10-01

The work described herein discusses the application of a frequency-wavenumber signal processing technique to signals from rectangular infrasound arrays for detection and estimation of the direction of travel of infrasound. Arrays of 100 sensors were arranged in square configurations with sensor spacing of 2 m. Wind noise data were collected at one site. Synthetic infrasound signals were superposed on top of the wind noise to determine the accuracy and sensitivity of the technique with respect to signal-to-noise ratio. The technique was then applied to an impulsive event recorded at a different site. Preliminary results demonstrated the feasibility of this approach.

Admissible Diffusion Wavelets and Their Applications in Space-Frequency Processing.

PubMed

Hou, Tingbo; Qin, Hong

2013-01-01

As signal processing tools, diffusion wavelets and biorthogonal diffusion wavelets have been propelled by recent research in mathematics. They employ diffusion as a smoothing and scaling process to empower multiscale analysis. However, their applications in graphics and visualization are overshadowed by nonadmissible wavelets and their expensive computation. In this paper, our motivation is to broaden the application scope to space-frequency processing of shape geometry and scalar fields. We propose the admissible diffusion wavelets (ADW) on meshed surfaces and point clouds. The ADW are constructed in a bottom-up manner that starts from a local operator in a high frequency, and dilates by its dyadic powers to low frequencies. By relieving the orthogonality and enforcing normalization, the wavelets are locally supported and admissible, hence facilitating data analysis and geometry processing. We define the novel rapid reconstruction, which recovers the signal from multiple bands of high frequencies and a low-frequency base in full resolution. It enables operations localized in both space and frequency by manipulating wavelet coefficients through space-frequency filters. This paper aims to build a common theoretic foundation for a host of applications, including saliency visualization, multiscale feature extraction, spectral geometry processing, etc.

Introduction to acoustic emission

NASA Technical Reports Server (NTRS)

Possa, G.

1983-01-01

Typical acoustic emission signal characteristics are described and techniques which localize the signal source by processing the acoustic delay data from multiple sensors are discussed. The instrumentation, which includes sensors, amplifiers, pulse counters, a minicomputer and output devices is examined. Applications are reviewed.

Signal processing system for electrotherapy applications

NASA Astrophysics Data System (ADS)

Płaza, Mirosław; Szcześniak, Zbigniew

2017-08-01

The system of signal processing for electrotherapeutic applications is proposed in the paper. The system makes it possible to model the curve of threshold human sensitivity to current (Dalziel's curve) in full medium frequency range (1kHz-100kHz). The tests based on the proposed solution were conducted and their results were compared with those obtained according to the assumptions of High Tone Power Therapy method and referred to optimum values. Proposed system has high dynamics and precision of mapping the curve of threshold human sensitivity to current and can be used in all methods where threshold curves are modelled.

Rare-earth-doped materials with application to optical signal processing, quantum information science, and medical imaging technology

NASA Astrophysics Data System (ADS)

Cone, R. L.; Thiel, C. W.; Sun, Y.; Böttger, Thomas; Macfarlane, R. M.

2012-02-01

Unique spectroscopic properties of isolated rare earth ions in solids offer optical linewidths rivaling those of trapped single atoms and enable a variety of recent applications. We design rare-earth-doped crystals, ceramics, and fibers with persistent or transient "spectral hole" recording properties for applications including high-bandwidth optical signal processing where light and our solids replace the high-bandwidth portion of the electronics; quantum cryptography and information science including the goal of storage and recall of single photons; and medical imaging technology for the 700-900 nm therapeutic window. Ease of optically manipulating rare-earth ions in solids enables capturing complex spectral information in 105 to 108 frequency bins. Combining spatial holography and spectral hole burning provides a capability for processing high-bandwidth RF and optical signals with sub-MHz spectral resolution and bandwidths of tens to hundreds of GHz for applications including range-Doppler radar and high bandwidth RF spectral analysis. Simply stated, one can think of these crystals as holographic recording media capable of distinguishing up to 108 different colors. Ultra-narrow spectral holes also serve as a vibration-insensitive sub-kHz frequency reference for laser frequency stabilization to a part in 1013 over tens of milliseconds. The unusual properties and applications of spectral hole burning of rare earth ions in optical materials are reviewed. Experimental results on the promising Tm3+:LiNbO3 material system are presented and discussed for medical imaging applications. Finally, a new application of these materials as dynamic optical filters for laser noise suppression is discussed along with experimental demonstrations and theoretical modeling of the process.

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

Hendrickson, Scott M.; Foster, Amy C.; Camacho, Ryan M.

In this paper, we provide a review of recent progress in integrated nonlinear photonics with a focus on emerging applications in all-optical signal processing, ultra-low-power all-optical switching, and quantum information processing.

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

A review of signals used in sleep analysis

PubMed Central

Roebuck, A; Monasterio, V; Gederi, E; Osipov, M; Behar, J; Malhotra, A; Penzel, T; Clifford, GD

2014-01-01

This article presents a review of signals used for measuring physiology and activity during sleep and techniques for extracting information from these signals. We examine both clinical needs and biomedical signal processing approaches across a range of sensor types. Issues with recording and analysing the signals are discussed, together with their applicability to various clinical disorders. Both univariate and data fusion (exploiting the diverse characteristics of the primary recorded signals) approaches are discussed, together with a comparison of automated methods for analysing sleep. PMID:24346125

Fault-Tolerant Signal Processing Architectures with Distributed Error Control.

DTIC Science & Technology

1985-01-01

Zm, Revisited," Information and Control, Vol. 37, pp. 100-104, 1978. 13. J. Wakerly , Error Detecting Codes. SeIf-Checkino Circuits and Applications ...However, the newer results concerning applications of real codes are still in the publication process. Hence, two very detailed appendices are included to...significant entities to be protected. While the distributed finite field approach afforded adequate protection, its applicability was restricted and

Signal quality and Bayesian signal processing in neurofeedback based on real-time fMRI.

PubMed

Koush, Yury; Zvyagintsev, Mikhail; Dyck, Miriam; Mathiak, Krystyna A; Mathiak, Klaus

2012-01-02

Real-time fMRI allows analysis and visualization of the brain activity online, i.e. within one repetition time. It can be used in neurofeedback applications where subjects attempt to control an activation level in a specified region of interest (ROI) of their brain. The signal derived from the ROI is contaminated with noise and artifacts, namely with physiological noise from breathing and heart beat, scanner drift, motion-related artifacts and measurement noise. We developed a Bayesian approach to reduce noise and to remove artifacts in real-time using a modified Kalman filter. The system performs several signal processing operations: subtraction of constant and low-frequency signal components, spike removal and signal smoothing. Quantitative feedback signal quality analysis was used to estimate the quality of the neurofeedback time series and performance of the applied signal processing on different ROIs. The signal-to-noise ratio (SNR) across the entire time series and the group event-related SNR (eSNR) were significantly higher for the processed time series in comparison to the raw data. Applied signal processing improved the t-statistic increasing the significance of blood oxygen level-dependent (BOLD) signal changes. Accordingly, the contrast-to-noise ratio (CNR) of the feedback time series was improved as well. In addition, the data revealed increase of localized self-control across feedback sessions. The new signal processing approach provided reliable neurofeedback, performed precise artifacts removal, reduced noise, and required minimal manual adjustments of parameters. Advanced and fast online signal processing algorithms considerably increased the quality as well as the information content of the control signal which in turn resulted in higher contingency in the neurofeedback loop. Copyright © 2011 Elsevier Inc. All rights reserved.

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation.

PubMed

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C; Wong, Willy; Daskalakis, Zafiris J; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline for TMS-EEG signal processing, this toolbox intends to promote the widespread utility and standardization of an emerging technology in brain research.

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation

PubMed Central

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C.; Wong, Willy; Daskalakis, Zafiris J.; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline for TMS-EEG signal processing, this toolbox intends to promote the widespread utility and standardization of an emerging technology in brain research. PMID:27774054

Amplitude-aware permutation entropy: Illustration in spike detection and signal segmentation.

PubMed

Azami, Hamed; Escudero, Javier

2016-05-01

Signal segmentation and spike detection are two important biomedical signal processing applications. Often, non-stationary signals must be segmented into piece-wise stationary epochs or spikes need to be found among a background of noise before being further analyzed. Permutation entropy (PE) has been proposed to evaluate the irregularity of a time series. PE is conceptually simple, structurally robust to artifacts, and computationally fast. It has been extensively used in many applications, but it has two key shortcomings. First, when a signal is symbolized using the Bandt-Pompe procedure, only the order of the amplitude values is considered and information regarding the amplitudes is discarded. Second, in the PE, the effect of equal amplitude values in each embedded vector is not addressed. To address these issues, we propose a new entropy measure based on PE: the amplitude-aware permutation entropy (AAPE). AAPE is sensitive to the changes in the amplitude, in addition to the frequency, of the signals thanks to it being more flexible than the classical PE in the quantification of the signal motifs. To demonstrate how the AAPE method can enhance the quality of the signal segmentation and spike detection, a set of synthetic and realistic synthetic neuronal signals, electroencephalograms and neuronal data are processed. We compare the performance of AAPE in these problems against state-of-the-art approaches and evaluate the significance of the differences with a repeated ANOVA with post hoc Tukey's test. In signal segmentation, the accuracy of AAPE-based method is higher than conventional segmentation methods. AAPE also leads to more robust results in the presence of noise. The spike detection results show that AAPE can detect spikes well, even when presented with single-sample spikes, unlike PE. For multi-sample spikes, the changes in AAPE are larger than in PE. We introduce a new entropy metric, AAPE, that enables us to consider amplitude information in the formulation of PE. The AAPE algorithm can be used in almost every irregularity-based application in various signal and image processing fields. We also made freely available the Matlab code of the AAPE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

IQM: An Extensible and Portable Open Source Application for Image and Signal Analysis in Java

PubMed Central

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM’s image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis. PMID:25612319

IQM: an extensible and portable open source application for image and signal analysis in Java.

PubMed

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM's image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis.

Analysis of swept-sine runs during modal identification

NASA Astrophysics Data System (ADS)

Gloth, G.; Sinapius, M.

2004-11-01

Experimental modal analysis of large aerospace structures in Europe combine nowadays the benefits of the very reliable but time-consuming phase resonance method and the application of phase separation techniques evaluating frequency response functions (FRF). FRFs of a test structure can be determined by a variety of means. Applied excitation signal waveforms include harmonic signals like stepped-sine excitation, periodic signals like multi-sine excitation, transient signals like impulse and swept-sine excitation, and stochastic signals like random. The current article focuses on slow swept-sine excitation which is a good trade-off between magnitude of excitation level needed for large aircraft and testing time. However, recent ground vibration tests (GVTs) brought up that reliable modal data from swept-sine test runs depend on a proper data processing. The article elucidates the strategy of modal analysis based on swept-sine excitation. The standards for the application of slowly swept sinusoids defined by the international organisation for standardisation in ISO 7626 part 2 are critically reviewed. The theoretical background of swept-sine testing is expounded with particular emphasis to the transition through structural resonances. The effect of different standard procedures of data processing like tracking filter, fast Fourier transform (FFT), and data reduction via averaging are investigated with respect to their influence on the FRFs and modal parameters. Particular emphasis is given to FRF distortions evoked by unsuitable data processing. All data processing methods are investigated on a numerical example. Their practical usefulness is demonstrated on test data taken from a recent GVT on a large aircraft. The revision of ISO 7626 part 2 is suggested regarding the application of slow swept-sine excitation. Recommendations about the proper FRF estimation from slow swept-sine excitation are given in order to enable the optimisation on these applications for future modal survey tests of large aerospace structures.

SignalPlant: an open signal processing software platform.

PubMed

Plesinger, F; Jurco, J; Halamek, J; Jurak, P

2016-07-01

The growing technical standard of acquisition systems allows the acquisition of large records, often reaching gigabytes or more in size as is the case with whole-day electroencephalograph (EEG) recordings, for example. Although current 64-bit software for signal processing is able to process (e.g. filter, analyze, etc) such data, visual inspection and labeling will probably suffer from rather long latency during the rendering of large portions of recorded signals. For this reason, we have developed SignalPlant-a stand-alone application for signal inspection, labeling and processing. The main motivation was to supply investigators with a tool allowing fast and interactive work with large multichannel records produced by EEG, electrocardiograph and similar devices. The rendering latency was compared with EEGLAB and proves significantly faster when displaying an image from a large number of samples (e.g. 163-times faster for 75  ×  10(6) samples). The presented SignalPlant software is available free and does not depend on any other computation software. Furthermore, it can be extended with plugins by third parties ensuring its adaptability to future research tasks and new data formats.

Creating the Infrastructure for Rapid Application Development and Processing Response to the HIRDLS Radiance Anomaly

NASA Astrophysics Data System (ADS)

Cavanaugh, C.; Gille, J.; Francis, G.; Nardi, B.; Hannigan, J.; McInerney, J.; Krinsky, C.; Barnett, J.; Dean, V.; Craig, C.

2005-12-01

The High Resolution Dynamics Limb Sounder (HIRDLS) instrument onboard the NASA Aura spacecraft experienced a rupture of the thermal blanketing material (Kapton) during the rapid depressurization of launch. The Kapton draped over the HIRDLS scan mirror, severely limiting the aperture through which HIRDLS views space and Earth's atmospheric limb. In order for HIRDLS to achieve its intended measurement goals, rapid characterization of the anomaly, and rapid recovery from it were required. The recovery centered around a new processing module inserted into the standard HIRDLS processing scheme, with a goal of minimizing the effect of the anomaly on the already existing processing modules. We describe the software infrastructure on which the new processing module was built, and how that infrastructure allows for rapid application development and processing response. The scope of the infrastructure spans three distinct anomaly recovery steps and the means for their intercommunication. Each of the three recovery steps (removing the Kapton-induced oscillation in the radiometric signal, removing the Kapton signal contamination upon the radiometric signal, and correcting for the partially-obscured atmospheric view) is completely modularized and insulated from the other steps, allowing focused and rapid application development towards a specific step, and neutralizing unintended inter-step influences, thus greatly shortening the design-development-test lifecycle. The intercommunication is also completely modularized and has a simple interface to which the three recovery steps adhere, allowing easy modification and replacement of specific recovery scenarios, thereby heightening the processing response.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

NASA Astrophysics Data System (ADS)

Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-01

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

Real-time digital signal processing for live electro-optic imaging.

PubMed

Sasagawa, Kiyotaka; Kanno, Atsushi; Tsuchiya, Masahiro

2009-08-31

We present an imaging system that enables real-time magnitude and phase detection of modulated signals and its application to a Live Electro-optic Imaging (LEI) system, which realizes instantaneous visualization of RF electric fields. The real-time acquisition of magnitude and phase images of a modulated optical signal at 5 kHz is demonstrated by imaging with a Si-based high-speed CMOS image sensor and real-time signal processing with a digital signal processor. In the LEI system, RF electric fields are probed with light via an electro-optic crystal plate and downconverted to an intermediate frequency by parallel optical heterodyning, which can be detected with the image sensor. The artifacts caused by the optics and the image sensor characteristics are corrected by image processing. As examples, we demonstrate real-time visualization of electric fields from RF circuits.

Resonance-Based Sparse Signal Decomposition and its Application in Mechanical Fault Diagnosis: A Review.

PubMed

Huang, Wentao; Sun, Hongjian; Wang, Weijie

2017-06-03

Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis has drawn considerable attention. In terms of the rich information hidden in fault vibration signals, the processing and analysis techniques of vibration signals have become a crucial research issue in the field of mechanical fault diagnosis. Based on the theory of sparse decomposition, Selesnick proposed a novel nonlinear signal processing method: resonance-based sparse signal decomposition (RSSD). Since being put forward, RSSD has become widely recognized, and many RSSD-based methods have been developed to guide mechanical fault diagnosis. This paper attempts to summarize and review the theoretical developments and application advances of RSSD in mechanical fault diagnosis, and to provide a more comprehensive reference for those interested in RSSD and mechanical fault diagnosis. Followed by a brief introduction of RSSD's theoretical foundation, based on different optimization directions, applications of RSSD in mechanical fault diagnosis are categorized into five aspects: original RSSD, parameter optimized RSSD, subband optimized RSSD, integrated optimized RSSD, and RSSD combined with other methods. On this basis, outstanding issues in current RSSD study are also pointed out, as well as corresponding instructional solutions. We hope this review will provide an insightful reference for researchers and readers who are interested in RSSD and mechanical fault diagnosis.

Analysis and logical modeling of biological signaling transduction networks

NASA Astrophysics Data System (ADS)

Sun, Zhongyao

The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

Resonance-Based Sparse Signal Decomposition and Its Application in Mechanical Fault Diagnosis: A Review

PubMed Central

Huang, Wentao; Sun, Hongjian; Wang, Weijie

2017-01-01

Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis has drawn considerable attention. In terms of the rich information hidden in fault vibration signals, the processing and analysis techniques of vibration signals have become a crucial research issue in the field of mechanical fault diagnosis. Based on the theory of sparse decomposition, Selesnick proposed a novel nonlinear signal processing method: resonance-based sparse signal decomposition (RSSD). Since being put forward, RSSD has become widely recognized, and many RSSD-based methods have been developed to guide mechanical fault diagnosis. This paper attempts to summarize and review the theoretical developments and application advances of RSSD in mechanical fault diagnosis, and to provide a more comprehensive reference for those interested in RSSD and mechanical fault diagnosis. Followed by a brief introduction of RSSD’s theoretical foundation, based on different optimization directions, applications of RSSD in mechanical fault diagnosis are categorized into five aspects: original RSSD, parameter optimized RSSD, subband optimized RSSD, integrated optimized RSSD, and RSSD combined with other methods. On this basis, outstanding issues in current RSSD study are also pointed out, as well as corresponding instructional solutions. We hope this review will provide an insightful reference for researchers and readers who are interested in RSSD and mechanical fault diagnosis. PMID:28587198

ICE: A Scalable, Low-Cost FPGA-Based Telescope Signal Processing and Networking System

NASA Astrophysics Data System (ADS)

Bandura, K.; Bender, A. N.; Cliche, J. F.; de Haan, T.; Dobbs, M. A.; Gilbert, A. J.; Griffin, S.; Hsyu, G.; Ittah, D.; Parra, J. Mena; Montgomery, J.; Pinsonneault-Marotte, T.; Siegel, S.; Smecher, G.; Tang, Q. Y.; Vanderlinde, K.; Whitehorn, N.

2016-03-01

We present an overview of the ‘ICE’ hardware and software framework that implements large arrays of interconnected field-programmable gate array (FPGA)-based data acquisition, signal processing and networking nodes economically. The system was conceived for application to radio, millimeter and sub-millimeter telescope readout systems that have requirements beyond typical off-the-shelf processing systems, such as careful control of interference signals produced by the digital electronics, and clocking of all elements in the system from a single precise observatory-derived oscillator. A new generation of telescopes operating at these frequency bands and designed with a vastly increased emphasis on digital signal processing to support their detector multiplexing technology or high-bandwidth correlators — data rates exceeding a terabyte per second — are becoming common. The ICE system is built around a custom FPGA motherboard that makes use of an Xilinx Kintex-7 FPGA and ARM-based co-processor. The system is specialized for specific applications through software, firmware and custom mezzanine daughter boards that interface to the FPGA through the industry-standard FPGA mezzanine card (FMC) specifications. For high density applications, the motherboards are packaged in 16-slot crates with ICE backplanes that implement a low-cost passive full-mesh network between the motherboards in a crate, allow high bandwidth interconnection between crates and enable data offload to a computer cluster. A Python-based control software library automatically detects and operates the hardware in the array. Examples of specific telescope applications of the ICE framework are presented, namely the frequency-multiplexed bolometer readout systems used for the South Pole Telescope (SPT) and Simons Array and the digitizer, F-engine, and networking engine for the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) radio interferometers.

Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram

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

Anant, K.S.

1997-06-01

In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective mathematical tool for the analysis of transient signals. The two key signal processing applications of the wavelet transform, namely feature identification and representation (i.e., compression), are shown by solving important problems involving the seismogram and the electrocardiogram. The seismic feature identification problem involved locating in time the P and S phase arrivals. Locating these arrivals accurately (particularly the S phase) has been a constant issue in seismic signal processing. In Chapter 3, I show that the wavelet transform can be used to locate both the Pmore » as well as the S phase using only information from single station three-component seismograms. This is accomplished by using the basis function (wave-let) of the wavelet transform as a matching filter and by processing information across scales of the wavelet domain decomposition. The `pick` time results are quite promising as compared to analyst picks. The representation application involved the compression of the electrocardiogram which is a recording of the electrical activity of the heart. Compression of the electrocardiogram is an important problem in biomedical signal processing due to transmission and storage limitations. In Chapter 4, I develop an electrocardiogram compression method that applies vector quantization to the wavelet transform coefficients. The best compression results were obtained by using orthogonal wavelets, due to their ability to represent a signal efficiently. Throughout this thesis the importance of choosing wavelets based on the problem at hand is stressed. In Chapter 5, I introduce a wavelet design method that uses linear prediction in order to design wavelets that are geared to the signal or feature being analyzed. The use of these designed wavelets in a test feature identification application led to positive results. The methods developed in this thesis; the feature identification methods of Chapter 3, the compression methods of Chapter 4, as well as the wavelet design methods of Chapter 5, are general enough to be easily applied to other transient signals.« less

Design and Experiment of Electrooculogram (EOG) System and Its Application to Control Mobile Robot

NASA Astrophysics Data System (ADS)

Sanjaya, W. S. M.; Anggraeni, D.; Multajam, R.; Subkhi, M. N.; Muttaqien, I.

2017-03-01

In this paper, we design and investigate a biological signal detection of eye movements (Electrooculogram). To detect a signal of Electrooculogram (EOG) used 4 instrument amplifier process; differential instrumentation amplifier, High Pass Filter (HPF) with 3 stage filters, Low Pass Filter (LPF) with 3 stage filters and Level Shifter circuit. The total of amplifying is 1000 times of gain, with frequency range 0.5-30 Hz. IC OP-Amp OP07 was used for all amplifying process. EOG signal will be read as analog input for Arduino microprocessor, and will interfaced with serial communication to PC Monitor using Processing® software. The result of this research show a differences value of eye movements. Differences signal of EOG have been applied to navigation control of the mobile robot. In this research, all communication process using Bluetooth HC-05.

Signal processing and calibration procedures for in situ diode-laser absorption spectroscopy.

PubMed

Werle, P W; Mazzinghi, P; D'Amato, F; De Rosa, M; Maurer, K; Slemr, F

2004-07-01

Gas analyzers based on tunable diode-laser spectroscopy (TDLS) provide high sensitivity, fast response and highly specific in situ measurements of several atmospheric trace gases simultaneously. Under optimum conditions even a shot noise limited performance can be obtained. For field applications outside the laboratory practical limitations are important. At ambient mixing ratios below a few parts-per-billion spectrometers become more and more sensitive towards noise, interference, drift effects and background changes associated with low level signals. It is the purpose of this review to address some of the problems which are encountered at these low levels and to describe a signal processing strategy for trace gas monitoring and a concept for in situ system calibration applicable for tunable diode-laser spectroscopy. To meet the requirement of quality assurance for field measurements and monitoring applications, procedures to check the linearity according to International Standard Organization regulations are described and some measurements of calibration functions are presented and discussed.

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.

Behavioral Signal Processing: Deriving Human Behavioral Informatics From Speech and Language

PubMed Central

Narayanan, Shrikanth; Georgiou, Panayiotis G.

2013-01-01

The expression and experience of human behavior are complex and multimodal and characterized by individual and contextual heterogeneity and variability. Speech and spoken language communication cues offer an important means for measuring and modeling human behavior. Observational research and practice across a variety of domains from commerce to healthcare rely on speech- and language-based informatics for crucial assessment and diagnostic information and for planning and tracking response to an intervention. In this paper, we describe some of the opportunities as well as emerging methodologies and applications of human behavioral signal processing (BSP) technology and algorithms for quantitatively understanding and modeling typical, atypical, and distressed human behavior with a specific focus on speech- and language-based communicative, affective, and social behavior. We describe the three important BSP components of acquiring behavioral data in an ecologically valid manner across laboratory to real-world settings, extracting and analyzing behavioral cues from measured data, and developing models offering predictive and decision-making support. We highlight both the foundational speech and language processing building blocks as well as the novel processing and modeling opportunities. Using examples drawn from specific real-world applications ranging from literacy assessment and autism diagnostics to psychotherapy for addiction and marital well being, we illustrate behavioral informatics applications of these signal processing techniques that contribute to quantifying higher level, often subjectively described, human behavior in a domain-sensitive fashion. PMID:24039277

Accuracy-Energy Configurable Sensor Processor and IoT Device for Long-Term Activity Monitoring in Rare-Event Sensing Applications

PubMed Central

2014-01-01

A specially designed sensor processor used as a main processor in IoT (internet-of-thing) device for the rare-event sensing applications is proposed. The IoT device including the proposed sensor processor performs the event-driven sensor data processing based on an accuracy-energy configurable event-quantization in architectural level. The received sensor signal is converted into a sequence of atomic events, which is extracted by the signal-to-atomic-event generator (AEG). Using an event signal processing unit (EPU) as an accelerator, the extracted atomic events are analyzed to build the final event. Instead of the sampled raw data transmission via internet, the proposed method delays the communication with a host system until a semantic pattern of the signal is identified as a final event. The proposed processor is implemented on a single chip, which is tightly coupled in bus connection level with a microcontroller using a 0.18 μm CMOS embedded-flash process. For experimental results, we evaluated the proposed sensor processor by using an IR- (infrared radio-) based signal reflection and sensor signal acquisition system. We successfully demonstrated that the expected power consumption is in the range of 20% to 50% compared to the result of the basement in case of allowing 10% accuracy error. PMID:25580458

Implementation of a Portable Personal EKG Signal Monitoring System

NASA Astrophysics Data System (ADS)

Tan, Tan-Hsu; Chang, Ching-Su; Chen, Yung-Fu; Lee, Cheng

This research develops a portable personal EKG signal monitoring system to help patients monitor their EKG signals instantly to avoid the occurrence of tragedies. This system is built with two main units: signal pro-cessing unit and monitoring and evaluation unit. The first unit consists of EKG signal sensor, signal amplifier, digitalization circuit, and related control circuits. The second unit is a software tool developed on an embedded Linux platform (called CSA). Experimental result indicates that the proposed system has the practical potential for users in health monitoring. It is demonstrated to be more convenient and with greater portability than the conventional PC-based EKG signal monitoring systems. Furthermore, all the application units embedded in the system are built with open source codes, no licensed fee is required for operating systems and authorized applications. Thus, the building cost is much lower than the traditional systems.

Directional dual-tree complex wavelet packet transforms for processing quadrature signals.

PubMed

Serbes, Gorkem; Gulcur, Halil Ozcan; Aydin, Nizamettin

2016-03-01

Quadrature signals containing in-phase and quadrature-phase components are used in many signal processing applications in every field of science and engineering. Specifically, Doppler ultrasound systems used to evaluate cardiovascular disorders noninvasively also result in quadrature format signals. In order to obtain directional blood flow information, the quadrature outputs have to be preprocessed using methods such as asymmetrical and symmetrical phasing filter techniques. These resultant directional signals can be employed in order to detect asymptomatic embolic signals caused by small emboli, which are indicators of a possible future stroke, in the cerebral circulation. Various transform-based methods such as Fourier and wavelet were frequently used in processing embolic signals. However, most of the times, the Fourier and discrete wavelet transforms are not appropriate for the analysis of embolic signals due to their non-stationary time-frequency behavior. Alternatively, discrete wavelet packet transform can perform an adaptive decomposition of the time-frequency axis. In this study, directional discrete wavelet packet transforms, which have the ability to map directional information while processing quadrature signals and have less computational complexity than the existing wavelet packet-based methods, are introduced. The performances of proposed methods are examined in detail by using single-frequency, synthetic narrow-band, and embolic quadrature signals.

Photorefractive Integrators and Correlators

DTIC Science & Technology

1992-12-01

The use of photorefractive crystals as optically addressed time integrating spatial light modulators in acousto - optic signal processing applications...adaptive acousto - optic processor. These results demonstrated the feasibility of using photorefractives for such applications.... Photorefractive, Acousto - optic processor.

GPU-accelerated algorithms for compressed signals recovery with application to astronomical imagery deblurring

NASA Astrophysics Data System (ADS)

Fiandrotti, Attilio; Fosson, Sophie M.; Ravazzi, Chiara; Magli, Enrico

2018-04-01

Compressive sensing promises to enable bandwidth-efficient on-board compression of astronomical data by lifting the encoding complexity from the source to the receiver. The signal is recovered off-line, exploiting GPUs parallel computation capabilities to speedup the reconstruction process. However, inherent GPU hardware constraints limit the size of the recoverable signal and the speedup practically achievable. In this work, we design parallel algorithms that exploit the properties of circulant matrices for efficient GPU-accelerated sparse signals recovery. Our approach reduces the memory requirements, allowing us to recover very large signals with limited memory. In addition, it achieves a tenfold signal recovery speedup thanks to ad-hoc parallelization of matrix-vector multiplications and matrix inversions. Finally, we practically demonstrate our algorithms in a typical application of circulant matrices: deblurring a sparse astronomical image in the compressed domain.

Reflectometric measurement of plasma imaging and applications

NASA Astrophysics Data System (ADS)

Mase, A.; Ito, N.; Oda, M.; Komada, Y.; Nagae, D.; Zhang, D.; Kogi, Y.; Tobimatsu, S.; Maruyama, T.; Shimazu, H.; Sakata, E.; Sakai, F.; Kuwahara, D.; Yoshinaga, T.; Tokuzawa, T.; Nagayama, Y.; Kawahata, K.; Yamaguchi, S.; Tsuji-Iio, S.; Domier, C. W.; Luhmann, N. C., Jr.; Park, H. K.; Yun, G.; Lee, W.; Padhi, S.; Kim, K. W.

2012-01-01

Progress in microwave and millimeter-wave technologies has made possible advanced diagnostics for application to various fields, such as, plasma diagnostics, radio astronomy, alien substance detection, airborne and spaceborne imaging radars called as synthetic aperture radars, living body measurements. Transmission, reflection, scattering, and radiation processes of electromagnetic waves are utilized as diagnostic tools. In this report we focus on the reflectometric measurements and applications to biological signals (vital signal detection and breast cancer detection) as well as plasma diagnostics, specifically by use of imaging technique and ultra-wideband radar technique.

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.

Chirp Scaling Algorithms for SAR Processing

NASA Technical Reports Server (NTRS)

Jin, M.; Cheng, T.; Chen, M.

1993-01-01

The chirp scaling SAR processing algorithm is both accurate and efficient. Successful implementation requires proper selection of the interval of output samples, which is a function of the chirp interval, signal sampling rate, and signal bandwidth. Analysis indicates that for both airborne and spaceborne SAR applications in the slant range domain a linear chirp scaling is sufficient. To perform nonlinear interpolation process such as to output ground range SAR images, one can use a nonlinear chirp scaling interpolator presented in this paper.

Fisher information matrix for branching processes with application to electron-multiplying charge-coupled devices

PubMed Central

Chao, Jerry; Ward, E. Sally; Ober, Raimund J.

2012-01-01

The high quantum efficiency of the charge-coupled device (CCD) has rendered it the imaging technology of choice in diverse applications. However, under extremely low light conditions where few photons are detected from the imaged object, the CCD becomes unsuitable as its readout noise can easily overwhelm the weak signal. An intended solution to this problem is the electron-multiplying charge-coupled device (EMCCD), which stochastically amplifies the acquired signal to drown out the readout noise. Here, we develop the theory for calculating the Fisher information content of the amplified signal, which is modeled as the output of a branching process. Specifically, Fisher information expressions are obtained for a general and a geometric model of amplification, as well as for two approximations of the amplified signal. All expressions pertain to the important scenario of a Poisson-distributed initial signal, which is characteristic of physical processes such as photon detection. To facilitate the investigation of different data models, a “noise coefficient” is introduced which allows the analysis and comparison of Fisher information via a scalar quantity. We apply our results to the problem of estimating the location of a point source from its image, as observed through an optical microscope and detected by an EMCCD. PMID:23049166

Asynchronous signal-dependent non-uniform sampler

NASA Astrophysics Data System (ADS)

Can-Cimino, Azime; Chaparro, Luis F.; Sejdić, Ervin

2014-05-01

Analog sparse signals resulting from biomedical and sensing network applications are typically non-stationary with frequency-varying spectra. By ignoring that the maximum frequency of their spectra is changing, uniform sampling of sparse signals collects unnecessary samples in quiescent segments of the signal. A more appropriate sampling approach would be signal-dependent. Moreover, in many of these applications power consumption and analog processing are issues of great importance that need to be considered. In this paper we present a signal dependent non-uniform sampler that uses a Modified Asynchronous Sigma Delta Modulator which consumes low-power and can be processed using analog procedures. Using Prolate Spheroidal Wave Functions (PSWF) interpolation of the original signal is performed, thus giving an asynchronous analog to digital and digital to analog conversion. Stable solutions are obtained by using modulated PSWFs functions. The advantage of the adapted asynchronous sampler is that range of frequencies of the sparse signal is taken into account avoiding aliasing. Moreover, it requires saving only the zero-crossing times of the non-uniform samples, or their differences, and the reconstruction can be done using their quantized values and a PSWF-based interpolation. The range of frequencies analyzed can be changed and the sampler can be implemented as a bank of filters for unknown range of frequencies. The performance of the proposed algorithm is illustrated with an electroencephalogram (EEG) signal.

Code Optimization for the Choi-Williams Distribution for ELINT Applications

DTIC Science & Technology

2009-12-01

Probability of Intercept N Number of Samples NPS Naval Postgraduate School SNR Signal To Noise Ratio WVD Wigner - Ville Distribution xvi THIS PAGE...Many of the optimizations developed can be applied to the computation of the Wigner - Ville distribution as well. This work is highly applicable in the...made can also be used to increase the speed at which the Wigner - Ville distribution (another signal processing algorithm) can be computed. These

A New High-Resolution Direction Finding Architecture Using Photonics and Neural Network Signal Processing for Miniature Air Vehicle Applications

DTIC Science & Technology

2015-09-01

3 4. Probability of Intercept .................................................................3 5. Superresolution ...intercept. This alignment gives the shortest mean-time-to-intercept and can be less than one second. 4 5. Superresolution For single signals...at each antenna element. For multiple signals, superresolution DF techniques are often used. These techniques can be broken down into beamforming

Generative Adversarial Networks: An Overview

NASA Astrophysics Data System (ADS)

Creswell, Antonia; White, Tom; Dumoulin, Vincent; Arulkumaran, Kai; Sengupta, Biswa; Bharath, Anil A.

2018-01-01

Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this through deriving backpropagation signals through a competitive process involving a pair of networks. The representations that can be learned by GANs may be used in a variety of applications, including image synthesis, semantic image editing, style transfer, image super-resolution and classification. The aim of this review paper is to provide an overview of GANs for the signal processing community, drawing on familiar analogies and concepts where possible. In addition to identifying different methods for training and constructing GANs, we also point to remaining challenges in their theory and application.

Beamforming array techniques for acoustic emission monitoring of large concrete structures

NASA Astrophysics Data System (ADS)

McLaskey, Gregory C.; Glaser, Steven D.; Grosse, Christian U.

2010-06-01

This paper introduces a novel method of acoustic emission (AE) analysis which is particularly suited for field applications on large plate-like reinforced concrete structures, such as walls and bridge decks. Similar to phased-array signal processing techniques developed for other non-destructive evaluation methods, this technique adapts beamforming tools developed for passive sonar and seismological applications for use in AE source localization and signal discrimination analyses. Instead of relying on the relatively weak P-wave, this method uses the energy-rich Rayleigh wave and requires only a small array of 4-8 sensors. Tests on an in-service reinforced concrete structure demonstrate that the azimuth of an artificial AE source can be determined via this method for sources located up to 3.8 m from the sensor array, even when the P-wave is undetectable. The beamforming array geometry also allows additional signal processing tools to be implemented, such as the VESPA process (VElocity SPectral Analysis), whereby the arrivals of different wave phases are identified by their apparent velocity of propagation. Beamforming AE can reduce sampling rate and time synchronization requirements between spatially distant sensors which in turn facilitates the use of wireless sensor networks for this application.

An ultra low energy biomedical signal processing system operating at near-threshold.

PubMed

Hulzink, J; Konijnenburg, M; Ashouei, M; Breeschoten, A; Berset, T; Huisken, J; Stuyt, J; de Groot, H; Barat, F; David, J; Van Ginderdeuren, J

2011-12-01

This paper presents a voltage-scalable digital signal processing system designed for the use in a wireless sensor node (WSN) for ambulatory monitoring of biomedical signals. To fulfill the requirements of ambulatory monitoring, power consumption, which directly translates to the WSN battery lifetime and size, must be kept as low as possible. The proposed processing platform is an event-driven system with resources to run applications with different degrees of complexity in an energy-aware way. The architecture uses effective system partitioning to enable duty cycling, single instruction multiple data (SIMD) instructions, power gating, voltage scaling, multiple clock domains, multiple voltage domains, and extensive clock gating. It provides an alternative processing platform where the power and performance can be scaled to adapt to the application need. A case study on a continuous wavelet transform (CWT)-based heart-beat detection shows that the platform not only preserves the sensitivity and positive predictivity of the algorithm but also achieves the lowest energy/sample for ElectroCardioGram (ECG) heart-beat detection publicly reported today.

Method and Apparatus for Reducing Noise from Near Ocean Surface Sources

DTIC Science & Technology

2001-10-01

reducing the acoustic noise from near-surface 4 sources using an array processing technique that utilizes 5 Multiple Signal Classification ( MUSIC ...sources without 13 degrading the signal level and quality of the TOI. The present 14 invention utilizes a unique application of the MUSIC beamforming...specific algorithm that utilizes a 5 MUSIC technique and estimates the direction of arrival (DOA) of 6 the acoustic signal signals and generates output

Behavioral Signal Processing: Deriving Human Behavioral Informatics From Speech and Language: Computational techniques are presented to analyze and model expressed and perceived human behavior-variedly characterized as typical, atypical, distressed, and disordered-from speech and language cues and their applications in health, commerce, education, and beyond.

PubMed

Narayanan, Shrikanth; Georgiou, Panayiotis G

2013-02-07

The expression and experience of human behavior are complex and multimodal and characterized by individual and contextual heterogeneity and variability. Speech and spoken language communication cues offer an important means for measuring and modeling human behavior. Observational research and practice across a variety of domains from commerce to healthcare rely on speech- and language-based informatics for crucial assessment and diagnostic information and for planning and tracking response to an intervention. In this paper, we describe some of the opportunities as well as emerging methodologies and applications of human behavioral signal processing (BSP) technology and algorithms for quantitatively understanding and modeling typical, atypical, and distressed human behavior with a specific focus on speech- and language-based communicative, affective, and social behavior. We describe the three important BSP components of acquiring behavioral data in an ecologically valid manner across laboratory to real-world settings, extracting and analyzing behavioral cues from measured data, and developing models offering predictive and decision-making support. We highlight both the foundational speech and language processing building blocks as well as the novel processing and modeling opportunities. Using examples drawn from specific real-world applications ranging from literacy assessment and autism diagnostics to psychotherapy for addiction and marital well being, we illustrate behavioral informatics applications of these signal processing techniques that contribute to quantifying higher level, often subjectively described, human behavior in a domain-sensitive fashion.

Application of space technologies for the purpose of education at the Belarusian state university

NASA Astrophysics Data System (ADS)

Liashkevich, Siarhey

Application of space technologies for the purpose of education at the Aerospace Educational Center of Belarusian state university is discussed. The aim of the work is to prepare launch of small satellite. Students are expected to participate in the design of control station, systems of communication, earth observation, navigation, and positioning. Benefit of such project-based learning from economical perspective is discussed. At present our training system at the base of EyasSat classroom satellite is used for management of satellite orientation and stabilization system. Principles of video processing, communication technologies and informational security for small spacecraft are developed at the base of Wi9M-2443 developer kit. More recent equipment allows obtaining the skills in digital signal processing at the base of FPGA. Development of ground station includes setup of 2.6 meter diameter dish for L-band, and spiral rotational antennas for UHF and VHF bands. Receiver equipment from National Instruments is used for digital signal processing and signal management.

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).

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.

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.

Invariance algorithms for processing NDE signals

NASA Astrophysics Data System (ADS)

Mandayam, Shreekanth; Udpa, Lalita; Udpa, Satish S.; Lord, William

1996-11-01

Signals that are obtained in a variety of nondestructive evaluation (NDE) processes capture information not only about the characteristics of the flaw, but also reflect variations in the specimen's material properties. Such signal changes may be viewed as anomalies that could obscure defect related information. An example of this situation occurs during in-line inspection of gas transmission pipelines. The magnetic flux leakage (MFL) method is used to conduct noninvasive measurements of the integrity of the pipe-wall. The MFL signals contain information both about the permeability of the pipe-wall and the dimensions of the flaw. Similar operational effects can be found in other NDE processes. This paper presents algorithms to render NDE signals invariant to selected test parameters, while retaining defect related information. Wavelet transform based neural network techniques are employed to develop the invariance algorithms. The invariance transformation is shown to be a necessary pre-processing step for subsequent defect characterization and visualization schemes. Results demonstrating the successful application of the method are presented.

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2011-01-01

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

Digital Radar-Signal Processors Implemented in FPGAs

NASA Technical Reports Server (NTRS)

Berkun, Andrew; Andraka, Ray

2004-01-01

High-performance digital electronic circuits for onboard processing of return signals in an airborne precipitation- measuring radar system have been implemented in commercially available field-programmable gate arrays (FPGAs). Previously, it was standard practice to downlink the radar-return data to a ground station for postprocessing a costly practice that prevents the nearly-real-time use of the data for automated targeting. In principle, the onboard processing could be performed by a system of about 20 personal- computer-type microprocessors; relative to such a system, the present FPGA-based processor is much smaller and consumes much less power. Alternatively, the onboard processing could be performed by an application-specific integrated circuit (ASIC), but in comparison with an ASIC implementation, the present FPGA implementation offers the advantages of (1) greater flexibility for research applications like the present one and (2) lower cost in the small production volumes typical of research applications. The generation and processing of signals in the airborne precipitation measuring radar system in question involves the following especially notable steps: The system utilizes a total of four channels two carrier frequencies and two polarizations at each frequency. The system uses pulse compression: that is, the transmitted pulse is spread out in time and the received echo of the pulse is processed with a matched filter to despread it. The return signal is band-limited and digitally demodulated to a complex baseband signal that, for each pulse, comprises a large number of samples. Each complex pair of samples (denoted a range gate in radar terminology) is associated with a numerical index that corresponds to a specific time offset from the beginning of the radar pulse, so that each such pair represents the energy reflected from a specific range. This energy and the average echo power are computed. The phase of each range bin is compared to the previous echo by complex conjugate multiplication to obtain the mean Doppler shift (and hence the mean and variance of the velocity of precipitation) of the echo at that range.

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.

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.

Cognitive Neural Prosthetics

PubMed Central

Andersen, Richard A.; Hwang, Eun Jung; Mulliken, Grant H.

2010-01-01

The cognitive neural prosthetic (CNP) is a very versatile method for assisting paralyzed patients and patients with amputations. The CNP records the cognitive state of the subject, rather than signals strictly related to motor execution or sensation. We review a number of high-level cortical signals and their application for CNPs, including intention, motor imagery, decision making, forward estimation, executive function, attention, learning, and multi-effector movement planning. CNPs are defined by the cognitive function they extract, not the cortical region from which the signals are recorded. However, some cortical areas may be better than others for particular applications. Signals can also be extracted in parallel from multiple cortical areas using multiple implants, which in many circumstances can increase the range of applications of CNPs. The CNP approach relies on scientific understanding of the neural processes involved in cognition, and many of the decoding algorithms it uses also have parallels to underlying neural circuit functions. PMID:19575625

Programmable optical processor chips: toward photonic RF filters with DSP-level flexibility and MHz-band selectivity

NASA Astrophysics Data System (ADS)

Xie, Yiwei; Geng, Zihan; Zhuang, Leimeng; Burla, Maurizio; Taddei, Caterina; Hoekman, Marcel; Leinse, Arne; Roeloffzen, Chris G. H.; Boller, Klaus-J.; Lowery, Arthur J.

2017-12-01

Integrated optical signal processors have been identified as a powerful engine for optical processing of microwave signals. They enable wideband and stable signal processing operations on miniaturized chips with ultimate control precision. As a promising application, such processors enables photonic implementations of reconfigurable radio frequency (RF) filters with wide design flexibility, large bandwidth, and high-frequency selectivity. This is a key technology for photonic-assisted RF front ends that opens a path to overcoming the bandwidth limitation of current digital electronics. Here, the recent progress of integrated optical signal processors for implementing such RF filters is reviewed. We highlight the use of a low-loss, high-index-contrast stoichiometric silicon nitride waveguide which promises to serve as a practical material platform for realizing high-performance optical signal processors and points toward photonic RF filters with digital signal processing (DSP)-level flexibility, hundreds-GHz bandwidth, MHz-band frequency selectivity, and full system integration on a chip scale.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures.

PubMed

Hegazy, Maha A; Lotfy, Hayam M; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-05

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Direct Digital Demultiplexing of Analog TDM Signals for Cable Reduction in Ultrasound Imaging Catheters

PubMed Central

Carpenter, Thomas M.; Rashid, M. Wasequr; Ghovanloo, Maysam; Cowell, David M. J.; Freear, Steven; Degertekin, F. Levent

2016-01-01

In real-time catheter based 3D ultrasound imaging applications, gathering data from the transducer arrays is difficult as there is a restriction on cable count due to the diameter of the catheter. Although area and power hungry multiplexing circuits integrated at the catheter tip are used in some applications, these are unsuitable for use in small sized catheters for applications like intracardiac imaging. Furthermore, the length requirement for catheters and limited power available to on-chip cable drivers leads to limited signal strength at the receiver end. In this paper an alternative approach using Analog Time Division Multiplexing (TDM) is presented which addresses the cable restrictions of ultrasound catheters. A novel digital demultiplexing technique is also described which allows for a reduction in the number of analog signal processing stages required. The TDM and digital demultiplexing schemes are demonstrated for an intracardiac imaging system that would operate in the 4 MHz to 11 MHz range. A TDM integrated circuit (IC) with 8:1 multiplexer is interfaced with a fast ADC through a micro-coaxial catheter cable bundle, and processed with an FPGA RTL simulation. Input signals to the TDM IC are recovered with −40 dB crosstalk between channels on the same micro-coax, showing the feasibility of this system for ultrasound imaging applications. PMID:27116738

GNSS Space-Time Interference Mitigation and Attitude Determination in the Presence of Interference Signals

PubMed Central

Daneshmand, Saeed; Jahromi, Ali Jafarnia; Broumandan, Ali; Lachapelle, Gérard

2015-01-01

The use of Space-Time Processing (STP) in Global Navigation Satellite System (GNSS) applications is gaining significant attention due to its effectiveness for both narrowband and wideband interference suppression. However, the resulting distortion and bias on the cross correlation functions due to space-time filtering is a major limitation of this technique. Employing the steering vector of the GNSS signals in the filter structure can significantly reduce the distortion on cross correlation functions and lead to more accurate pseudorange measurements. This paper proposes a two-stage interference mitigation approach in which the first stage estimates an interference-free subspace before the acquisition and tracking phases and projects all received signals into this subspace. The next stage estimates array attitude parameters based on detecting and employing GNSS signals that are less distorted due to the projection process. Attitude parameters enable the receiver to estimate the steering vector of each satellite signal and use it in the novel distortionless STP filter to significantly reduce distortion and maximize Signal-to-Noise Ratio (SNR). GPS signals were collected using a six-element antenna array under open sky conditions to first calibrate the antenna array. Simulated interfering signals were then added to the digitized samples in software to verify the applicability of the proposed receiver structure and assess its performance for several interference scenarios. PMID:26016909

GNSS space-time interference mitigation and attitude determination in the presence of interference signals.

PubMed

Daneshmand, Saeed; Jahromi, Ali Jafarnia; Broumandan, Ali; Lachapelle, Gérard

2015-05-26

The use of Space-Time Processing (STP) in Global Navigation Satellite System (GNSS) applications is gaining significant attention due to its effectiveness for both narrowband and wideband interference suppression. However, the resulting distortion and bias on the cross correlation functions due to space-time filtering is a major limitation of this technique. Employing the steering vector of the GNSS signals in the filter structure can significantly reduce the distortion on cross correlation functions and lead to more accurate pseudorange measurements. This paper proposes a two-stage interference mitigation approach in which the first stage estimates an interference-free subspace before the acquisition and tracking phases and projects all received signals into this subspace. The next stage estimates array attitude parameters based on detecting and employing GNSS signals that are less distorted due to the projection process. Attitude parameters enable the receiver to estimate the steering vector of each satellite signal and use it in the novel distortionless STP filter to significantly reduce distortion and maximize Signal-to-Noise Ratio (SNR). GPS signals were collected using a six-element antenna array under open sky conditions to first calibrate the antenna array. Simulated interfering signals were then added to the digitized samples in software to verify the applicability of the proposed receiver structure and assess its performance for several interference scenarios.

Mixed-signal 0.18μm CMOS and SiGe BiCMOS foundry technologies for ROIC applications

NASA Astrophysics Data System (ADS)

Kar-Roy, Arjun; Howard, David; Racanelli, Marco; Scott, Mike; Hurwitz, Paul; Zwingman, Robert; Chaudhry, Samir; Jordan, Scott

2010-10-01

Today's readout integrated-circuits (ROICs) require a high level of integration of high performance analog and low power digital logic. TowerJazz offers a commercial 0.18μm CMOS technology platform for mixed-signal, RF, and high performance analog applications which can be used for ROIC applications. The commercial CA18HD dual gate oxide 1.8V/3.3V and CA18HA dual gate oxide 1.8V/5V RF/mixed signal processes, consisting of six layers of metallization, have high density stacked linear MIM capacitors, high-value resistors, triple-well isolation and thick top aluminum metal. The CA18HA process also has scalable drain extended LDMOS devices, up to 40V Vds, for high-voltage sensor applications, and high-performance bipolars for low noise requirements in ROICs. Also discussed are the available features of the commercial SBC18 SiGe BiCMOS platform with SiGe NPNs operating up to 200/200GHz (fT/fMAX frequencies in manufacturing and demonstrated to 270 GHz fT, for reduced noise and integrated RF capabilities which could be used in ROICs. Implementation of these technologies in a thick film SOI process for integrated RF switch and power management and the availability of high fT vertical PNPs to enable complementary BiCMOS (CBiCMOS), for RF enabled ROICs, are also described in this paper.

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

A modular, programmable measurement system for physiological and spaceflight applications

NASA Technical Reports Server (NTRS)

Hines, John W.; Ricks, Robert D.; Miles, Christopher J.

1993-01-01

The NASA-Ames Sensors 2000! Program has developed a small, compact, modular, programmable, sensor signal conditioning and measurement system, initially targeted for Life Sciences Spaceflight Programs. The system consists of a twelve-slot, multi-layer, distributed function backplane, a digital microcontroller/memory subsystem, conditioned and isolated power supplies, and six application-specific, physiological signal conditioners. Each signal condition is capable of being programmed for gains, offsets, calibration and operate modes, and, in some cases, selectable outputs and functional modes. Presently, the system has the capability for measuring ECG, EMG, EEG, Temperature, Respiration, Pressure, Force, and Acceleration parameters, in physiological ranges. The measurement system makes heavy use of surface-mount packaging technology, resulting in plug in modules sized 125x55 mm. The complete 12-slot system is contained within a volume of 220x150x70mm. The system's capabilities extend well beyond the specific objectives of NASA programs. Indeed, the potential commercial uses of the technology are virtually limitless. In addition to applications in medical and biomedical sensing, the system might also be used in process control situations, in clinical or research environments, in general instrumentation systems, factory processing, or any other applications where high quality measurements are required.

A modular, programmable measurement system for physiological and spaceflight applications

NASA Astrophysics Data System (ADS)

Hines, John W.; Ricks, Robert D.; Miles, Christopher J.

1993-02-01

The NASA-Ames Sensors 2000] Program has developed a small, compact, modular, programmable, sensor signal conditioning and measurement system, initially targeted for Life Sciences Spaceflight Programs. The system consists of a twelve-slot, multi-layer, distributed function backplane, a digital microcontroller/memory subsystem, conditioned and isolated power supplies, and six application-specific, physiological signal conditioners. Each signal condition is capable of being programmed for gains, offsets, calibration and operate modes, and, in some cases, selectable outputs and functional modes. Presently, the system has the capability for measuring ECG, EMG, EEG, Temperature, Respiration, Pressure, Force, and Acceleration parameters, in physiological ranges. The measurement system makes heavy use of surface-mount packaging technology, resulting in plug in modules sized 125x55 mm. The complete 12-slot system is contained within a volume of 220x150x70mm. The system's capabilities extend well beyond the specific objectives of NASA programs. Indeed, the potential commercial uses of the technology are virtually limitless. In addition to applications in medical and biomedical sensing, the system might also be used in process control situations, in clinical or research environments, in general instrumentation systems, factory processing, or any other applications where high quality measurements are required.

Association rule mining in the US Vaccine Adverse Event Reporting System (VAERS).

PubMed

Wei, Lai; Scott, John

2015-09-01

Spontaneous adverse event reporting systems are critical tools for monitoring the safety of licensed medical products. Commonly used signal detection algorithms identify disproportionate product-adverse event pairs and may not be sensitive to more complex potential signals. We sought to develop a computationally tractable multivariate data-mining approach to identify product-multiple adverse event associations. We describe an application of stepwise association rule mining (Step-ARM) to detect potential vaccine-symptom group associations in the US Vaccine Adverse Event Reporting System. Step-ARM identifies strong associations between one vaccine and one or more adverse events. To reduce the number of redundant association rules found by Step-ARM, we also propose a clustering method for the post-processing of association rules. In sample applications to a trivalent intradermal inactivated influenza virus vaccine and to measles, mumps, rubella, and varicella (MMRV) vaccine and in simulation studies, we find that Step-ARM can detect a variety of medically coherent potential vaccine-symptom group signals efficiently. In the MMRV example, Step-ARM appears to outperform univariate methods in detecting a known safety signal. Our approach is sensitive to potentially complex signals, which may be particularly important when monitoring novel medical countermeasure products such as pandemic influenza vaccines. The post-processing clustering algorithm improves the applicability of the approach as a screening method to identify patterns that may merit further investigation. Copyright © 2015 John Wiley & Sons, Ltd.

Computational models of human vision with applications

NASA Technical Reports Server (NTRS)

Wandell, B. A.

1985-01-01

Perceptual problems in aeronautics were studied. The mechanism by which color constancy is achieved in human vision was examined. A computable algorithm was developed to model the arrangement of retinal cones in spatial vision. The spatial frequency spectra are similar to the spectra of actual cone mosaics. The Hartley transform as a tool of image processing was evaluated and it is suggested that it could be used in signal processing applications, GR image processing.

REVIEW ARTICLE: Spectrophotometric applications of digital signal processing

NASA Astrophysics Data System (ADS)

Morawski, Roman Z.

2006-09-01

Spectrophotometry is more and more often the method of choice not only in analysis of (bio)chemical substances, but also in the identification of physical properties of various objects and their classification. The applications of spectrophotometry include such diversified tasks as monitoring of optical telecommunications links, assessment of eating quality of food, forensic classification of papers, biometric identification of individuals, detection of insect infestation of seeds and classification of textiles. In all those applications, large numbers of data, generated by spectrophotometers, are processed by various digital means in order to extract measurement information. The main objective of this paper is to review the state-of-the-art methodology for digital signal processing (DSP) when applied to data provided by spectrophotometric transducers and spectrophotometers. First, a general methodology of DSP applications in spectrophotometry, based on DSP-oriented models of spectrophotometric data, is outlined. Then, the most important classes of DSP methods for processing spectrophotometric data—the methods for DSP-aided calibration of spectrophotometric instrumentation, the methods for the estimation of spectra on the basis of spectrophotometric data, the methods for the estimation of spectrum-related measurands on the basis of spectrophotometric data—are presented. Finally, the methods for preprocessing and postprocessing of spectrophotometric data are overviewed. Throughout the review, the applications of DSP are illustrated with numerous examples related to broadly understood spectrophotometry.

Performance-driven Multimodality Sensor Fusion

DTIC Science & Technology

2012-01-23

in IEEE Intl Conf. on Acoust., Speech , Signal Processing, (Dallas), Mar. 2010. [10] K. Sricharan, R. Raich, and A. Hero III, “Boundary compensated knn ...nearest neighbor ( kNN ) plug-in estima- tors, we have developed a generally applicable theory that gives analytical closed-form expressions for asymptotic...Co-PI’s Raich and Hero and was published in the IEEE Proc. of 2011 Intl Conf. on Acoustics, Speech , and Signal Processing. 2.4 Dimension estimation in

Role of biomolecular logic systems in biosensors and bioactuators

NASA Astrophysics Data System (ADS)

Mailloux, Shay; Katz, Evgeny

2014-09-01

An overview of recent advances in biosensors and bioactuators based on biocomputing systems is presented. Biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce an output in the form of a YES/NO response. Compared to traditional single-analyte sensing devices, the biocomputing approach enables high-fidelity multianalyte biosensing, which is particularly beneficial for biomedical applications. Multisignal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert medical personnel of medical emergencies together with immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly as exemplified for liver injury. Wide-ranging applications of multianalyte digital biosensors in medicine, environmental monitoring, and homeland security are anticipated. "Smart" bioactuators, for signal-triggered drug release, for example, were designed by interfacing switchable electrodes with biocomputing systems. Integration of biosensing and bioactuating systems with biomolecular information processing systems advances the potential for further scientific innovations and various practical applications.

Application of advanced signal processing techniques to the rectification and registration of spaceborne imagery. [technology transfer, data transmission

NASA Technical Reports Server (NTRS)

Caron, R. H.; Rifman, S. S.; Simon, K. W.

1974-01-01

The development of an ERTS/MSS image processing system responsive to the needs of the user community is discussed. An overview of the TRW ERTS/MSS processor is presented, followed by a more detailed discussion of image processing functions satisfied by the system. The particular functions chosen for discussion are evolved from advanced signal processing techniques rooted in the areas of communication and control. These examples show how classical aerospace technology can be transferred to solve the more contemporary problems confronting the users of spaceborne imagery.

Empirical modeling for intelligent, real-time manufacture control

NASA Technical Reports Server (NTRS)

Xu, Xiaoshu

1994-01-01

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

An integrated domain specific language for post-processing and visualizing electrophysiological signals in Java.

PubMed

Strasser, T; Peters, T; Jagle, H; Zrenner, E; Wilke, R

2010-01-01

Electrophysiology of vision - especially the electroretinogram (ERG) - is used as a non-invasive way for functional testing of the visual system. The ERG is a combined electrical response generated by neural and non-neuronal cells in the retina in response to light stimulation. This response can be recorded and used for diagnosis of numerous disorders. For both clinical practice and clinical trials it is important to process those signals in an accurate and fast way and to provide the results as structured, consistent reports. Therefore, we developed a freely available and open-source framework in Java (http://www.eye.uni-tuebingen.de/project/idsI4sigproc). The framework is focused on an easy integration with existing applications. By leveraging well-established software patterns like pipes-and-filters and fluent interfaces as well as by designing the application programming interfaces (API) as an integrated domain specific language (DSL) the overall framework provides a smooth learning curve. Additionally, it already contains several processing methods and visualization features and can be extended easily by implementing the provided interfaces. In this way, not only can new processing methods be added but the framework can also be adopted for other areas of signal processing. This article describes in detail the structure and implementation of the framework and demonstrate its application through the software package used in clinical practice and clinical trials at the University Eye Hospital Tuebingen one of the largest departments in the field of visual electrophysiology in Europe.

Smart signal processing for an evolving electric grid

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Modular, bluetooth enabled, wireless electroencephalograph (EEG) platform.

PubMed

Lovelace, Joseph A; Witt, Tyler S; Beyette, Fred R

2013-01-01

A design for a modular, compact, and accurate wireless electroencephalograph (EEG) system is proposed. EEG is the only non-invasive measure for neuronal function of the brain. Using a number of digital signal processing (DSP) techniques, this neuronal function can be acquired and processed into meaningful representations of brain activity. The system described here utilizes Bluetooth to wirelessly transmit the digitized brain signal for an end application use. In this way, the system is portable, and modular in terms of the device to which it can interface. Brain Computer Interface (BCI) has become a popular extension of EEG systems in modern research. This design serves as a platform for applications using BCI capability.

Low power signal processing electronics for wearable medical devices.

PubMed

Casson, Alexander J; Rodriguez-Villegas, Esther

2010-01-01

Custom designed microchips, known as Application Specific Integrated Circuits (ASICs), offer the lowest possible power consumption electronics. However, this comes at the cost of a longer, more complex and more costly design process compared to one using generic, off-the-shelf components. Nevertheless, their use is essential in future truly wearable medical devices that must operate for long periods of time from physically small, energy limited batteries. This presentation will demonstrate the state-of-the-art in ASIC technology for providing online signal processing for use in these wearable medical devices.

Application of the wavelet packet transform to vibration signals for surface roughness monitoring in CNC turning operations

NASA Astrophysics Data System (ADS)

García Plaza, E.; Núñez López, P. J.

2018-01-01

The wavelet packet transform method decomposes a time signal into several independent time-frequency signals called packets. This enables the temporary location of transient events occurring during the monitoring of the cutting processes, which is advantageous in monitoring condition and fault diagnosis. This paper proposes the monitoring of surface roughness using a single low cost sensor that is easily implemented in numerical control machine tools in order to make on-line decisions on workpiece surface finish quality. Packet feature extraction in vibration signals was applied to correlate the sensor signals to measured surface roughness. For the successful application of the WPT method, mother wavelets, packet decomposition level, and appropriate packet selection methods should be considered, but are poorly understood aspects in the literature. In this novel contribution, forty mother wavelets, optimal decomposition level, and packet reduction methods were analysed, as well as identifying the effective frequency range providing the best packet feature extraction for monitoring surface finish. The results show that mother wavelet biorthogonal 4.4 in decomposition level L3 with the fusion of the orthogonal vibration components (ax + ay + az) were the best option in the vibration signal and surface roughness correlation. The best packets were found in the medium-high frequency DDA (6250-9375 Hz) and high frequency ADA (9375-12500 Hz) ranges, and the feed acceleration component ay was the primary source of information. The packet reduction methods forfeited packets with relevant features to the signal, leading to poor results for the prediction of surface roughness. WPT is a robust vibration signal processing method for the monitoring of surface roughness using a single sensor without other information sources, satisfactory results were obtained in comparison to other processing methods with a low computational cost.

DigiSeis—A software component for digitizing seismic signals using the PC sound card

NASA Astrophysics Data System (ADS)

Amin Khan, Khalid; Akhter, Gulraiz; Ahmad, Zulfiqar

2012-06-01

An innovative software-based approach to develop an inexpensive experimental seismic recorder is presented. This approach requires no hardware as the built-in PC sound card is used for digitization of seismic signals. DigiSeis, an ActiveX component is developed to capture the digitized seismic signals from the sound card and deliver them to applications for processing and display. A seismic recorder application software SeisWave is developed over this component, which provides real-time monitoring and display of seismic events picked by a pair of external geophones. This recorder can be used as an educational aid for conducting seismic experiments. It can also be connected with suitable seismic sensors to record earthquakes. The software application and the ActiveX component are available for download. This component can be used to develop seismic recording applications according to user specific requirements.

Photonic arbitrary waveform generation applicable to multiband UWB communications.

PubMed

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

2010-12-06

A novel photonic structure for arbitrary waveform generation (AWG) is proposed based on the electrooptical intensity modulation of a broadband optical signal which is transmitted by a dispersive element and the optoelectrical processing is realized by combining an interferometric structure with balanced photodetection. The generated waveform can be fully reconfigured through the control of the optical source power spectrum and the interferometric structure. The use of balanced photodetection permits to remove the baseband component of the generated signal which is relevant in certain applications. We have theoretically described and experimentally demonstrated the feasibility of the system by means of the generation of different pulse shapes. Specifically, the proposed structure has been applicable to generate Multiband UWB signaling formats regarding to the FCC requirements in order to show the flexibility of the system.

Application of Data Mining and Knowledge Discovery Techniques to Enhance Binary Target Detection and Decision-Making for Compromised Visual Images

DTIC Science & Technology

2004-11-01

affords exciting opportunities in target detection. The input signal may be a sum of sine waves, it could be an auditory signal, or possibly a visual...rendering of a scene. Since image processing is an area in which the original data are stationary in some sense ( auditory signals suffer from...11 Example 1 of SR - Identification of a Subliminal Signal below a Threshold .......................... 13 Example 2 of SR

Functional roles of fibroblast growth factor receptors (FGFRs) signaling in human cancers.

PubMed

Tiong, Kai Hung; Mah, Li Yen; Leong, Chee-Onn

2013-12-01

The fibroblast growth factor receptors (FGFRs) regulate important biological processes including cell proliferation and differentiation during development and tissue repair. Over the past decades, numerous pathological conditions and developmental syndromes have emerged as a consequence of deregulation in the FGFRs signaling network. This review aims to provide an overview of FGFR family, their complex signaling pathways in tumorigenesis, and the current development and application of therapeutics targeting the FGFRs signaling for treatment of refractory human cancers.

Application of the GNU Radio platform in the multistatic radar

NASA Astrophysics Data System (ADS)

Szlachetko, Boguslaw; Lewandowski, Andrzej

2009-06-01

This document presents the application of the Software Defined Radio-based platform in the multistatic radar. This platform consists of four-sensor linear antenna, Universal Software Radio Peripheral (USRP) hardware (radio frequency frontend) and GNU-Radio PC software. The paper provides information about architecture of digital signal processing performed by USRP's FPGA (digital down converting blocks) and PC host (implementation of the multichannel digital beamforming). The preliminary results of the signal recording performed by our experimental platform are presented.

A Review of Classification Techniques of EMG Signals during Isotonic and Isometric Contractions

PubMed Central

Nazmi, Nurhazimah; Abdul Rahman, Mohd Azizi; Yamamoto, Shin-Ichiroh; Ahmad, Siti Anom; Zamzuri, Hairi; Mazlan, Saiful Amri

2016-01-01

In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI) applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG) beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who would like to select the most appropriate methodology in classifying motion patterns, especially during different types of contractions. For feature extraction, the probability density function (PDF) of EMG signals will be the main interest of this study. Following that, a brief explanation of the different methods for pre-processing, feature extraction and classifying EMG signals will be compared 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:27548165

Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, Thomas; Jong, Jen-Yi

1986-01-01

An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.

Enhanced Data-Acquisition System

NASA Technical Reports Server (NTRS)

Mustain, Roy W.

1990-01-01

Time-consuming, costly digitization of analog signals on magnetic tape eliminated. Proposed data-acquisition system provides nearly immediate access to data in incoming signals by digitizing and recording them both on magnetic tape and on optical disk. Tape and/or disk later played back to reconstruct signals in analog or digital form for analysis. Of interest in industrial and scientific applications in which necessary to digitize, store, and/or process large quantities of experimental data.

Error Propagation in a System Model

NASA Technical Reports Server (NTRS)

Schloegel, Kirk (Inventor); Bhatt, Devesh (Inventor); Oglesby, David V. (Inventor); Madl, Gabor (Inventor)

2015-01-01

Embodiments of the present subject matter can enable the analysis of signal value errors for system models. In an example, signal value errors can be propagated through the functional blocks of a system model to analyze possible effects as the signal value errors impact incident functional blocks. This propagation of the errors can be applicable to many models of computation including avionics models, synchronous data flow, and Kahn process networks.

Methods and Apparatus for Reducing Multipath Signal Error Using Deconvolution

NASA Technical Reports Server (NTRS)

Kumar, Rajendra (Inventor); Lau, Kenneth H. (Inventor)

1999-01-01

A deconvolution approach to adaptive signal processing has been applied to the elimination of signal multipath errors as embodied in one preferred embodiment in a global positioning system receiver. The method and receiver of the present invention estimates then compensates for multipath effects in a comprehensive manner. Application of deconvolution, along with other adaptive identification and estimation techniques, results in completely novel GPS (Global Positioning System) receiver architecture.

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

Candy, J. V.

Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate.more » In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.« less

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.

Global Assessment of New GRACE Mascons Solutions for Hydrologic Applications

NASA Astrophysics Data System (ADS)

Save, H.; Zhang, Z.; Scanlon, B. R.; Wiese, D. N.; Landerer, F. W.; Long, D.; Longuevergne, L.; Chen, J.

2016-12-01

Advances in GRACE (Gravity Recovery and Climate Experiment) satellite data processing using new mass concentration (mascon) solutions have greatly increased the spatial localization and amplitude of recovered total Terrestrial Water Storage (TWS) signals; however, limited testing has been conduct on land hydrologic applications. In this study we compared TWS anomalies from (1) Center for Space Research mascons (CSR-M) solution with (2) NASA JPL mascon (JPL-M) solution, and with (3) a CSR gridded spherical harmonic rescaled (sf) solution from Tellus (CSRT-GSH.sf) in 176 river basins covering 80% of the global land area. There is good correspondence in TWS anomalies from mascons (CSR-M and JPL-M) and SH solutions based on high correlations between time series (rank correlation coefficients mostly >0.9). The long-term trends in basin TWS anomalies represent a relatively small signal (up to ±20 mm/yr) with differences among GRACE solutions and inter-basin variability increasing with decreasing basin size. Long-term TWS declines are greatest in (semi)arid and irrigated basins. Annual and semiannual signals have much larger amplitudes (up to ±250 mm). There is generally good agreement among GRACE solutions, increasing confidence in seasonal fluctuations from GRACE data. Rescaling spherical harmonics to restore lost signal increases agreement with mascons solutions for long-term trends and seasonal fluctuations. There are many advantages to using GRACE mascons solutions relative to SH solutions, such as reduced leakage from land to ocean increasing signal amplitude, and constraining results by applying geophysical data during processing with little or no post-processing requirements, making mascons more user friendly for non-geodetic users. This inter-comparison of various GRACE solutions should allow hydrologists to better select suitable GRACE products for hydrologic applications.

Controlling basins of attraction in a neural network-based telemetry monitor

NASA Technical Reports Server (NTRS)

Bell, Benjamin; Eilbert, James L.

1988-01-01

The size of the basins of attraction around fixed points in recurrent neural nets (NNs) can be modified by a training process. Controlling these attractive regions by presenting training data with various amount of noise added to the prototype signal vectors is discussed. Application of this technique to signal processing results in a classification system whose sensitivity can be controlled. This new technique is applied to the classification of temporal sequences in telemetry data.

Distribution of Software Changes for Battlefield Computer Systems: A lingering Problem

DTIC Science & Technology

1983-06-03

Defense, 10 June 1963), pp. 1-4. 3 Ibid. 4Automatic Data Processing Systems, Book - 1 Introduction (U.S. Army Signal School, Fort Monmouth, New Jersey, 15...January 1960) , passim. 5Automatic Data Processing Systems, Book - 2 Army Use of ADPS (U.S. Army Signal School, Fort Monmouth, New Jersey, 15 October...execute an application or utility program. It controls how the computer functions during a given operation. Utility programs are merely general use

SSME propellant path leak detection real-time

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

Generation and coherent detection of QPSK signal using a novel method of digital signal processing

NASA Astrophysics Data System (ADS)

Zhao, Yuan; Hu, Bingliang; He, Zhen-An; Xie, Wenjia; Gao, Xiaohui

2018-02-01

We demonstrate an optical quadrature phase-shift keying (QPSK) signal transmitter and an optical receiver for demodulating optical QPSK signal with homodyne detection and digital signal processing (DSP). DSP on the homodyne detection scheme is employed without locking the phase of the local oscillator (LO). In this paper, we present an extracting one-dimensional array of down-sampling method for reducing unwanted samples of constellation diagram measurement. Such a novel scheme embodies the following major advantages over the other conventional optical QPSK signal detection methods. First, this homodyne detection scheme does not need strict requirement on LO in comparison with linear optical sampling, such as having a flat spectral density and phase over the spectral support of the source under test. Second, the LabVIEW software is directly used for recovering the QPSK signal constellation without employing complex DSP circuit. Third, this scheme is applicable to multilevel modulation formats such as M-ary PSK and quadrature amplitude modulation (QAM) or higher speed signals by making minor changes.

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.

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.

Playback system designed for X-Band SAR

NASA Astrophysics Data System (ADS)

Yuquan, Liu; Changyong, Dou

2014-03-01

SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement.

Application of homomorphic signal processing to stress wave factor analysis

NASA Technical Reports Server (NTRS)

Karagulle, H.; Williams, J. H., Jr.; Lee, S. S.

1985-01-01

The stress wave factor (SWF) signal, which is the output of an ultrasonic testing system where the transmitting and receiving transducers are coupled to the same face of the test structure, is analyzed in the frequency domain. The SWF signal generated in an isotropic elastic plate is modelled as the superposition of successive reflections. The reflection which is generated by the stress waves which travel p times as a longitudinal (P) wave and s times as a shear (S) wave through the plate while reflecting back and forth between the bottom and top faces of the plate is designated as the reflection with p, s. Short-time portions of the SWF signal are considered for obtaining spectral information on individual reflections. If the significant reflections are not overlapped, the short-time Fourier analysis is used. A summary of the elevant points of homomorphic signal processing, which is also called cepstrum analysis, is given. Homomorphic signal processing is applied to short-time SWF signals to obtain estimates of the log spectra of individual reflections for cases in which the reflections are overlapped. Two typical SWF signals generated in aluminum plates (overlapping and non-overlapping reflections) are analyzed.

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.

Signal Coherence Recovery Using Acousto-Optic Fourier Transform Architectures

DTIC Science & Technology

1990-06-14

processing of data in ground- and space-based applications. We have implemented a prototype one-dimensional time-integrating acousto - optic (AO) Fourier...theory of optimum coherence recovery (CR) applicable in computation-limited environments. We have demonstrated direct acousto - optic implementation of CR

Infrared readout electronics; Proceedings of the Meeting, Orlando, FL, Apr. 21, 22, 1992

NASA Technical Reports Server (NTRS)

Fossum, Eric R. (Editor)

1992-01-01

The present volume on IR readout electronics discusses cryogenic readout using silicon devices, cryogenic readout using III-V and LTS devices, multiplexers for higher temperatures, and focal-plane signal processing electronics. Attention is given to the optimization of cryogenic CMOS processes for sub-10-K applications, cryogenic measurements of aerojet GaAs n-JFETs, inP-based heterostructure device technology for ultracold readout applications, and a three-terminal semiconductor-superconductor transimpedance amplifier. Topics addressed include unfulfilled needs in IR astronomy focal-plane readout electronics, IR readout integrated circuit technology for tactical missile systems, and radiation-hardened 10-bit A/D for FPA signal processing. Also discussed are the implementation of a noise reduction circuit for spaceflight IR spectrometers, a real-time processor for staring receivers, and a fiber-optic link design for INMOS transputers.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

A Preliminary Assessment of Soviet Development of Optimum Signal Discrimination Techniques: Optimum Space-Time Processing

DTIC Science & Technology

1982-10-01

thermal noise and radioastronomy is probably the application Shirman had in mind for that work. Kuriksha considers a wide class of two-dimensional...this point has been discussed In terms of EM wave propagation, signal detection, and parameter estimation in such fields as radar and radioastronomy

[Application of the mixed programming with Labview and Matlab in biomedical signal analysis].

PubMed

Yu, Lu; Zhang, Yongde; Sha, Xianzheng

2011-01-01

This paper introduces the method of mixed programming with Labview and Matlab, and applies this method in a pulse wave pre-processing and feature detecting system. The method has been proved suitable, efficient and accurate, which has provided a new kind of approach for biomedical signal analysis.

Neural networks and applications tutorial

NASA Astrophysics Data System (ADS)

Guyon, I.

1991-09-01

The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.

High-coherence mid-infrared dual-comb spectroscopy spanning 2.6 to 5.2 μm

NASA Astrophysics Data System (ADS)

Ycas, Gabriel; Giorgetta, Fabrizio R.; Baumann, Esther; Coddington, Ian; Herman, Daniel; Diddams, Scott A.; Newbury, Nathan R.

2018-04-01

Mid-infrared dual-comb spectroscopy has the potential to supplant conventional Fourier-transform spectroscopy in applications requiring high resolution, accuracy, signal-to-noise ratio and speed. Until now, mid-infrared dual-comb spectroscopy has been limited to narrow optical bandwidths or low signal-to-noise ratios. Using digital signal processing and broadband frequency conversion in waveguides, we demonstrate a mid-infrared dual-comb spectrometer covering 2.6 to 5.2 µm with comb-tooth resolution, sub-MHz frequency precision and accuracy, and a spectral signal-to-noise ratio as high as 6,500. As a demonstration, we measure the highly structured, broadband cross-section of propane from 2,840 to 3,040 cm-1, the complex phase/amplitude spectra of carbonyl sulfide from 2,000 to 2,100 cm-1, and of a methane, acetylene and ethane mixture from 2,860 to 3,400 cm-1. The combination of broad bandwidth, comb-mode resolution and high brightness will enable accurate mid-infrared spectroscopy in precision laboratory experiments and non-laboratory applications including open-path atmospheric gas sensing, process monitoring and combustion.

A Review of Diagnostic Techniques for ISHM Applications

NASA Technical Reports Server (NTRS)

Patterson-Hine, Ann; Biswas, Gautam; Aaseng, Gordon; Narasimhan, Sriam; Pattipati, Krishna

2005-01-01

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Advanced optical network architecture for integrated digital avionics

NASA Astrophysics Data System (ADS)

Morgan, D. Reed

1996-12-01

For the first time in the history of avionics, the network designer now has a choice in selecting the media that interconnects the sources and sinks of digital data on aircraft. Electrical designs are already giving way to photonics in application areas where the data rate times distance product is large or where special design requirements such as low weight or EMI considerations are critical. Future digital avionic architectures will increasingly favor the use of photonic interconnects as network data rates of one gigabit/second and higher are needed to support real-time operation of high-speed integrated digital processing. As the cost of optical network building blocks is reduced and as temperature-rugged laser sources are matured, metal interconnects will be forced to retreat to applications spanning shorter and shorter distances. Although the trend is already underway, the widespread use of digital optics will first occur at the system level, where gigabit/second, real-time interconnects between sensors, processors, mass memories and displays separated by a least of few meters will be required. The application of photonic interconnects for inter-printed wiring board signalling across the backplane will eventually find application for gigabit/second applications since signal degradation over copper traces occurs before one gigabit/second and 0.5 meters are reached. For the foreseeable future however, metal interconnects will continue to be used to interconnect devices on printed wiring boards since 5 gigabit/second signals can be sent over metal up to around 15 centimeters. Current-day applications of optical interconnects at the system level are described and a projection of how advanced optical interconnect technology will be driven by the use of high speed integrated digital processing on future aircraft is presented. The recommended advanced network for application in the 2010 time frame is a fiber-based system with a signalling speed of around 2-3 gigabits per second. This switch-based unified network will interconnect sensors, displays, mass memory and controls and displays to computer modules within the processing complex. The characteristics of required building blocks needed for the future are described. These building blocks include the fiber, an optical switch, a laser-based transceiver, blind-mate connectors and an optical backplane.

Digital Detection and Processing of Multiple Quadrature Harmonics for EPR Spectroscopy

PubMed Central

Ahmad, R.; Som, S.; Kesselring, E.; Kuppusamy, P.; Zweier, J.L.; Potter, L.C.

2010-01-01

A quadrature digital receiver and associated signal estimation procedure are reported for L-band electron paramagnetic resonance (EPR) spectroscopy. The approach provides simultaneous acquisition and joint processing of multiple harmonics in both in-phase and out-of-phase channels. The digital receiver, based on a high-speed dual-channel analog-to-digital converter, allows direct digital down-conversion with heterodyne processing using digital capture of the microwave reference signal. Thus, the receiver avoids noise and nonlinearity associated with analog mixers. Also, the architecture allows for low-Q anti-alias filtering and does not require the sampling frequency to be time-locked to the microwave reference. A noise model applicable for arbitrary contributions of oscillator phase noise is presented, and a corresponding maximum-likelihood estimator of unknown parameters is also reported. The signal processing is applicable for Lorentzian lineshape under nonsaturating conditions. The estimation is carried out using a convergent iterative algorithm capable of jointly processing the in-phase and out-of-phase data in the presence of phase noise and unknown microwave phase. Cramér-Rao bound analysis and simulation results demonstrate a significant reduction in linewidth estimation error using quadrature detection, for both low and high values of phase noise. EPR spectroscopic data are also reported for illustration. PMID:20971667

Digital detection and processing of multiple quadrature harmonics for EPR spectroscopy.

PubMed

Ahmad, R; Som, S; Kesselring, E; Kuppusamy, P; Zweier, J L; Potter, L C

2010-12-01

A quadrature digital receiver and associated signal estimation procedure are reported for L-band electron paramagnetic resonance (EPR) spectroscopy. The approach provides simultaneous acquisition and joint processing of multiple harmonics in both in-phase and out-of-phase channels. The digital receiver, based on a high-speed dual-channel analog-to-digital converter, allows direct digital down-conversion with heterodyne processing using digital capture of the microwave reference signal. Thus, the receiver avoids noise and nonlinearity associated with analog mixers. Also, the architecture allows for low-Q anti-alias filtering and does not require the sampling frequency to be time-locked to the microwave reference. A noise model applicable for arbitrary contributions of oscillator phase noise is presented, and a corresponding maximum-likelihood estimator of unknown parameters is also reported. The signal processing is applicable for Lorentzian lineshape under nonsaturating conditions. The estimation is carried out using a convergent iterative algorithm capable of jointly processing the in-phase and out-of-phase data in the presence of phase noise and unknown microwave phase. Cramér-Rao bound analysis and simulation results demonstrate a significant reduction in linewidth estimation error using quadrature detection, for both low and high values of phase noise. EPR spectroscopic data are also reported for illustration. Copyright © 2010 Elsevier Inc. All rights reserved.

A MUSIC-based method for SSVEP signal processing.

PubMed

Chen, Kun; Liu, Quan; Ai, Qingsong; Zhou, Zude; Xie, Sheng Quan; Meng, Wei

2016-03-01

The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100%. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications.

Noiseless intensity amplification of repetitive signals by coherent addition using the temporal Talbot effect

PubMed Central

Maram, Reza; Van Howe, James; Li, Ming; Azaña, José

2014-01-01

Amplification of signal intensity is essential for initiating physical processes, diagnostics, sensing, communications and measurement. During traditional amplification, the signal is amplified by multiplying the signal carriers through an active gain process, requiring the use of an external power source. In addition, the signal is degraded by noise and distortions that typically accompany active gain processes. We show noiseless intensity amplification of repetitive optical pulse waveforms with gain from 2 to ~20 without using active gain. The proposed method uses a dispersion-induced temporal self-imaging (Talbot) effect to redistribute and coherently accumulate energy of the original repetitive waveforms into fewer replica waveforms. In addition, we show how our passive amplifier performs a real-time average of the wave-train to reduce its original noise fluctuation, as well as enhances the extinction ratio of pulses to stand above the noise floor. Our technique is applicable to repetitive waveforms in any spectral region or wave system. PMID:25319207

Cancer systems biology: signal processing for cancer research

PubMed Central

Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei

2011-01-01

In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts. PMID:21439242

Fluorescence lifetime measurements in flow cytometry

NASA Astrophysics Data System (ADS)

Beisker, Wolfgang; Klocke, Axel

1997-05-01

Fluorescence lifetime measurements provide insights int eh dynamic and structural properties of dyes and their micro- environment. The implementation of fluorescence lifetime measurements in flow cytometric systems allows to monitor large cell and particle populations with high statistical significance. In our system, a modulated laser beam is used for excitation and the phase shift of the fluorescence signal recorded with a fast computer controlled digital oscilloscope is processed digitally to determine the phase shift with respect to a reference beam by fast fourier transform. Total fluorescence intensity as well as other parameters can be determined simultaneously from the same fluorescence signal. We use the epi-illumination design to allow the use of high numerical apertures to collect as much light as possible to ensure detection of even weak fluorescence. Data storage and processing is done comparable to slit-scan flow cytometric data using data analysis system. The results are stored, displayed, combined with other parameters and analyzed as normal listmode data. In our report we discuss carefully the signal to noise ratio for analog and digital processed lifetime signals to evaluate the theoretical minimum fluorescence intensity for lifetime measurements. Applications to be presented include DNA staining, parameters of cell functions as well as different applications in non-mammalian cells such as algae.

Efficient sensor network vehicle classification using peak harmonics of acoustic emissions

NASA Astrophysics Data System (ADS)

William, Peter E.; Hoffman, Michael W.

2008-04-01

An application is proposed for detection and classification of battlefield ground vehicles using the emitted acoustic signal captured at individual sensor nodes of an ad hoc Wireless Sensor Network (WSN). We make use of the harmonic characteristics of the acoustic emissions of battlefield vehicles, in reducing both the computations carried on the sensor node and the transmitted data to the fusion center for reliable and effcient classification of targets. Previous approaches focus on the lower frequency band of the acoustic emissions up to 500Hz; however, we show in the proposed application how effcient discrimination between battlefield vehicles is performed using features extracted from higher frequency bands (50 - 1500Hz). The application shows that selective time domain acoustic features surpass equivalent spectral features. Collaborative signal processing is utilized, such that estimation of certain signal model parameters is carried by the sensor node, in order to reduce the communication between the sensor node and the fusion center, while the remaining model parameters are estimated at the fusion center. The transmitted data from the sensor node to the fusion center ranges from 1 ~ 5% of the sampled acoustic signal at the node. A variety of classification schemes were examined, such as maximum likelihood, vector quantization and artificial neural networks. Evaluation of the proposed application, through processing of an acoustic data set with comparison to previous results, shows that the improvement is not only in the number of computations but also in the detection and false alarm rate as well.

Biosensor system-on-a-chip including CMOS-based signal processing circuits and 64 carbon nanotube-based sensors for the detection of a neurotransmitter.

PubMed

Lee, Byung Yang; Seo, Sung Min; Lee, Dong Joon; Lee, Minbaek; Lee, Joohyung; Cheon, Jun-Ho; Cho, Eunju; Lee, Hyunjoong; Chung, In-Young; Park, Young June; Kim, Suhwan; Hong, Seunghun

2010-04-07

We developed a carbon nanotube (CNT)-based biosensor system-on-a-chip (SoC) for the detection of a neurotransmitter. Here, 64 CNT-based sensors were integrated with silicon-based signal processing circuits in a single chip, which was made possible by combining several technological breakthroughs such as efficient signal processing, uniform CNT networks, and biocompatible functionalization of CNT-based sensors. The chip was utilized to detect glutamate, a neurotransmitter, where ammonia, a byproduct of the enzymatic reaction of glutamate and glutamate oxidase on CNT-based sensors, modulated the conductance signals to the CNT-based sensors. This is a major technological advancement in the integration of CNT-based sensors with microelectronics, and this chip can be readily integrated with larger scale lab-on-a-chip (LoC) systems for various applications such as LoC systems for neural networks.

Embedded neural recording with TinyOS-based wireless-enabled processor modules.

PubMed

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

2010-04-01

To create a wireless neural recording system that can benefit from the continuous advancements being made in embedded microcontroller and communications technologies, an embedded-system-based architecture for wireless neural recording has been designed, fabricated, and tested. The system consists of commercial-off-the-shelf wireless-enabled processor modules (motes) for communicating the neural signals, and a back-end database server and client application for archiving and browsing the neural signals. A neural-signal-acquisition application has been developed to enable the mote to either acquire neural signals at a rate of 4000 12-bit samples per second, or detect and transmit spike heights and widths sampled at a rate of 16670 12-bit samples per second on a single channel. The motes acquire neural signals via a custom low-noise neural-signal amplifier with adjustable gain and high-pass corner frequency that has been designed, and fabricated in a 1.5-microm CMOS process. In addition to browsing acquired neural data, the client application enables the user to remotely toggle modes of operation (real-time or spike-only), as well as amplifier gain and high-pass corner frequency.

A novel structured dictionary for fast processing of 3D medical images, with application to computed tomography restoration and denoising

NASA Astrophysics Data System (ADS)

Karimi, Davood; Ward, Rabab K.

2016-03-01

Sparse representation of signals in learned overcomplete dictionaries has proven to be a powerful tool with applications in denoising, restoration, compression, reconstruction, and more. Recent research has shown that learned overcomplete dictionaries can lead to better results than analytical dictionaries such as wavelets in almost all image processing applications. However, a major disadvantage of these dictionaries is that their learning and usage is very computationally intensive. In particular, finding the sparse representation of a signal in these dictionaries requires solving an optimization problem that leads to very long computational times, especially in 3D image processing. Moreover, the sparse representation found by greedy algorithms is usually sub-optimal. In this paper, we propose a novel two-level dictionary structure that improves the performance and the speed of standard greedy sparse coding methods. The first (i.e., the top) level in our dictionary is a fixed orthonormal basis, whereas the second level includes the atoms that are learned from the training data. We explain how such a dictionary can be learned from the training data and how the sparse representation of a new signal in this dictionary can be computed. As an application, we use the proposed dictionary structure for removing the noise and artifacts in 3D computed tomography (CT) images. Our experiments with real CT images show that the proposed method achieves results that are comparable with standard dictionary-based methods while substantially reducing the computational time.

Design and evaluation of online arithmetic for signal processing applications on FPGAs

NASA Astrophysics Data System (ADS)

Galli, Reto; Tenca, Alexandre F.

2001-11-01

This paper shows the design and the evaluation of on-line arithmetic modules for the most common operators used in DSP applications, using FPGAs as the target technology. The designs are highly optimized for the target technology and the common range of precision in DSP. The results are based on experimental data collected using CAD tools. All designs are synthesized for the same type of devices (Xilinx XC4000) for comparison, avoiding rough estimates of the system performance, and generating a more reliable and detailed comparison of on-line signal processing solutions with other state of the art approaches, such as distributed arithmetic. We show that on-line designs have a hard stand for basic DSP applications that use only addition and multiplication. However, we also show that on-line designs are able to overtake other approaches as the applications become more sophisticated, e.g. when data dependencies exist, or when non constant multiplicands restrict the use of other approaches.

Near DC force measurement using PVDF sensors

NASA Astrophysics Data System (ADS)

Ramanathan, Arun Kumar; Headings, Leon M.; Dapino, Marcelo J.

2018-03-01

There is a need for high-performance force sensors capable of operating at frequencies near DC while producing a minimal mass penalty. Example application areas include steering wheel sensors, powertrain torque sensors, robotic arms, and minimally invasive surgery. The beta crystallographic phase polyvinylidene fluoride (PVDF) films are suitable for this purpose owing to their large piezoelectric constant. Unlike conventional capacitive sensors, beta crystallographic phase PVDF films exhibit a broad linear range and can potentially be designed to operate without complex electronics or signal processing. A fundamental challenge that prevents the implementation of PVDF in certain high-performance applications is their inability to measure static signals, which results from their first-order electrical impedance. Charge readout algorithms have been implemented which address this issue only partially, as they often require integration of the output signal to obtain the applied force profile, resulting in signal drift and signal processing complexities. In this paper, we propose a straightforward real time drift compensation strategy that is applicable to high output impedance PVDF films. This strategy makes it possible to utilize long sample times with a minimal loss of accuracy; our measurements show that the static output remains within 5% of the original value during half-hour measurements. The sensitivity and full-scale range are shown to be determined by the feedback capacitance of the charge amplifier. A linear model of the PVDF sensor system is developed and validated against experimental measurements, along with benchmark tests against a commercial load cell.

Application of spectral decomposition of ²²²Rn activity concentration signal series measured in Niedźwiedzia Cave to identification of mechanisms responsible for different time-period variations.

PubMed

Przylibski, Tadeusz Andrzej; Wyłomańska, Agnieszka; Zimroz, Radosław; Fijałkowska-Lichwa, Lidia

2015-10-01

The authors present an application of spectral decomposition of (222)Rn activity concentration signal series as a mathematical tool used for distinguishing processes determining temporal changes of radon concentration in cave air. The authors demonstrate that decomposition of monitored signal such as (222)Rn activity concentration in cave air facilitates characterizing the processes affecting changes in the measured concentration of this gas. Thanks to this, one can better correlate and characterize the influence of various processes on radon behaviour in cave air. Distinguishing and characterising these processes enables the understanding of radon behaviour in cave environment and it may also enable and facilitate using radon as a precursor of geodynamic phenomena in the lithosphere. Thanks to the conducted analyses, the authors confirmed the unquestionable influence of convective air exchange between the cave and the atmosphere on seasonal and short-term (diurnal) changes in (222)Rn activity concentration in cave air. Thanks to the applied methodology of signal analysis and decomposition, the authors also identified a third process affecting (222)Rn activity concentration changes in cave air. This is a deterministic process causing changes in radon concentration, with a distribution different from the Gaussian one. The authors consider these changes to be the effect of turbulent air movements caused by the movement of visitors in caves. This movement is heterogeneous in terms of the number of visitors per group and the number of groups visiting a cave per day and per year. Such a process perfectly elucidates the observed character of the registered changes in (222)Rn activity concentration in one of the decomposed components of the analysed signal. The obtained results encourage further research into precise relationships between the registered (222)Rn activity concentration changes and factors causing them, as well as into using radon as a precursor of geodynamic phenomena in the lithosphere. Copyright © 2015 Elsevier Ltd. All rights reserved.

On-chip photonic microsystem for optical signal processing based on silicon and silicon nitride platforms

NASA Astrophysics Data System (ADS)

Li, Yu; Li, Jiachen; Yu, Hongchen; Yu, Hai; Chen, Hongwei; Yang, Sigang; Chen, Minghua

2018-04-01

The explosive growth of data centers, cloud computing and various smart devices is limited by the current state of microelectronics, both in terms of speed and heat generation. Benefiting from the large bandwidth, promising low power consumption and passive calculation capability, experts believe that the integrated photonics-based signal processing and transmission technologies can break the bottleneck of microelectronics technology. In recent years, integrated photonics has become increasingly reliable and access to the advanced fabrication process has been offered by various foundries. In this paper, we review our recent works on the integrated optical signal processing system. We study three different kinds of on-chip signal processors and use these devices to build microsystems for the fields of microwave photonics, optical communications and spectrum sensing. The microwave photonics front receiver was demonstrated with a signal processing range of a full-band (L-band to W-band). A fully integrated microwave photonics transceiver without the on-chip laser was realized on silicon photonics covering the signal frequency of up 10 GHz. An all-optical orthogonal frequency division multiplexing (OFDM) de-multiplier was also demonstrated and used for an OFDM communication system with the rate of 64 Gbps. Finally, we show our work on the monolithic integrated spectrometer with a high resolution of about 20 pm at the central wavelength of 1550 nm. These proposed on-chip signal processing systems potential applications in the fields of radar, 5G wireless communication, wearable devices and optical access networks.

Photonics-based real-time ultra-high-range-resolution radar with broadband signal generation and processing.

PubMed

Zhang, Fangzheng; Guo, Qingshui; Pan, Shilong

2017-10-23

Real-time and high-resolution target detection is highly desirable in modern radar applications. Electronic techniques have encountered grave difficulties in the development of such radars, which strictly rely on a large instantaneous bandwidth. In this article, a photonics-based real-time high-range-resolution radar is proposed with optical generation and processing of broadband linear frequency modulation (LFM) signals. A broadband LFM signal is generated in the transmitter by photonic frequency quadrupling, and the received echo is de-chirped to a low frequency signal by photonic frequency mixing. The system can operate at a high frequency and a large bandwidth while enabling real-time processing by low-speed analog-to-digital conversion and digital signal processing. A conceptual radar is established. Real-time processing of an 8-GHz LFM signal is achieved with a sampling rate of 500 MSa/s. Accurate distance measurement is implemented with a maximum error of 4 mm within a range of ~3.5 meters. Detection of two targets is demonstrated with a range-resolution as high as 1.875 cm. We believe the proposed radar architecture is a reliable solution to overcome the limitations of current radar on operation bandwidth and processing speed, and it is hopefully to be used in future radars for real-time and high-resolution target detection and imaging.

Shared address collectives using counter mechanisms

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

Blocksome, Michael; Dozsa, Gabor; Gooding, Thomas M

A shared address space on a compute node stores data received from a network and data to transmit to the network. The shared address space includes an application buffer that can be directly operated upon by a plurality of processes, for instance, running on different cores on the compute node. A shared counter is used for one or more of signaling arrival of the data across the plurality of processes running on the compute node, signaling completion of an operation performed by one or more of the plurality of processes, obtaining reservation slots by one or more of the pluralitymore » of processes, or combinations thereof.« less

A sequential method for spline approximation with variable knots. [recursive piecewise polynomial signal processing

NASA Technical Reports Server (NTRS)

Mier Muth, A. M.; Willsky, A. S.

1978-01-01

In this paper we describe a method for approximating a waveform by a spline. The method is quite efficient, as the data are processed sequentially. The basis of the approach is to view the approximation problem as a question of estimation of a polynomial in noise, with the possibility of abrupt changes in the highest derivative. This allows us to bring several powerful statistical signal processing tools into play. We also present some initial results on the application of our technique to the processing of electrocardiograms, where the knot locations themselves may be some of the most important pieces of diagnostic information.

On adaptive robustness approach to Anti-Jam signal processing

NASA Astrophysics Data System (ADS)

Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

Smart fabrics: integrating fiber optic sensors and information networks.

PubMed

El-Sherif, Mahmoud

2004-01-01

"Smart Fabrics" are defined as fabrics capable of monitoring their own "health", and sensing environmental conditions. They consist of special type of sensors, signal processing, and communication network embedded into textile substrate. Available conventional sensors and networking systems are not fully technologically mature for such applications. New classes of miniature sensors, signal processing and networking systems are urgently needed for such application. Also, the methodology for integration into textile structures has to be developed. In this paper, the development of smart fabrics with embedded fiber optic systems is presented for applications in health monitoring and diagnostics. Successful development of such smart fabrics with embedded sensors and networks is mainly dependent on the development of the proper miniature sensors technology, and on the integration of these sensors into textile structures. The developed smart fabrics will be discussed and samples of the results will be presented.

MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

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

Eichel, Paul H.

2013-08-01

MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962more » leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.« less

SNMR pulse sequence phase cycling

DOEpatents

Walsh, David O; Grunewald, Elliot D

2013-11-12

Technologies applicable to SNMR pulse sequence phase cycling are disclosed, including SNMR acquisition apparatus and methods, SNMR processing apparatus and methods, and combinations thereof. SNMR acquisition may include transmitting two or more SNMR pulse sequences and applying a phase shift to a pulse in at least one of the pulse sequences, according to any of a variety cycling techniques. SNMR processing may include combining SNMR from a plurality of pulse sequences comprising pulses of different phases, so that desired signals are preserved and indesired signals are canceled.

Two-Dimensional Signal Processing and Storage and Theory and Applications of Electromagnetic Measurements.

DTIC Science & Technology

1986-01-01

7 O-AI6 175 TWO- 1NENSION L SIGNAL PROCESSING AD STORAGE AND IA-1 ATLANTA SCHOOL OF ELECTRICAL ENGINEERING.. ULRSSIFIED R SCHAFER ET AL. SI JAN... ELECTRICAL ENGINEERING L’- ATLANTA, GEORGIA 30332 .’ -.. .. ~ i 4 2 i 2 " 𔃾, I IT= J ., . 4 2.~ i1 ov--.,-w. A -A *- t . . . SECURITY CLASSIFICATION O0...School of Electrical Engineering Atlanta, Georgia 30332 Research Triangle Park, NC 27709 •e. NAME OP PUNOINGMSONSORING 0b. OPPIC SYMBOL L PROCUREMENT

Success Story of Radar Technology in Automotive Applications

NASA Astrophysics Data System (ADS)

Meinecke, Marc-Michael; Jerhot, Jiři

2012-05-01

The radar technology has a long history of over more than one century. In contrast to this its application in the automotive domain is a quite young activity. The enablers of this relatively new research field are presented in this article from a car manufacturers perspective covering aspects of signal processing algorithms, hardware and driver assistance applications.

A design study of a signal detection system. [for search of extraterrestrial radio sources

NASA Technical Reports Server (NTRS)

Healy, T. J.

1980-01-01

A system is described which can aid in the search for radio signals from extraterrestrial sources, or in other applications characterized by low signal-to-noise ratios and very high data rates. The system follows a multichannel (16 million bin) spectrum analyzer, and has critical processing, system control, and memory fuctions. The design includes a moderately rich set of algorithms to be used in parallel to detect signals of unknown form. A multi-threshold approach is used to obtain high and low signal sensitivities. Relatively compact and transportable memory systems are specified.

Customizing cell signaling using engineered genetic logic circuits.

PubMed

Wang, Baojun; Buck, Martin

2012-08-01

Cells live in an ever-changing environment and continuously sense, process and react to environmental signals using their inherent signaling and gene regulatory networks. Recently, there have been great advances on rewiring the native cell signaling and gene networks to program cells to sense multiple noncognate signals and integrate them in a logical manner before initiating a desired response. Here, we summarize the current state-of-the-art of engineering synthetic genetic logic circuits to customize cellular signaling behaviors, and discuss their promising applications in biocomputing, environmental, biotechnological and biomedical areas as well as the remaining challenges in this growing field. Copyright © 2012 Elsevier Ltd. All rights reserved.

A modular cell-based biosensor using engineered genetic logic circuits to detect and integrate multiple environmental signals

PubMed Central

Wang, Baojun; Barahona, Mauricio; Buck, Martin

2013-01-01

Cells perceive a wide variety of cellular and environmental signals, which are often processed combinatorially to generate particular phenotypic responses. Here, we employ both single and mixed cell type populations, pre-programmed with engineered modular cell signalling and sensing circuits, as processing units to detect and integrate multiple environmental signals. Based on an engineered modular genetic AND logic gate, we report the construction of a set of scalable synthetic microbe-based biosensors comprising exchangeable sensory, signal processing and actuation modules. These cellular biosensors were engineered using distinct signalling sensory modules to precisely identify various chemical signals, and combinations thereof, with a quantitative fluorescent output. The genetic logic gate used can function as a biological filter and an amplifier to enhance the sensing selectivity and sensitivity of cell-based biosensors. In particular, an Escherichia coli consortium-based biosensor has been constructed that can detect and integrate three environmental signals (arsenic, mercury and copper ion levels) via either its native two-component signal transduction pathways or synthetic signalling sensors derived from other bacteria in combination with a cell-cell communication module. We demonstrate how a modular cell-based biosensor can be engineered predictably using exchangeable synthetic gene circuit modules to sense and integrate multiple-input signals. This study illustrates some of the key practical design principles required for the future application of these biosensors in broad environmental and healthcare areas. PMID:22981411

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.

A Novel AMARS Technique for Baseline Wander Removal Applied to Photoplethysmogram.

PubMed

Timimi, Ammar A K; Ali, M A Mohd; Chellappan, K

2017-06-01

A new digital filter, AMARS (aligning minima of alternating random signal) has been derived using trigonometry to regulate signal pulsations inline. The pulses are randomly presented in continuous signals comprising frequency band lower than the signal's mean rate. Frequency selective filters are conventionally employed to reject frequencies undesired by specific applications. However, these conventional filters only reduce the effects of the rejected range producing a signal superimposed by some baseline wander (BW). In this work, filters of different ranges and techniques were independently configured to preprocess a photoplethysmogram, an optical biosignal of blood volume dynamics, producing wave shapes with several BWs. The AMARS application effectively removed the encountered BWs to assemble similarly aligned trends. The removal implementation was found repeatable in both ear and finger photoplethysmograms, emphasizing the importance of BW removal in biosignal processing in retaining its structural, functional and physiological properties. We also believe that AMARS may be relevant to other biological and continuous signals modulated by similar types of baseline volatility.

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.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

ISLE (Image and Signal Processing LISP Environment) reference manual

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

Sherwood, R.J.; Searfus, R.M.

1990-01-01

ISLE is a rapid prototyping system for performing image and signal processing. It is designed to meet the needs of a person doing development of image and signal processing algorithms in a research environment. The image and signal processing modules in ISLE form a very capable package in themselves. They also provide a rich environment for quickly and easily integrating user-written software modules into the package. ISLE is well suited to applications in which there is a need to develop a processing algorithm in an interactive manner. It is straightforward to develop the algorithms, load it into ISLE, apply themore » algorithm to an image or signal, display the results, then modify the algorithm and repeat the develop-load-apply-display cycle. ISLE consists of a collection of image and signal processing modules integrated into a cohesive package through a standard command interpreter. ISLE developer elected to concentrate their effort on developing image and signal processing software rather than developing a command interpreter. A COMMON LISP interpreter was selected for the command interpreter because it already has the features desired in a command interpreter, it supports dynamic loading of modules for customization purposes, it supports run-time parameter and argument type checking, it is very well documented, and it is a commercially supported product. This manual is intended to be a reference manual for the ISLE functions The functions are grouped into a number of categories and briefly discussed in the Function Summary chapter. The full descriptions of the functions and all their arguments are given in the Function Descriptions chapter. 6 refs.« less

Micro-electro-mechanical systems (MEMS) and agile lensing-based modules for communications, sensing and signal processing

NASA Astrophysics Data System (ADS)

Reza, Syed Azer

This dissertation proposes the use of the emerging Micro-Electro-Mechanical Systems (MEMS) and agile lensing optical device technologies to design novel and powerful signal conditioning and sensing modules for advanced applications in optical communications, physical parameter sensing and RF/optical signal processing. For example, these new module designs have experimentally demonstrated exceptional features such as stable loss broadband operations and high > 60 dB optical dynamic range signal filtering capabilities. The first part of the dissertation describes the design and demonstration of digital MEMS-based signal processing modules for communication systems and sensor networks using the TI DLP (Digital Light Processing) technology. Examples of such modules include optical power splitters, narrowband and broadband variable fiber optical attenuators, spectral shapers and filters. Compared to prior works, these all-digital designs have advantages of repeatability, accuracy, and reliability that are essential for advanced communications and sensor applications. The next part of the dissertation proposes, analyzes and demonstrates the use of analog opto-fluidic agile lensing technology for sensor networks and test and measurement systems. Novel optical module designs for distance sensing, liquid level sensing, three-dimensional object shape sensing and variable photonic delay lines are presented and experimentally demonstrated. Compared to prior art module designs, the proposed analog-mode modules have exceptional performances, particularly for extreme environments (e.g., caustic liquids) where the free-space agile beam-based sensor provide remote non-contact access for physical sensing operations. The dissertation also presents novel modules involving hybrid analog-digital photonic designs that make use of the different optical device technologies to deliver the best features of both analog and digital optical device operations and controls. Digital controls are achieved through the use of the digital MEMS technology and analog controls are realized by employing opto-fluidic agile lensing technology and acousto-optic technology. For example, variable fiber-optic attenuators and spectral filters are proposed using the hybrid design. Compared to prior art module designs, these hybrid designs provide a higher module dynamic range and increased resolution that are critical in various advanced system applications. In summary, the dissertation shows the added power of hybrid optical designs using both the digital and analog photonic signal processing versus just all-digital or all-analog module designs.

Mechanomyographic Parameter Extraction Methods: An Appraisal for Clinical Applications

PubMed Central

Ibitoye, Morufu Olusola; Hamzaid, Nur Azah; Zuniga, Jorge M.; Hasnan, Nazirah; Wahab, Ahmad Khairi Abdul

2014-01-01

The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity. PMID:25479326

An Intelligent Computer-Based System for Sign Language Tutoring

ERIC Educational Resources Information Center

Ritchings, Tim; Khadragi, Ahmed; Saeb, Magdy

2012-01-01

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

Parachute deploy/Release mechanism

NASA Technical Reports Server (NTRS)

Robelen, D. B.

1979-01-01

Mechanism operated by signals from single radio-control channel deploy and releases small drogue parachute from flying aircraft. Technique has uses in industrial process control and in recreational hobby applications.

Remote sensing, imaging, and signal engineering

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

Brase, J.M.

1993-03-01

This report discusses the Remote Sensing, Imaging, and Signal Engineering (RISE) trust area which has been very active in working to define new directions. Signal and image processing have always been important support for existing programs at Lawrence Livermore National Laboratory (LLNL), but now these technologies are becoming central to the formation of new programs. Exciting new applications such as high-resolution telescopes, radar remote sensing, and advanced medical imaging are allowing us to participate in the development of new programs.

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

PubMed

Gallagher, N C

1976-04-01

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

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

PubMed Central

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

2010-01-01

In this paper, the least-mean-squares (LMS) algorithm was used to eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications. This kind of accelerometer is designed to be easily mounted in hard to reach places on vehicles under test, and they usually feature ranges from 50 to 2,000 g (where is the gravitational acceleration, 9.81 m/s2) and frequency responses to 3,000 Hz or higher, with DC response, durable cables, reliable performance and relatively low cost. However, here we show that the response of the sensor under test had a lot of noise and we carried out the signal processing stage by using both conventional and optimal adaptive filtering. Usually, designers have to build their specific analog and digital signal processing circuits, and this fact increases considerably the cost of the entire sensor system and the results are not always satisfactory, because the relevant signal is sometimes buried in a broad-band noise background where the unwanted information and the relevant signal sometimes share a very similar frequency band. Thus, in order to deal with this problem, here we used the LMS adaptive filtering algorithm and compare it with others based on the kind of filters that are typically used for automotive applications. The experimental results are satisfactory. PMID:22315542

Implementation of a smartphone wireless accelerometer platform for establishing deep brain stimulation treatment efficacy of essential tremor with machine learning.

PubMed

LeMoyne, Robert; Tomycz, Nestor; Mastroianni, Timothy; McCandless, Cyrus; Cozza, Michael; Peduto, David

2015-01-01

Essential tremor (ET) is a highly prevalent movement disorder. Patients with ET exhibit a complex progressive and disabling tremor, and medical management often fails. Deep brain stimulation (DBS) has been successfully applied to this disorder, however there has been no quantifiable way to measure tremor severity or treatment efficacy in this patient population. The quantified amelioration of kinetic tremor via DBS is herein demonstrated through the application of a smartphone (iPhone) as a wireless accelerometer platform. The recorded acceleration signal can be obtained at a setting of the subject's convenience and conveyed by wireless transmission through the Internet for post-processing anywhere in the world. Further post-processing of the acceleration signal can be classified through a machine learning application, such as the support vector machine. Preliminary application of deep brain stimulation with a smartphone for acquisition of a feature set and machine learning for classification has been successfully applied. The support vector machine achieved 100% classification between deep brain stimulation in `on' and `off' mode based on the recording of an accelerometer signal through a smartphone as a wireless accelerometer platform.

Robust Nonlinear Causality Analysis of Nonstationary Multivariate Physiological Time Series.

PubMed

Schack, Tim; Muma, Michael; Feng, Mengling; Guan, Cuntai; Zoubir, Abdelhak M

2018-06-01

An important research area in biomedical signal processing is that of quantifying the relationship between simultaneously observed time series and to reveal interactions between the signals. Since biomedical signals are potentially nonstationary and the measurements may contain outliers and artifacts, we introduce a robust time-varying generalized partial directed coherence (rTV-gPDC) function. The proposed method, which is based on a robust estimator of the time-varying autoregressive (TVAR) parameters, is capable of revealing directed interactions between signals. By definition, the rTV-gPDC only displays the linear relationships between the signals. We therefore suggest to approximate the residuals of the TVAR process, which potentially carry information about the nonlinear causality by a piece-wise linear time-varying moving-average model. The performance of the proposed method is assessed via extensive simulations. To illustrate the method's applicability to real-world problems, it is applied to a neurophysiological study that involves intracranial pressure, arterial blood pressure, and brain tissue oxygenation level (PtiO2) measurements. The rTV-gPDC reveals causal patterns that are in accordance with expected cardiosudoral meachanisms and potentially provides new insights regarding traumatic brain injuries. The rTV-gPDC is not restricted to the above problem but can be useful in revealing interactions in a broad range of applications.

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.

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

Multi-Frequency Signal Detection Based on Frequency Exchange and Re-Scaling Stochastic Resonance and Its Application to Weak Fault Diagnosis.

PubMed

Liu, Jinjun; Leng, Yonggang; Lai, Zhihui; Fan, Shengbo

2018-04-25

Mechanical fault diagnosis usually requires not only identification of the fault characteristic frequency, but also detection of its second and/or higher harmonics. However, it is difficult to detect a multi-frequency fault signal through the existing Stochastic Resonance (SR) methods, because the characteristic frequency of the fault signal as well as its second and higher harmonics frequencies tend to be large parameters. To solve the problem, this paper proposes a multi-frequency signal detection method based on Frequency Exchange and Re-scaling Stochastic Resonance (FERSR). In the method, frequency exchange is implemented using filtering technique and Single SideBand (SSB) modulation. This new method can overcome the limitation of "sampling ratio" which is the ratio of the sampling frequency to the frequency of target signal. It also ensures that the multi-frequency target signals can be processed to meet the small-parameter conditions. Simulation results demonstrate that the method shows good performance for detecting a multi-frequency signal with low sampling ratio. Two practical cases are employed to further validate the effectiveness and applicability of this method.

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.

A hybrid silicon membrane spatial light modulator for optical information processing

NASA Technical Reports Server (NTRS)

Pape, D. R.; Hornbeck, L. J.

1984-01-01

A new two dimensional, fast, analog, electrically addressable, silicon based membrane spatial light modulator (SLM) was developed for optical information processing applications. Coherent light reflected from the mirror elements is phase modulated producing an optical Fourier transform of an analog signal input to the device. The DMD architecture and operating parameters related to this application are presented. A model is developed that describes the optical Fourier transform properties of the DMD.

Multichannel/Multisensor Signal Processing In Uncertain Environments With Application To Multitarget Tracking.

DTIC Science & Technology

1998-05-22

NUMBER PR-98-1 T. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) Office of Naval Research Ballston Center Tower One One North Quincy...unlimited. 12 b. DISTRIBUTION CODE 19980601 082 13. ABSTRACT (Maximum 200 words) This research project is concerned with two distinct aspects of analysis...Environments With Application To Multitarget Tracking This research project is concerned with two distinct aspects of analysis and processing of sig

Fractal Point Process and Queueing Theory and Application to Communication Networks

DTIC Science & Technology

1999-12-31

use of nonlinear dynamics and chaos in the design of innovative analog error-protection codes for com- munications applications. In the chaos...the fol- lowing theses, patent, and papers. 1. A. Narula, M. D. Trott , and G. W. Wornell, "Information-Theoretic Analysis of Multiple-Antenna...Bounds," in Proc. Int. Conf. Dec. Control, (Japan), Dec. 1996. 5. G. W. Wornell and M. D. Trott , "Efficient Signal Processing Tech- niques for

Snore related signals processing in a private cloud computing system.

PubMed

Qian, Kun; Guo, Jian; Xu, Huijie; Zhu, Zhaomeng; Zhang, Gongxuan

2014-09-01

Snore related signals (SRS) have been demonstrated to carry important information about the obstruction site and degree in the upper airway of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) patients in recent years. To make this acoustic signal analysis method more accurate and robust, big SRS data processing is inevitable. As an emerging concept and technology, cloud computing has motivated numerous researchers and engineers to exploit applications both in academic and industry field, which could have an ability to implement a huge blue print in biomedical engineering. Considering the security and transferring requirement of biomedical data, we designed a system based on private cloud computing to process SRS. Then we set the comparable experiments of processing a 5-hour audio recording of an OSAHS patient by a personal computer, a server and a private cloud computing system to demonstrate the efficiency of the infrastructure we proposed.

Signal processing of anthropometric data

NASA Astrophysics Data System (ADS)

Zimmermann, W. J.

1983-09-01

The Anthropometric Measurements Laboratory has accumulated a large body of data from a number of previous experiments. The data is very noisy, therefore it requires the application of some signal processing schemes. Moreover, it was not regarded as time series measurements but as positional information; hence, the data is stored as coordinate points as defined by the motion of the human body. The accumulated data defines two groups or classes. Some of the data was collected from an experiment designed to measure the flexibility of the limbs, referred to as radial movement. The remaining data was collected from experiments designed to determine the surface of the reach envelope. An interactive signal processing package was designed and implemented. Since the data does not include time this package does not include a time series element. Presently the results is restricted to processing data obtained from those experiments designed to measure flexibility.

Signal processing of anthropometric data

NASA Technical Reports Server (NTRS)

Zimmermann, W. J.

1983-01-01

The Anthropometric Measurements Laboratory has accumulated a large body of data from a number of previous experiments. The data is very noisy, therefore it requires the application of some signal processing schemes. Moreover, it was not regarded as time series measurements but as positional information; hence, the data is stored as coordinate points as defined by the motion of the human body. The accumulated data defines two groups or classes. Some of the data was collected from an experiment designed to measure the flexibility of the limbs, referred to as radial movement. The remaining data was collected from experiments designed to determine the surface of the reach envelope. An interactive signal processing package was designed and implemented. Since the data does not include time this package does not include a time series element. Presently the results is restricted to processing data obtained from those experiments designed to measure flexibility.

Space Debris Detection on the HPDP, a Coarse-Grained Reconfigurable Array Architecture for Space

NASA Astrophysics Data System (ADS)

Suarez, Diego Andres; Bretz, Daniel; Helfers, Tim; Weidendorfer, Josef; Utzmann, Jens

2016-08-01

Stream processing, widely used in communications and digital signal processing applications, requires high- throughput data processing that is achieved in most cases using Application-Specific Integrated Circuit (ASIC) designs. Lack of programmability is an issue especially in space applications, which use on-board components with long life-cycles requiring applications updates. To this end, the High Performance Data Processor (HPDP) architecture integrates an array of coarse-grained reconfigurable elements to provide both flexible and efficient computational power suitable for stream-based data processing applications in space. In this work the capabilities of the HPDP architecture are demonstrated with the implementation of a real-time image processing algorithm for space debris detection in a space-based space surveillance system. The implementation challenges and alternatives are described making trade-offs to improve performance at the expense of negligible degradation of detection accuracy. The proposed implementation uses over 99% of the available computational resources. Performance estimations based on simulations show that the HPDP can amply match the application requirements.

Regulation mechanisms in mixed and pure culture microbial fermentation.

PubMed

Hoelzle, Robert D; Virdis, Bernardino; Batstone, Damien J

2014-11-01

Mixed-culture fermentation is a key central process to enable next generation biofuels and biocommodity production due to economic and process advantages over application of pure cultures. However, a key limitation to the application of mixed-culture fermentation is predicting culture product response, related to metabolic regulation mechanisms. This is also a limitation in pure culture bacterial fermentation. This review evaluates recent literature in both pure and mixed culture studies with a focus on understanding how regulation and signaling mechanisms interact with metabolic routes and activity. In particular, we focus on how microorganisms balance electron sinking while maximizing catabolic energy generation. Analysis of these mechanisms and their effect on metabolism dynamics is absent in current models of mixed-culture fermentation. This limits process prediction and control, which in turn limits industrial application of mixed-culture fermentation. A key mechanism appears to be the role of internal electron mediating cofactors, and related regulatory signaling. This may determine direction of electrons towards either hydrogen or reduced organics as end-products and may form the basis for future mechanistic models. © 2014 Wiley Periodicals, Inc.

Single photon laser altimeter simulator and statistical signal processing

NASA Astrophysics Data System (ADS)

Vacek, Michael; Prochazka, Ivan

2013-05-01

Spaceborne altimeters are common instruments onboard the deep space rendezvous spacecrafts. They provide range and topographic measurements critical in spacecraft navigation. Simultaneously, the receiver part may be utilized for Earth-to-satellite link, one way time transfer, and precise optical radiometry. The main advantage of single photon counting approach is the ability of processing signals with very low signal-to-noise ratio eliminating the need of large telescopes and high power laser source. Extremely small, rugged and compact microchip lasers can be employed. The major limiting factor, on the other hand, is the acquisition time needed to gather sufficient volume of data in repetitive measurements in order to process and evaluate the data appropriately. Statistical signal processing is adopted to detect signals with average strength much lower than one photon per measurement. A comprehensive simulator design and range signal processing algorithm are presented to identify a mission specific altimeter configuration. Typical mission scenarios (celestial body surface landing and topographical mapping) are simulated and evaluated. The high interest and promising single photon altimeter applications are low-orbit (˜10 km) and low-radial velocity (several m/s) topographical mapping (asteroids, Phobos and Deimos) and landing altimetry (˜10 km) where range evaluation repetition rates of ˜100 Hz and 0.1 m precision may be achieved. Moon landing and asteroid Itokawa topographical mapping scenario simulations are discussed in more detail.

Realization of guitar audio effects using methods of digital signal processing

NASA Astrophysics Data System (ADS)

Buś, Szymon; Jedrzejewski, Konrad

2015-09-01

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

ECG Holter monitor with alert system and mobile application

NASA Astrophysics Data System (ADS)

Teron, Abigail C.; Rivera, Pedro A.; Goenaga, Miguel A.

2016-05-01

This paper proposes a new approach on the Holter monitor by creating a portable Electrocardiogram (ECG) Holter monitor that will alert the user by detecting abnormal heart beats using a digital signal processing software. The alarm will be triggered when the patient experiences arrhythmias such as bradycardia and tachycardia. The equipment is simple, comfortable and small in size that fit in the hand. It can be used at any time and any moment by placing three leads to the person's chest which is connected to an electronic circuit. The ECG data will be transmitted via Bluetooth to the memory of a selected mobile phone using an application that will store the collected data for up to 24 hrs. The arrhythmia is identified by comparing the reference signals with the user's signal. The diagnostic results demonstrate that the ECG Holter monitor alerts the user when an arrhythmia is detected thru the Holter monitor and mobile application.

Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning.

PubMed

Lin, Chin-Teng; Chen, Yu-Chieh; Huang, Teng-Yi; Chiu, Tien-Ting; Ko, Li-Wei; Liang, Sheng-Fu; Hsieh, Hung-Yi; Hsu, Shang-Hwa; Duann, Jeng-Ren

2008-05-01

Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments.

Working Memory and Hearing Aid Processing: Literature Findings, Future Directions, and Clinical Applications

PubMed Central

Souza, Pamela; Arehart, Kathryn; Neher, Tobias

2015-01-01

Working memory—the ability to process and store information—has been identified as an important aspect of speech perception in difficult listening environments. Working memory can be envisioned as a limited-capacity system which is engaged when an input signal cannot be readily matched to a stored representation or template. This “mismatch” is expected to occur more frequently when the signal is degraded. Because working memory capacity varies among individuals, those with smaller capacity are expected to demonstrate poorer speech understanding when speech is degraded, such as in background noise. However, it is less clear whether (and how) working memory should influence practical decisions, such as hearing treatment. Here, we consider the relationship between working memory capacity and response to specific hearing aid processing strategies. Three types of signal processing are considered, each of which will alter the acoustic signal: fast-acting wide-dynamic range compression, which smooths the amplitude envelope of the input signal; digital noise reduction, which may inadvertently remove speech signal components as it suppresses noise; and frequency compression, which alters the relationship between spectral peaks. For fast-acting wide-dynamic range compression, a growing body of data suggests that individuals with smaller working memory capacity may be more susceptible to such signal alterations, and may receive greater amplification benefit with “low alteration” processing. While the evidence for a relationship between wide-dynamic range compression and working memory appears robust, the effects of working memory on perceptual response to other forms of hearing aid signal processing are less clear cut. We conclude our review with a discussion of the opportunities (and challenges) in translating information on individual working memory into clinical treatment, including clinically feasible measures of working memory. PMID:26733899

All-Optical Fibre Networks For Coal Mines

NASA Astrophysics Data System (ADS)

Zientkiewicz, Jacek K.

1987-09-01

A topic of the paper is fiber-optic integrated network (FOIN) suited to the most hostile environments existing in coal mines. The use of optical fibres for transmission of mine instrumentation data offers the prospects of improved safety and immunity to electromagnetic interference (EMI). The feasibility of optically powered sensors has opened up new opportunities for research into optical signal processing architectures. This article discusses a new fibre-optic sensor network involving a time domain multiplexing(TDM)scheme and optical signal processing techniques. The pros and cons of different FOIN topologies with respect to coal mine applications are considered. The emphasis has been placed on a recently developed all-optical fibre network using spread spectrum code division multiple access (COMA) techniques. The all-optical networks have applications in explosive environments where electrical isolation is required.

Signal processing with a summing operational amplifier in multicomponent potentiometric titrations.

PubMed

Parczewski, A

1987-06-01

It has been proved that application of two indicator electrodes connected to the ordinary titration apparatus through an auxiliary electronic device (a summing operational amplifier) significantly extends the scope of multicomponent potentiometric titrations in which the analytes are determined simultaneously from a single titration curve. For each analyte there is a corresponding potential jump on the titration curve. By application of the proposed auxiliary device, the sum of the electrode potentials is measured. The device also enables the relative sizes of the potential jumps at the end-points on the titration curve to be varied. The advantages of the proposed signal processing are exemplified by complexometric potentiometric titrations of Fe(III) and Cu(II) in mixtures, with a platinum electrode and a copper ion-selective electrode as the indicator electrodes.

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

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

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

Imaging synthetic aperture radar

DOEpatents

Burns, Bryan L.; Cordaro, J. Thomas

1997-01-01

A linear-FM SAR imaging radar method and apparatus to produce a real-time image by first arranging the returned signals into a plurality of subaperture arrays, the columns of each subaperture array having samples of dechirped baseband pulses, and further including a processing of each subaperture array to obtain coarse-resolution in azimuth, then fine-resolution in range, and lastly, to combine the processed subapertures to obtain the final fine-resolution in azimuth. Greater efficiency is achieved because both the transmitted signal and a local oscillator signal mixed with the returned signal can be varied on a pulse-to-pulse basis as a function of radar motion. Moreover, a novel circuit can adjust the sampling location and the A/D sample rate of the combined dechirped baseband signal which greatly reduces processing time and hardware. The processing steps include implementing a window function, stabilizing either a central reference point and/or all other points of a subaperture with respect to doppler frequency and/or range as a function of radar motion, sorting and compressing the signals using a standard fourier transforms. The stabilization of each processing part is accomplished with vector multiplication using waveforms generated as a function of radar motion wherein these waveforms may be synthesized in integrated circuits. Stabilization of range migration as a function of doppler frequency by simple vector multiplication is a particularly useful feature of the invention; as is stabilization of azimuth migration by correcting for spatially varying phase errors prior to the application of an autofocus process.

Cavitation controlled acoustic probe for fabric spot cleaning and moisture monitoring

DOEpatents

Sheen, Shuh-Haw; Chien, Hual-Te; Raptis, Apostolos C.

1997-01-01

A method and apparatus are provided for monitoring a fabric. An acoustic probe generates acoustic waves relative to the fabric. An acoustic sensor, such as an accelerometer is coupled to the acoustic probe for generating a signal representative of cavitation activity in the fabric. The generated cavitation activity representative signal is processed to indicate moisture content of the fabric. A feature of the invention is a feedback control signal is generated responsive to the generated cavitation activity representative signal. The feedback control signal can be used to control the energy level of the generated acoustic waves and to control the application of a cleaning solution to the fabric.

Video-signal improvement using comb filtering techniques.

NASA Technical Reports Server (NTRS)

Arndt, G. D.; Stuber, F. M.; Panneton, R. J.

1973-01-01

Significant improvement in the signal-to-noise performance of television signals has been obtained through the application of comb filtering techniques. This improvement is achieved by removing the inherent redundancy in the television signal through linear prediction and by utilizing the unique noise-rejection characteristics of the receiver comb filter. Theoretical and experimental results describe the signal-to-noise ratio and picture-quality improvement obtained through the use of baseband comb filters and the implementation of a comb network as the loop filter in a phase-lock-loop demodulator. Attention is given to the fact that noise becomes correlated when processed by the receiver comb filter.

Estimation of frequency offset in mobile satellite modems

NASA Technical Reports Server (NTRS)

Cowley, W. G.; Rice, M.; Mclean, A. N.

1993-01-01

In mobilesat applications, frequency offset on the received signal must be estimated and removed prior to further modem processing. A straightforward method of estimating the carrier frequency offset is to raise the received MPSK signal to the M-th power, and then estimate the location of the peak spectral component. An analysis of the lower signal to noise threshold of this method is carried out for BPSK signals. Predicted thresholds are compared to simulation results. It is shown how the method can be extended to pi/M MPSK signals. A real-time implementation of frequency offset estimation for the Australian mobile satellite system is described.

An Examination of Application of Artificial Neural Network in Cognitive Radios

NASA Astrophysics Data System (ADS)

Bello Salau, H.; Onwuka, E. N.; Aibinu, A. M.

2013-12-01

Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined.

Robust Adaptive Modified Newton Algorithm for Generalized Eigendecomposition and Its Application

NASA Astrophysics Data System (ADS)

Yang, Jian; Yang, Feng; Xi, Hong-Sheng; Guo, Wei; Sheng, Yanmin

2007-12-01

We propose a robust adaptive algorithm for generalized eigendecomposition problems that arise in modern signal processing applications. To that extent, the generalized eigendecomposition problem is reinterpreted as an unconstrained nonlinear optimization problem. Starting from the proposed cost function and making use of an approximation of the Hessian matrix, a robust modified Newton algorithm is derived. A rigorous analysis of its convergence properties is presented by using stochastic approximation theory. We also apply this theory to solve the signal reception problem of multicarrier DS-CDMA to illustrate its practical application. The simulation results show that the proposed algorithm has fast convergence and excellent tracking capability, which are important in a practical time-varying communication environment.

Mobile/android application for QRS detection using zero cross method

NASA Astrophysics Data System (ADS)

Rizqyawan, M. I.; Simbolon, A. I.; Suhendra, M. A.; Amri, M. F.; Kusumandari, D. E.

2018-03-01

In automatic ECG signal processing, one of the main topics of research is QRS complex detection. Detecting correct QRS complex or R peak is important since it is used to measure several other ECG metrics. One of the robust methods for QRS detection is Zero Cross method. This method uses an addition of high-frequency signal and zero crossing count to detect QRS complex which has a low-frequency oscillation. This paper presents an application of QRS detection using Zero Cross algorithm in the Android-based system. The performance of the algorithm in the mobile environment is measured. The result shows that this method is suitable for real-time QRS detection in a mobile application.

Introduction to the Discrete Fourier Series Considering Both Mathematical and Engineering Aspects--A Linear Algebra Approach

ERIC Educational Resources Information Center

Kohaupt, Ludwig

2015-01-01

The discrete Fourier series is a valuable tool developed and used by mathematicians and engineers alike. One of the most prominent applications is signal processing. Usually, it is important that the signals be transmitted fast, for example, when transmitting images over large distances such as between the moon and the earth or when generating…

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.

Analog Module Architecture for Space-Qualified Field-Programmable Mixed-Signal Arrays

NASA Technical Reports Server (NTRS)

Edwards, R. Timothy; Strohbehn, Kim; Jaskulek, Steven E.; Katz, Richard

1999-01-01

Spacecraft require all manner of both digital and analog circuits. Onboard digital systems are constructed almost exclusively from field-programmable gate array (FPGA) circuits providing numerous advantages over discrete design including high integration density, high reliability, fast turn-around design cycle time, lower mass, volume, and power consumption, and lower parts acquisition and flight qualification costs. Analog and mixed-signal circuits perform tasks ranging from housekeeping to signal conditioning and processing. These circuits are painstakingly designed and built using discrete components due to a lack of options for field-programmability. FPAA (Field-Programmable Analog Array) and FPMA (Field-Programmable Mixed-signal Array) parts exist but not in radiation-tolerant technology and not necessarily in an architecture optimal for the design of analog circuits for spaceflight applications. This paper outlines an architecture proposed for an FPAA fabricated in an existing commercial digital CMOS process used to make radiation-tolerant antifuse-based FPGA devices. The primary concerns are the impact of the technology and the overall array architecture on the flexibility of programming, the bandwidth available for high-speed analog circuits, and the accuracy of the components for high-performance applications.

Information Acquisition, Analysis and Integration

DTIC Science & Technology

2016-08-03

of sensing and processing, theory, applications, signal processing, image and video processing, machine learning , technology transfer. 16. SECURITY... learning . 5. Solved elegantly old problems like image and video debluring, intro- ducing new revolutionary approaches. 1 DISTRIBUTION A: Distribution...Polatkan, G. Sapiro, D. Blei, D. B. Dunson, and L. Carin, “ Deep learning with hierarchical convolution factor analysis,” IEEE 6 DISTRIBUTION A

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

System on a chip with MPEG-4 capability

NASA Astrophysics Data System (ADS)

Yassa, Fathy; Schonfeld, Dan

2002-12-01

Current products supporting video communication applications rely on existing computer architectures. RISC processors have been used successfully in numerous applications over several decades. DSP processors have become ubiquitous in signal processing and communication applications. Real-time applications such as speech processing in cellular telephony rely extensively on the computational power of these processors. Video processors designed to implement the computationally intensive codec operations have also been used to address the high demands of video communication applications (e.g., cable set-top boxes and DVDs). This paper presents an overview of a system-on-chip (SOC) architecture used for real-time video in wireless communication applications. The SOC specifications answer to the system requirements imposed by the application environment. A CAM-based video processor is used to accelerate data intensive video compression tasks such as motion estimations and filtering. Other components are dedicated to system level data processing and audio processing. A rich set of I/Os allows the SOC to communicate with other system components such as baseband and memory subsystems.

Radioastronomic signal processing cores for the SKA radio telescope

NASA Astrophysics Data System (ADS)

Comorett, G.; Chiarucc, S.; Belli, C.

Modern radio telescopes require the processing of wideband signals, with sample rates from tens of MHz to tens of GHz, and are composed from hundreds up to a million of individual antennas. Digital signal processing of these signals include digital receivers (the digital equivalent of the heterodyne receiver), beamformers, channelizers, spectrometers. FPGAs present the advantage of providing a relatively low power consumption, relative to GPUs or dedicated computers, a wide signal data path, and high interconnectivity. Efficient algorithms have been developed for these applications. Here we will review some of the signal processing cores developed for the SKA telescope. The LFAA beamformer/channelizer architecture is based on an oversampling channelizer, where the channelizer output sampling rate and channel spacing can be set independently. This is useful where an overlap between adjacent channels is required to provide an uniform spectral coverage. The architecture allows for an efficient and distributed channelization scheme, with a final resolution corresponding to a million of spectral channels, minimum leakage and high out-of-band rejection. An optimized filter design procedure is used to provide an equiripple response with a very large number of spectral channels. A wideband digital receiver has been designed in order to select the processed bandwidth of the SKA Mid receiver. The receiver extracts a 2.5 MHz bandwidth form a 14 GHz input bandwidth. The design allows for non-integer ratios between the input and output sampling rates, with a resource usage comparable to that of a conventional decimating digital receiver. Finally, some considerations on quantization of radioastronomic signals are presented. Due to the stochastic nature of the signal, quantization using few data bits is possible. Good accuracies and dynamic range are possible even with 2-3 bits, but the nonlinearity in the correlation process must be corrected in post-processing. With at least 6 bits it is possible to have a very linear response of the instrument, with nonlinear terms below 80 dB, providing the signal amplitude is kept within bounds.

Tacholess order-tracking approach for wind turbine gearbox fault detection

NASA Astrophysics Data System (ADS)

Wang, Yi; Xie, Yong; Xu, Guanghua; Zhang, Sicong; Hou, Chenggang

2017-09-01

Monitoring of wind turbines under variable-speed operating conditions has become an important issue in recent years. The gearbox of a wind turbine is the most important transmission unit; it generally exhibits complex vibration signatures due to random variations in operating conditions. Spectral analysis is one of the main approaches in vibration signal processing. However, spectral analysis is based on a stationary assumption and thus inapplicable to the fault diagnosis of wind turbines under variable-speed operating conditions. This constraint limits the application of spectral analysis to wind turbine diagnosis in industrial applications. Although order-tracking methods have been proposed for wind turbine fault detection in recent years, current methods are only applicable to cases in which the instantaneous shaft phase is available. For wind turbines with limited structural spaces, collecting phase signals with tachometers or encoders is difficult. In this study, a tacholess order-tracking method for wind turbines is proposed to overcome the limitations of traditional techniques. The proposed method extracts the instantaneous phase from the vibration signal, resamples the signal at equiangular increments, and calculates the order spectrum for wind turbine fault identification. The effectiveness of the proposed method is experimentally validated with the vibration signals of wind turbines.

A configurable and low-power mixed signal SoC for portable ECG monitoring applications.

PubMed

Kim, Hyejung; Kim, Sunyoung; Van Helleputte, Nick; Artes, Antonio; Konijnenburg, Mario; Huisken, Jos; Van Hoof, Chris; Yazicioglu, Refet Firat

2014-04-01

This paper describes a mixed-signal ECG System-on-Chip (SoC) that is capable of implementing configurable functionality with low-power consumption for portable ECG monitoring applications. A low-voltage and high performance analog front-end extracts 3-channel ECG signals and single channel electrode-tissue-impedance (ETI) measurement with high signal quality. This can be used to evaluate the quality of the ECG measurement and to filter motion artifacts. A custom digital signal processor consisting of 4-way SIMD processor provides the configurability and advanced functionality like motion artifact removal and R peak detection. A built-in 12-bit analog-to-digital converter (ADC) is capable of adaptive sampling achieving a compression ratio of up to 7, and loop buffer integration reduces the power consumption for on-chip memory access. The SoC is implemented in 0.18 μm CMOS process and consumes 32 μ W from a 1.2 V while heart beat detection application is running, and integrated in a wireless ECG monitoring system with Bluetooth protocol. Thanks to the ECG SoC, the overall system power consumption can be reduced significantly.

Dynamic pathway modeling of signal transduction networks: a domain-oriented approach.

PubMed

Conzelmann, Holger; Gilles, Ernst-Dieter

2008-01-01

Mathematical models of biological processes become more and more important in biology. The aim is a holistic understanding of how processes such as cellular communication, cell division, regulation, homeostasis, or adaptation work, how they are regulated, and how they react to perturbations. The great complexity of most of these processes necessitates the generation of mathematical models in order to address these questions. In this chapter we provide an introduction to basic principles of dynamic modeling and highlight both problems and chances of dynamic modeling in biology. The main focus will be on modeling of s transduction pathways, which requires the application of a special modeling approach. A common pattern, especially in eukaryotic signaling systems, is the formation of multi protein signaling complexes. Even for a small number of interacting proteins the number of distinguishable molecular species can be extremely high. This combinatorial complexity is due to the great number of distinct binding domains of many receptors and scaffold proteins involved in signal transduction. However, these problems can be overcome using a new domain-oriented modeling approach, which makes it possible to handle complex and branched signaling pathways.

Annotation and prediction of stress and workload from physiological and inertial signals.

PubMed

Ghosh, Arindam; Danieli, Morena; Riccardi, Giuseppe

2015-08-01

Continuous daily stress and high workload can have negative effects on individuals' physical and mental well-being. It has been shown that physiological signals may support the prediction of stress and workload. However, previous research is limited by the low diversity of signals concurring to such predictive tasks and controlled experimental design. In this paper we present 1) a pipeline for continuous and real-life acquisition of physiological and inertial signals 2) a mobile agent application for on-the-go event annotation and 3) an end-to-end signal processing and classification system for stress and workload from diverse signal streams. We study physiological signals such as Galvanic Skin Response (GSR), Skin Temperature (ST), Inter Beat Interval (IBI) and Blood Volume Pulse (BVP) collected using a non-invasive wearable device; and inertial signals collected from accelerometer and gyroscope sensors. We combine them with subjects' inputs (e.g. event tagging) acquired using the agent application, and their emotion regulation scores. In our experiments we explore signal combination and selection techniques for stress and workload prediction from subjects whose signals have been recorded continuously during their daily life. The end-to-end classification system is described for feature extraction, signal artifact removal, and classification. We show that a combination of physiological, inertial and user event signals provides accurate prediction of stress for real-life users and signals.

Oversampling of digitized images. [effects on interpolation in signal processing

NASA Technical Reports Server (NTRS)

Fischel, D.

1976-01-01

Oversampling is defined as sampling with a device whose characteristic width is greater than the interval between samples. This paper shows why oversampling should be avoided and discusses the limitations in data processing if circumstances dictate that oversampling cannot be circumvented. Principally, oversampling should not be used to provide interpolating data points. Rather, the time spent oversampling should be used to obtain more signal with less relative error, and the Sampling Theorem should be employed to provide any desired interpolated values. The concepts are applicable to single-element and multielement detectors.

DSPSR: Digital Signal Processing Software for Pulsar Astronomy

NASA Astrophysics Data System (ADS)

van Straten, W.; Bailes, M.

2010-10-01

DSPSR, written primarily in C++, is an open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. The library implements an extensive range of modular algorithms for use in coherent dedispersion, filterbank formation, pulse folding, and other tasks. The software is installed and compiled using the standard GNU configure and make system, and is able to read astronomical data in 18 different file formats, including FITS, S2, CPSR, CPSR2, PuMa, PuMa2, WAPP, ASP, and Mark5.

Comparison of digital signal processing modules in gamma-ray spectrometry.

PubMed

Lépy, Marie-Christine; Cissé, Ousmane Ibrahima; Pierre, Sylvie

2014-05-01

Commercial digital signal-processing modules have been tested for their applicability to gamma-ray spectrometry. The tests were based on the same n-type high purity germanium detector. The spectrum quality was studied in terms of energy resolution and peak area versus shaping parameters, using a Eu-152 point source. The stability of a reference peak count rate versus the total count rate was also examined. The reliability of the quantitative results is discussed for their use in measurement at the metrological level. © 2013 Published by Elsevier Ltd.

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

NASA Technical Reports Server (NTRS)

Kishoni, D.; Heyman, J. S.

1986-01-01

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

Glass-type wireless PPG measuring system.

PubMed

Lee, E M; Shin, J Y; Hong, J H; Cha, E J; Lee, T S

2010-01-01

This paper is about a glass-type wireless bio-signal transmitter that can monitor the user's health state in daily life. The device implemented in this study consists of the transmission part and the receiving part. The transmission part includes a photoplethysmography(PPG) sensor for detecting pulse wave signals, accelerometer for detecting kinetic signals, and a wireless controller for transmitting acquired bio-information. The receiving part is designed to check and process transmitted data through interoperation with a PC. In the experiments, we collected data during a sitting posture and repeated sit-to-stand motion in laboratory environment, and analyzed the data. As to accuracy, the correlation between the peak-to-peak intervals in the signals of the Biopac equipment and the developed device measured in a sitting posture was 97.5%, and that measured in sit-to-stand motion was 87%. In addition, when bio-signals were transmitted through wireless communication, the transmission was successful 100% without any error. When pulse wave signals and kinetic signals were obtained and compared, the results proved the accuracy and daily applicability of the developed device, and the glass-type wireless bio-signal transmission system is expected to be applicable to unobtrusive health monitoring for the user.

Research for the jamming mechanism of high-frequency laser to the laser seeker

NASA Astrophysics Data System (ADS)

Zheng, Xingyuan; Zhang, Haiyang; Wang, Yunping; Feng, Shuang; Zhao, Changming

2013-08-01

High-frequency laser will be able to enter the enemy laser signal processing systems without encoded identification and a copy. That makes it one of the research directions of new interference sources. In order to study the interference mechanism of high-frequency laser to laser guided weapons. According to the principle of high-frequency laser interference, a series of related theoretical models such as a semi-active laser seeker coded identification model, a time door model, multi-signal processing model and a interference signal modulation processing model are established. Then seeker interfere with effective 3σ criterion is proposed. Based on this, the study of the effect of multi-source interference and signal characteristics of the effect of high repetition frequency laser interference are key research. According to the simulation system testing, the results show that the multi-source interference and interference signal frequency modulation can effectively enhance the interference effect. While the interference effect of the interference signal amplitude modulation is not obvious. The research results will provide the evaluation of high-frequency laser interference effect and provide theoretical references for high-frequency laser interference system application.

NeuroPigPen: A Scalable Toolkit for Processing Electrophysiological Signal Data in Neuroscience Applications Using Apache Pig

PubMed Central

Sahoo, Satya S.; Wei, Annan; Valdez, Joshua; Wang, Li; Zonjy, Bilal; Tatsuoka, Curtis; Loparo, Kenneth A.; Lhatoo, Samden D.

2016-01-01

The recent advances in neurological imaging and sensing technologies have led to rapid increase in the volume, rate of data generation, and variety of neuroscience data. This “neuroscience Big data” represents a significant opportunity for the biomedical research community to design experiments using data with greater timescale, large number of attributes, and statistically significant data size. The results from these new data-driven research techniques can advance our understanding of complex neurological disorders, help model long-term effects of brain injuries, and provide new insights into dynamics of brain networks. However, many existing neuroinformatics data processing and analysis tools were not built to manage large volume of data, which makes it difficult for researchers to effectively leverage this available data to advance their research. We introduce a new toolkit called NeuroPigPen that was developed using Apache Hadoop and Pig data flow language to address the challenges posed by large-scale electrophysiological signal data. NeuroPigPen is a modular toolkit that can process large volumes of electrophysiological signal data, such as Electroencephalogram (EEG), Electrocardiogram (ECG), and blood oxygen levels (SpO2), using a new distributed storage model called Cloudwave Signal Format (CSF) that supports easy partitioning and storage of signal data on commodity hardware. NeuroPigPen was developed with three design principles: (a) Scalability—the ability to efficiently process increasing volumes of data; (b) Adaptability—the toolkit can be deployed across different computing configurations; and (c) Ease of programming—the toolkit can be easily used to compose multi-step data processing pipelines using high-level programming constructs. The NeuroPigPen toolkit was evaluated using 750 GB of electrophysiological signal data over a variety of Hadoop cluster configurations ranging from 3 to 30 Data nodes. The evaluation results demonstrate that the toolkit is highly scalable and adaptable, which makes it suitable for use in neuroscience applications as a scalable data processing toolkit. As part of the ongoing extension of NeuroPigPen, we are developing new modules to support statistical functions to analyze signal data for brain connectivity research. In addition, the toolkit is being extended to allow integration with scientific workflow systems. NeuroPigPen is released under BSD license at: https://sites.google.com/a/case.edu/neuropigpen/. PMID:27375472

NeuroPigPen: A Scalable Toolkit for Processing Electrophysiological Signal Data in Neuroscience Applications Using Apache Pig.

PubMed

Sahoo, Satya S; Wei, Annan; Valdez, Joshua; Wang, Li; Zonjy, Bilal; Tatsuoka, Curtis; Loparo, Kenneth A; Lhatoo, Samden D

2016-01-01

The recent advances in neurological imaging and sensing technologies have led to rapid increase in the volume, rate of data generation, and variety of neuroscience data. This "neuroscience Big data" represents a significant opportunity for the biomedical research community to design experiments using data with greater timescale, large number of attributes, and statistically significant data size. The results from these new data-driven research techniques can advance our understanding of complex neurological disorders, help model long-term effects of brain injuries, and provide new insights into dynamics of brain networks. However, many existing neuroinformatics data processing and analysis tools were not built to manage large volume of data, which makes it difficult for researchers to effectively leverage this available data to advance their research. We introduce a new toolkit called NeuroPigPen that was developed using Apache Hadoop and Pig data flow language to address the challenges posed by large-scale electrophysiological signal data. NeuroPigPen is a modular toolkit that can process large volumes of electrophysiological signal data, such as Electroencephalogram (EEG), Electrocardiogram (ECG), and blood oxygen levels (SpO2), using a new distributed storage model called Cloudwave Signal Format (CSF) that supports easy partitioning and storage of signal data on commodity hardware. NeuroPigPen was developed with three design principles: (a) Scalability-the ability to efficiently process increasing volumes of data; (b) Adaptability-the toolkit can be deployed across different computing configurations; and (c) Ease of programming-the toolkit can be easily used to compose multi-step data processing pipelines using high-level programming constructs. The NeuroPigPen toolkit was evaluated using 750 GB of electrophysiological signal data over a variety of Hadoop cluster configurations ranging from 3 to 30 Data nodes. The evaluation results demonstrate that the toolkit is highly scalable and adaptable, which makes it suitable for use in neuroscience applications as a scalable data processing toolkit. As part of the ongoing extension of NeuroPigPen, we are developing new modules to support statistical functions to analyze signal data for brain connectivity research. In addition, the toolkit is being extended to allow integration with scientific workflow systems. NeuroPigPen is released under BSD license at: https://sites.google.com/a/case.edu/neuropigpen/.

Time-frequency signal analysis and synthesis - The choice of a method and its application

NASA Astrophysics Data System (ADS)

Boashash, Boualem

In this paper, the problem of choosing a method for time-frequency signal analysis is discussed. It is shown that a natural approach leads to the introduction of the concepts of the analytic signal and instantaneous frequency. The Wigner-Ville Distribution (WVD) is a method of analysis based upon these concepts and it is shown that an accurate Time-Frequency representation of a signal can be obtained by using the WVD for the analysis of a class of signals referred to as 'asymptotic'. For this class of signals, the instantaneous frequency describes an important physical parameter characteristic of the process under investigation. The WVD procedure for signal analysis and synthesis is outlined and its properties are reviewed for deterministic and random signals.

Time-Frequency Signal Analysis And Synthesis The Choice Of A Method And Its Application

NASA Astrophysics Data System (ADS)

Boashash, Boualem

1988-02-01

In this paper, the problem of choosing a method for time-frequency signal analysis is discussed. It is shown that a natural approach leads to the introduction of the concepts of the analytic signal and in-stantaneous frequency. The Wigner-Ville Distribution (WVD) is a method of analysis based upon these concepts and it is shown that an accurate Time-Frequency representation of a signal can be obtained by using the WVD for the analysis of a class of signals referred to as "asymptotic". For this class of signals, the instantaneous frequency describes an important physical parameter characteristic of the process under investigation. The WVD procedure for signal analysis and synthesis is outlined and its properties are reviewed for deterministic and random signals.

Electron beam deflection control system of a welding and surface modification installation

NASA Astrophysics Data System (ADS)

Koleva, E.; Dzharov, V.; Gerasimov, V.; Tsvetkov, K.; Mladenov, G.

2018-03-01

In the present work, we examined the patterns of the electron beam motion when controlling the transverse with respect to the axis of the beam homogeneous magnetic field created by the coils of the deflection system the electron gun. During electron beam processes, the beam motion is determined the process type (welding, surface modification, etc.), the technological mode, the design dimensions of the electron gun and the shape of the processed samples. The electron beam motion is defined by the cumulative action of two cosine-like control signals generated by a functional generator. The signal control is related to changing the amplitudes, frequencies and phases (phase differences) of the generated voltages. We realized the motion control by applying a graphical user interface developed by us and an Arduino Uno programmable microcontroller. The signals generated were calibrated using experimental data from the available functional generator. The free and precise motion on arbitrary trajectories determines the possible applications of an electron beam process to carrying out various scientific research tasks in material processing.

The analysis of decimation and interpolation in the linear canonical transform domain.

PubMed

Xu, Shuiqing; Chai, Yi; Hu, Youqiang; Huang, Lei; Feng, Li

2016-01-01

Decimation and interpolation are the two basic building blocks in the multirate digital signal processing systems. As the linear canonical transform (LCT) has been shown to be a powerful tool for optics and signal processing, it is worthwhile and interesting to analyze the decimation and interpolation in the LCT domain. In this paper, the definition of equivalent filter in the LCT domain have been given at first. Then, by applying the definition, the direct implementation structure and polyphase networks for decimator and interpolator in the LCT domain have been proposed. Finally, the perfect reconstruction expressions for differential filters in the LCT domain have been presented as an application. The proposed theorems in this study are the bases for generalizations of the multirate signal processing in the LCT domain, which can advance the filter banks theorems in the LCT domain.

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.

Signal processing methods for in-situ creep specimen monitoring

NASA Astrophysics Data System (ADS)

Guers, Manton J.; Tittmann, Bernhard R.

2018-04-01

Previous work investigated using guided waves for monitoring creep deformation during accelerated life testing. The basic objective was to relate observed changes in the time-of-flight to changes in the environmental temperature and specimen gage length. The work presented in this paper investigated several signal processing strategies for possible application in the in-situ monitoring system. Signal processing methods for both group velocity (wave-packet envelope) and phase velocity (peak tracking) time-of-flight were considered. Although the Analytic Envelope found via the Hilbert transform is commonly applied for group velocity measurements, erratic behavior in the indicated time-of-flight was observed when this technique was applied to the in-situ data. The peak tracking strategies tested had generally linear trends, and tracking local minima in the raw waveform ultimately showed the most consistent results.

Automated speech understanding: the next generation

NASA Astrophysics Data System (ADS)

Picone, J.; Ebel, W. J.; Deshmukh, N.

1995-04-01

Modern speech understanding systems merge interdisciplinary technologies from Signal Processing, Pattern Recognition, Natural Language, and Linguistics into a unified statistical framework. These systems, which have applications in a wide range of signal processing problems, represent a revolution in Digital Signal Processing (DSP). Once a field dominated by vector-oriented processors and linear algebra-based mathematics, the current generation of DSP-based systems rely on sophisticated statistical models implemented using a complex software paradigm. Such systems are now capable of understanding continuous speech input for vocabularies of several thousand words in operational environments. The current generation of deployed systems, based on small vocabularies of isolated words, will soon be replaced by a new technology offering natural language access to vast information resources such as the Internet, and provide completely automated voice interfaces for mundane tasks such as travel planning and directory assistance.

The application of charge-coupled device processors in automatic-control systems

NASA Technical Reports Server (NTRS)

Mcvey, E. S.; Parrish, E. A., Jr.

1977-01-01

The application of charge-coupled device (CCD) processors to automatic-control systems is suggested. CCD processors are a new form of semiconductor component with the unique ability to process sampled signals on an analog basis. Specific implementations of controllers are suggested for linear time-invariant, time-varying, and nonlinear systems. Typical processing time should be only a few microseconds. This form of technology may become competitive with microprocessors and minicomputers in addition to supplementing them.

Study and application of acoustic emission testing in fault diagnosis of low-speed heavy-duty gears.

PubMed

Gao, Lixin; Zai, Fenlou; Su, Shanbin; Wang, Huaqing; Chen, Peng; Liu, Limei

2011-01-01

Most present studies on the acoustic emission signals of rotating machinery are experiment-oriented, while few of them involve on-spot applications. In this study, a method of redundant second generation wavelet transform based on the principle of interpolated subdivision was developed. With this method, subdivision was not needed during the decomposition. The lengths of approximation signals and detail signals were the same as those of original ones, so the data volume was twice that of original signals; besides, the data redundancy characteristic also guaranteed the excellent analysis effect of the method. The analysis of the acoustic emission data from the faults of on-spot low-speed heavy-duty gears validated the redundant second generation wavelet transform in the processing and denoising of acoustic emission signals. Furthermore, the analysis illustrated that the acoustic emission testing could be used in the fault diagnosis of on-spot low-speed heavy-duty gears and could be a significant supplement to vibration testing diagnosis.

Study and Application of Acoustic Emission Testing in Fault Diagnosis of Low-Speed Heavy-Duty Gears

PubMed Central

Gao, Lixin; Zai, Fenlou; Su, Shanbin; Wang, Huaqing; Chen, Peng; Liu, Limei

2011-01-01

Most present studies on the acoustic emission signals of rotating machinery are experiment-oriented, while few of them involve on-spot applications. In this study, a method of redundant second generation wavelet transform based on the principle of interpolated subdivision was developed. With this method, subdivision was not needed during the decomposition. The lengths of approximation signals and detail signals were the same as those of original ones, so the data volume was twice that of original signals; besides, the data redundancy characteristic also guaranteed the excellent analysis effect of the method. The analysis of the acoustic emission data from the faults of on-spot low-speed heavy-duty gears validated the redundant second generation wavelet transform in the processing and denoising of acoustic emission signals. Furthermore, the analysis illustrated that the acoustic emission testing could be used in the fault diagnosis of on-spot low-speed heavy-duty gears and could be a significant supplement to vibration testing diagnosis. PMID:22346592

Industrial Raman gas sensing for real-time system control

NASA Astrophysics Data System (ADS)

Buric, M.; Mullen, J.; Chorpening, B.; Woodruff, S.

2014-06-01

Opportunities exist to improve on-line process control in energy applications with a fast, non-destructive measurement of gas composition. Here, we demonstrate a Raman sensing system which is capable of reporting the concentrations of numerous species simultaneously with sub-percent accuracy and sampling times below one-second for process control applications in energy or chemical production. The sensor is based upon a hollow-core capillary waveguide with a 300 micron bore with reflective thin-film metal and dielectric linings. The effect of using such a waveguide in a Raman process is to integrate Raman photons along the length of the sample-filled waveguide, thus permitting the acquisition of very large Raman signals for low-density gases in a short time. The resultant integrated Raman signals can then be used for quick and accurate analysis of a gaseous mixture. The sensor is currently being tested for energy applications such as coal gasification, turbine control, well-head monitoring for exploration or production, and non-conventional gas utilization. In conjunction with an ongoing commercialization effort, the researchers have recently completed two prototype instruments suitable for hazardous area operation and testing. Here, we report pre-commercialization testing of those field prototypes for control applications in gasification or similar processes. Results will be discussed with respect to accuracy, calibration requirements, gas sampling techniques, and possible control strategies of industrial significance.

An experimental adaptive array to suppress weak interfering signals

NASA Technical Reports Server (NTRS)

Walton, Eric K.; Gupta, Inder J.; Ksienski, Aharon A.; Ward, James

1988-01-01

An experimental adaptive antenna system to suppress weak interfering signals is described. It is a sidelobe canceller with two auxiliary elements. Modified feedback loops are used to control the array weights. The received signals are simulated in hardware for parameter control. Digital processing is used for algorithm implementation and performance evaluation. The experimental results are presented. They show that interfering signals as much as 10 dB below the thermal noise level in the main channel are suppressed by 20-30 dB. Such a system has potential application in suppressing the interference encountered in direct broadcast satellite communication systems.

Multipath induced errors in meteorological Doppler/interferometer location systems

NASA Technical Reports Server (NTRS)

Wallace, R. G.

1984-01-01

One application of an RF interferometer aboard a low-orbiting spacecraft to determine the location of ground-based transmitters is in tracking high-altitude balloons for meteorological studies. A source of error in this application is reflection of the signal from the sea surface. Through propagating and signal analysis, the magnitude of the reflection-induced error in both Doppler frequency measurements and interferometer phase measurements was estimated. The theory of diffuse scattering from random surfaces was applied to obtain the power spectral density of the reflected signal. The processing of the combined direct and reflected signals was then analyzed to find the statistics of the measurement error. It was found that the error varies greatly during the satellite overpass and attains its maximum value at closest approach. The maximum values of interferometer phase error and Doppler frequency error found for the system configuration considered were comparable to thermal noise-induced error.

An Informative Interpretation of Decision Theory: The Information Theoretic Basis for Signal-to-Noise Ratio and Log Likelihood Ratio

DOE PAGES

Polcari, J.

2013-08-16

The signal processing concept of signal-to-noise ratio (SNR), in its role as a performance measure, is recast within the more general context of information theory, leading to a series of useful insights. Establishing generalized SNR (GSNR) as a rigorous information theoretic measure inherent in any set of observations significantly strengthens its quantitative performance pedigree while simultaneously providing a specific definition under general conditions. This directly leads to consideration of the log likelihood ratio (LLR): first, as the simplest possible information-preserving transformation (i.e., signal processing algorithm) and subsequently, as an absolute, comparable measure of information for any specific observation exemplar. Furthermore,more » the information accounting methodology that results permits practical use of both GSNR and LLR as diagnostic scalar performance measurements, directly comparable across alternative system/algorithm designs, applicable at any tap point within any processing string, in a form that is also comparable with the inherent performance bounds due to information conservation.« less

Acousto-Optic Tunable Filter for Time-Domain Processing of Ultra-Short Optical Pulses,

DTIC Science & Technology

The application of acousto - optic tunable filters for shaping of ultra-fast pulses in the time domain is analyzed and demonstrated. With the rapid...advance of acousto - optic tunable filter (AOTF) technology, the opportunity for sophisticated signal processing capabilities arises. AOTFs offer unique

76 FR 11199 - Application(s) for Duty-Free Entry of Scientific Instruments

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-01

... of the central nervous systems of freshwater prawns. Justification for Duty-Free Entry: There are no... 120 kV accelerating voltage, and an electron gun assembly with Cool Beam Illumination System--LaB6..., flexibility of software for signal acquisition and image processing, overall system stability, and ease of use...

ASIC For Complex Fixed-Point Arithmetic

NASA Technical Reports Server (NTRS)

Petilli, Stephen G.; Grimm, Michael J.; Olson, Erlend M.

1995-01-01

Application-specific integrated circuit (ASIC) performs 24-bit, fixed-point arithmetic operations on arrays of complex-valued input data. High-performance, wide-band arithmetic logic unit (ALU) designed for use in computing fast Fourier transforms (FFTs) and for performing ditigal filtering functions. Other applications include general computations involved in analysis of spectra and digital signal processing.

An Energy Efficient ECG Signal Processor Detecting Cardiovascular Diseases on Smartphone.

PubMed

Jain, Sanjeev Kumar; Bhaumik, Basabi

2017-04-01

A novel disease diagnostic algorithm for ECG signal processing based on forward search is implemented in Application Specific Integrated Circuit (ASIC) for cardiovascular disease diagnosis on smartphone. An ASIC is fabricated using 130-nm CMOS low leakage process technology. The area of our PQRST ASIC is 1.21 mm 2 . The energy dissipation of PQRST ASIC is 96 pJ with a supply voltage of 0.9 V. The outputs from the ASIC are fed to an Android application that generates diagnostic report and can be sent to a cardiologist via email. The ASIC and Android application are verified for the detection of bundle branch block, hypertrophy, arrhythmia and myocardial infarction using Physionet PTB diagnostic ECG database. The failed detection rate is 0.69%, 0.69%, 0.34% and 1.72% for bundle branch block, hypertrophy, arrhythmia and myocardial infarction respectively. The AV block is detected in all the three patients in the Physionet St. Petersburg arrhythmia database. Our proposed ASIC together with our Android application is the most suitable for an energy efficient wearable cardiovascular disease detection system.

Application of temporal moments and other signal processing algorithms to analysis of ultrasonic signals through melting wax

DOE PAGES

Lau, Sarah J.; Moore, David G.; Stair, Sarah L.; ...

2016-01-01

Ultrasonic analysis is being explored as a way to capture events during melting of highly dispersive wax. Typical events include temperature changes in the material, phase transition of the material, surface flows and reformations, and void filling as the material melts. Melt tests are performed with wax to evaluate the usefulness of different signal processing algorithms in capturing event data. Several algorithm paths are being pursued. The first looks at changes in the velocity of the signal through the material. This is only appropriate when the changes from one ultrasonic signal to the next can be represented by a linearmore » relationship, which is not always the case. The second tracks changes in the frequency content of the signal. The third algorithm tracks changes in the temporal moments of a signal over a full test. This method does not require that the changes in the signal be represented by a linear relationship, but attaching changes in the temporal moments to physical events can be difficult. This study describes the algorithm paths applied to experimental data from ultrasonic signals as wax melts and explores different ways to display the results.« less

R.F Microphotonics for NASA Space Communications Applications

NASA Technical Reports Server (NTRS)

Pouch, John; Nguyen, Hung; Lee, Richard; Miranda, Felix; Hossein-Zadeh, Mani; Cohen, David; Levi, A. F. J.

2007-01-01

An RF microphotonic receiver has-been developed at Ka-band. The receiver consists of a lithium niobate micro-disk that enables RF-optical coupling to occur. The modulated optical signal (- 200 THz) is detected by the high-speed photonic signal processing electronics. When compared with an electronic approach, the microphotonic receiver technology offers 10 times smaller volume, smaller weight, and smaller power consumption; greater sensitivity; and optical isolation for use in extreme environments. The status of the technology development will be summarized, and the potential application of the receiver to NASA space communications systems will be described.

A miniature on-chip multi-functional ECG signal processor with 30 µW ultra-low power consumption.

PubMed

Liu, Xin; Zheng, Yuan Jin; Phyu, Myint Wai; Zhao, Bin; Je, Minkyu; Yuan, Xiao Jun

2010-01-01

In this paper, a miniature low-power Electrocardiogram (ECG) signal processing application specific integrated circuit (ASIC) chip is proposed. This chip provides multiple critical functions for ECG analysis using a systematic wavelet transform algorithm and a novel SRAM-based ASIC architecture, while achieves low cost and high performance. Using 0.18 µm CMOS technology and 1 V power supply, this ASIC chip consumes only 29 µW and occupies an area of 3 mm(2). This on-chip ECG processor is highly suitable for reliable real-time cardiac status monitoring applications.

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.

IDSP- INTERACTIVE DIGITAL SIGNAL PROCESSOR

NASA Technical Reports Server (NTRS)

Mish, W. H.

1994-01-01

The Interactive Digital Signal Processor, IDSP, consists of a set of time series analysis "operators" based on the various algorithms commonly used for digital signal analysis work. The processing of a digital time series to extract information is usually achieved by the application of a number of fairly standard operations. However, it is often desirable to "experiment" with various operations and combinations of operations to explore their effect on the results. IDSP is designed to provide an interactive and easy-to-use system for this type of digital time series analysis. The IDSP operators can be applied in any sensible order (even recursively), and can be applied to single time series or to simultaneous time series. IDSP is being used extensively to process data obtained from scientific instruments onboard spacecraft. It is also an excellent teaching tool for demonstrating the application of time series operators to artificially-generated signals. IDSP currently includes over 43 standard operators. Processing operators provide for Fourier transformation operations, design and application of digital filters, and Eigenvalue analysis. Additional support operators provide for data editing, display of information, graphical output, and batch operation. User-developed operators can be easily interfaced with the system to provide for expansion and experimentation. Each operator application generates one or more output files from an input file. The processing of a file can involve many operators in a complex application. IDSP maintains historical information as an integral part of each file so that the user can display the operator history of the file at any time during an interactive analysis. IDSP is written in VAX FORTRAN 77 for interactive or batch execution and has been implemented on a DEC VAX-11/780 operating under VMS. The IDSP system generates graphics output for a variety of graphics systems. The program requires the use of Versaplot and Template plotting routines and IMSL Math/Library routines. These software packages are not included in IDSP. The virtual memory requirement for the program is approximately 2.36 MB. The IDSP system was developed in 1982 and was last updated in 1986. Versaplot is a registered trademark of Versatec Inc. Template is a registered trademark of Template Graphics Software Inc. IMSL Math/Library is a registered trademark of IMSL Inc.

Application of convolve-multiply-convolve SAW processor for satellite communications

NASA Technical Reports Server (NTRS)

Lie, Y. S.; Ching, M.

1991-01-01

There is a need for a satellite communications receiver than can perform simultaneous multi-channel processing of single channel per carrier (SCPC) signals originating from various small (mobile or fixed) earth stations. The number of ground users can be as many as 1000. Conventional techniques of simultaneously processing these signals is by employing as many RF-bandpass filters as the number of channels. Consequently, such an approach would result in a bulky receiver, which becomes impractical for satellite applications. A unique approach utilizing a realtime surface acoustic wave (SAW) chirp transform processor is presented. The application of a Convolve-Multiply-Convolve (CMC) chirp transform processor is described. The CMC processor transforms each input channel into a unique timeslot, while preserving its modulation content (in this case QPSK). Subsequently, each channel is individually demodulated without the need of input channel filters. Circuit complexity is significantly reduced, because the output frequency of the CMC processor is common for all input channel frequencies. The results of theoretical analysis and experimental results are in good agreement.

Photonics for aerospace sensors

NASA Astrophysics Data System (ADS)

Pellegrino, John; Adler, Eric D.; Filipov, Andree N.; Harrison, Lorna J.; van der Gracht, Joseph; Smith, Dale J.; Tayag, Tristan J.; Viveiros, Edward A.

1992-11-01

The maturation in the state-of-the-art of optical components is enabling increased applications for the technology. Most notable is the ever-expanding market for fiber optic data and communications links, familiar in both commercial and military markets. The inherent properties of optics and photonics, however, have suggested that components and processors may be designed that offer advantages over more commonly considered digital approaches for a variety of airborne sensor and signal processing applications. Various academic, industrial, and governmental research groups have been actively investigating and exploiting these properties of high bandwidth, large degree of parallelism in computation (e.g., processing in parallel over a two-dimensional field), and interconnectivity, and have succeeded in advancing the technology to the stage of systems demonstration. Such advantages as computational throughput and low operating power consumption are highly attractive for many computationally intensive problems. This review covers the key devices necessary for optical signal and image processors, some of the system application demonstration programs currently in progress, and active research directions for the implementation of next-generation architectures.

Mobile Cardiac Health-care Monitoring and Notification with Real Time Tachycardia and Bradycardia Arrhythmia Detection.

PubMed

Golzar, Mina; Fotouhi-Ghazvini, Faranak; Rabbani, Hossein; Zakeri, Fahimeh Sadat

2017-01-01

The increasing trend of heart disease has turned the attention of researchers toward the use of portable connected technologies. The necessity of continuous special care for cardiovascular patients is an inevitable fact. In this research, a new wireless electrocardiographic (ECG) signal-monitoring system based on smartphone is presented. This system has two main sections. The first section consists of a sensor which receives ECG signals via an amplifier, then filters and digitizes the signal, and prepares it to be transmitted. The signals are stored, processed, and then displayed in a mobile application. The application alarms in dangerous situations and sends the location of the cardiac patient to family or health-care staff. The results obtained from the analysis of the electrocardiogram signals on 20 different people have been compared with the traditional ECG in hospital by a cardiologist. The signal is instantly transmitted by 200 sample per second to mobile phone. The raw data are processed, the anomaly is detected, and the signal is drawn on the interface in about 70 s. Therefore, the delay is not noticeable by the patient. With respect to rate of data transmission to hospital, different internet connections such as 2G, 3G, 4G, WiFi, WiMax, or Long-Term Evolution (LTE) could be used. Data transmission ranges from 9.6 kbps to 20 Mbps. Therefore, the physician could receive data with no delay. A performance accuracy of 91.62% is obtained from the wireless ECG system. It conforms to the hospital's diagnostic standard system while providing a portable monitoring anywhere at anytime.

Computer Music

NASA Astrophysics Data System (ADS)

Cook, Perry R.

This chapter covers algorithms, technologies, computer languages, and systems for computer music. Computer music involves the application of computers and other digital/electronic technologies to music composition, performance, theory, history, and the study of perception. The field combines digital signal processing, computational algorithms, computer languages, hardware and software systems, acoustics, psychoacoustics (low-level perception of sounds from the raw acoustic signal), and music cognition (higher-level perception of musical style, form, emotion, etc.).

A Modular Mixed Signal VLSI Design Approach for Digital Radar Applications

DTIC Science & Technology

2007-03-01

convenience, denote e−j 2π N nk by WN , so equation (2.2) becomes: X(k) = N−1∑ n=0 x(n)W knN , k = 0, 1, 2, ..., N − 1 (2.3) which can be expanded into... Speech , and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on, 3, 1994. 18. Soliman, Samir S. and Mandyam D. Srinath

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.

The Roadmaker's algorithm for the discrete pulse transform.

PubMed

Laurie, Dirk P

2011-02-01

The discrete pulse transform (DPT) is a decomposition of an observed signal into a sum of pulses, i.e., signals that are constant on a connected set and zero elsewhere. Originally developed for 1-D signal processing, the DPT has recently been generalized to more dimensions. Applications in image processing are currently being investigated. The time required to compute the DPT as originally defined via the successive application of LULU operators (members of a class of minimax filters studied by Rohwer) has been a severe drawback to its applicability. This paper introduces a fast method for obtaining such a decomposition, called the Roadmaker's algorithm because it involves filling pits and razing bumps. It acts selectively only on those features actually present in the signal, flattening them in order of increasing size by subtracing an appropriate positive or negative pulse, which is then appended to the decomposition. The implementation described here covers 1-D signal as well as two and 3-D image processing in a single framework. This is achieved by considering the signal or image as a function defined on a graph, with the geometry specified by the edges of the graph. Whenever a feature is flattened, nodes in the graph are merged, until eventually only one node remains. At that stage, a new set of edges for the same nodes as the graph, forming a tree structure, defines the obtained decomposition. The Roadmaker's algorithm is shown to be equivalent to the DPT in the sense of obtaining the same decomposition. However, its simpler operators are not in general equivalent to the LULU operators in situations where those operators are not applied successively. A by-product of the Roadmaker's algorithm is that it yields a proof of the so-called Highlight Conjecture, stated as an open problem in 2006. We pay particular attention to algorithmic details and complexity, including a demonstration that in the 1-D case, and also in the case of a complete graph, the Roadmaker's algorithm has optimal complexity: it runs in time O(m), where m is the number of arcs in the graph.

Seismic data fusion anomaly detection

NASA Astrophysics Data System (ADS)

Harrity, Kyle; Blasch, Erik; Alford, Mark; Ezekiel, Soundararajan; Ferris, David

2014-06-01

Detecting anomalies in non-stationary signals has valuable applications in many fields including medicine and meteorology. These include uses such as identifying possible heart conditions from an Electrocardiography (ECG) signals or predicting earthquakes via seismographic data. Over the many choices of anomaly detection algorithms, it is important to compare possible methods. In this paper, we examine and compare two approaches to anomaly detection and see how data fusion methods may improve performance. The first approach involves using an artificial neural network (ANN) to detect anomalies in a wavelet de-noised signal. The other method uses a perspective neural network (PNN) to analyze an arbitrary number of "perspectives" or transformations of the observed signal for anomalies. Possible perspectives may include wavelet de-noising, Fourier transform, peak-filtering, etc.. In order to evaluate these techniques via signal fusion metrics, we must apply signal preprocessing techniques such as de-noising methods to the original signal and then use a neural network to find anomalies in the generated signal. From this secondary result it is possible to use data fusion techniques that can be evaluated via existing data fusion metrics for single and multiple perspectives. The result will show which anomaly detection method, according to the metrics, is better suited overall for anomaly detection applications. The method used in this study could be applied to compare other signal processing algorithms.

Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning

NASA Astrophysics Data System (ADS)

García Plaza, E.; Núñez López, P. J.

2018-01-01

On-line monitoring of surface finish in machining processes has proven to be a substantial advancement over traditional post-process quality control techniques by reducing inspection times and costs and by avoiding the manufacture of defective products. This study applied techniques for processing cutting force signals based on the wavelet packet transform (WPT) method for the monitoring of surface finish in computer numerical control (CNC) turning operations. The behaviour of 40 mother wavelets was analysed using three techniques: global packet analysis (G-WPT), and the application of two packet reduction criteria: maximum energy (E-WPT) and maximum entropy (SE-WPT). The optimum signal decomposition level (Lj) was determined to eliminate noise and to obtain information correlated to surface finish. The results obtained with the G-WPT method provided an in-depth analysis of cutting force signals, and frequency ranges and signal characteristics were correlated to surface finish with excellent results in the accuracy and reliability of the predictive models. The radial and tangential cutting force components at low frequency provided most of the information for the monitoring of surface finish. The E-WPT and SE-WPT packet reduction criteria substantially reduced signal processing time, but at the expense of discarding packets with relevant information, which impoverished the results. The G-WPT method was observed to be an ideal procedure for processing cutting force signals applied to the real-time monitoring of surface finish, and was estimated to be highly accurate and reliable at a low analytical-computational cost.

Reprint of Design of synthetic microbial communities for biotechnological production processes.

PubMed

Jagmann, Nina; Philipp, Bodo

2014-12-20

In their natural habitats microorganisms live in multi-species communities, in which the community members exhibit complex metabolic interactions. In contrast, biotechnological production processes catalyzed by microorganisms are usually carried out with single strains in pure cultures. A number of production processes, however, may be more efficiently catalyzed by the concerted action of microbial communities. This review will give an overview of organismic interactions between microbial cells and of biotechnological applications of microbial communities. It focuses on synthetic microbial communities that consist of microorganisms that have been genetically engineered. Design principles for such synthetic communities will be exemplified based on plausible scenarios for biotechnological production processes. These design principles comprise interspecific metabolic interactions via cross-feeding, regulation by interspecific signaling processes via metabolites and autoinducing signal molecules, and spatial structuring of synthetic microbial communities. In particular, the implementation of metabolic interdependencies, of positive feedback regulation and of inducible cell aggregation and biofilm formation will be outlined. Synthetic microbial communities constitute a viable extension of the biotechnological application of metabolically engineered single strains and enlarge the scope of microbial production processes. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantitative analysis of phosphoinositide 3-kinase (PI3K) signaling using live-cell total internal reflection fluorescence (TIRF) microscopy.

PubMed

Johnson, Heath E; Haugh, Jason M

2013-12-02

This unit focuses on the use of total internal reflection fluorescence (TIRF) microscopy and image analysis methods to study the dynamics of signal transduction mediated by class I phosphoinositide 3-kinases (PI3Ks) in mammalian cells. The first four protocols cover live-cell imaging experiments, image acquisition parameters, and basic image processing and segmentation. These methods are generally applicable to live-cell TIRF experiments. The remaining protocols outline more advanced image analysis methods, which were developed in our laboratory for the purpose of characterizing the spatiotemporal dynamics of PI3K signaling. These methods may be extended to analyze other cellular processes monitored using fluorescent biosensors. Copyright © 2013 John Wiley & Sons, Inc.

Stimulation-evoked Ca2+ signals in astrocytic processes at hippocampal CA3-CA1 synapses of adult mice are modulated by glutamate and ATP.

PubMed

Tang, Wannan; Szokol, Karolina; Jensen, Vidar; Enger, Rune; Trivedi, Chintan A; Hvalby, Øivind; Helm, P Johannes; Looger, Loren L; Sprengel, Rolf; Nagelhus, Erlend A

2015-02-18

To date, it has been difficult to reveal physiological Ca(2+) events occurring within the fine astrocytic processes of mature animals. The objective of the study was to explore whether neuronal activity evokes astrocytic Ca(2+) signals at glutamatergic synapses of adult mice. We stimulated the Schaffer collateral/commissural fibers in acute hippocampal slices from adult mice transduced with the genetically encoded Ca(2+) indicator GCaMP5E driven by the glial fibrillary acidic protein promoter. Two-photon imaging revealed global stimulation-evoked astrocytic Ca(2+) signals with distinct latencies, rise rates, and amplitudes in fine processes and somata. Specifically, the Ca(2+) signals in the processes were faster and of higher amplitude than those in the somata. A combination of P2 purinergic and group I/II metabotropic glutamate receptor (mGluR) antagonists reduced the amplitude of the Ca(2+) transients by 30-40% in both astrocytic compartments. Blockage of the mGluRs alone only modestly reduced the magnitude of the stimulation-evoked Ca(2+) signals in processes and failed to affect the somatic Ca(2+) response. Local application of group I or I/II mGluR agonists or adenosine triphosphate (ATP) elicited global astrocytic Ca(2+) signals that mimicked the stimulation-evoked astrocytic Ca(2+) responses. We conclude that stimulation-evoked Ca(2+) signals in astrocytic processes at CA3-CA1 synapses of adult mice (1) differ from those in astrocytic somata and (2) are modulated by glutamate and ATP. Copyright © 2015 the authors 0270-6474/15/353016-06$15.00/0.

Redox Signaling Mechanisms in Nervous System Development.

PubMed

Olguín-Albuerne, Mauricio; Morán, Julio

2018-06-20

Numerous studies have demonstrated the actions of reactive oxygen species (ROS) as regulators of several physiological processes. In this study, we discuss how redox signaling mechanisms operate to control different processes such as neuronal differentiation, oligodendrocyte differentiation, dendritic growth, and axonal growth. Recent Advances: Redox homeostasis regulates the physiology of neural stem cells (NSCs). Notably, the neuronal differentiation process of NSCs is determined by a change toward oxidative metabolism, increased levels of mitochondrial ROS, increased activity of NADPH oxidase (NOX) enzymes, decreased levels of Nrf2, and differential regulation of different redoxins. Furthermore, during the neuronal maturation processes, NOX and MICAL produce ROS to regulate cytoskeletal dynamics, which control the dendritic and axonal growth, as well as the axonal guidance. The redox homeostasis changes are, in part, attributed to cell metabolism and compartmentalized production of ROS, which is regulated, sensed, and transduced by different molecules such as thioredoxins, glutaredoxins, peroxiredoxins, and nucleoredoxin to control different signaling pathways in different subcellular regions. The study of how these elements cooperatively act is essential for the understanding of nervous system development, as well as the application of regenerative therapies that recapitulate these processes. The information about these topics in the last two decades leads us to the conclusion that the role of ROS signaling in development of the nervous system is more important than it was previously believed and makes clear the importance of exploring in more detail the mechanisms of redox signaling. Antioxid. Redox Signal. 28, 1603-1625.

A method for reduction of Acoustic Emission (AE) data with application in machine failure detection and diagnosis

NASA Astrophysics Data System (ADS)

Vicuña, Cristián Molina; Höweler, Christoph

2017-12-01

The use of AE in machine failure diagnosis has increased over the last years. Most AE-based failure diagnosis strategies use digital signal processing and thus require the sampling of AE signals. High sampling rates are required for this purpose (e.g. 2 MHz or higher), leading to streams of large amounts of data. This situation is aggravated if fine resolution and/or multiple sensors are required. These facts combine to produce bulky data, typically in the range of GBytes, for which sufficient storage space and efficient signal processing algorithms are required. This situation probably explains why, in practice, AE-based methods consist mostly in the calculation of scalar quantities such as RMS and Kurtosis, and the analysis of their evolution in time. While the scalar-based approach offers the advantage of maximum data reduction; it has the disadvantage that most part of the information contained in the raw AE signal is lost unrecoverably. This work presents a method offering large data reduction, while keeping the most important information conveyed by the raw AE signal, useful for failure detection and diagnosis. The proposed method consist in the construction of a synthetic, unevenly sampled signal which envelopes the AE bursts present on the raw AE signal in a triangular shape. The constructed signal - which we call TriSignal - also permits the estimation of most scalar quantities typically used for failure detection. But more importantly, it contains the information of the time of occurrence of the bursts, which is key for failure diagnosis. Lomb-Scargle normalized periodogram is used to construct the TriSignal spectrum, which reveals the frequency content of the TriSignal and provides the same information as the classic AE envelope. The paper includes application examples in planetary gearbox and low-speed rolling element bearing.

Digital algorithms for parallel pipelined single-detector homodyne fringe counting in laser interferometry

NASA Astrophysics Data System (ADS)

Rerucha, Simon; Sarbort, Martin; Hola, Miroslava; Cizek, Martin; Hucl, Vaclav; Cip, Ondrej; Lazar, Josef

2016-12-01

The homodyne detection with only a single detector represents a promising approach in the interferometric application which enables a significant reduction of the optical system complexity while preserving the fundamental resolution and dynamic range of the single frequency laser interferometers. We present the design, implementation and analysis of algorithmic methods for computational processing of the single-detector interference signal based on parallel pipelined processing suitable for real time implementation on a programmable hardware platform (e.g. the FPGA - Field Programmable Gate Arrays or the SoC - System on Chip). The algorithmic methods incorporate (a) the single detector signal (sine) scaling, filtering, demodulations and mixing necessary for the second (cosine) quadrature signal reconstruction followed by a conic section projection in Cartesian plane as well as (a) the phase unwrapping together with the goniometric and linear transformations needed for the scale linearization and periodic error correction. The digital computing scheme was designed for bandwidths up to tens of megahertz which would allow to measure the displacements at the velocities around half metre per second. The algorithmic methods were tested in real-time operation with a PC-based reference implementation that employed the advantage pipelined processing by balancing the computational load among multiple processor cores. The results indicate that the algorithmic methods are suitable for a wide range of applications [3] and that they are bringing the fringe counting interferometry closer to the industrial applications due to their optical setup simplicity and robustness, computational stability, scalability and also a cost-effectiveness.

Cubic spline interpolation with overlapped window and data reuse for on-line Hilbert Huang transform biomedical microprocessor.

PubMed

Chang, Nai-Fu; Chiang, Cheng-Yi; Chen, Tung-Chien; Chen, Liang-Gee

2011-01-01

On-chip implementation of Hilbert-Huang transform (HHT) has great impact to analyze the non-linear and non-stationary biomedical signals on wearable or implantable sensors for the real-time applications. Cubic spline interpolation (CSI) consumes the most computation in HHT, and is the key component for the HHT processor. In tradition, CSI in HHT is usually performed after the collection of a large window of signals, and the long latency violates the realtime requirement of the applications. In this work, we propose to keep processing the incoming signals on-line with small and overlapped data windows without sacrificing the interpolation accuracy. 58% multiplication and 73% division of CSI are saved after the data reuse between the data windows.

Multi-Frequency Signal Detection Based on Frequency Exchange and Re-Scaling Stochastic Resonance and Its Application to Weak Fault Diagnosis

PubMed Central

Leng, Yonggang; Fan, Shengbo

2018-01-01

Mechanical fault diagnosis usually requires not only identification of the fault characteristic frequency, but also detection of its second and/or higher harmonics. However, it is difficult to detect a multi-frequency fault signal through the existing Stochastic Resonance (SR) methods, because the characteristic frequency of the fault signal as well as its second and higher harmonics frequencies tend to be large parameters. To solve the problem, this paper proposes a multi-frequency signal detection method based on Frequency Exchange and Re-scaling Stochastic Resonance (FERSR). In the method, frequency exchange is implemented using filtering technique and Single SideBand (SSB) modulation. This new method can overcome the limitation of "sampling ratio" which is the ratio of the sampling frequency to the frequency of target signal. It also ensures that the multi-frequency target signals can be processed to meet the small-parameter conditions. Simulation results demonstrate that the method shows good performance for detecting a multi-frequency signal with low sampling ratio. Two practical cases are employed to further validate the effectiveness and applicability of this method. PMID:29693577

Adaptive Noise Suppression Using Digital Signal Processing

NASA Technical Reports Server (NTRS)

Kozel, David; Nelson, Richard

1996-01-01

A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.

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

NASA Astrophysics Data System (ADS)

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

2012-10-01

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

Dynamic control and information processing in chemical reaction systems by tuning self-organization behavior

NASA Astrophysics Data System (ADS)

Lebiedz, Dirk; Brandt-Pollmann, Ulrich

2004-09-01

Specific external control of chemical reaction systems and both dynamic control and signal processing as central functions in biochemical reaction systems are important issues of modern nonlinear science. For example nonlinear input-output behavior and its regulation are crucial for the maintainance of the life process that requires extensive communication between cells and their environment. An important question is how the dynamical behavior of biochemical systems is controlled and how they process information transmitted by incoming signals. But also from a general point of view external forcing of complex chemical reaction processes is important in many application areas ranging from chemical engineering to biomedicine. In order to study such control issues numerically, here, we choose a well characterized chemical system, the CO oxidation on Pt(110), which is interesting per se as an externally forced chemical oscillator model. We show numerically that tuning of temporal self-organization by input signals in this simple nonlinear chemical reaction exhibiting oscillatory behavior can in principle be exploited for both specific external control of dynamical system behavior and processing of complex information.

Coherent-subspace array processing based on wavelet covariance: an application to broad-band, seismo-volcanic signals

NASA Astrophysics Data System (ADS)

Saccorotti, G.; Nisii, V.; Del Pezzo, E.

2008-07-01

Long-Period (LP) and Very-Long-Period (VLP) signals are the most characteristic seismic signature of volcano dynamics, and provide important information about the physical processes occurring in magmatic and hydrothermal systems. These events are usually characterized by sharp spectral peaks, which may span several frequency decades, by emergent onsets, and by a lack of clear S-wave arrivals. These two latter features make both signal detection and location a challenging task. In this paper, we propose a processing procedure based on Continuous Wavelet Transform of multichannel, broad-band data to simultaneously solve the signal detection and location problems. Our method consists of two steps. First, we apply a frequency-dependent threshold to the estimates of the array-averaged WCO in order to locate the time-frequency regions spanned by coherent arrivals. For these data, we then use the time-series of the complex wavelet coefficients for deriving the elements of the spatial Cross-Spectral Matrix. From the eigenstructure of this matrix, we eventually estimate the kinematic signals' parameters using the MUltiple SIgnal Characterization (MUSIC) algorithm. The whole procedure greatly facilitates the detection and location of weak, broad-band signals, in turn avoiding the time-frequency resolution trade-off and frequency leakage effects which affect conventional covariance estimates based upon Windowed Fourier Transform. The method is applied to explosion signals recorded at Stromboli volcano by either a short-period, small aperture antenna, or a large-aperture, broad-band network. The LP (0.2 < T < 2s) components of the explosive signals are analysed using data from the small-aperture array and under the plane-wave assumption. In this manner, we obtain a precise time- and frequency-localization of the directional properties for waves impinging at the array. We then extend the wavefield decomposition method using a spherical wave front model, and analyse the VLP components (T > 2s) of the explosion recordings from the broad-band network. Source locations obtained this way are fully compatible with those retrieved from application of more traditional (and computationally expensive) time-domain techniques, such as the Radial Semblance method.

A Power-Efficient Bio-Potential Acquisition Device with DS-MDE Sensors for Long-Term Healthcare Monitoring Applications

PubMed Central

Chang, Chia-Lin; Chang, Chih-Wei; Huang, Hong-Yi; Hsu, Chen-Ming; Huang, Chia-Hsuan; Chiou, Jin-Chern; Luo, Ching-Hsing

2010-01-01

This work describes a power-efficient bio-potential acquisition device for long-term healthcare applications that is implemented using novel microelectromechanical dry electrodes (MDE) and a low power bio-potential processing chip. Using micromachining technology, an attempt is also made to enhance the sensing reliability and stability by fabricating a diamond-shaped MDE (DS-MDE) that has a satisfactory self-stability capability and superior electric conductivity when attached onto skin without any extra skin tissue injury technology. To acquire differential bio-potentials such as ECG signals, the proposed processing chip fabricated in a standard CMOS process has a high common mode rejection ratio (C.M.R.R.) differential amplifier and a 12-bit analog-to-digital converter (ADC). Use of the proposed system and integrate simple peripheral commercial devices can obtain the ECG signal efficiently without additional skin tissue injury and ensure continuous monitoring more than 70 hours with a 400 mAh battery. PMID:22399907

A power-efficient bio-potential acquisition device with DS-MDE sensors for long-term healthcare monitoring applications.

PubMed

Chang, Chia-Lin; Chang, Chih-Wei; Huang, Hong-Yi; Hsu, Chen-Ming; Huang, Chia-Hsuan; Chiou, Jin-Chern; Luo, Ching-Hsing

2010-01-01

This work describes a power-efficient bio-potential acquisition device for long-term healthcare applications that is implemented using novel microelectromechanical dry electrodes (MDE) and a low power bio-potential processing chip. Using micromachining technology, an attempt is also made to enhance the sensing reliability and stability by fabricating a diamond-shaped MDE (DS-MDE) that has a satisfactory self-stability capability and superior electric conductivity when attached onto skin without any extra skin tissue injury technology. To acquire differential bio-potentials such as ECG signals, the proposed processing chip fabricated in a standard CMOS process has a high common mode rejection ratio (C.M.R.R.) differential amplifier and a 12-bit analog-to-digital converter (ADC). Use of the proposed system and integrate simple peripheral commercial devices can obtain the ECG signal efficiently without additional skin tissue injury and ensure continuous monitoring more than 70 hours with a 400 mAh battery.

Implementation of Bluetooth technology in processing aspheric mirrors

NASA Astrophysics Data System (ADS)

Chen, Dong-yun; Li, Xiao-jin

2010-10-01

This paper adopts the Bluetooth wireless transmission to replace the conducting rings currently using in the active lap process to overcome the cost and abrasion problems brought by the conducting rings, which has great significance for reducing the costs of processing large aspheric mirrors. Based on the actual application requirements, Article proposes the overall program of using Bluetooth technology as data transmission, including the active lap-side and machine tool-side: In the machine tool-side, the MCU separately connects with Bluetooth module and the sensor via UART0 and UART1 serial port, and when the MCU receives the signals sending from the sensor, the MCU packs and then sends them through the Bluetooth module; while in the active lap side, the CCAL reads-out the position signals of sensor detecting in dual-port memory via one-side ports, and the other side ports connect with the MCU's high ports P4-P7, so the MCU can unpacks and stores the position signals receiving via Bluetooth module. This paper designs and implements the system's hardware circuit, and mainly introduces the ways of serial and parallel. Based upon the realized system, design the test program for the Bluetooth wireless transmission and the experiment results, in the condition of the active lap processing large aspheric mirrors, showed that Bluetooth technology can meet the requirements of practical applications.

Systems modelling methodology for the analysis of apoptosis signal transduction and cell death decisions.

PubMed

Rehm, Markus; Prehn, Jochen H M

2013-06-01

Systems biology and systems medicine, i.e. the application of systems biology in a clinical context, is becoming of increasing importance in biology, drug discovery and health care. Systems biology incorporates knowledge and methods that are applied in mathematics, physics and engineering, but may not be part of classical training in biology. We here provide an introduction to basic concepts and methods relevant to the construction and application of systems models for apoptosis research. We present the key methods relevant to the representation of biochemical processes in signal transduction models, with a particular reference to apoptotic processes. We demonstrate how such models enable a quantitative and temporal analysis of changes in molecular entities in response to an apoptosis-inducing stimulus, and provide information on cell survival and cell death decisions. We introduce methods for analyzing the spatial propagation of cell death signals, and discuss the concepts of sensitivity analyses that enable a prediction of network responses to disturbances of single or multiple parameters. Copyright © 2013 Elsevier Inc. All rights reserved.

Wavelet transform processing applied to partial discharge evaluation

NASA Astrophysics Data System (ADS)

Macedo, E. C. T.; Araújo, D. B.; da Costa, E. G.; Freire, R. C. S.; Lopes, W. T. A.; Torres, I. S. M.; de Souza Neto, J. M. R.; Bhatti, S. A.; Glover, I. A.

2012-05-01

Partial Discharge (PD) is characterized by high frequency current pulses that occur in high voltage (HV) electrical equipments originated from gas ionization process when damaged insulation is submitted to high values of electric field [1]. PD monitoring is a useful method of assessing the aging degree of the insulation, manufacturing defects or chemical/mechanical damage. Many sources of noise (e.g. radio transmissions, commutator noise from rotating machines, power electronics switching circuits, corona discharge, etc.) can directly affect the PD estimation. Among the many mathematical techniques that can be applied to de-noise PD signals, the wavelet transform is one of the most powerful. It can simultaneously supply information about the pulse occurrence, time and pulse spectrum, and also de-noise in-field measured PD signals. In this paper is described the application of wavelet transform in the suppression of the main types of noise that can affect the observation and analysis of PD signals in high voltage apparatus. In addition, is presented a study that indicates the appropriated mother-wavelet for this application based on the cross-correlation factor.

Ion-Exchanged Waveguides for Signal Processing Applications - A Novel Electrolytic Process.

DTIC Science & Technology

1987-03-07

were constructed of aluminium : the thermo- limitations in the melt are not expected to dominate couple sheath was stainless steel. the exchange rate...silver ion, D is its T, C0 , and t) with Schott 8011 glass (left) and a Fisher self-diffusion coefficient, and t is the time of diffusion. microscope

AFIT/AFOSR Workshop on the Role of Wavelets in Signal Processing Applications

DTIC Science & Technology

1992-08-28

Stein and G. Weiss, "Fourier analysis on Eucildean spaces," Princeton University Press, 1971. [V] G. Vitali, Sulla condizione di chiusura di un sistema ...present the more general framework into wavelets fit, suggesting hence companion ways of time-scale analysis for self-similar and 1/f-type processes

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.

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

PubMed

Loukas, Constantinos; Brown, Peter

2012-07-01

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

Spaceborne SAR Imaging Algorithm for Coherence Optimized.

PubMed

Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun

2016-01-01

This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application.

Spaceborne SAR Imaging Algorithm for Coherence Optimized

PubMed Central

Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun

2016-01-01

This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446

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.

Computational Nanotechnology of Molecular Materials, Electronics and Machines

NASA Technical Reports Server (NTRS)

Srivastava, D.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

This viewgraph presentation covers carbon nanotubes, their characteristics, and their potential future applications. The presentation include predictions on the development of nanostructures and their applications, the thermal characteristics of carbon nanotubes, mechano-chemical effects upon carbon nanotubes, molecular electronics, and models for possible future nanostructure devices. The presentation also proposes a neural model for signal processing.

MASTERS: A Virtual Lab on Multimedia Systems for Telecommunications, Medical, and Remote Sensing Applications

ERIC Educational Resources Information Center

Alexiadis, D. S.; Mitianoudis, N.

2013-01-01

Digital signal processing (DSP) has been an integral part of most electrical, electronic, and computer engineering curricula. The applications of DSP in multimedia (audio, image, video) storage, transmission, and analysis are also widely taught at both the undergraduate and post-graduate levels, as digital multimedia can be encountered in most…

Profile and Instrumentation Driven Methods for Embedded Signal Processing

DTIC Science & Technology

2015-01-01

applications,” Computers, IEEE Transactions on, vol. 37, no. 9, pp. 1088–1098, Sep 1988. [7] Massimo Ravasi and Marco Mattavelli, “High-level algorithmic...profiling,” in Digital Media and its Application in Museum Heritages, Second Workshop on, Dec 2007, pp. 353–358. [15] H. Hubert , B. Stabernack, and K.-I. Wels

Theory and Measurement of Signal-to-Noise Ratio in Continuous-Wave Noise Radar.

PubMed

Stec, Bronisław; Susek, Waldemar

2018-05-06

Determination of the signal power-to-noise power ratio on the input and output of reception systems is essential to the estimation of their quality and signal reception capability. This issue is especially important in the case when both signal and noise have the same characteristic as Gaussian white noise. This article considers the problem of how a signal-to-noise ratio is changed as a result of signal processing in the correlation receiver of a noise radar in order to determine the ability to detect weak features in the presence of strong clutter-type interference. These studies concern both theoretical analysis and practical measurements of a noise radar with a digital correlation receiver for 9.2 GHz bandwidth. Firstly, signals participating individually in the correlation process are defined and the terms signal and interference are ascribed to them. Further studies show that it is possible to distinguish a signal and a noise on the input and output of a correlation receiver, respectively, when all the considered noises are in the form of white noise. Considering the above, a measurement system is designed in which it is possible to represent the actual conditions of noise radar operation and power measurement of a useful noise signal and interference noise signals—in particular the power of an internal leakage signal between a transmitter and a receiver of the noise radar. The proposed measurement stands and the obtained results show that it is possible to optimize with the use of the equipment and not with the complex processing of a noise signal. The radar parameters depend on its prospective application, such as short- and medium-range radar, ground-penetrating radar, and through-the-wall detection radar.

Intelligent fiber optic sensor for solution concentration examination

NASA Astrophysics Data System (ADS)

Borecki, Michal; Kruszewski, Jerzy

2003-09-01

This paper presents the working principles of intelligent fiber-optic intensity sensor used for solution concentration examination. The sensor head is the ending of the large core polymer optical fiber. The head works on the reflection intensity basis. The reflected signal level depends on Fresnel reflection and reflection on suspended matter when the head is submersed in solution. The sensor head is mounted on a lift. For detection purposes the signal includes head submerging, submersion, emerging and emergence is measured. This way the viscosity turbidity and refraction coefficient has an effect on measured signal. The signal forthcoming from head is processed electrically in opto-electronic interface. Then it is feed to neural network. The novelty of presented sensor is implementation of neural network that works in generalization mode. The sensor resolution depends on opto-electronic signal conversion precision and neural network learning accuracy. Therefore, the number and quality of points used for learning process is very important. The example sensor application for examination of liquid soap concentration in water is presented in the paper.

Immune signaling by RIG-I-like receptors

PubMed Central

Loo, Yueh-Ming; Gale, Michael

2011-01-01

The RIG-I-like receptors (RLRs) RIG-I, MDA5, and LGP2 play a major role in pathogen sensing of RNA virus infection to initiate and modulate antiviral immunity. The RLRs detect viral RNA ligands or processed self RNA in the cytoplasm to triggers innate immunity and inflammation and to impart gene expression that serves to control infection. Importantly, RLRs cooperate in signaling crosstalk networks with Toll-like receptors and other factors to impart innate immunity and to modulate the adaptive immune response. RLR regulation occurs at a variety of levels ranging from autoregulation to ligand and co-factor interactions and post-translational modifications. Abberant RLR signaling or dysregulation of RLR expression is now implicated in the development of autoimmune diseases. Understanding the processes of RLR signaling and response will provide insights to guide RLR-targeted therapeutics for antiviral and immune modifying applications. PMID:21616437

Fast, optically controlled Kerr phase shifter for digital signal processing.

PubMed

Li, R B; Deng, L; Hagley, E W; Payne, M G; Bienfang, J C; Levine, Z H

2013-05-01

We demonstrate an optically controlled Kerr phase shifter using a room-temperature 85Rb vapor operating in a Raman gain scheme. Phase shifts from zero to π relative to an unshifted reference wave are observed, and gated operations are demonstrated. We further demonstrate the versatile digital manipulation of encoded signal light with an encoded phase-control light field using an unbalanced Mach-Zehnder interferometer. Generalizations of this scheme should be capable of full manipulation of a digitized signal field at high speed, opening the door to future applications.

Application of multirate digital filter banks to wideband all-digital phase-locked loops design

NASA Technical Reports Server (NTRS)

Sadr, Ramin; Shah, Biren; Hinedi, Sami

1993-01-01

A new class of architecture for all-digital phase-locked loops (DPLL's) is presented in this article. These architectures, referred to as parallel DPLL (PDPLL), employ multirate digital filter banks (DFB's) to track signals with a lower processing rate than the Nyquist rate, without reducing the input (Nyquist) bandwidth. The PDPLL basically trades complexity for hardware-processing speed by introducing parallel processing in the receiver. It is demonstrated here that the DPLL performance is identical to that of a PDPLL for both steady-state and transient behavior. A test signal with a time-varying Doppler characteristic is used to compare the performance of both the DPLL and the PDPLL.

Application of multirate digital filter banks to wideband all-digital phase-locked loops design

NASA Astrophysics Data System (ADS)

Sadr, Ramin; Shah, Biren; Hinedi, Sami

1993-06-01

A new class of architecture for all-digital phase-locked loops (DPLL's) is presented in this article. These architectures, referred to as parallel DPLL (PDPLL), employ multirate digital filter banks (DFB's) to track signals with a lower processing rate than the Nyquist rate, without reducing the input (Nyquist) bandwidth. The PDPLL basically trades complexity for hardware-processing speed by introducing parallel processing in the receiver. It is demonstrated here that the DPLL performance is identical to that of a PDPLL for both steady-state and transient behavior. A test signal with a time-varying Doppler characteristic is used to compare the performance of both the DPLL and the PDPLL.

Application of multirate digital filter banks to wideband all-digital phase-locked loops design

NASA Astrophysics Data System (ADS)

Sadr, R.; Shah, B.; Hinedi, S.

1992-11-01

A new class of architecture for all-digital phase-locked loops (DPLL's) is presented in this article. These architectures, referred to as parallel DPLL (PDPLL), employ multirate digital filter banks (DFB's) to track signals with a lower processing rate than the Nyquist rate, without reducing the input (Nyquist) bandwidth. The PDPLL basically trades complexity for hardware-processing speed by introducing parallel processing in the receiver. It is demonstrated here that the DPLL performance is identical to that of a PDPLL for both steady-state and transient behavior. A test signal with a time-varying Doppler characteristic is used to compare the performance of both the DPLL and the PDPLL.

Application of multirate digital filter banks to wideband all-digital phase-locked loops design

NASA Technical Reports Server (NTRS)

Sadr, R.; Shah, B.; Hinedi, S.

1992-01-01

A new class of architecture for all-digital phase-locked loops (DPLL's) is presented in this article. These architectures, referred to as parallel DPLL (PDPLL), employ multirate digital filter banks (DFB's) to track signals with a lower processing rate than the Nyquist rate, without reducing the input (Nyquist) bandwidth. The PDPLL basically trades complexity for hardware-processing speed by introducing parallel processing in the receiver. It is demonstrated here that the DPLL performance is identical to that of a PDPLL for both steady-state and transient behavior. A test signal with a time-varying Doppler characteristic is used to compare the performance of both the DPLL and the PDPLL.

Mobile Healthcare for Automatic Driving Sleep-Onset Detection Using Wavelet-Based EEG and Respiration Signals

PubMed Central

Lee, Boon-Giin; Lee, Boon-Leng; Chung, Wan-Young

2014-01-01

Driving drowsiness is a major cause of traffic accidents worldwide and has drawn the attention of researchers in recent decades. This paper presents an application for in-vehicle non-intrusive mobile-device-based automatic detection of driver sleep-onset in real time. The proposed application classifies the driving mental fatigue condition by analyzing the electroencephalogram (EEG) and respiration signals of a driver in the time and frequency domains. Our concept is heavily reliant on mobile technology, particularly remote physiological monitoring using Bluetooth. Respiratory events are gathered, and eight-channel EEG readings are captured from the frontal, central, and parietal (Fpz-Cz, Pz-Oz) regions. EEGs are preprocessed with a Butterworth bandpass filter, and features are subsequently extracted from the filtered EEG signals by employing the wavelet-packet-transform (WPT) method to categorize the signals into four frequency bands: α, β, θ, and δ. A mutual information (MI) technique selects the most descriptive features for further classification. The reduction in the number of prominent features improves the sleep-onset classification speed in the support vector machine (SVM) and results in a high sleep-onset recognition rate. Test results reveal that the combined use of the EEG and respiration signals results in 98.6% recognition accuracy. Our proposed application explores the possibility of processing long-term multi-channel signals. PMID:25264954

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.

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

PubMed

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

2007-01-01

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

High-efficiency (6 + 1) × 1 pump-signal combiner based on low-deformation and high-precision alignment fabrication

NASA Astrophysics Data System (ADS)

Zou, Shuzhen; Chen, Han; Yu, Haijuan; Sun, Jing; Zhao, Pengfei; Lin, Xuechun

2017-12-01

We demonstrate a new method for fabricating a (6 + 1) × 1 pump-signal combiner based on the reduction of signal fiber diameter by corrosion. This method avoids the mismatch loss of the splice between the signal fiber and the output fiber caused by the signal fiber taper processing. The optimum radius of the corroded signal fiber was calculated according to the analysis of the influence of the cladding thickness on the laser propagating in the fiber core. Besides, we also developed a two-step splicing method to complete the high-precision alignment between the signal fiber core and the output fiber core. A high-efficiency (6 + 1) × 1 pump-signal combiner was produced with an average pump power transmission efficiency of 98.0% and a signal power transmission efficiency of 97.7%, which is well suitable for application to high-power fiber laser system.

Integrated circuits for accurate linear analogue electric signal processing

NASA Astrophysics Data System (ADS)

Huijsing, J. H.

1981-11-01

The main lines in the design of integrated circuits for accurate analog linear electric signal processing in a frequency range including DC are investigated. A categorization of universal active electronic devices is presented on the basis of the connections of one of the terminals of the input and output ports to the common ground potential. The means for quantifying the attributes of four types of universal active electronic devices are included. The design of integrated operational voltage amplifiers (OVA) is discussed. Several important applications in the field of general instrumentation are numerically evaluated, and the design of operatinal floating amplifiers is presented.

Interpretation of interference signals in label free integrated interferometric biosensors

NASA Astrophysics Data System (ADS)

Heikkinen, Hanna; Wang, Meng; Okkonen, Matti; Hast, Jukka; Myllylä, Risto

2006-02-01

In the future fast, simple and reliable biosensors will be needed to detect various analytes from different biosamples. This is due to fact that the needs of traditional health care are changing. In the future homecare of patients and peoples' responsibility for their own health will increase. Also, different wellness applications need new parameters to be analysed, reducing costs of traditional health care, which are increasing rapidly. One fascinating and promising sensor type for these applications is an integrated optical interferometric immunosensor, which is manufactured using organic materials. The use of organic materials opens up enormous possibilities to develop different biochemical functions. In label free biosensors the measurement is based on detecting changes in refractive index, which typically are in the range of 10 -6-10 -8 [1]. In this research, theoretically generated interferograms are used to compare various signal processing methods. The goal is to develop an efficient method to analyse the interferogram. Different time domain signal processing methods are studied to determine the measuring resolution and efficiency of these methods. A low cost CCD -element is used in detecting the interferogram dynamics. It was found that in most of the signal processing methods the measuring resolution was mainly limited by pixel size. With calculation of Pearson's correlation coefficient, subpixel resolution was achieved which means that nanometer range optical path differences can be measured. This results in the refractive index resolution of the order of 10 -7.

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

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.; Kakad, Yogendra P.

2001-10-01

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

BCI2000: a general-purpose brain-computer interface (BCI) system.

PubMed

Schalk, Gerwin; McFarland, Dennis J; Hinterberger, Thilo; Birbaumer, Niels; Wolpaw, Jonathan R

2004-06-01

Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods, processing algorithms, output formats, and operating protocols. However, the typical BCI system is designed specifically for one particular BCI method and is, therefore, not suited to the systematic studies that are essential for continued progress. In response to this problem, we have developed a documented general-purpose BCI research and development platform called BCI2000. BCI2000 can incorporate alone or in combination any brain signals, signal processing methods, output devices, and operating protocols. This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BC12000 system is based upon and gives examples of successful BCI implementations using this system. To date, we have used BCI2000 to create BCI systems for a variety of brain signals, processing methods, and applications. The data show that these systems function well in online operation and that BCI2000 satisfies the stringent real-time requirements of BCI systems. By substantially reducing labor and cost, BCI2000 facilitates the implementation of different BCI systems and other psychophysiological experiments. It is available with full documentation and free of charge for research or educational purposes and is currently being used in a variety of studies by many research groups.

Subspace Dimensionality: A Tool for Automated QC in Seismic Array Processing

NASA Astrophysics Data System (ADS)

Rowe, C. A.; Stead, R. J.; Begnaud, M. L.

2013-12-01

Because of the great resolving power of seismic arrays, the application of automated processing to array data is critically important in treaty verification work. A significant problem in array analysis is the inclusion of bad sensor channels in the beamforming process. We are testing an approach to automated, on-the-fly quality control (QC) to aid in the identification of poorly performing sensor channels prior to beam-forming in routine event detection or location processing. The idea stems from methods used for large computer servers, when monitoring traffic at enormous numbers of nodes is impractical on a node-by node basis, so the dimensionality of the node traffic is instead monitoried for anomalies that could represent malware, cyber-attacks or other problems. The technique relies upon the use of subspace dimensionality or principal components of the overall system traffic. The subspace technique is not new to seismology, but its most common application has been limited to comparing waveforms to an a priori collection of templates for detecting highly similar events in a swarm or seismic cluster. In the established template application, a detector functions in a manner analogous to waveform cross-correlation, applying a statistical test to assess the similarity of the incoming data stream to known templates for events of interest. In our approach, we seek not to detect matching signals, but instead, we examine the signal subspace dimensionality in much the same way that the method addresses node traffic anomalies in large computer systems. Signal anomalies recorded on seismic arrays affect the dimensional structure of the array-wide time-series. We have shown previously that this observation is useful in identifying real seismic events, either by looking at the raw signal or derivatives thereof (entropy, kurtosis), but here we explore the effects of malfunctioning channels on the dimension of the data and its derivatives, and how to leverage this effect for identifying bad array elements through a jackknifing process to isolate the anomalous channels, so that an automated analysis system might discard them prior to FK analysis and beamforming on events of interest.

EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model.

PubMed

Menegaldo, Luciano Luporini; de Oliveira, Liliam Fernandes; Minato, Kin K

2014-04-04

This paper describes the "EMG Driven Force Estimator (EMGD-FE)", a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. An example of the application's functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues.

Adaptive Two Dimensional RLS (Recursive Least Squares) Algorithms

DTIC Science & Technology

1989-03-01

in Monterey wonderful. IX I. INTRODUCTION Adaptive algorithms have been used successfully for many years in a wide range of digital signal...SIMULATION RESULTS The 2-D FRLS algorithm was tested both on computer-generated data and on digitized images. For a baseline reference the 2-D L:rv1S...Alexander, S. T. Adaptivt Signal Processing: Theory and Applications. Springer- Verlag, New York. 1986. 7. Bellanger, Maurice G. Adaptive Digital

Noncoherent detection of periodic signals

NASA Technical Reports Server (NTRS)

Gagliardi, R. M.

1974-01-01

The optimal Bayes detector for a general periodic waveform having uniform delay and additive white Gaussian noise is examined. It is shown that the detector is much more complex than that for the well known cases of pure sine waves (i.e. classical noncoherent detection) and narrowband signals. An interpretation of the optimal processing is presented, and several implementations are discussed. The results have application to the noncoherent detection of optical square waves.

A Differential Monolithically Integrated Inductive Linear Displacement Measurement Microsystem

PubMed Central

Podhraški, Matija; Trontelj, Janez

2016-01-01

An inductive linear displacement measurement microsystem realized as a monolithic Application-Specific Integrated Circuit (ASIC) is presented. The system comprises integrated microtransformers as sensing elements, and analog front-end electronics for signal processing and demodulation, both jointly fabricated in a conventional commercially available four-metal 350-nm CMOS process. The key novelty of the presented system is its full integration, straightforward fabrication, and ease of application, requiring no external light or magnetic field source. Such systems therefore have the possibility of substituting certain conventional position encoder types. The microtransformers are excited by an AC signal in MHz range. The displacement information is modulated into the AC signal by a metal grating scale placed over the microsystem, employing a differential measurement principle. Homodyne mixing is used for the demodulation of the scale displacement information, returned by the ASIC as a DC signal in two quadrature channels allowing the determination of linear position of the target scale. The microsystem design, simulations, and characterization are presented. Various system operating conditions such as frequency, phase, target scale material and distance have been experimentally evaluated. The best results have been achieved at 4 MHz, demonstrating a linear resolution of 20 µm with steel and copper scale, having respective sensitivities of 0.71 V/mm and 0.99 V/mm. PMID:26999146

A Differential Monolithically Integrated Inductive Linear Displacement Measurement Microsystem.

PubMed

Podhraški, Matija; Trontelj, Janez

2016-03-17

An inductive linear displacement measurement microsystem realized as a monolithic Application-Specific Integrated Circuit (ASIC) is presented. The system comprises integrated microtransformers as sensing elements, and analog front-end electronics for signal processing and demodulation, both jointly fabricated in a conventional commercially available four-metal 350-nm CMOS process. The key novelty of the presented system is its full integration, straightforward fabrication, and ease of application, requiring no external light or magnetic field source. Such systems therefore have the possibility of substituting certain conventional position encoder types. The microtransformers are excited by an AC signal in MHz range. The displacement information is modulated into the AC signal by a metal grating scale placed over the microsystem, employing a differential measurement principle. Homodyne mixing is used for the demodulation of the scale displacement information, returned by the ASIC as a DC signal in two quadrature channels allowing the determination of linear position of the target scale. The microsystem design, simulations, and characterization are presented. Various system operating conditions such as frequency, phase, target scale material and distance have been experimentally evaluated. The best results have been achieved at 4 MHz, demonstrating a linear resolution of 20 µm with steel and copper scale, having respective sensitivities of 0.71 V/mm and 0.99 V/mm.

Biophysically Inspired Rational Design of Structured Chimeric Substrates for DNAzyme Cascade Engineering

PubMed Central

Lakin, Matthew R.; Brown, Carl W.; Horwitz, Eli K.; Fanning, M. Leigh; West, Hannah E.; Stefanovic, Darko; Graves, Steven W.

2014-01-01

The development of large-scale molecular computational networks is a promising approach to implementing logical decision making at the nanoscale, analogous to cellular signaling and regulatory cascades. DNA strands with catalytic activity (DNAzymes) are one means of systematically constructing molecular computation networks with inherent signal amplification. Linking multiple DNAzymes into a computational circuit requires the design of substrate molecules that allow a signal to be passed from one DNAzyme to another through programmed biochemical interactions. In this paper, we chronicle an iterative design process guided by biophysical and kinetic constraints on the desired reaction pathways and use the resulting substrate design to implement heterogeneous DNAzyme signaling cascades. A key aspect of our design process is the use of secondary structure in the substrate molecule to sequester a downstream effector sequence prior to cleavage by an upstream DNAzyme. Our goal was to develop a concrete substrate molecule design to achieve efficient signal propagation with maximal activation and minimal leakage. We have previously employed the resulting design to develop high-performance DNAzyme-based signaling systems with applications in pathogen detection and autonomous theranostics. PMID:25347066

Ridge extraction from the time-frequency representation (TFR) of signals based on an image processing approach: application to the analysis of uterine electromyogram AR TFR.

PubMed

Terrien, Jérémy; Marque, Catherine; Germain, Guy

2008-05-01

Time-frequency representations (TFRs) of signals are increasingly being used in biomedical research. Analysis of such representations is sometimes difficult, however, and is often reduced to the extraction of ridges, or local energy maxima. In this paper, we describe a new ridge extraction method based on the image processing technique of active contours or snakes. We have tested our method on several synthetic signals and for the analysis of uterine electromyogram or electrohysterogram (EHG) recorded during gestation in monkeys. We have also evaluated a postprocessing algorithm that is especially suited for EHG analysis. Parameters are evaluated on real EHG signals in different gestational periods. The presented method gives good results when applied to synthetic as well as EHG signals. We have been able to obtain smaller ridge extraction errors when compared to two other methods specially developed for EHG. The gradient vector flow (GVF) snake method, or GVF-snake method, appears to be a good ridge extraction tool, which could be used on TFR of mono or multicomponent signals with good results.

System and method of reducing motion-induced noise in the optical detection of an ultrasound signal in a moving body of material

DOEpatents

Habeger, Jr., Charles C.; LaFond, Emmanuel F.; Brodeur, Pierre; Gerhardstein, Joseph P.

2002-01-01

The present invention provides a system and method to reduce motion-induced noise in the detection of ultrasonic signals in a moving sheet or body of material. An ultrasonic signal is generated in a sheet of material and a detection laser beam is moved along the surface of the material. By moving the detection laser in the same direction as the direction of movement of the sheet of material the amount of noise induced in the detection of the ultrasonic signal is reduced. The scanner is moved at approximately the same speed as the moving material. The system and method may be used for many applications, such in a paper making process or steel making process. The detection laser may be directed by a scanner. The movement of the scanner is synchronized with the anticipated arrival of the ultrasonic signal under the scanner. A photodetector may be used to determine when a ultrasonic pulse has been directed to the moving sheet of material so that the scanner may be synchronized the anticipated arrival of the ultrasonic signal.

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

Damage localization by statistical evaluation of signal-processed mode shapes

NASA Astrophysics Data System (ADS)

Ulriksen, M. D.; Damkilde, L.

2015-07-01

Due to their inherent, ability to provide structural information on a local level, mode shapes and t.lieir derivatives are utilized extensively for structural damage identification. Typically, more or less advanced mathematical methods are implemented to identify damage-induced discontinuities in the spatial mode shape signals, hereby potentially facilitating damage detection and/or localization. However, by being based on distinguishing damage-induced discontinuities from other signal irregularities, an intrinsic deficiency in these methods is the high sensitivity towards measurement, noise. The present, article introduces a damage localization method which, compared to the conventional mode shape-based methods, has greatly enhanced robustness towards measurement, noise. The method is based on signal processing of spatial mode shapes by means of continuous wavelet, transformation (CWT) and subsequent, application of a generalized discrete Teager-Kaiser energy operator (GDTKEO) to identify damage-induced mode shape discontinuities. In order to evaluate whether the identified discontinuities are in fact, damage-induced, outlier analysis of principal components of the signal-processed mode shapes is conducted on the basis of T2-statistics. The proposed method is demonstrated in the context, of analytical work with a free-vibrating Euler-Bernoulli beam under noisy conditions.

Joint Acoustic and Modulation Frequency

NASA Astrophysics Data System (ADS)

Atlas, Les; Shamma, Shihab A.

2003-12-01

There is a considerable evidence that our perception of sound uses important features which is related to underlying signal modulations. This topic has been studied extensively via perceptual experiments, yet there are few, if any, well-developed signal processing methods which capitalize on or model these effects. We begin by summarizing evidence of the importance of modulation representations from psychophysical, physiological, and other sources. The concept of a two-dimensional joint acoustic and modulation frequency representation is proposed. A simple single sinusoidal amplitude modulator of a sinusoidal carrier is then used to illustrate properties of an unconstrained and ideal joint representation. Added constraints are required to remove or reduce undesired interference terms and to provide invertibility. It is then noted that the constraints would also apply to more general and complex cases of broader modulation and carriers. Applications in single-channel speaker separation and in audio coding are used to illustrate the applicability of this joint representation. Other applications in signal analysis and filtering are suggested.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-03-10

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

AlliedSignal driver's viewer enhancement (DVE) for paramilitary and commercial applications

NASA Astrophysics Data System (ADS)

Emanuel, Michael; Caron, Hubert; Kovacevic, Branislav; Faina-Cherkaoui, Marcela; Wrobel, Leslie; Turcotte, Gilles

1999-07-01

AlliedSignal Driver's Viewer Enhancement (DVE) system is a thermal imager using a 320 X 240 uncooled microbolometer array. This high performance system was initially developed for military combat and tactical wheeled vehicles. It features a very small sensor head remotely mounted from the display, control and processing module. The sensor head has a modular design and is being adapted to various commercial applications such as truck and car-driving aid, using specifically designed low cost optics. Tradeoffs in the system design, system features and test results are discussed in this paper. A short video shows footage of the DVE system while driving at night.

Spectrally encoded optical fibre sensor systems and their application in process control, environmental and structural monitoring

NASA Astrophysics Data System (ADS)

Willsch, Reinhardt; Ecke, Wolfgang; Schwotzer, Gunter

2005-09-01

Different types of advanced optical fibre sensor systems using similar spectral interrogation principles and potential low-cost polychromator optoelectronic signal processing instrumentation will be presented, and examples of their industrial application are demonstrated. These are such sensors as multimode fibre based humidity, temperature, and pressure sensors with extrinsic microoptical Fabry-Perot transducers for process control in gas industry, UV absorption evanescent field sensors for organic pollution monitoring in groundwater, and single mode fibre Bragg grating (FBG) multiplexed strain & vibration and temperature sensor networks for structural health monitoring applications in electric power facilities, aerospace, railways, geotechnical and civil engineering. Recent results of current investigations applying FBGs and microstructured fibres for chemical sensing will be discussed.

Advanced Signal Processing for High Temperatures Health Monitoring of Condensed Water Height in Steam Pipes

NASA Technical Reports Server (NTRS)

Lih, Shyh-Shiuh; Bar-Cohen, Yoseph; Lee, Hyeong Jae; Takano, Nobuyuki; Bao, Xiaoqi

2013-01-01

An advanced signal processing methodology is being developed to monitor the height of condensed water thru the wall of a steel pipe while operating at temperatures as high as 250deg. Using existing techniques, previous study indicated that, when the water height is low or there is disturbance in the environment, the predicted water height may not be accurate. In recent years, the use of the autocorrelation and envelope techniques in the signal processing has been demonstrated to be a very useful tool for practical applications. In this paper, various signal processing techniques including the auto correlation, Hilbert transform, and the Shannon Energy Envelope methods were studied and implemented to determine the water height in the steam pipe. The results have shown that the developed method provides a good capability for monitoring the height in the regular conditions. An alternative solution for shallow water or no water conditions based on a developed hybrid method based on Hilbert transform (HT) with a high pass filter and using the optimized windowing technique is suggested. Further development of the reported methods would provide a powerful tool for the identification of the disturbances of water height inside the pipe.

The Integration and Applications of Organic Thin Film Transistors and Ferroelectric Polymers

NASA Astrophysics Data System (ADS)

Hsu, Yu-Jen

Organic thin film transistors and ferroelectric polymer (polyvinylidene difluoride) sheet material are integrated to form various sensors for stress/strain, acoustic wave, and Infrared (heat) sensing applications. Different from silicon-based transistors, organic thin film transistors can be fabricated and processed in room-temperature and integrated with a variety of substrates. On the other hand, polyvinylidene difluoride (PVDF) exhibits ferroelectric properties that are highly useful for sensor applications. The wide frequency bandwidth (0.001 Hz to 10 GHz), vast dynamic range (100n to 10M psi), and high elastic compliance (up to 3 percent) make PVDF a more suitable candidate over ceramic piezoelectric materials for thin and flexible sensor applications. However, the low Curie temperature may have impeded its integration with silicon technology. Organic thin film transistors, however, do not have the limitation of processing temperature, hence can serve as transimpedance amplifiers to convert the charge signal generated by PVDF into current signal that are more measurable and less affected by any downstream parasitics. Piezoelectric sensors are useful for a range of applications, but passive arrays suffer from crosstalk and signal attenuation which have complicated the development of array-based PVDF sensors. We have used organic field effect transistors, which are compatible with the low Curie temperature of a flexible piezoelectric polymer,PVDF, to monolithically fabricate transimpedance amplifiers directly on the sensor surface and convert the piezoelectric charge signal into a current signal which can be detected even in the presence of parasitic capacitances. The device couples the voltage generated by the PVDF film under strain into the gate of the organic thin film transistors (OFET) using an arrangement that allows the full piezoelectric voltage to couple to the channel, while also increasing the charge retention time. A bipolar detector is created by using a UV-Ozone treatment to shift the threshold voltage and increase the current of the transistor under both compressive and tensile strain. An array of strain sensors which maps the strain field on a PVDF film surface is demonstrated in this work. The strain sensor experience inspires a tone analyzer built using distributed resonator architecture on a tensioned piezoelectric PVDF sheet. This sheet is used as both the resonator and detection element. Two architectures are demonstrated; one uses distributed directly addressed elements as a proof of concept, and the other integrates organic thin film transistor-based transimpedance amplifiers monolithically with the PVDF sheet to convert the piezoelectric charge signal into a current signal for future applications such as sound field imaging. The PVDF sheet material is instrumented along its length and the amplitude response at 15 sites is recorded and analyzed as a function of the frequency of excitation. The determination of the dominant frequency component of an incoming sound is demonstrated using linear system decomposition of the time-averaged response of the sheet using no time domain detection. Our design allows for the determination of the spectral composition of a sound using the mechanical signal processing provided by the amplitude response and eliminates the need for time-domain electronic signal processing of the incoming signal. The concepts of the PVDF strain sensor and the tone analyzer trigger the idea of an active matrix microphone through the integration of organic thin film transistors with a freestanding piezoelectric polymer sheet. Localized acoustic pressure detection is enabled by switch transistors and local transimpedance amplification built into the active matrix architecture. The frequency of detection ranges from DC to 15KHz; the bandwidth is extended using an architecture that provides for virtually zero gate/source and gate/drain capacitance at the sensing transistors and low overlap capacitance at the switch transistors. A series of measurements are taken to demonstrate localized acoustic wave detection, high pitch sound diffraction pattern mapping, and directional listening. This system permits the direct visualization of a two dimensional sound field in a format that was previously inaccessible. In addition to the piezoelectric property, pyroelectricity is also exhibited by PVDF and is essential in the world of sensors. An integration of PVDF and OFET for the IR heat sensing is demonstrated to prove the concept of converting pyroelectric charge signal to a electric current signal. The basic pyroelectricity of PVDF sheet is first examined before making a organic transistor integrated IR sensor. Then, two types of architectures are designed and tested. The first one uses the structure similar to the PVDF strain sensor, and the second one uses a PVDF capacitor to gate the integrated OFETs. The conversion from pyroelectric signal to transistor current signal is observed and characterized. This design provides a flexible and gain-tunable version for IR heat sensors.

Application of EOF/PCA-based methods in the post-processing of GRACE derived water variations

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen

2010-05-01

Two problems that users of monthly GRACE gravity field solutions face are 1) the presence of correlated noise in the Stokes coefficients that increases with harmonic degree and causes ‘striping', and 2) the fact that different physical signals are overlaid and difficult to separate from each other in the data. These problems are termed the signal-noise separation problem and the signal-signal separation problem. Methods that are based on principal component analysis and empirical orthogonal functions (PCA/EOF) have been frequently proposed to deal with these problems for GRACE. However, different strategies have been applied to different (spatial: global/regional, spectral: global/order-wise, geoid/equivalent water height) representations of the GRACE level 2 data products, leading to differing results and a general feeling that PCA/EOF-based methods are to be applied ‘with care'. In addition, it is known that conventional EOF/PCA methods force separated modes to be orthogonal, and that, on the other hand, to either EOFs or PCs an arbitrary orthogonal rotation can be applied. The aim of this paper is to provide a common theoretical framework and to study the application of PCA/EOF-based methods as a signal separation tool due to post-process GRACE data products. In order to investigate and illustrate the applicability of PCA/EOF-based methods, we have employed them on GRACE level 2 monthly solutions based on the Center for Space Research, University of Texas (CSR/UT) RL04 products and on the ITG-GRACE03 solutions from the University of Bonn, and on various representations of them. Our results show that EOF modes do reveal the dominating annual, semiannual and also long-periodic signals in the global water storage variations, but they also show how choosing different strategies changes the outcome and may lead to unexpected results.

Chemical modulation of glycerolipid signaling and metabolic pathways

PubMed Central

Scott, Sarah A.; Mathews, Thomas P.; Ivanova, Pavlina T.; Lindsley, Craig W.; Brown, H. Alex

2014-01-01

Thirty years ago, glycerolipids captured the attention of biochemical researchers as novel cellular signaling entities. We now recognize that these biomolecules occupy signaling nodes critical to a number of physiological and pathological processes. Thus, glycerolipid-metabolizing enzymes present attractive targets for new therapies. A number of fields—ranging from neuroscience and cancer to diabetes and obesity—have elucidated the signaling properties of glycerolipids. The biochemical literature teems with newly emerging small molecule inhibitors capable of manipulating glycerolipid metabolism and signaling. This ever-expanding pool of chemical modulators appears daunting to those interested in exploiting glycerolipid-signaling pathways in their model system of choice. This review distills the current body of literature surrounding glycerolipid metabolism into a more approachable format, facilitating the application of small molecule inhibitors to novel systems. PMID:24440821

Nonparametric Signal Extraction and Measurement Error in the Analysis of Electroencephalographic Activity During Sleep

PubMed Central

Crainiceanu, Ciprian M.; Caffo, Brian S.; Di, Chong-Zhi; Punjabi, Naresh M.

2009-01-01

We introduce methods for signal and associated variability estimation based on hierarchical nonparametric smoothing with application to the Sleep Heart Health Study (SHHS). SHHS is the largest electroencephalographic (EEG) collection of sleep-related data, which contains, at each visit, two quasi-continuous EEG signals for each subject. The signal features extracted from EEG data are then used in second level analyses to investigate the relation between health, behavioral, or biometric outcomes and sleep. Using subject specific signals estimated with known variability in a second level regression becomes a nonstandard measurement error problem. We propose and implement methods that take into account cross-sectional and longitudinal measurement error. The research presented here forms the basis for EEG signal processing for the SHHS. PMID:20057925

Encoder fault analysis system based on Moire fringe error signal

NASA Astrophysics Data System (ADS)

Gao, Xu; Chen, Wei; Wan, Qiu-hua; Lu, Xin-ran; Xie, Chun-yu

2018-02-01

Aiming at the problem of any fault and wrong code in the practical application of photoelectric shaft encoder, a fast and accurate encoder fault analysis system is researched from the aspect of Moire fringe photoelectric signal processing. DSP28335 is selected as the core processor and high speed serial A/D converter acquisition card is used. And temperature measuring circuit using AD7420 is designed. Discrete data of Moire fringe error signal is collected at different temperatures and it is sent to the host computer through wireless transmission. The error signal quality index and fault type is displayed on the host computer based on the error signal identification method. The error signal quality can be used to diagnosis the state of error code through the human-machine interface.

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.

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

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.

Acoustic Signal Processing in Photorefractive Optical Systems.

NASA Astrophysics Data System (ADS)

Zhou, Gan

This thesis discusses applications of the photorefractive effect in the context of acoustic signal processing. The devices and systems presented here illustrate the ideas and optical principles involved in holographic processing of acoustic information. The interest in optical processing stems from the similarities between holographic optical systems and contemporary models for massively parallel computation, in particular, neural networks. An initial step in acoustic processing is the transformation of acoustic signals into relevant optical forms. A fiber-optic transducer with photorefractive readout transforms acoustic signals into optical images corresponding to their short-time spectrum. The device analyzes complex sound signals and interfaces them with conventional optical correlators. The transducer consists of 130 multimode optical fibers sampling the spectral range of 100 Hz to 5 kHz logarithmically. A physical model of the human cochlea can help us understand some characteristics of human acoustic transduction and signal representation. We construct a life-sized cochlear model using elastic membranes coupled with two fluid-filled chambers, and use a photorefractive novelty filter to investigate its response. The detection sensitivity is determined to be 0.3 angstroms per root Hz at 2 kHz. Qualitative agreement is found between the model response and physiological data. Delay lines map time-domain signals into space -domain and permit holographic processing of temporal information. A parallel optical delay line using dynamic beam coupling in a rotating photorefractive crystal is presented. We experimentally demonstrate a 64 channel device with 0.5 seconds of time-delay and 167 Hz bandwidth. Acoustic signal recognition is described in a photorefractive system implementing the time-delay neural network model. The system consists of a photorefractive optical delay-line and a holographic correlator programmed in a LiNbO_3 crystal. We demonstrate the recognition of synthesized chirps as well as spoken words. A photorefractive ring resonator containing an optical delay line can learn temporal information through self-organization. We experimentally investigate a system that learns by itself and picks out the most-frequently -presented signals from the input. We also give results demonstrating the separation of two orthogonal temporal signals into two competing ring resonators.

Mobile Cardiac Health-care Monitoring and Notification with Real Time Tachycardia and Bradycardia Arrhythmia Detection

PubMed Central

Golzar, Mina; Fotouhi-Ghazvini, Faranak; Rabbani, Hossein; Zakeri, Fahimeh Sadat

2017-01-01

Background: The increasing trend of heart disease has turned the attention of researchers toward the use of portable connected technologies. The necessity of continuous special care for cardiovascular patients is an inevitable fact. Methods: In this research, a new wireless electrocardiographic (ECG) signal-monitoring system based on smartphone is presented. This system has two main sections. The first section consists of a sensor which receives ECG signals via an amplifier, then filters and digitizes the signal, and prepares it to be transmitted. The signals are stored, processed, and then displayed in a mobile application. The application alarms in dangerous situations and sends the location of the cardiac patient to family or health-care staff. Results: The results obtained from the analysis of the electrocardiogram signals on 20 different people have been compared with the traditional ECG in hospital by a cardiologist. The signal is instantly transmitted by 200 sample per second to mobile phone. The raw data are processed, the anomaly is detected, and the signal is drawn on the interface in about 70 s. Therefore, the delay is not noticeable by the patient. With respect to rate of data transmission to hospital, different internet connections such as 2G, 3G, 4G, WiFi, WiMax, or Long-Term Evolution (LTE) could be used. Data transmission ranges from 9.6 kbps to 20 Mbps. Therefore, the physician could receive data with no delay. Conclusions: A performance accuracy of 91.62% is obtained from the wireless ECG system. It conforms to the hospital's diagnostic standard system while providing a portable monitoring anywhere at anytime. PMID:29204376

Sensor/amplifier for weak light sources

NASA Technical Reports Server (NTRS)

Desmet, D. J.; Jason, A. J.; Parr, A. C.

1980-01-01

Light sensor/amplifier circuit detects weak light converts it into strong electrical signal in electrically noisy environment. Circuit is relatively simple and uses inexpensive, readily available components. Device is useful in such applications as fire detection and photographic processing.

Solution-Processed Flexible Organic Ferroelectric Phototransistor.

PubMed

Zhao, Qiang; Wang, Hanlin; Jiang, Lang; Zhen, Yonggang; Dong, Huanli; Hu, Wenping

2017-12-20

In this article, we demonstrate ferroelectric insulator, P(VDF-TrFE), can be integrated with red light sensitive polymeric semiconductor, P(DPP-TzBT), toward ferroelectric organic phototransistors (OPTs). This ferroelectricity-modulated phototransistor possesses different nonvolatile and tunable dark current states due to P(VDF-TrFE)'s remnant polarization. As a result, the OPT is endowed with a tunable dark current level ranging from 1 nA to 100 nA. Once the OPT is programmed or electrically polarized, its photo-to-dark (signal-to-noise) ratio can be "flexible" during photodetection process, without gate bias application. This kind of organic ferroelectric phototransistor has great potential in detecting wide ranges of light signals with good linearity. Moreover, its tuning mechanism discussed in this work can be helpful to understand the operation mechanism of organic phototransistor (OPT). It can be promising for novel photodetection application in plastic electronic devices.

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

PubMed

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

2015-12-14

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

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.

Remote Whispering Applying Time Reversal

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

Anderson, Brian Eric

The purpose of this project was to explore the use of time reversal technologies as a means for communication to a targeted individual or location. The idea is to have the privacy of whispering in one’s ear, but to do this remotely from loudspeakers not located near the target. Applications of this work include communicating with hostages and survivors in rescue operations, communicating imaging and operational conditions in deep drilling operations, monitoring storage of spent nuclear fuel in storage casks without wires, or clandestine activities requiring signaling between specific points. This technology provides a solution in any application where wiresmore » and radio communications are not possible or not desired. It also may be configured to self calibrate on a regular basis to adjust for changing conditions. These communications allow two people to converse with one another in real time, converse in an inaudible frequency range or medium (i.e. using ultrasonic frequencies and/or sending vibrations through a structure), or send information for a system to interpret (even allowing remote control of a system using sound). The time reversal process allows one to focus energy to a specific location in space and to send a clean transmission of a selected signal only to that location. In order for the time reversal process to work, a calibration signal must be obtained. This signal may be obtained experimentally using an impulsive sound, a known chirp signal, or other known signals. It may also be determined from a numerical model of a known environment in which the focusing is desired or from passive listening over time to ambient noise.« less

Digital approach to stabilizing optical frequency combs and beat notes of CW lasers

NASA Astrophysics Data System (ADS)

Čížek, Martin; Číp, Ondřej; Å míd, Radek; Hrabina, Jan; Mikel, Břetislav; Lazar, Josef

2013-10-01

In cases when it is necessary to lock optical frequencies generated by an optical frequency comb to a precise radio frequency (RF) standard (GPS-disciplined oscillator, H-maser, etc.) the usual practice is to implement phase and frequency-locked loops. Such system takes the signal generated by the RF standard (usually 10 MHz or 100 MHz) as a reference and stabilizes the repetition and offset frequencies of the comb contained in the RF output of the f-2f interferometer. These control loops are usually built around analog electronic circuits processing the output signals from photo detectors. This results in transferring the stability of the standard from RF to optical frequency domain. The presented work describes a different approach based on digital signal processing and software-defined radio algorithms used for processing the f-2f and beat-note signals. Several applications of digital phase and frequency locks to a RF standard are demonstrated: the repetition (frep) and offset frequency (fceo) of the comb, and the frequency of the beat note between a CW laser source and a single component of the optical frequency comb spectrum.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

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.

Optical fiber sensor technique for strain measurement

DOEpatents

Butler, Michael A.; Ginley, David S.

1989-01-01

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

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

NASA Astrophysics Data System (ADS)

Patanè, Domenico; Ferrari, Ferruccio

1997-11-01

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

Bacterial signaling ecology and potential applications during aquatic biofilm construction.

PubMed

Vega, Leticia M; Alvarez, Pedro J; McLean, Robert J C

2014-07-01

In their natural environment, bacteria and other microorganisms typically grow as surface-adherent biofilm communities. Cell signal processes, including quorum signaling, are now recognized as being intimately involved in the development and function of biofilms. In contrast to their planktonic (unattached) counterparts, bacteria within biofilms are notoriously resistant to many traditional antimicrobial agents and so represent a major challenge in industry and medicine. Although biofilms impact many human activities, they actually represent an ancient mode of bacterial growth as shown in the fossil record. Consequently, many aquatic organisms have evolved strategies involving signal manipulation to control or co-exist with biofilms. Here, we review the chemical ecology of biofilms and propose mechanisms whereby signal manipulation can be used to promote or control biofilms.

What does voice-processing technology support today?

PubMed Central

Nakatsu, R; Suzuki, Y

1995-01-01

This paper describes the state of the art in applications of voice-processing technologies. In the first part, technologies concerning the implementation of speech recognition and synthesis algorithms are described. Hardware technologies such as microprocessors and DSPs (digital signal processors) are discussed. Software development environment, which is a key technology in developing applications software, ranging from DSP software to support software also is described. In the second part, the state of the art of algorithms from the standpoint of applications is discussed. Several issues concerning evaluation of speech recognition/synthesis algorithms are covered, as well as issues concerning the robustness of algorithms in adverse conditions. Images Fig. 3 PMID:7479720

A mobile ferromagnetic shape detection sensor using a Hall sensor array and magnetic imaging.

PubMed

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a mobile Hall sensor array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the mobile Hall sensor array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of mobile Hall sensor array system for actual shape detection. The results prove that the mobile Hall sensor array system is able to perform magnetic imaging in identifying various ferromagnetic materials.

A Mobile Ferromagnetic Shape Detection Sensor Using a Hall Sensor Array and Magnetic Imaging

PubMed Central

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a Mobile Hall Sensor Array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the Mobile Hall Sensor Array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of Mobile Hall Sensor Array system for actual shape detection. The results prove that the Mobile Hall Sensor Array system is able to perform magnetic imaging in identifying various ferromagnetic materials. PMID:22346653

High Frequency Sampling of TTL Pulses on a Raspberry Pi for Diffuse Correlation Spectroscopy Applications.

PubMed

Tivnan, Matthew; Gurjar, Rajan; Wolf, David E; Vishwanath, Karthik

2015-08-12

Diffuse Correlation Spectroscopy (DCS) is a well-established optical technique that has been used for non-invasive measurement of blood flow in tissues. Instrumentation for DCS includes a correlation device that computes the temporal intensity autocorrelation of a coherent laser source after it has undergone diffuse scattering through a turbid medium. Typically, the signal acquisition and its autocorrelation are performed by a correlation board. These boards have dedicated hardware to acquire and compute intensity autocorrelations of rapidly varying input signal and usually are quite expensive. Here we show that a Raspberry Pi minicomputer can acquire and store a rapidly varying time-signal with high fidelity. We show that this signal collected by a Raspberry Pi device can be processed numerically to yield intensity autocorrelations well suited for DCS applications. DCS measurements made using the Raspberry Pi device were compared to those acquired using a commercial hardware autocorrelation board to investigate the stability, performance, and accuracy of the data acquired in controlled experiments. This paper represents a first step toward lowering the instrumentation cost of a DCS system and may offer the potential to make DCS become more widely used in biomedical applications.

High Frequency Sampling of TTL Pulses on a Raspberry Pi for Diffuse Correlation Spectroscopy Applications

PubMed Central

Tivnan, Matthew; Gurjar, Rajan; Wolf, David E.; Vishwanath, Karthik

2015-01-01

Diffuse Correlation Spectroscopy (DCS) is a well-established optical technique that has been used for non-invasive measurement of blood flow in tissues. Instrumentation for DCS includes a correlation device that computes the temporal intensity autocorrelation of a coherent laser source after it has undergone diffuse scattering through a turbid medium. Typically, the signal acquisition and its autocorrelation are performed by a correlation board. These boards have dedicated hardware to acquire and compute intensity autocorrelations of rapidly varying input signal and usually are quite expensive. Here we show that a Raspberry Pi minicomputer can acquire and store a rapidly varying time-signal with high fidelity. We show that this signal collected by a Raspberry Pi device can be processed numerically to yield intensity autocorrelations well suited for DCS applications. DCS measurements made using the Raspberry Pi device were compared to those acquired using a commercial hardware autocorrelation board to investigate the stability, performance, and accuracy of the data acquired in controlled experiments. This paper represents a first step toward lowering the instrumentation cost of a DCS system and may offer the potential to make DCS become more widely used in biomedical applications. PMID:26274961

Interpretation of the auto-mutual information rate of decrease in the context of biomedical signal analysis. Application to electroencephalogram recordings.

PubMed

Escudero, Javier; Hornero, Roberto; Abásolo, Daniel

2009-02-01

The mutual information (MI) is a measure of both linear and nonlinear dependences. It can be applied to a time series and a time-delayed version of the same sequence to compute the auto-mutual information function (AMIF). Moreover, the AMIF rate of decrease (AMIFRD) with increasing time delay in a signal is correlated with its entropy and has been used to characterize biomedical data. In this paper, we aimed at gaining insight into the dependence of the AMIFRD on several signal processing concepts and at illustrating its application to biomedical time series analysis. Thus, we have analysed a set of synthetic sequences with the AMIFRD. The results show that the AMIF decreases more quickly as bandwidth increases and that the AMIFRD becomes more negative as there is more white noise contaminating the time series. Additionally, this metric detected changes in the nonlinear dynamics of a signal. Finally, in order to illustrate the analysis of real biomedical signals with the AMIFRD, this metric was applied to electroencephalogram (EEG) signals acquired with eyes open and closed and to ictal and non-ictal intracranial EEG recordings.

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

Bakhtiari, S.; Liao, S.; Elmer, T.

This paper analyzes heart rate (HR) information from physiological tracings collected with a remote millimeter wave (mmW) I-Q sensor for biometric monitoring applications. A parameter optimization method based on the nonlinear Levenberg-Marquardt algorithm is used. The mmW sensor works at 94 GHz and can detect the vital signs of a human subject from a few to tens of meters away. The reflected mmW signal is typically affected by respiration, body movement, background noise, and electronic system noise. Processing of the mmW radar signal is, thus, necessary to obtain the true HR. The down-converted received signal in this case consists ofmore » both the real part (I-branch) and the imaginary part (Q-branch), which can be considered as the cosine and sine of the received phase of the HR signal. Instead of fitting the converted phase angle signal, the method directly fits the real and imaginary parts of the HR signal, which circumvents the need for phase unwrapping. This is particularly useful when the SNR is low. Also, the method identifies both beat-to-beat HR and individual heartbeat magnitude, which is valuable for some medical diagnosis applications. The mean HR here is compared to that obtained using the discrete Fourier transform.« less

Experiments with recursive estimation in astronomical image processing

NASA Technical Reports Server (NTRS)

Busko, I.

1992-01-01

Recursive estimation concepts were applied to image enhancement problems since the 70's. However, very few applications in the particular area of astronomical image processing are known. These concepts were derived, for 2-dimensional images, from the well-known theory of Kalman filtering in one dimension. The historic reasons for application of these techniques to digital images are related to the images' scanned nature, in which the temporal output of a scanner device can be processed on-line by techniques borrowed directly from 1-dimensional recursive signal analysis. However, recursive estimation has particular properties that make it attractive even in modern days, when big computer memories make the full scanned image available to the processor at any given time. One particularly important aspect is the ability of recursive techniques to deal with non-stationary phenomena, that is, phenomena which have their statistical properties variable in time (or position in a 2-D image). Many image processing methods make underlying stationary assumptions either for the stochastic field being imaged, for the imaging system properties, or both. They will underperform, or even fail, when applied to images that deviate significantly from stationarity. Recursive methods, on the contrary, make it feasible to perform adaptive processing, that is, to process the image by a processor with properties tuned to the image's local statistical properties. Recursive estimation can be used to build estimates of images degraded by such phenomena as noise and blur. We show examples of recursive adaptive processing of astronomical images, using several local statistical properties to drive the adaptive processor, as average signal intensity, signal-to-noise and autocorrelation function. Software was developed under IRAF, and as such will be made available to interested users.

Phase Retrieval for Radio Telescope and Antenna Control

NASA Technical Reports Server (NTRS)

Dean, Bruce

2011-01-01

Phase-retrieval is a general term used in optics to describe the estimation of optical imperfections or "aberrations." The purpose of this innovation is to develop the application of phase retrieval to radio telescope and antenna control in the millimeter wave band. Earlier techniques do not approximate the incoherent subtraction process as a coherent propagation. This approximation reduces the noise in the data and allows a straightforward application of conventional phase retrieval techniques for radio telescope and antenna control. The application of iterative-transform phase retrieval to radio telescope and antenna control is made by approximating the incoherent subtraction process as a coherent propagation. Thus, for systems utilizing both positive and negative polarity feeds, this approximation allows both surface and alignment errors to be assessed without the use of additional hardware or laser metrology. Knowledge of the antenna surface profile allows errors to be corrected at a given surface temperature and observing angle. In addition to imperfections of the antenna surface figure, the misalignment of multiple antennas operating in unison can reduce or degrade the signal-to-noise ratio of the received or broadcast signals. This technique also has application to the alignment of antenna array configurations.

Crossbar Nanocomputer Development

DTIC Science & Technology

2012-04-01

their utilization. Areas such as neuromorphic computing, signal processing, arithmetic processing, and crossbar computing are only some of the...due to its intrinsic, network-on- chip flexibility to re-route around defects. Preliminary efforts in crossbar computing have been demonstrated by...they approach their scaling limits [2]. Other applications that memristive devices are suited for include FPGA [3], encryption [4], and neuromorphic

ALMA Correlator Real-Time Data Processor

NASA Astrophysics Data System (ADS)

Pisano, J.; Amestica, R.; Perez, J.

2005-10-01

The design of a real-time Linux application utilizing Real-Time Application Interface (RTAI) to process real-time data from the radio astronomy correlator for the Atacama Large Millimeter Array (ALMA) is described. The correlator is a custom-built digital signal processor which computes the cross-correlation function of two digitized signal streams. ALMA will have 64 antennas with 2080 signal streams each with a sample rate of 4 giga-samples per second. The correlator's aggregate data output will be 1 gigabyte per second. The software is defined by hard deadlines with high input and processing data rates, while requiring interfaces to non real-time external computers. The designed computer system - the Correlator Data Processor or CDP, consists of a cluster of 17 SMP computers, 16 of which are compute nodes plus a master controller node all running real-time Linux kernels. Each compute node uses an RTAI kernel module to interface to a 32-bit parallel interface which accepts raw data at 64 megabytes per second in 1 megabyte chunks every 16 milliseconds. These data are transferred to tasks running on multiple CPUs in hard real-time using RTAI's LXRT facility to perform quantization corrections, data windowing, FFTs, and phase corrections for a processing rate of approximately 1 GFLOPS. Highly accurate timing signals are distributed to all seventeen computer nodes in order to synchronize them to other time-dependent devices in the observatory array. RTAI kernel tasks interface to the timing signals providing sub-millisecond timing resolution. The CDP interfaces, via the master node, to other computer systems on an external intra-net for command and control, data storage, and further data (image) processing. The master node accesses these external systems utilizing ALMA Common Software (ACS), a CORBA-based client-server software infrastructure providing logging, monitoring, data delivery, and intra-computer function invocation. The software is being developed in tandem with the correlator hardware which presents software engineering challenges as the hardware evolves. The current status of this project and future goals are also presented.

Categorisation of full waveform data provided by laser scanning devices

NASA Astrophysics Data System (ADS)

Ullrich, Andreas; Pfennigbauer, Martin

2011-11-01

In 2004, a laser scanner device for commercial airborne laser scanning applications, the RIEGL LMS-Q560, was introduced to the market, making use of a radical alternative approach to the traditional analogue signal detection and processing schemes found in LIDAR instruments so far: digitizing the echo signals received by the instrument for every laser pulse and analysing these echo signals off-line in a so-called full waveform analysis in order to retrieve almost all information contained in the echo signal using transparent algorithms adaptable to specific applications. In the field of laser scanning the somewhat unspecific term "full waveform data" has since been established. We attempt a categorisation of the different types of the full waveform data found in the market. We discuss the challenges in echo digitization and waveform analysis from an instrument designer's point of view and we will address the benefits to be gained by using this technique, especially with respect to the so-called multi-target capability of pulsed time-of-flight LIDAR instruments.

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%.

A Volterra series-based method for extracting target echoes in the seafloor mining environment.

PubMed

Zhao, Haiming; Ji, Yaqian; Hong, Yujiu; Hao, Qi; Ma, Liyong

2016-09-01

The purpose of this research was to evaluate the applicability of the Volterra adaptive method to predict the target echo of an ultrasonic signal in an underwater seafloor mining environment. There is growing interest in mining of seafloor minerals because they offer an alternative source of rare metals. Mining the minerals cause the seafloor sediments to be stirred up and suspended in sea water. In such an environment, the target signals used for seafloor mapping are unable to be detected because of the unavoidable presence of volume reverberation induced by the suspended sediments. The detection of target signals in reverberation is currently performed using a stochastic model (for example, the autoregressive (AR) model) based on the statistical characterisation of reverberation. However, we examined a new method of signal detection in volume reverberation based on the Volterra series by confirming that the reverberation is a chaotic signal and generated by a deterministic process. The advantage of this method over the stochastic model is that attributions of the specific physical process are considered in the signal detection problem. To test the Volterra series based method and its applicability to target signal detection in the volume reverberation environment derived from the seafloor mining process, we simulated the real-life conditions of seafloor mining in a water filled tank of dimensions of 5×3×1.8m. The bottom of the tank was covered with 10cm of an irregular sand layer under which 5cm of an irregular cobalt-rich crusts layer was placed. The bottom was interrogated by an acoustic wave generated as 16μs pulses of 500kHz frequency. This frequency is demonstrated to ensure a resolution on the order of one centimetre, which is adequate in exploration practice. Echo signals were collected with a data acquisition card (PCI 1714 UL, 12-bit). Detection of the target echo in these signals was performed by both the Volterra series based model and the AR model. The results obtained confirm that the Volterra series based method is more efficient in the detection of the signal in reverberation than the conventional AR model (the accuracy is 80% for the PIM-Volterra prediction model versus 40% for the AR model). Copyright © 2016 Elsevier B.V. All rights reserved.

Metafusion: A breakthrough in metallurgy

NASA Technical Reports Server (NTRS)

Joseph, Adrian A.

1994-01-01

The Metafuse Process is a patented development in the field of thin film coatings utilizing cold fusion which results in a true inter-dispersion of dissimilar materials along a gradual transition gradient through a boundary of several hundred atomic layers. The process is performed at ambient temperatures and pressures requiring relatively little energy and creating little or no heat. The process permits a remarkable range of material combinations and joining of materials which are normally incompatible. Initial applications include titanium carbide into and onto the copper resistance welding electrodes and tungsten carbide onto the cutting edges of tool steel blades. The process is achieved through application of an RF signal of low power and is based on the theory of vacancy fusion.

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

Advanced processing for high-bandwidth sensor systems

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Blain, Phil C.; Bloch, Jeffrey J.; Brislawn, Christopher M.; Brumby, Steven P.; Cafferty, Maureen M.; Dunham, Mark E.; Frigo, Janette R.; Gokhale, Maya; Harvey, Neal R.; Kenyon, Garrett; Kim, Won-Ha; Layne, J.; Lavenier, Dominique D.; McCabe, Kevin P.; Mitchell, Melanie; Moore, Kurt R.; Perkins, Simon J.; Porter, Reid B.; Robinson, S.; Salazar, Alfonso; Theiler, James P.; Young, Aaron C.

2000-11-01

Compute performance and algorithm design are key problems of image processing and scientific computing in general. For example, imaging spectrometers are capable of producing data in hundreds of spectral bands with millions of pixels. These data sets show great promise for remote sensing applications, but require new and computationally intensive processing. The goal of the Deployable Adaptive Processing Systems (DAPS) project at Los Alamos National Laboratory is to develop advanced processing hardware and algorithms for high-bandwidth sensor applications. The project has produced electronics for processing multi- and hyper-spectral sensor data, as well as LIDAR data, while employing processing elements using a variety of technologies. The project team is currently working on reconfigurable computing technology and advanced feature extraction techniques, with an emphasis on their application to image and RF signal processing. This paper presents reconfigurable computing technology and advanced feature extraction algorithm work and their application to multi- and hyperspectral image processing. Related projects on genetic algorithms as applied to image processing will be introduced, as will the collaboration between the DAPS project and the DARPA Adaptive Computing Systems program. Further details are presented in other talks during this conference and in other conferences taking place during this symposium.

Using Pattern Recognition and Discriminance Analysis to Predict Critical Events in Large Signal Databases

NASA Astrophysics Data System (ADS)

Feller, Jens; Feller, Sebastian; Mauersberg, Bernhard; Mergenthaler, Wolfgang

2009-09-01

Many applications in plant management require close monitoring of equipment performance, in particular with the objective to prevent certain critical events. At each point in time, the information available to classify the criticality of the process, is represented through the historic signal database as well as the actual measurement. This paper presents an approach to detect and predict critical events, based on pattern recognition and discriminance analysis.

47 CFR 73.3572 - Processing of TV broadcast, Class A TV broadcast, low power TV, TV translators, and TV booster...

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 4 2013-10-01 2013-10-01 false Processing of TV broadcast, Class A TV... Rules Applicable to All Broadcast Stations § 73.3572 Processing of TV broadcast, Class A TV broadcast... considered minor only if the change(s) will not increase the signal range of the Class A TV, low power TV or...

47 CFR 73.3572 - Processing of TV broadcast, Class A TV broadcast, low power TV, TV translators, and TV booster...

Code of Federal Regulations, 2012 CFR

2012-10-01

... 47 Telecommunication 4 2012-10-01 2012-10-01 false Processing of TV broadcast, Class A TV... Rules Applicable to All Broadcast Stations § 73.3572 Processing of TV broadcast, Class A TV broadcast... considered minor only if the change(s) will not increase the signal range of the Class A TV, low power TV or...

47 CFR 73.3572 - Processing of TV broadcast, Class A TV broadcast, low power TV, TV translators, and TV booster...

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 4 2011-10-01 2011-10-01 false Processing of TV broadcast, Class A TV... Rules Applicable to All Broadcast Stations § 73.3572 Processing of TV broadcast, Class A TV broadcast... considered minor only if the change(s) will not increase the signal range of the Class A TV, low power TV or...

47 CFR 73.3572 - Processing of TV broadcast, Class A TV broadcast, low power TV, TV translators, and TV booster...

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 4 2014-10-01 2014-10-01 false Processing of TV broadcast, Class A TV... Rules Applicable to All Broadcast Stations § 73.3572 Processing of TV broadcast, Class A TV broadcast... considered minor only if the change(s) will not increase the signal range of the Class A TV, low power TV or...

Signal processing and analysis for copper layer thickness measurement within a large variation range in the CMP process.

PubMed

Li, Hongkai; Zhao, Qian; Lu, Xinchun; Luo, Jianbin

2017-11-01

In the copper (Cu) chemical mechanical planarization (CMP) process, accurate determination of a process reaching the end point is of great importance. Based on the eddy current technology, the in situ thickness measurement of the Cu layer is feasible. Previous research studies focus on the application of the eddy current method to the metal layer thickness measurement or endpoint detection. In this paper, an in situ measurement system, which is independently developed by using the eddy current method, is applied to the actual Cu CMP process. A series of experiments are done for further analyzing the dynamic response characteristic of the output signal within different thickness variation ranges. In this study, the voltage difference of the output signal is used to represent the thickness of the Cu layer, and we can extract the voltage difference variations from the output signal fast by using the proposed data processing algorithm. The results show that the voltage difference decreases as thickness decreases in the conventional measurement range and the sensitivity increases at the same time. However, it is also found that there exists a thickness threshold, and the correlation is negative, when the thickness is more than the threshold. Furthermore, it is possible that the in situ measurement system can be used within a larger Cu layer thickness variation range by creating two calibration tables.

Efficient audio signal processing for embedded systems

NASA Astrophysics Data System (ADS)

Chiu, Leung Kin

As mobile platforms continue to pack on more computational power, electronics manufacturers start to differentiate their products by enhancing the audio features. However, consumers also demand smaller devices that could operate for longer time, hence imposing design constraints. In this research, we investigate two design strategies that would allow us to efficiently process audio signals on embedded systems such as mobile phones and portable electronics. In the first strategy, we exploit properties of the human auditory system to process audio signals. We designed a sound enhancement algorithm to make piezoelectric loudspeakers sound ”richer" and "fuller." Piezoelectric speakers have a small form factor but exhibit poor response in the low-frequency region. In the algorithm, we combine psychoacoustic bass extension and dynamic range compression to improve the perceived bass coming out from the tiny speakers. We also developed an audio energy reduction algorithm for loudspeaker power management. The perceptually transparent algorithm extends the battery life of mobile devices and prevents thermal damage in speakers. This method is similar to audio compression algorithms, which encode audio signals in such a ways that the compression artifacts are not easily perceivable. Instead of reducing the storage space, however, we suppress the audio contents that are below the hearing threshold, therefore reducing the signal energy. In the second strategy, we use low-power analog circuits to process the signal before digitizing it. We designed an analog front-end for sound detection and implemented it on a field programmable analog array (FPAA). The system is an example of an analog-to-information converter. The sound classifier front-end can be used in a wide range of applications because programmable floating-gate transistors are employed to store classifier weights. Moreover, we incorporated a feature selection algorithm to simplify the analog front-end. A machine learning algorithm AdaBoost is used to select the most relevant features for a particular sound detection application. In this classifier architecture, we combine simple "base" analog classifiers to form a strong one. We also designed the circuits to implement the AdaBoost-based analog classifier.

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

NASA Astrophysics Data System (ADS)

Lee, Dong-Sup; Cho, Dae-Seung; Kim, Kookhyun; Jeon, Jae-Jin; Jung, Woo-Jin; Kang, Myeng-Hwan; Kim, Jae-Ho

2015-01-01

Independent Component Analysis (ICA), one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: instability and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to validate the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

Bacteriorhodopsin films for optical signal processing and data storage

NASA Technical Reports Server (NTRS)

Walkup, John F. (Principal Investigator); Mehrl, David J. (Principal Investigator)

1996-01-01

This report summarizes the research results obtained on NASA Ames Grant NAG 2-878 entitled 'Investigations of Bacteriorhodopsin Films for Optical Signal Processing and Data Storage.' Specifically we performed research, at Texas Tech University, on applications of Bacteriorhodopisin film to both (1) dynamic spatial filtering and (2) holographic data storage. In addition, measurements of the noise properties of an acousto-optical matrix-vestor multiplier built for NASA Ames by Photonic Systems Inc. were performed at NASA Ames' Photonics Laboratory. This research resulted in two papers presented at major optical data processing conferences and a journal paper which is to appear in APPLIED OPTICS. A new proposal for additional BR research has recently been submitted to NASA Ames Research Center.

Agile waveforms for joint SAR-GMTI processing

NASA Astrophysics Data System (ADS)

Jaroszewski, Steven; Corbeil, Allan; McMurray, Stephen; Majumder, Uttam; Bell, Mark R.; Corbeil, Jeffrey; Minardi, Michael

2016-05-01

Wideband radar waveforms that employ spread-spectrum techniques were investigated and experimentally tested. The waveforms combine bi-phase coding with a traditional LFM chirp and are applicable to joint SAR-GMTI processing. After de-spreading, the received signals can be processed to support simultaneous GMTI and high resolution SAR imaging missions by airborne radars. The spread spectrum coding techniques can provide nearly orthogonal waveforms and offer enhanced operations in some environments by distributing the transmitted energy over a large instantaneous bandwidth. The LFM component offers the desired Doppler tolerance. In this paper, the waveforms are formulated and a shift-register approach for de-spreading the received signals is described. Hardware loop-back testing has shown the feasibility of using these waveforms in experimental radar test bed.