Science.gov

Sample records for biomedical signal processing

  1. Review of biomedical signal and image processing

    PubMed Central

    2013-01-01

    This article is a review of the book “Biomedical Signal and Image Processing” by Kayvan Najarian and Robert Splinter, which is published by CRC Press, Taylor & Francis Group. It will evaluate the contents of the book and discuss its suitability as a textbook, while mentioning highlights of the book, and providing comparison with other textbooks.

  2. Software for biomedical engineering signal processing laboratory experiments.

    PubMed

    Tompkins, Willis J; Wilson, J

    2009-01-01

    In the early 1990's we developed a special computer program called UW DigiScope to provide a mechanism for anyone interested in biomedical digital signal processing to study the field without requiring any other instrument except a personal computer. There are many digital filtering and pattern recognition algorithms used in processing biomedical signals. In general, students have very limited opportunity to have hands-on access to the mechanisms of digital signal processing. In a typical course, the filters are designed non-interactively, which does not provide the student with significant understanding of the design constraints of such filters nor their actual performance characteristics. UW DigiScope 3.0 is the first major update since version 2.0 was released in 1994. This paper provides details on how the new version based on MATLAB! works with signals, including the filter design tool that is the programming interface between UW DigiScope and processing algorithms. PMID:19964035

  3. SoC-based architecture for biomedical signal processing.

    PubMed

    Gutiérrez-Rivas, R; Hernández, A; García, J J; Marnane, W

    2015-01-01

    Over the last decades, many algorithms have been proposed for processing biomedical signals. Most of these algorithms have been focused on the elimination of noise and artifacts existing in these signals, so they can be used for automatic monitoring and/or diagnosis applications. With regard to remote monitoring, the use of portable devices often requires a reduced number of resources and power consumption, being necessary to reach a trade-off between the accuracy of algorithms and their computational complexity. This paper presents a SoC (System-on-Chip) architecture, based on a FPGA (Field-Programmable Gate Array) device, suitable for the implementation of biomedical signal processing. The proposal has been successfully validated by implementing an efficient QRS complex detector. The results show that, using a reduced amount of resources, values of sensitivity and positive predictive value above 99.49% are achieved, which make the proposed approach suitable for telemedicine applications. PMID:26737663

  4. Power optimization in wearable biomedical systems: a signal processing perspective

    NASA Astrophysics Data System (ADS)

    Ghasemzadeh, Hassan

    2012-10-01

    Wearable monitoring systems have caught considerable attention recently due to their potential in many domains including smart health and well-being. These new biomedical monitoring systems aim to provide continuous patient monitoring and proactive care options. Realization of this vision requires research that addresses a number of challenges, in particular, regarding limited resources that the wearable sensor networks offer. This paper presents an overview of different strategies for prolonging system lifetimes through power optimization in such systems. Particular emphasis is given to enhancing processing and communication architectures with respect to the signal processing requirements of the system.

  5. 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

  6. Multidimensional Processes: In Italy, biomedical signal and image processing embraces a multiparametric, multimodal, multiscale paradigm.

    PubMed

    Bianchi, Anna M; Baselli, Giuseppe; Babiloni, Fabio; Rizzo, Giovanna

    2015-01-01

    Biomedical studies, both in research and in clinical applications, deal with the management of large amounts of data. Different sensors and transducers, advances in technologies, and the availability of innovative medical equipment and instrumentation all contribute to the ability to make biological measurements at different scales, ranging from systems, to organs, to tissues, to cells, right down to proteins and genes. Biomedical signals and data carry important information about the system or the organ that generated them. PMID:26186053

  7. Design of a novel biomedical signal processing and analysis tool for functional neuroimaging.

    PubMed

    Kaçar, Sezgin; Sakoğlu, Ünal

    2016-03-01

    In this paper, a MATLAB-based graphical user interface (GUI) software tool for general biomedical signal processing and analysis of functional neuroimaging data is introduced. Specifically, electroencephalography (EEG) and electrocardiography (ECG) signals can be processed and analyzed by the developed tool, which incorporates commonly used temporal and frequency analysis methods. In addition to common methods, the tool also provides non-linear chaos analysis with Lyapunov exponents and entropies; multivariate analysis with principal and independent component analyses; and pattern classification with discriminant analysis. This tool can also be utilized for training in biomedical engineering education. This easy-to-use and easy-to-learn, intuitive tool is described in detail in this paper. PMID:26679001

  8. 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

  9. 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

    2013-01-01

    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

  10. 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

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

    PubMed

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

    2015-01-01

    Recent developments in "Big Data" have brought significant gains in the ability to process large amounts of data on commodity server hardware. Stream computing is a relatively new paradigm in this area, addressing the need to process data in real time with very low latency. While this approach has been developed for dealing with large scale data from the world of business, security and finance, there is a natural overlap with clinical needs for physiological signal processing. In this work we present a case study of streams processing applied to a typical physiological signal processing problem: QRS detection from ECG data. PMID:26737641

  12. Optimal rate filters for biomedical point processes.

    PubMed

    McNames, James

    2005-01-01

    Rate filters are used to estimate the mean event rate of many biomedical signals that can be modeled as point processes. Historically these filters have been designed using principles from two distinct fields. Signal processing principles are used to optimize the filter's frequency response. Kernel estimation principles are typically used to optimize the asymptotic statistical properties. This paper describes a design methodology that combines these principles from both fields to optimize the frequency response subject to constraints on the filter's order, symmetry, time-domain ripple, DC gain, and minimum impulse response. Initial results suggest that time-domain ripple and a negative impulse response are necessary to design a filter with a reasonable frequency response. This suggests that some of the common assumptions about the properties of rate filters should be reconsidered. PMID:17282132

  13. Telemedicine optoelectronic biomedical data processing system

    NASA Astrophysics Data System (ADS)

    Prosolovska, Vita V.

    2010-08-01

    The telemedicine optoelectronic biomedical data processing system is created to share medical information for the control of health rights and timely and rapid response to crisis. The system includes the main blocks: bioprocessor, analog-digital converter biomedical images, optoelectronic module for image processing, optoelectronic module for parallel recording and storage of biomedical imaging and matrix screen display of biomedical images. Rated temporal characteristics of the blocks defined by a particular triggering optoelectronic couple in analog-digital converters and time imaging for matrix screen. The element base for hardware implementation of the developed matrix screen is integrated optoelectronic couples produced by selective epitaxy.

  14. Modeling biomedical experimental processes with OBI

    PubMed Central

    2010-01-01

    Background Experimental descriptions are typically stored as free text without using standardized terminology, creating challenges in comparison, reproduction and analysis. These difficulties impose limitations on data exchange and information retrieval. Results The Ontology for Biomedical Investigations (OBI), developed as a global, cross-community effort, provides a resource that represents biomedical investigations in an explicit and integrative framework. Here we detail three real-world applications of OBI, provide detailed modeling information and explain how to use OBI. Conclusion We demonstrate how OBI can be applied to different biomedical investigations to both facilitate interpretation of the experimental process and increase the computational processing and integration within the Semantic Web. The logical definitions of the entities involved allow computers to unambiguously understand and integrate different biological experimental processes and their relevant components. Availability OBI is available at http://purl.obolibrary.org/obo/obi/2009-11-02/obi.owl PMID:20626927

  15. UMLS knowledge for biomedical language processing.

    PubMed Central

    McCray, A T; Aronson, A R; Browne, A C; Rindflesch, T C; Razi, A; Srinivasan, S

    1993-01-01

    This paper describes efforts to provide access to the free text in biomedical databases. The focus of the effort is the development of SPECIALIST, an experimental natural language processing system for the biomedical domain. The system includes a broad coverage parser supported by a large lexicon, modules that provide access to the extensive Unified Medical Language System (UMLS) Knowledge Sources, and a retrieval module that permits experiments in information retrieval. The UMLS Metathesaurus and Semantic Network provide a rich source of biomedical concepts and their interrelationships. Investigations have been conducted to determine the type of information required to effect a map between the language of queries and the language of relevant documents. Mappings are never straightforward and often involve multiple inferences. PMID:8472004

  16. Detection of Events in Biomedical Signals by a Rényi Entropy Measure

    NASA Astrophysics Data System (ADS)

    Gabarda, S.; Cristóbal, G.; Martínez-Alajarín, J.; Ruiz, R.

    2006-10-01

    Biomedical signals contain important information about the healthy condition of human beings. Anomalous events in these signals are commonly associated to diseases. The information content enclosed by time-frequency representations (TFR) of biomedical signals can be explored by means of different Rényi entropy measures. To be precise, Rényi entropy can be approached under different normalizations, producing different outcomes. The best choice depends upon the particularities of the application considered. In this paper we propose a new processing scheme to the problem of events detection in biomedical signals, based on a particular normalization of the Rény entropy measurement. As in the case of another TFR's, the pseudo-Wigner distribution (PWD) of a biomedical signal can take negative values and thus it cannot be properly interpreted as a probability density function. Therefore a complexity measure based on the classical Shannon entropy cannot be used and a generalized measure such as the Rényi entropy is required. Our method allows the identification of the events as the moments having the highest amount of information (entropy) along the temporal data. This provides localized information about normal and pathological events in biomedical signals. Therefore, the diagnosis of diseases is facilitated in this way. The method is illustrated with examples of application to phonocardiograms and electrocardiograms and result are discussed.

  17. Visual parameter optimisation for biomedical image processing

    PubMed Central

    2015-01-01

    Background Biomedical image processing methods require users to optimise input parameters to ensure high-quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results We present a visualisation method that transforms users' ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches. PMID:26329538

  18. Application of the dual-tree complex wavelet transform in biomedical signal denoising.

    PubMed

    Wang, Fang; Ji, Zhong

    2014-01-01

    In biomedical signal processing, Gibbs oscillation and severe frequency aliasing may occur when using the traditional discrete wavelet transform (DWT). Herein, a new denoising algorithm based on the dual-tree complex wavelet transform (DTCWT) is presented. Electrocardiogram (ECG) signals and heart sound signals are denoised based on the DTCWT. The results prove that the DTCWT is efficient. The signal-to-noise ratio (SNR) and the mean square error (MSE) are used to compare the denoising effect. Results of the paired samples t-test show that the new method can remove noise more thoroughly and better retain the boundary and texture of the signal. PMID:24211889

  19. Design and analysis of low-power body area networks based on biomedical signals

    NASA Astrophysics Data System (ADS)

    Hu, Fengye; Li, Shasha; Xue, Tao; Li, Guofeng

    2012-06-01

    A body area network (BAN) as one branch of Sensor Networks, is an inter-disciplinary area which holds great promises for revolutionising the current health care systems. BAN combines the real-time updating of biomedical data with the continuous and dynamic health care monitoring closely. A number of intelligence biomedical sensors can be integrated into a wireless BAN system, and the system can be used for prevention, diagnosis and timely treatment of various medical conditions. In this article, we propose a data fusion technique for a BAN based on biomedical signals. This proposed solution is of much lower complexity than conventional techniques and hence can significantly reduce the power consumption in the BAN. The technology is carried out by removing redundant and unnecessary sample information and shifting a large portion of processing and control loads to the remote control centre in an asymmetric manner. This approach not only reduces the power consumption of biosensor nodes in a BAN, but also ensures the integrity of the biomedical information. In addition, we present a self-designed distributed time-space correlation compressive sensing model and propose an efficient algorithm based on biomedical signals. Simulation results show that the proposed algorithm can not only reconstruct the original signal with high accuracy and but also achieve significant reduction in power consumption.

  20. Recent advances in natural language processing for biomedical applications.

    PubMed

    Collier, Nigel; Nazarenko, Adeline; Baud, Robert; Ruch, Patrick

    2006-06-01

    We survey a set a recent advances in natural language processing applied to biomedical applications, which were presented in Geneva, Switzerland, in 2004 at an international workshop. While text mining applied to molecular biology and biomedical literature can report several interesting achievements, we observe that studies applied to clinical contents are still rare. In general, we argue that clinical corpora, including electronic patient records, must be made available to fill the gap between bioinformatics and medical informatics. PMID:16139564

  1. Signal Processing, Analysis, & Display

    SciTech Connect

    Lager, Darrell; Azevado, Stephen

    1986-06-01

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

  2. Biomedical Simulation Models of Human Auditory Processes

    NASA Technical Reports Server (NTRS)

    Bicak, Mehmet M. A.

    2012-01-01

    Detailed acoustic engineering models that explore noise propagation mechanisms associated with noise attenuation and transmission paths created when using hearing protectors such as earplugs and headsets in high noise environments. Biomedical finite element (FE) models are developed based on volume Computed Tomography scan data which provides explicit external ear, ear canal, middle ear ossicular bones and cochlea geometry. Results from these studies have enabled a greater understanding of hearing protector to flesh dynamics as well as prioritizing noise propagation mechanisms. Prioritization of noise mechanisms can form an essential framework for exploration of new design principles and methods in both earplug and earcup applications. These models are currently being used in development of a novel hearing protection evaluation system that can provide experimentally correlated psychoacoustic noise attenuation. Moreover, these FE models can be used to simulate the effects of blast related impulse noise on human auditory mechanisms and brain tissue.

  3. Advanced signal processing

    NASA Astrophysics Data System (ADS)

    Creasey, D. J.

    1985-12-01

    A collection of papers on advanced signal processing in radar, sonar, and communications is presented. The topics addressed include: transmitter aerials, high-power amplifier design for active sonar, radar transmitters, receiver array technology for sonar, new underwater acoustic detectors, diversity techniques in communications receivers, GaAs IC amplifiers for radar and communication receivers, integrated optical techniques for acoustooptic receivers, logarithmic receivers, CCD processors for sonar, acoustooptic correlators, designing in silicon, very high performance integrated circuits, and digital filters. Also discussed are: display types, scan converters in sonar, display ergonomics, simulators, high throughput sonar processors, optical fiber systems for signal processing, satellite communications, VLSI array processor for image and signal processing, ADA, future of cryogenic devices for signal processing applications, advanced image understanding, and VLSI architectures for real-time image processing.

  4. A Hierarchical Method for Removal of Baseline Drift from Biomedical Signals: Application in ECG Analysis

    PubMed Central

    Luo, Yurong; Hargraves, Rosalyn H.; Bai, Ou; Qi, Xuguang; Ward, Kevin R.; Pfaffenberger, Michael Paul

    2013-01-01

    Noise can compromise the extraction of some fundamental and important features from biomedical signals and hence prohibit accurate analysis of these signals. Baseline wander in electrocardiogram (ECG) signals is one such example, which can be caused by factors such as respiration, variations in electrode impedance, and excessive body movements. Unless baseline wander is effectively removed, the accuracy of any feature extracted from the ECG, such as timing and duration of the ST-segment, is compromised. This paper approaches this filtering task from a novel standpoint by assuming that the ECG baseline wander comes from an independent and unknown source. The technique utilizes a hierarchical method including a blind source separation (BSS) step, in particular independent component analysis, to eliminate the effect of the baseline wander. We examine the specifics of the components causing the baseline wander and the factors that affect the separation process. Experimental results reveal the superiority of the proposed algorithm in removing the baseline wander. PMID:23766720

  5. Signal Processing, Analysis, & Display

    Energy Science and Technology Software Center (ESTSC)

    1986-06-01

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

  6. Signal processing for microcalorimeters

    NASA Astrophysics Data System (ADS)

    Szymkowiak, A. E.; Kelley, R. L.; Moseley, S. H.; Stahle, C. K.

    1993-11-01

    Most of the power in the signals from microcalorimeters occurs at relatively low frequencies. At these frequencies, typical amplifiers will have significant amounts of 1/f noise. Our laboratory systems can also suffer from pickup at several harmonics of the AC power line, and from microphonic pickup at frequencies that vary with the configuration of the apparatus. We have developed some optimal signal processing techniques in order to construct the best possible estimates of our pulse heights in the presence of these non-ideal effects. In addition to a discussion of our laboratory systems, we present our plans for providing this kind of signal processing in flight experiments.

  7. Multichannel quantification of biomedical magnetic resonance spectroscopic signals

    NASA Astrophysics Data System (ADS)

    Vanhamme, Leen; Van Huffel, Sabine

    1998-10-01

    Quantification of individual magnetic resonance spectroscopy (MRS) signals modeled as a sum of exponentially damped sinusoids, is possible using interactive nonlinear least-squares fitting methods which provide maximum likelihood parameter estimates or using fully automatic, but statistically suboptical black-box methods. In kinetic experiments consecutive time series of MRS spectra are measured in which some of the parameters are known to remain constant over time. The purpose of this paper is to show how the previously mentioned methods can be extended to the simultaneous processing of all spectra in the time series using this additional information between the spectra. We will show that this approach yields statistically better results than processing the different signals separately.

  8. 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

  9. Array signal processing

    SciTech Connect

    Haykin, S.; Justice, J.H.; Owsley, N.L.; Yen, J.L.; Kak, A.C.

    1985-01-01

    This is the first book to be devoted completely to array signal processing, a subject that has become increasingly important in recent years. The book consists of six chapters. Chapter 1, which is introductory, reviews some basic concepts in wave propagation. The remaining five chapters deal with the theory and applications of array signal processing in (a) exploration seismology, (b) passive sonar, (c) radar, (d) radio astronomy, and (e) tomographic imaging. The various chapters of the book are self-contained. The book is written by a team of five active researchers, who are specialists in the individual fields covered by the pertinent chapters.

  10. Characterization of the Biomedical Query Mediation Process

    PubMed Central

    Hruby, Gregory W.; Boland, Mary Regina; Cimino, James J.; Gao, Junfeng; Wilcox, Adam B.; Hirschberg, Julia; Weng, Chunhua

    To most medical researchers, databases are obscure black boxes. Query analysts are often indispensable guides aiding researchers to perform mediated data queries. However, this approach does not scale up and is time-consuming and expensive. We analyzed query mediation dialogues to inform future designs of intelligent query mediation systems. Thirty-one mediated query sessions for 22 research projects were recorded and transcribed. We analyzed 10 of these to develop an annotation schema for dialogue acts through iterative refinement. Three coders independently annotated all 3160 dialogue acts. We assessed the inter-rater agreement and resolved disagreement by group consensus. This study contributes early knowledge of the query negotiation space for medical research. We conclude that research data query formulation is not a straightforward translation from researcher data needs to database queries, but rather iterative, process-oriented needs assessment and refinement. PMID:24303242

  11. Telemetry Ranging: Signal Processing

    NASA Astrophysics Data System (ADS)

    Hamkins, J.; Kinman, P.; Xie, H.; Vilnrotter, V.; Dolinar, S.

    2016-02-01

    This article describes the details of the signal processing used in a telemetry ranging system in which timing information is extracted from the downlink telemetry signal in order to compute spacecraft range. A previous article describes telemetry ranging concepts and architecture, which are a slight variation of a scheme published earlier. As in that earlier work, the telemetry ranging concept eliminates the need for a dedicated downlink ranging signal to communicate the necessary timing information. The present article describes the operation and performance of the major receiver functions on the spacecraft and the ground --- many of which are standard tracking loops already in use in JPL's flight and ground radios --- and how they can be used to provide the relevant information for making a range measurement. It also describes the implementation of these functions in software, and performance of an end-to-end software simulation of the telemetry ranging system.

  12. Natural Language Processing Methods and Systems for Biomedical Ontology Learning

    PubMed Central

    Liu, Kaihong; Hogan, William R.; Crowley, Rebecca S.

    2010-01-01

    While the biomedical informatics community widely acknowledges the utility of domain ontologies, there remain many barriers to their effective use. One important requirement of domain ontologies is that they must achieve a high degree of coverage of the domain concepts and concept relationships. However, the development of these ontologies is typically a manual, time-consuming, and often error-prone process. Limited resources result in missing concepts and relationships as well as difficulty in updating the ontology as knowledge changes. Methodologies developed in the fields of natural language processing, information extraction, information retrieval and machine learning provide techniques for automating the enrichment of an ontology from free-text documents. In this article, we review existing methodologies and developed systems, and discuss how existing methods can benefit the development of biomedical ontologies. PMID:20647054

  13. 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

  14. Digital signal processing

    NASA Astrophysics Data System (ADS)

    Morgera, Salvatore D.; Krishna, Hari

    Computationally efficient digital signal-processing algorithms over finite fields are developed analytically, and the relationship of these algorithms to algebraic error-correcting codes is explored. A multidisciplinary approach is employed, in an effort to make the results accessible to engineers, mathematicians, and computer scientists. Chapters are devoted to systems of bilinear forms, efficient finite-field algorithms, multidimensional methods, a new class of linear codes, and a new error-control scheme.

  15. Powerline noise elimination in biomedical signals via blind source separation and wavelet analysis.

    PubMed

    Akwei-Sekyere, Samuel

    2015-01-01

    The distortion of biomedical signals by powerline noise from recording biomedical devices has the potential to reduce the quality and convolute the interpretations of the data. Usually, powerline noise in biomedical recordings are extinguished via band-stop filters. However, due to the instability of biomedical signals, the distribution of signals filtered out may not be centered at 50/60 Hz. As a result, self-correction methods are needed to optimize the performance of these filters. Since powerline noise is additive in nature, it is intuitive to model powerline noise in a raw recording and subtract it from the raw data in order to obtain a relatively clean signal. This paper proposes a method that utilizes this approach by decomposing the recorded signal and extracting powerline noise via blind source separation and wavelet analysis. The performance of this algorithm was compared with that of a 4th order band-stop Butterworth filter, empirical mode decomposition, independent component analysis and, a combination of empirical mode decomposition with independent component analysis. The proposed method was able to expel sinusoidal signals within powerline noise frequency range with higher fidelity in comparison with the mentioned techniques, especially at low signal-to-noise ratio. PMID:26157639

  16. Powerline noise elimination in biomedical signals via blind source separation and wavelet analysis

    PubMed Central

    2015-01-01

    The distortion of biomedical signals by powerline noise from recording biomedical devices has the potential to reduce the quality and convolute the interpretations of the data. Usually, powerline noise in biomedical recordings are extinguished via band-stop filters. However, due to the instability of biomedical signals, the distribution of signals filtered out may not be centered at 50/60 Hz. As a result, self-correction methods are needed to optimize the performance of these filters. Since powerline noise is additive in nature, it is intuitive to model powerline noise in a raw recording and subtract it from the raw data in order to obtain a relatively clean signal. This paper proposes a method that utilizes this approach by decomposing the recorded signal and extracting powerline noise via blind source separation and wavelet analysis. The performance of this algorithm was compared with that of a 4th order band-stop Butterworth filter, empirical mode decomposition, independent component analysis and, a combination of empirical mode decomposition with independent component analysis. The proposed method was able to expel sinusoidal signals within powerline noise frequency range with higher fidelity in comparison with the mentioned techniques, especially at low signal-to-noise ratio. PMID:26157639

  17. Digital signal processing

    NASA Astrophysics Data System (ADS)

    Meyer, G.

    The theory, realization techniques, and applications of digital filtering are surveyed, with an emphasis on the development of software, in a handbook for advanced students of electrical and electronic engineering and practicing development engineers. The foundations of the theory of discrete signals and systems are introduced. The design of one-dimensional linear systems is discussed, and the techniques are expanded to the treatment of two-dimensional discrete and multidimensional analog systems. Numerical systems, quantification and limitation, and the characteristics of particular signal-processing devices are considered in a section on design realization. An appendix contains definitions of the basic mathematical concepts, derivations and proofs, and tables of integration and differentiation formulas.

  18. Hilbert-Huang transformation-based time-frequency analysis methods in biomedical signal applications.

    PubMed

    Lin, Chin-Feng; Zhu, Jin-De

    2012-03-01

    Hilbert-Huang transformation, wavelet transformation, and Fourier transformation are the principal time-frequency analysis methods. These transformations can be used to discuss the frequency characteristics of linear and stationary signals, the time-frequency features of linear and non-stationary signals, the time-frequency features of non-linear and non-stationary signals, respectively. The Hilbert-Huang transformation is a combination of empirical mode decomposition and Hilbert spectral analysis. The empirical mode decomposition uses the characteristics of signals to adaptively decompose them to several intrinsic mode functions. Hilbert transforms are then used to transform the intrinsic mode functions into instantaneous frequencies, to obtain the signal's time-frequency-energy distributions and features. Hilbert-Huang transformation-based time-frequency analysis can be applied to natural physical signals such as earthquake waves, winds, ocean acoustic signals, mechanical diagnosis signals, and biomedical signals. In previous studies, we examined Hilbert-Huang transformation-based time-frequency analysis of the electroencephalogram FPI signals of clinical alcoholics, and 'sharp I' wave-based Hilbert-Huang transformation time-frequency features. In this paper, we discuss the application of Hilbert-Huang transformation-based time-frequency analysis to biomedical signals, such as electroencephalogram, electrocardiogram signals, electrogastrogram recordings, and speech signals. PMID:22558835

  19. Compact biomedical pulsed signal generator for bone tissue stimulation

    DOEpatents

    Kronberg, J.W.

    1993-06-08

    An apparatus for stimulating bone tissue for stimulating bone growth or treating osteoporosis by applying directly to the skin of the patient an alternating current electrical signal comprising wave forms known to simulate the piezoelectric constituents in bone. The apparatus may, by moving a switch, stimulate bone growth or treat osteoporosis, as desired. Based on low-power CMOS technology and enclosed in a moisture-resistant case shaped to fit comfortably, two astable multivibrators produce the desired waveforms. The amplitude, pulse width and pulse frequency, and the subpulse width and subpulse frequency of the waveforms are adjustable. The apparatus, preferably powered by a standard 9-volt battery, includes signal amplitude sensors and warning signals indicate an output is being produced and the battery needs to be replaced.

  20. Compact biomedical pulsed signal generator for bone tissue stimulation

    DOEpatents

    Kronberg, James W.

    1993-01-01

    An apparatus for stimulating bone tissue for stimulating bone growth or treating osteoporosis by applying directly to the skin of the patient an alternating current electrical signal comprising wave forms known to simulate the piezoelectric constituents in bone. The apparatus may, by moving a switch, stimulate bone growth or treat osteoporosis, as desired. Based on low-power CMOS technology and enclosed in a moisture-resistant case shaped to fit comfortably, two astable multivibrators produce the desired waveforms. The amplitude, pulse width and pulse frequency, and the subpulse width and subpulse frequency of the waveforms are adjustable. The apparatus, preferably powered by a standard 9-volt battery, includes signal amplitude sensors and warning signals indicate an output is being produced and the battery needs to be replaced.

  1. [Signal Processing Suite Design

    NASA Technical Reports Server (NTRS)

    Sahr, John D.; Mir, Hasan; Morabito, Andrew; Grossman, Matthew

    2003-01-01

    Our role in this project was to participate in the design of the signal processing suite to analyze plasma density measurements on board a small constellation (3 or 4) satellites in Low Earth Orbit. As we are new to space craft experiments, one of the challenges was to simply gain understanding of the quantity of data which would flow from the satellites, and possibly to interact with the design teams in generating optimal sampling patterns. For example, as the fleet of satellites were intended to fly through the same volume of space (displaced slightly in time and space), the bulk plasma structure should be common among the spacecraft. Therefore, an optimal, limited bandwidth data downlink would take advantage of this commonality. Also, motivated by techniques in ionospheric radar, we hoped to investigate the possibility of employing aperiodic sampling in order to gain access to a wider spatial spectrum without suffering aliasing in k-space.

  2. Analog and digital signal processing

    NASA Astrophysics Data System (ADS)

    Baher, H.

    The techniques of signal processing in both the analog and digital domains are addressed in a fashion suitable for undergraduate courses in modern electrical engineering. The topics considered include: spectral analysis of continuous and discrete signals, analysis of continuous and discrete systems and networks using transform methods, design of analog and digital filters, digitization of analog signals, power spectrum estimation of stochastic signals, FFT algorithms, finite word-length effects in digital signal processes, linear estimation, and adaptive filtering.

  3. Automatic fall detection using wearable biomedical signal measurement terminal.

    PubMed

    Nguyen, Thuy-Trang; Cho, Myeong-Chan; Lee, Tae-Soo

    2009-01-01

    In our study, we developed a mobile waist-mounted device which can monitor the subject's acceleration signal and detect the fall events in real-time with high accuracy and automatically send an emergency message to a remote server via CDMA module. When fall event happens, the system also generates an alarm sound at 50Hz to alarm other people until a subject can sit up or stand up. A Kionix KXM52-1050 tri-axial accelerometer and a Bellwave BSM856 CDMA standalone modem were used to detect and manage fall events. We used not only a simple threshold algorithm but also some supporting methods to increase an accuracy of our system (nearly 100% in laboratory environment). Timely fall detection can prevent regrettable death due to long-lie effect; therefore increase the independence of elderly people in an unsupervised living environment. PMID:19964661

  4. Signal and Image Processing Operations

    Energy Science and Technology Software Center (ESTSC)

    1995-05-10

    VIEW is a software system for processing arbitrary multidimensional signals. It provides facilities for numerical operations, signal displays, and signal databasing. The major emphasis of the system is on the processing of time-sequences and multidimensional images. The system is designed to be both portable and extensible. It runs currently on UNIX systems, primarily SUN workstations.

  5. Signal processing in SETI

    NASA Technical Reports Server (NTRS)

    Cullers, D. K.; Linscott, I. R.; Oliver, B. M.

    1985-01-01

    It is believed that the Galaxy might contain ten billion potential life sites. In view of the physical inaccessibility of extraterrestrial life on account of the vast distances involved, a logical first step in a search for extraterrestrial intelligence (SETI) appears to be an attempt to detect signals already being radiated. The characteristics of the signals to be expected are discussed together with the search strategy of a NASA program. It is pointed out that all presently planned searches will use existing radio-astronomy antennas. If no extraterrestrial intelligence signals are discovered, society will have to decide whether SETI justifies a dedicated facility of much greater collecting area. Attention is given to a multichannel spectrum analyzer, CW signal detection, pulse detection, the pattern detector, and details of SETI system operation.

  6. Digital processing of bandpass signals

    NASA Astrophysics Data System (ADS)

    Jackson, M. C.; Matthewson, P.

    Modern radar and radio systems rely on digital signal processing to enhance the quality of received signals. Prior to such processing, these signals must be converted to digital form. The historical development of signal digitization is briefly discussed in this paper and leads to a description of some current work on digital mixing. A method of directly sampling a band-limited intermediate frequency (i.f.) signal is presented, using a pair of digital mixer channels to produce complex low-pass samples of the signal envelope. The method is found to produce well matched channel outputs. Finally, the applicability of the method to radar is discussed.

  7. Digital signal processing the Tevatron BPM signals

    SciTech Connect

    Cancelo, G.; James, E.; Wolbers, S.; /Fermilab

    2005-05-01

    The Beam Position Monitor (TeV BPM) readout system at Fermilab's Tevatron has been updated and is currently being commissioned. The new BPMs use new analog and digital hardware to achieve better beam position measurement resolution. The new system reads signals from both ends of the existing directional stripline pickups to provide simultaneous proton and antiproton measurements. The signals provided by the two ends of the BPM pickups are processed by analog band-pass filters and sampled by 14-bit ADCs at 74.3MHz. A crucial part of this work has been the design of digital filters that process the signal. This paper describes the digital processing and estimation techniques used to optimize the beam position measurement. The BPM electronics must operate in narrow-band and wide-band modes to enable measurements of closed-orbit and turn-by-turn positions. The filtering and timing conditions of the signals are tuned accordingly for the operational modes. The analysis and the optimized result for each mode are presented.

  8. Signal processing in SETI.

    PubMed

    Cullers, D K; Linscott, I R; Oliver, B M

    1985-11-01

    The development of a multi-channel spectrum analyzer (MCSA) for the SETI program is described. The spectrum analyzer is designed for both all-sky surveys and targeted searches. The mechanisms of the MCSA are explained and a diagram is provided. Detection of continuous wave signals, pulses, and patterns is examined. PMID:11542023

  9. A Proposal of a Novel RFID Tag with Biomedical Signal Sensing Functions

    NASA Astrophysics Data System (ADS)

    Nakajima, Akira; Inoue, Takahiro; Tsuneda, Akio

    A novel RFID tag with sensing functions of biomedical signals is proposed in this paper. This RFID tag is developed for sensing heart rate, respiration, and body temperature of a human, which is intended for a secure and intensive health care of humans at hospital or at home. The features of this RFID tag are identification of indivisuals by ID call and collation, on-demand measurement of vital signals, and a medium-range(<8m) data communication. The developed prototype RFID tag works at ±1.5V supply voltage, and it was implemented on a PCB attached to a belt. Its performances were confirmed with experiments.

  10. Software and Algorithms for Biomedical Image Data Processing and Visualization

    NASA Technical Reports Server (NTRS)

    Talukder, Ashit; Lambert, James; Lam, Raymond

    2004-01-01

    A new software equipped with novel image processing algorithms and graphical-user-interface (GUI) tools has been designed for automated analysis and processing of large amounts of biomedical image data. The software, called PlaqTrak, has been specifically used for analysis of plaque on teeth of patients. New algorithms have been developed and implemented to segment teeth of interest from surrounding gum, and a real-time image-based morphing procedure is used to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The PlaqTrak system integrates these components into a single software suite with an easy-to-use GUI (see Figure 1) that allows users to do an end-to-end run of a patient s record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image. The automated and accurate processing of the captured images to segment each tooth [see Figure 2(a)] and then detect plaque on a tooth-by-tooth basis is a critical component of the PlaqTrak system to do clinical trials and analysis with minimal human intervention. These features offer distinct advantages over other competing systems that analyze groups of teeth or synthetic teeth. PlaqTrak divides each segmented tooth into eight regions using an advanced graphics morphing procedure [see results on a chipped tooth in Figure 2(b)], and a pattern recognition classifier is then used to locate plaque [red regions in Figure 2(d)] and enamel regions. The morphing allows analysis within regions of teeth, thereby facilitating detailed statistical analysis such as the amount of plaque present on the biting surfaces on teeth. This software system is applicable to a host of biomedical applications, such as cell analysis and life detection, or robotic applications, such

  11. SIG. Signal Processing, Analysis, & Display

    SciTech Connect

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

    1992-01-22

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

  12. SIG. Signal Processing, Analysis, & Display

    SciTech Connect

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

    1992-01-22

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

  13. SIG. Signal Processing, Analysis, & Display

    SciTech Connect

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

    1992-01-22

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

  14. Evolution of a processing system in a large biomedical library.

    PubMed

    Darling, L; Fayollat, J

    1976-01-01

    The processing system used in the UCLA Biomedical Library is modest in size and still under development. Its origins date back to a batch mode serials control system begun in the mid-1960s. This was converted to an on-line system which currently has modules for check-in, updating and retrieval, claims, bindery preparation, and invoice information. Titles can be retrieved at the terminal by search of any word in the title, by subject heading, language, country of publication, and type of publication. The system is adaptable to network use and at present is shared with one other library. To the serials system has been added a computer-assisted cataloging and card production system. The latter utilizes serials nucleus software as well as design for data input and data storage. In-house listings and coding procedures overlap in a general way. Work is under way on further integration of the two processing subsystems and a feasibility study has been completed for addition of a subsystem for acquisitions which will combine and adapt features of the other two; for example, information retrieval characteristics from both, catalog coding and programs for acceptance of data, serials programs for claims, and other output programs. Cost benefits of the subsystems are described and discussed. PMID:1247705

  15. Signal processing in magnetoencephalography.

    PubMed

    Vrba, J; Robinson, S E

    2001-10-01

    The subject of this article is detection of brain magnetic fields, or magnetoencephalography (MEG). The brain fields are many orders of magnitude smaller than the environmental magnetic noise and their measurement represent a significant metrological challenge. The only detectors capable of resolving such small fields and at the same time handling the large dynamic range of the environmental noise are superconducting quantum interference devices (or SQUIDs). The SQUIDs are coupled to the brain magnetic fields using combinations of superconducting coils called flux transformers (primary sensors). The environmental noise is attenuated by a combination of shielding, primary sensor geometry, and synthetic methods. One of the most successful synthetic methods for noise elimination is synthetic higher-order gradiometers. How the gradiometers can be synthesized is shown and examples of their noise cancellation effectiveness are given. The MEG signals measured on the scalp surface must be interpreted and converted into information about the distribution of currents within the brain. This task is complicated by the fact that such inversion is nonunique. Additional mathematical simplifications, constraints, or assumptions must be employed to obtain useful source images. Methods for the interpretation of the MEG signals include the popular point current dipole, minimum norm methods, spatial filtering, beamformers, MUSIC, and Bayesian techniques. The use of synthetic aperture magnetometry (a class of beamformers) is illustrated in examples of interictal epileptic spiking and voluntary hand-motor activity. PMID:11812209

  16. Biomedical image and signal de-noising using dual tree complex wavelet transform

    NASA Astrophysics Data System (ADS)

    Rizi, F. Yousefi; Noubari, H. Ahmadi; Setarehdan, S. K.

    2011-10-01

    Dual tree complex wavelet transform(DTCWT) is a form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The purposes of de-noising are reducing noise level and improving signal to noise ratio (SNR) without distorting the signal or image. This paper proposes a method for removing white Gaussian noise from ECG signals and biomedical images. The discrete wavelet transform (DWT) is very valuable in a large scope of de-noising problems. However, it has limitations such as oscillations of the coefficients at a singularity, lack of directional selectivity in higher dimensions, aliasing and consequent shift variance. The complex wavelet transform CWT strategy that we focus on in this paper is Kingsbury's and Selesnick's dual tree CWT (DTCWT) which outperforms the critically decimated DWT in a range of applications, such as de-noising. Each complex wavelet is oriented along one of six possible directions, and the magnitude of each complex wavelet has a smooth bell-shape. In the final part of this paper, we present biomedical image and signal de-noising by the means of thresholding magnitude of the wavelet coefficients.

  17. Signal processing development

    NASA Astrophysics Data System (ADS)

    Barrett, T. B.; Marshall, R.; Bloom, J.; Comer, C.; Caulfield, J.; Warde, C.; Salour, M.

    1989-11-01

    This electron microscope has been applied to the study of the growth of thin epitaxial films on silicon substrates. The study of the nature of platinum-silicide films formed by heating evaporated platinum films on these substrates is discussed. The use of ultra high vacuum systems together with a residual gas analyzer (RGA) is discussed as they relate to the preparation of silicides, a dielectric layer of silicon monoxide is evaporated and an ion beam implanter is used to form a special buried layer as a step toward silicon devices. Synthesis and single crystal growth of indium phosphide in a one-step in-situ process at high ambient pressures is discussed. Analysis of heat transfer by convection, conduction, and radiation in a closed pressure vessel is given. A set of source modules and NOS procedures have been prepared to permit easy access to a 3-dimensional, non-isotrophic ray-tracing program (the Jones - Stephenson program). This system is designed to be run on a CDC CYBER computer system or equivalent using the operating system.

  18. 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. PMID:25205499

  19. Systolic processor for signal processing

    SciTech Connect

    Frank, G.A.; Greenawalt, E.M.; Kulkarni, A.V.

    1982-01-01

    A systolic array is a natural architecture for a high-performance signal processor, in part because of the extensive use of inner-product operations in signal processing. The modularity and simple interconnection of systolic arrays promise to simplify the development of cost-effective, high-performance, special-purpose processors. ESL incorporated has built a proof of concept model of a systolic processor. It is flexible enough to permit experimentation with a variety of algorithms and applications. ESL is exploring the application of systolic processors to image- and signal-processing problems. This paper describes this experimental system and some of its applications to signal processing. ESL is also pursuing new types of systolic architectures, including the VLSI implementation of systolic cells for solving systems of linear equations. These new systolic architectures allow the real-time design of adaptive filters. 14 references.

  20. Comparison between Hilbert Huang transform and scalogram methods on non-stationary biomedical signals: application to laser Doppler flowmetry recordings

    NASA Astrophysics Data System (ADS)

    Roulier, Rémy; Humeau, Anne; Flatley, Thomas P.; Abraham, Pierre

    2005-11-01

    A significant transient increase in laser Doppler flowmetry (LDF) signals is observed in response to a local and progressive cutaneous pressure application on healthy subjects. This reflex may be impaired in diabetic patients. The work presents a comparison between two signal processing methods that provide a clarification of this phenomenon. Analyses by the scalogram and the Hilbert-Huang transform (HHT) of LDF signals recorded at rest and during a local and progressive cutaneous pressure application are performed on healthy and type 1 diabetic subjects. Three frequency bands, corresponding to myogenic, neurogenic and endothelial related metabolic activities, are studied at different time intervals in order to take into account the dynamics of the phenomenon. The results show that both the scalogram and the HHT methods lead to the same conclusions concerning the comparisons of the myogenic, neurogenic and endothelial related metabolic activities—during the progressive pressure and at rest—in healthy and diabetic subjects. However, the HHT shows more details that may be obscured by the scalogram. Indeed, the non-locally adaptative limitations of the scalogram can remove some definition from the data. These results may improve knowledge on the above-mentioned reflex as well as on non-stationary biomedical signal processing methods.

  1. BioSigPlot: an opensource tool for the visualization of multi-channel biomedical signals with Matlab.

    PubMed

    Boudet, Samuel; Peyrodie, Laurent; Gallois, Philippe; de l'Aulnoit, Denis Houzé; Cao, Hua; Forzy, Gérard

    2013-01-01

    This paper presents a Matlab-based software (MathWorks inc.) called BioSigPlot for the visualization of multi-channel biomedical signals, particularly for the EEG. This tool is designed for researchers on both engineering and medicine who have to collaborate to visualize and analyze signals. It aims to provide a highly customizable interface for signal processing experimentation in order to plot several kinds of signals while integrating the common tools for physician. The main advantages compared to other existing programs are the multi-dataset displaying, the synchronization with video and the online processing. On top of that, this program uses object oriented programming, so that the interface can be controlled by both graphic controls and command lines. It can be used as EEGlab plug-in but, since it is not limited to EEG, it would be distributed separately. BioSigPlot is distributed free of charge (http://biosigplot.sourceforge.net), under the terms of GNU Public License for non-commercial use and open source development. PMID:24110098

  2. Surface Characteristics of Titanium during ECM Process for Biomedical Applications

    SciTech Connect

    Dhobe, Shirish D.; Doloi, B.; Bhattacharyya, B.

    2011-01-17

    Electrochemical machining is described as the controlled removal of metal by anodic dissolution of the workpiece in electrolyte cell. Titanium is extensively used in aerospace, defence, biomedical applications. The human response to implanted titanium parts strongly related to the implant surface conditions. The aim of this paper is to present experimental investigation on electrochemically machined surface characteristics acquired on titanium, utilizing developed cross flow electrolyte system. It is observed that applied voltage and electrolyte flow rate are the some of the persuading parameter to attain desired surface characteristics on machined surface. Attempt has made to develop surface along with self-generated oxide layer, which facilitates in improving the corrosion and chemical resistance of titanium implant in biomedical application. The surface roughness of oxide layered machined surface obtained within 2.4 {mu}m to 2.93 {mu}m, which is within acceptable value for functional attachment between bone and implant.

  3. Signal processor for processing ultrasonic receiver signals

    DOEpatents

    Fasching, George E.

    1980-01-01

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

  4. Interactive Processing and Visualization of Image Data forBiomedical and Life Science Applications

    SciTech Connect

    Staadt, Oliver G.; Natarjan, Vijay; Weber, Gunther H.; Wiley,David F.; Hamann, Bernd

    2007-02-01

    Background: Applications in biomedical science and life science produce large data sets using increasingly powerful imaging devices and computer simulations. It is becoming increasingly difficult for scientists to explore and analyze these data using traditional tools. Interactive data processing and visualization tools can support scientists to overcome these limitations. Results: We show that new data processing tools and visualization systems can be used successfully in biomedical and life science applications. We present an adaptive high-resolution display system suitable for biomedical image data, algorithms for analyzing and visualization protein surfaces and retinal optical coherence tomography data, and visualization tools for 3D gene expression data. Conclusion: We demonstrated that interactive processing and visualization methods and systems can support scientists in a variety of biomedical and life science application areas concerned with massive data analysis.

  5. Techniques of EMG signal analysis: detection, processing, classification and applications

    PubMed Central

    Hussain, M.S.; Mohd-Yasin, F.

    2006-01-01

    Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications. PMID:16799694

  6. VLSI mixed signal processing system

    NASA Technical Reports Server (NTRS)

    Alvarez, A.; Premkumar, A. B.

    1993-01-01

    An economical and efficient VLSI implementation of a mixed signal processing system (MSP) is presented in this paper. The MSP concept is investigated and the functional blocks of the proposed MSP are described. The requirements of each of the blocks are discussed in detail. A sample application using active acoustic cancellation technique is described to demonstrate the power of the MSP approach.

  7. Line scan CCD image processing for biomedical application

    NASA Astrophysics Data System (ADS)

    Lee, Choon-Young; Yan, Lei; Lee, Sang-Ryong

    2010-02-01

    Blood samples are frequently analyzed for the blood disorders or other diseases in the research and clinic applications. Most of the analyses are related to blood cell counts and blood cell sizes. In this paper, the line scan CCD imaging system is developed, which is based on the Texas Instruments' TMS320C6416T (DSP6416), a high performance digital signal processor and Altera's Field programmable Gate Array (FPGA) EP3C25F324. It is used to acquire and process the images of blood cells for counting the number of cells, sizing and positioning them. The cell image is captured by line scan CCD sensor and then the digital image data converted by Analogue Front-End (AFE) are transferred into FPGA, after pre-processing they are transferred into DSP6416 through the interface of First In First Out (FIFO) in FPGA and External Memory Interfaces (EMIF) of DSP6416. Then the image data are processed in DSP6416. Experimental results show that this system is useful and efficient.

  8. A 1V low power second-order delta-sigma modulator for biomedical signal application.

    PubMed

    Hsu, Chih-Han; Tang, Kea-Tiong

    2013-01-01

    This paper presents the design and implementation of a low-power delta-sigma modulator for biomedical application with a standard 90 nm CMOS technology. The delta-sigma architecture is implemented as 2nd order feedforward architecture. A low quiescent current operational transconductance amplifier (OTA) is utilized to reduce power consumption. This delta-sigma modulator operated in 1V power supply, and achieved 64.87 dB signal to noise distortion ratio (SNDR) at 10 KHz bandwidth with an oversampling ratio (OSR) of 64. The power consumption is 17.14 µW, and the figure-of-merit (FOM) is 0.60 pJ/conv. PMID:24110111

  9. Acoustic signal processing toolbox for array processing

    NASA Astrophysics Data System (ADS)

    Pham, Tien; Whipps, Gene T.

    2003-08-01

    The US Army Research Laboratory (ARL) has developed an acoustic signal processing toolbox (ASPT) for acoustic sensor array processing. The intent of this document is to describe the toolbox and its uses. The ASPT is a GUI-based software that is developed and runs under MATLAB. The current version, ASPT 3.0, requires MATLAB 6.0 and above. ASPT contains a variety of narrowband (NB) and incoherent and coherent wideband (WB) direction-of-arrival (DOA) estimation and beamforming algorithms that have been researched and developed at ARL. Currently, ASPT contains 16 DOA and beamforming algorithms. It contains several different NB and WB versions of the MVDR, MUSIC and ESPRIT algorithms. In addition, there are a variety of pre-processing, simulation and analysis tools available in the toolbox. The user can perform simulation or real data analysis for all algorithms with user-defined signal model parameters and array geometries.

  10. 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.

  11. 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.

  12. Analysis of biomedical signals by flicker-noise spectroscopy: Identification of photosensitive epilepsy using magnetoencephalograms

    NASA Astrophysics Data System (ADS)

    Timashev, S. F.; Polyakov, Yu. S.; Yulmetyev, R. M.; Demin, S. A.; Panischev, O. Yu.; Shimojo, S.; Bhattacharya, J.

    2009-04-01

    The flicker-noise spectroscopy (FNS) approach is used to determine the dynamic characteristics of neuromagnetic responses by analyzing the magnetoencephalographic (MEG) signals recorded as the response of a group of control human subjects and a patient with photosensitive epilepsy (PSE) to equiluminant flickering stimuli of different color combinations. Parameters characterizing the analyzed stochastic biomedical signals for different frequency bands are identified. It is shown that the classification of the parameters of analyzed MEG responses with respect to different frequency bands makes it possible to separate the contribution of the chaotic component from the overall complex dynamics of the signals. It is demonstrated that the chaotic component can be adequately described by the anomalous diffusion approximation in the case of control subjects. On the other hand, the chaotic component for the patient is characterized by a large number of high-frequency resonances. This implies that healthy organisms can suppress the perturbations brought about by the flickering stimuli and reorganize themselves. The organisms affected by photosensitive epilepsy no longer have this ability. This result also gives a way to simulate the separate stages of the brain cortex activity in vivo. The examples illustrating the use of the “FNS device” for identifying even the slightest individual differences in the activity of human brains using their responses to external standard stimuli show a unique possibility to develop the “individual medicine” of the future.

  13. Lagrange wavelets for signal processing.

    PubMed

    Shi, Z; Wei, G W; Kouri, D J; Hoffman, D K; Bao, Z

    2001-01-01

    This paper deals with the design of interpolating wavelets based on a variety of Lagrange functions, combined with novel signal processing techniques for digital imaging. Halfband Lagrange wavelets, B-spline Lagrange wavelets and Gaussian Lagrange (Lagrange distributed approximating functional (DAF)) wavelets are presented as specific examples of the generalized Lagrange wavelets. Our approach combines the perceptually dependent visual group normalization (VGN) technique and a softer logic masking (SLM) method. These are utilized to rescale the wavelet coefficients, remove perceptual redundancy and obtain good visual performance for digital image processing. PMID:18255493

  14. Wave-based signal processing

    NASA Astrophysics Data System (ADS)

    McClure, Mark Richard

    The efficacy of imbedding knowledge of wave-scattering phenomenology into the processing of remote-sensing data is examined. In particular, the processing of radar and sonar phase history and synthetic-aperture imagery is considered. Algorithms are developed for effecting signal denoising, feature extraction (for use in target identification/classification) and detection. Three classes of algorithms are presented: (1) superresolution, (2) adaptive-signal decomposition, and (3) template matching. A superresolution signal-processing algorithm is used for the identification of wavefronts from the fields scattered from several canonical targets. Particular wave objects that are examined are single and multiple edge diffraction, scattering from flat and curved surfaces, cone diffraction, and creeping waves. General properties of superresolution processing of such data--independent of the particular algorithm used--are assessed through examination of the Cramer-Rao bounds. The method of matching pursuits is used to effect data-adaptive signal decomposition. This algorithm utilizes a nonlinear iterative procedure to project a given waveform onto a particular dictionary. For scattering problems, the most appropriate dictionary is composed of waveobjects consistent with the underlying wave phenomenology. A signal scattered from most targets of interest can be decomposed in terms of wavefronts, resonances, and chirps--and each of these subclasses can be further subdivided based on characteristic wave physics. Here the efficacy of applying the method of matching pursuits with a wave-based dictionary is examined, for the processing of scattering data. Detection test statistics are derived based on matching-pursuits results from each dictionary separately as well as with the cumulative results from multiple dictionaries. Examples are presented using measured data, for wideband, time-domain acoustic scattering from a submerged elastic shell. Finally, a full-wave electromagnetic

  15. Photonic signal processing for biomedical and industrial ultrasonic probes

    NASA Astrophysics Data System (ADS)

    Riza, Nabeel A.

    1996-12-01

    Ultrasonics has been widely used in medical, industrial, and scientific applications. In medical applications, ultrasonics is an essential diagnostic method in internal medicine, urology, and vascular surgery. High-Intensity Focussed Ultrasound (HIFU) and lithotripsy applications use relatively low ultrasonic frequencies (< 100 KHz), while a 5-15 MHz band is typically used in diagnostic external cavity imaging ultrasound. Today, with endoscopic applications in mind, a very high ultrasonic frequency, e.g., 100 MHz, probe with high (> 50%) instantaneous bandwidths is highly desirable as higher frequencies give higher imaging resolution and smaller physical dimensions of the front-end intracavity transducer array. It is desirable to have an ultrasonic energy control system that, with minimal hardware change, is compact and can operate over wide tunable and instantaneous bandwidths a requirement for different ultrasonic medical modes. Today, passive fiber-optics (FO's) coupled with active photonic devices, could lead to this multi-band, ultra-compact ultrasonic system. Hence, we have put forth, perhaps, the first proposal using photonic beamforming and fiber remoting of the front-end ultrasonic probe, for both narrowband1 and wideband2-3 ultrasonic arrays.

  16. Nanotubes for noisy signal processing

    NASA Astrophysics Data System (ADS)

    Lee, Ian Yenyin

    Nanotubes can process noisy signals. We present two central results in support of this general thesis and make an informed extrapolation that uses nanotubes to improve body armor. The first result is that noise can help nanotubes detect weak signals. The finding confirmed a stochastic-resonance theoretical prediction that noise can enhance detection at the nano-level. Laboratory experiments with nanotubes showed that three types of noise improved three measures of detection. Small amounts of Gaussian, uniform, and Cauchy additive white noise increased mutual-information, cross-correlation, and bit-error-rate measures before degrading them with further increases in noise. Nanotubes can apply this noise-enhancement and nanotube electrical and mechanical properties to improve signal processing. Similar noise enhancement may benefit a proposed nanotube-array cochlear-model spectral processing. The second result is that nanotube antennas can directly detect narrowband electromagnetic (EM) signals. The finding showed that nanotube and thin-wire dipoles are similar: They are resonant and narrowband and can implement linear-array designs if the EM waves in the nanotubes propagate at or near the free-space velocity of light. The nanotube-antenna prediction is based on a Fresnel-zone or near-zone analysis of antenna impedance using a quantum-conductor model. The analysis also predicts a failure to resonate if the nanotube EM-wave propagation is much slower than free-space light propagation. We extrapolate based on applied and theoretical analysis of body armor. Field experiments used a baseball comparison and statistical and other techniques to model body-armor bruising effects. A baseball comparison showed that a large caliber handgun bullet can hit an armored chest as hard as a fast baseball can hit a bare chest. Adaptive fuzzy systems learned to predict a bruise profile directly from the experimental data and also from statistical analysis of the data. Nanotube signal

  17. Nuclear sensor signal processing circuit

    DOEpatents

    Kallenbach, Gene A.; Noda, Frank T.; Mitchell, Dean J.; Etzkin, Joshua L.

    2007-02-20

    An apparatus and method are disclosed for a compact and temperature-insensitive nuclear sensor that can be calibrated with a non-hazardous radioactive sample. The nuclear sensor includes a gamma ray sensor that generates tail pulses from radioactive samples. An analog conditioning circuit conditions the tail-pulse signals from the gamma ray sensor, and a tail-pulse simulator circuit generates a plurality of simulated tail-pulse signals. A computer system processes the tail pulses from the gamma ray sensor and the simulated tail pulses from the tail-pulse simulator circuit. The nuclear sensor is calibrated under the control of the computer. The offset is adjusted using the simulated tail pulses. Since the offset is set to zero or near zero, the sensor gain can be adjusted with a non-hazardous radioactive source such as, for example, naturally occurring radiation and potassium chloride.

  18. Noninvasive biomedical sensor

    NASA Astrophysics Data System (ADS)

    Ling, Daniel; Bullock, Audra

    2003-07-01

    A non-invasive biomedical sensor for monitoring glucose levels is described. The sensor utilizes laser light to determine glucose levels in urine, but could also be used for drug screening and diagnosis of other medical conditions. The glucose measurement is based on modulation spectroscopy with harmonic analysis. Active signal processing and filtering are used to increase the signal-to-noise ratio and decreases the measurement time to allow for real time sample analysis. Preliminary data are given which show the concentration of glucose in a control sample. Future applications of this technology, for example, as a portable multipurpose bio-medical analysis tool, are explored.

  19. Advanced detectors and signal processing

    NASA Technical Reports Server (NTRS)

    Greve, D. W.; Rasky, P. H. L.; Kryder, M. H.

    1986-01-01

    Continued progress is reported toward development of a silicon on garnet technology which would allow fabrication of advanced detection and signal processing circuits on bubble memories. The first integrated detectors and propagation patterns have been designed and incorporated on a new mask set. In addition, annealing studies on spacer layers are performed. Based on those studies, a new double layer spacer is proposed which should reduce contamination of the silicon originating in the substrate. Finally, the magnetic sensitivity of uncontaminated detectors from the last lot of wafers is measured. The measured sensitivity is lower than anticipated but still higher than present magnetoresistive detectors.

  20. Signal Processing Expert Code (SPEC)

    SciTech Connect

    Ames, H.S.

    1985-12-01

    The purpose of this paper is to describe a prototype expert system called SPEC which was developed to demonstrate the utility of providing an intelligent interface for users of SIG, a general purpose signal processing code. The expert system is written in NIL, runs on a VAX 11/750 and consists of a backward chaining inference engine and an English-like parser. The inference engine uses knowledge encoded as rules about the formats of SIG commands and about how to perform frequency analyses using SIG. The system demonstrated that expert system can be used to control existing codes.

  1. Texture in Biomedical Images

    NASA Astrophysics Data System (ADS)

    Petrou, Maria

    An overview of texture analysis methods is given and the merits of each method for biomedical applications are discussed. Methods discussed include Markov random fields, Gibbs distributions, co-occurrence matrices, Gabor functions and wavelets, Karhunen-Loève basis images, and local symmetry and orientation from the monogenic signal. Some example applications of texture to medical image processing are reviewed.

  2. VLSI systems design for digital signal processing. Volume 1 - Signal processing and signal processors

    NASA Astrophysics Data System (ADS)

    Bowen, B. A.; Brown, W. R.

    This book is concerned with the design of digital signal processing systems which utilize VLSI (Very Large Scale Integration) components. The presented material is intended for use by electrical engineers at the senior undergraduate or introductory graduate level. It is the purpose of this volume to present an overview of the important elements of background theory, processing techniques, and hardware evolution. Digital signals are considered along with linear systems and digital filters, taking into account the transform analysis of deterministic signals, a statistical signal model, time domain representations of discrete-time linear systems, and digital filter design techniques and implementation issues. Attention is given to aspects of detection and estimation, digital signal processing algorithms and techniques, issues which must be resolved in a processor design methodology, the fundamental concepts of high performance processing in terms of two early super computers, and the extension of these concepts to more recent processors.

  3. BioThreads: a novel VLIW-based chip multiprocessor for accelerating biomedical image processing applications.

    PubMed

    Stevens, David; Chouliaras, Vassilios; Azorin-Peris, Vicente; Zheng, Jia; Echiadis, Angelos; Hu, Sijung

    2012-06-01

    We discuss BioThreads, a novel, configurable, extensible system-on-chip multiprocessor and its use in accelerating biomedical signal processing applications such as imaging photoplethysmography (IPPG). BioThreads is derived from the LE1 open-source VLIW chip multiprocessor and efficiently handles instruction, data and thread-level parallelism. In addition, it supports a novel mechanism for the dynamic creation, and allocation of software threads to uncommitted processor cores by implementing key POSIX Threads primitives directly in hardware, as custom instructions. In this study, the BioThreads core is used to accelerate the calculation of the oxygen saturation map of living tissue in an experimental setup consisting of a high speed image acquisition system, connected to an FPGA board and to a host system. Results demonstrate near-linear acceleration of the core kernels of the target blood perfusion assessment with increasing number of hardware threads. The BioThreads processor was implemented on both standard-cell and FPGA technologies; in the first case and for an issue width of two, full real-time performance is achieved with 4 cores whereas on a mid-range Xilinx Virtex6 device this is achieved with 10 dual-issue cores. An 8-core LE1 VLIW FPGA prototype of the system achieved 240 times faster execution time than the scalar Microblaze processor demonstrating the scalability of the proposed solution to a state-of-the-art FPGA vendor provided soft CPU core. PMID:23853147

  4. New Windows based Color Morphological Operators for Biomedical Image Processing

    NASA Astrophysics Data System (ADS)

    Pastore, Juan; Bouchet, Agustina; Brun, Marcel; Ballarin, Virginia

    2016-04-01

    Morphological image processing is well known as an efficient methodology for image processing and computer vision. With the wide use of color in many areas, the interest on the color perception and processing has been growing rapidly. Many models have been proposed to extend morphological operators to the field of color images, dealing with some new problems not present previously in the binary and gray level contexts. These solutions usually deal with the lattice structure of the color space, or provide it with total orders, to be able to define basic operators with required properties. In this work we propose a new locally defined ordering, in the context of window based morphological operators, for the definition of erosions-like and dilation-like operators, which provides the same desired properties expected from color morphology, avoiding some of the drawbacks of the prior approaches. Experimental results show that the proposed color operators can be efficiently used for color image processing.

  5. Commercial applications in biomedical processing in the microgravity environment

    NASA Astrophysics Data System (ADS)

    Johnson, Terry C.; Taub, Floyd

    1995-01-01

    A series of studies have shown that a purified cell regulatory sialoglycopeptide (CeReS) that arrests cell division and induces cellular differentiation is fully capable of functionally interacting with target insect and mammalian cells in the microgravity environment. Data from several shuttle missions suggest that the signal transduction events that are known to be associated with CeReS action function as well in microgravity as in ground-based experiments. The molecular events known to be associated with CeReS include an ability to interfere with Ca2+ metabolism, the subsequent alkalinization of cell cytosol, and the inhibition of the phosphorylation of the nuclear protein product encoded by the retinoblastoma (RB) gene. The ability of CeReS to function in microgravity opens a wide variety of applications in space life sciences.

  6. Antimicrobial thermoplastic materials for biomedical applications prepared by melt processing

    NASA Astrophysics Data System (ADS)

    Botta, L.; Scaffaro, R.; Ceraulo, M.; Gallo, G.

    2014-05-01

    In this work thermoplastic polymers with antimicrobial properties were prepared by incorporating an antibiotic, i.e., ciprofloxacin (CFX), by melt processing. Two different polymers were used as matrices, i.e., polypropylene (PP) and poly(lactid acid) (PLA) and different concentrations of CFX have been incorporated. The antimicrobial properties, the release kinetic and the mechanical performances of the prepared materials were evaluated.

  7. Large-scale combining signals from both biomedical literature and the FDA Adverse Event Reporting System (FAERS) to improve post-marketing drug safety signal detection

    PubMed Central

    2014-01-01

    Background Independent data sources can be used to augment post-marketing drug safety signal detection. The vast amount of publicly available biomedical literature contains rich side effect information for drugs at all clinical stages. In this study, we present a large-scale signal boosting approach that combines over 4 million records in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and over 21 million biomedical articles. Results The datasets are comprised of 4,285,097 records from FAERS and 21,354,075 MEDLINE articles. We first extracted all drug-side effect (SE) pairs from FAERS. Our study implemented a total of seven signal ranking algorithms. We then compared these different ranking algorithms before and after they were boosted with signals from MEDLINE sentences or abstracts. Finally, we manually curated all drug-cardiovascular (CV) pairs that appeared in both data sources and investigated whether our approach can detect many true signals that have not been included in FDA drug labels. We extracted a total of 2,787,797 drug-SE pairs from FAERS with a low initial precision of 0.025. The ranking algorithm combined signals from both FAERS and MEDLINE, significantly improving the precision from 0.025 to 0.371 for top-ranked pairs, representing a 13.8 fold elevation in precision. We showed by manual curation that drug-SE pairs that appeared in both data sources were highly enriched with true signals, many of which have not yet been included in FDA drug labels. Conclusions We have developed an efficient and effective drug safety signal ranking and strengthening approach We demonstrate that large-scale combining information from FAERS and biomedical literature can significantly contribute to drug safety surveillance. PMID:24428898

  8. The National Institute of Biomedical Imaging and Bioengineering and NIH grant process: an overview.

    PubMed

    Wolbarst, Anthony B; Hendee, William R

    2007-01-01

    The National Institutes of Health (NIH) comprise the largest single source of funding in the world for the support of biomedical research. Much of the work of the NIH focuses on the elucidation of fundamental biophysical, biochemical, and biologic aspects of the molecular, cellular, and tissue processes underlying both healthy and diseased states of biologic systems and on the development of cures for the latter. In 2000, the National Institute of Biomedical Imaging and Bioengineering (NIBIB) was created with a somewhat different focus: Rather than concentration on a specific organ system or category of disease, the primary objective of the NIBIB is the advancement of technologies and tools that contribute to all aspects of biomedical research and health care delivery, especially in the imaging sciences and bioengineering. This article provides an overview of the ways in which NIH funds research, with an emphasis on NIBIB support of biomedical imaging. It is intended for radiologists, radiation oncologists, medical physicists, and other readers of this journal, especially those with limited experience in the complex process of obtaining NIH grant support. PMID:17185660

  9. Korteweg-de Vries-Kuramoto-Sivashinsky filters in biomedical image processing

    NASA Astrophysics Data System (ADS)

    Arango, Juan C.

    2015-09-01

    The Kuramoto- Sivashinsky operator is applied to the two-dimensional solution of the Korteweg-de Vries equation and the resulting filter is applied via convolution to image processing. The full procedure is implemented using an algorithm: prototyped with the Maple package named Image Tools. Some experiments were performed using biomedical images, infrared images obtained with smartphones and images generated by photon diffusion. The results from these experiments show that the Kuramoto-Sivashinsky-Korteweg-de Vries Filters are excellent tools for enhancement of images with interesting applications in image processing at general and biomedical image processing in particular. It is expected that the incorporation of the Kuramoto-Sivashinsky-Korteweg-de Vries Filters in standard programs for image processing will led to important improvements in various fields of optical engineering.

  10. Characterization of processed tooth hydroxyapatite for potential biomedical implant applications.

    PubMed

    Oktar, F N; Kesenci, K; Pişkin, E

    1999-07-01

    In this study hydroxyapatite (HA) (100-150 microns) derived from freshly-extracted human teeth in laboratory conditions was investigated. Scanning electron microscope (SEM), energy dispersive x-ray spectroscopy (EDXS), wet chemical, ion chromatographic peak method (ICP), atomic absorption, x-ray diffraction and infra-red (IR) were performed separately for HA obtained from dentine and enamel. This naturally derived HA did not differ from synthetic ones. Its production was simple when compared with other methods. Processed tooth HA could safely be used in animal subjects prior to human studies as a graft material after biocompatibility studies fully conducted. PMID:10427420

  11. A Processable Shape Memory Polymer System for Biomedical Applications.

    PubMed

    Hearon, Keith; Wierzbicki, Mark A; Nash, Landon D; Landsman, Todd L; Laramy, Christine; Lonnecker, Alexander T; Gibbons, Michael C; Ur, Sarah; Cardinal, Kristen O; Wilson, Thomas S; Wooley, Karen L; Maitland, Duncan J

    2015-06-24

    Polyurethane shape memory polymers (SMPs) with tunable thermomechanical properties and advanced processing capabilities are synthesized, characterized, and implemented in the design of a microactuator medical device prototype. The ability to manipulate glass transition temperature (Tg ) and crosslink density in low-molecular weight aliphatic thermoplastic polyurethane SMPs is demonstrated using a synthetic approach that employs UV catalyzed thiol-ene "click" reactions to achieve postpolymerization crosslinking. Polyurethanes containing varying C=C functionalization are synthesized, solution blended with polythiol crosslinking agents and photoinitiator and subjected to UV irradiation, and the effects of number of synthetic parameters on crosslink density are reported. Thermomechanical properties are highly tunable, including glass transitions tailorable between 30 and 105 °C and rubbery moduli tailorable between 0.4 and 20 MPa. This new SMP system exhibits high toughness for many formulations, especially in the case of low crosslink density materials, for which toughness exceeds 90 MJ m(-3) at select straining temperatures. To demonstrate the advanced processing capability and synthetic versatility of this new SMP system, a laser-actuated SMP microgripper device for minimally invasive delivery of endovascular devices is fabricated, shown to exhibit an average gripping force of 1.43 ± 0.37 N and successfully deployed in an in vitro experimental setup under simulated physiological conditions. PMID:25925212

  12. BPSK Demodulation Using Digital Signal Processing

    NASA Technical Reports Server (NTRS)

    Garcia, Thomas R.

    1996-01-01

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

  13. Development of a novel forming process for biomedical composites

    NASA Astrophysics Data System (ADS)

    Kennedy, Kenneth Carroll, II

    The technologies of photopolymerization and pultrusion were combined to produce a novel composite-forming process-photopultrusion. The process was used to produce continuous-length, unidirectional-fiber-reinforced-polymer composites (UFRPs) from photopolymerized methacrylate copolymers and silicate-glass fibers. Investigating the basic mechanical and morphological characteristics of 0.5mm-circular UFRPs revealed that exceptional properties were produced with an S2-glasssp°ler reinforcing yarn and a network copolymer matrix of 2,2-Bis (4-(2-hydroxy-3-methacryloxypropoxylphenyl) propane (Bis-GMA) with triethylene glycol dimethacrylate (TEGDMA). The tensile and flexural moduli and the tensile and flexural strengths varied linearly with the %vol-reinforcement; at 66%vol-reinforcement they attained maximums of 63, 60, 2.7, and 1.7GPa, respectively-revealing a high degree of interphasic bonding. At lower %vol-reinforcements the filaments concentrated near the perimeter of the UFRPs. Higher %vol-reinforcements yielded more homogeneous distributions and uniform shapes. Investigating the 3-month hydrothermal aging behaviors of quartz- and S2-glasssp°ler-reinforced UFRPs revealed that both sorbed water in proportion to the polymeric content in the composites (4 to 5%wt-matrix), but that the former also sorbed in proportion to the interfacial surface area. The flexural properties decreased and then stabilized within 1week. The losses ranged from about 0 to 25%-the higher losses corresponding to the moduli of the high-%vol-reinforcement S2-glasssp°ler UFRPs. Notwithstanding this degradation, these highly-reinforced S2-glasssp°ler composites exhibited superior flexural properties (aged modulus and strength ≈53 and 1.2GPa, respectively) that were suitable for structural orthopaedic implantation. This was attributed to the initial development of strong interphasic bonds that were only partially susceptible to hydrolytic degradation. Finally, investigating

  14. 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.

  15. Study Of Adaptive-Array Signal Processing

    NASA Technical Reports Server (NTRS)

    Satorius, Edgar H.; Griffiths, Lloyd

    1990-01-01

    Report describes study of adaptive signal-processing techniques for suppression of mutual satellite interference in mobile (on ground)/satellite communication system. Presents analyses and numerical simulations of performances of two approaches to signal processing for suppression of interference. One approach, known as "adaptive side lobe canceling", second called "adaptive temporal processing".

  16. Correlation theory-based signal processing method for CMF signals

    NASA Astrophysics Data System (ADS)

    Shen, Yan-lin; Tu, Ya-qing

    2016-06-01

    Signal processing precision of Coriolis mass flowmeter (CMF) signals affects measurement accuracy of Coriolis mass flowmeters directly. To improve the measurement accuracy of CMFs, a correlation theory-based signal processing method for CMF signals is proposed, which is comprised of the correlation theory-based frequency estimation method and phase difference estimation method. Theoretical analysis shows that the proposed method eliminates the effect of non-integral period sampling signals on frequency and phase difference estimation. The results of simulations and field experiments demonstrate that the proposed method improves the anti-interference performance of frequency and phase difference estimation and has better estimation performance than the adaptive notch filter, discrete Fourier transform and autocorrelation methods in terms of frequency estimation and the data extension-based correlation, Hilbert transform, quadrature delay estimator and discrete Fourier transform methods in terms of phase difference estimation, which contributes to improving the measurement accuracy of Coriolis mass flowmeters.

  17. Fundamental and applied studies in nanoparticle biomedical imaging, stabilization, and processing

    NASA Astrophysics Data System (ADS)

    Pansare, Vikram J.

    Nanoparticle carrier systems are gaining importance in the rapidly expanding field of biomedical whole animal imaging where they provide long circulating, real time imaging capability. This thesis presents a new paradigm in imaging whereby long wavelength fluorescent or photoacoustically active contrast agents are embedded in the hydrophobic core of nanocarriers formed by Flash NanoPrecipitation. The long wavelength allows for improved optical penetration depth. Compared to traditional contrast agents where fluorophores are placed on the surface, this allows for improved signal, increased stability, and molecular targeting capabilities. Several types of long wavelength hydrophobic dyes based on acene, cyanine, and bacteriochlorin scaffolds are utilized and animal results obtained for nanocarrier systems used in both fluorescent and photoacoustic imaging modes. Photoacoustic imaging is particularly promising due to its high resolution, excellent penetration depth, and ability to provide real-time functional information. Fundamental studies in nanoparticle stabilization are also presented for two systems: model alumina nanoparticles and charge stabilized polystyrene nanoparticles. Motivated by the need for stable suspensions of alumina-based nanocrystals for security printing applications, results are presented for the adsorption of various small molecule charged hydrophobes onto the surface of alumina nanoparticles. Results are also presented for the production of charge stabilized polystyrene nanoparticles via Flash NanoPrecipitation, allowing for the independent control of polymer molecular weight and nanoparticle size, which is not possible by traditional emulsion polymerization routes. Lastly, methods for processing nanoparticle systems are explored. The increasing use of nanoparticle therapeutics in the pharmaceutical industry has necessitated the development of scalable, industrially relevant processing methods. Ultrafiltration is particularly well suited for

  18. Signal processing in ultrasound. [for diagnostic medicine

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  19. Bistatic SAR: Signal Processing and Image Formation.

    SciTech Connect

    Wahl, Daniel E.; Yocky, David A.

    2014-10-01

    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, 2013 on Kirtland Air Force Base, New Mexico.

  20. Processing of real ELT signals for Sarsat

    NASA Astrophysics Data System (ADS)

    Chung, T.; Carter, C. R.

    1987-01-01

    The performance of different processing strategies on real signals recorded from an emergency locator transmitter (ELT) test bed in Ottawa is examined. A processor based on the use of ordered statistics is developed. This new processor greatly reduces the interference produced by the ELT sidebands while maintaining good detection performance on weak signals. In addition, the maximum entropy method is found to be effective in processing ELT signals having noncoherent characteristics.

  1. Fiber-optic lattice signal processing

    NASA Astrophysics Data System (ADS)

    Moslehi, B.; Goodman, J. W.; Shaw, H. J.; Tur, M.

    1984-07-01

    It is pointed out that fiber-optic signal processing devices can be constructed to perform various functions, such as convolution, correlation, matrix operations, and frequency filtering. Previous studies have concentrated on classical tapped-delay-line forms (transversal filters). The present investigation is concerned with different fiber-optic structures, taking into account lattice (or ladder) forms, which can be used as alternatives for performing optical signal processing. The elements to perform the various signal processing operations are considered along with fiber-optic lattice configurations. Aspects of mathematical analysis are discussed, taking into account Z-transform techniques, transfer-matrix and chain-matrix formulations, modern control theory formulations, and positive optical systems. Attention is given to time-domain signal processing applications, and frequency-domain signal processing applications.

  2. Methods of processing biomedical image of retinal macular region of the eye

    NASA Astrophysics Data System (ADS)

    Pavlov, S. V.; Vassilenko, V. B.; Vovkotrub, D. V.; Poplavskaya, A. A.; Hotra, O.

    2013-01-01

    In this paper we report a new method for determination of macular area of the retina obtained by optical coherent tomography (OCT). A novel program of image processing was developed for this purpose. The improved efficiency of proposed tools and it accuracy in the determination of the parameters in the macular area was checked by comparison of results with the standard procedure of processing of the biomedical images of this class. All calculation were obtained from the retina tomograms by using coherent optical topographic scanner STRATUS OCT 3000

  3. BioLemmatizer: a lemmatization tool for morphological processing of biomedical text

    PubMed Central

    2012-01-01

    Background The wide variety of morphological variants of domain-specific technical terms contributes to the complexity of performing natural language processing of the scientific literature related to molecular biology. For morphological analysis of these texts, lemmatization has been actively applied in the recent biomedical research. Results In this work, we developed a domain-specific lemmatization tool, BioLemmatizer, for the morphological analysis of biomedical literature. The tool focuses on the inflectional morphology of English and is based on the general English lemmatization tool MorphAdorner. The BioLemmatizer is further tailored to the biological domain through incorporation of several published lexical resources. It retrieves lemmas based on the use of a word lexicon, and defines a set of rules that transform a word to a lemma if it is not encountered in the lexicon. An innovative aspect of the BioLemmatizer is the use of a hierarchical strategy for searching the lexicon, which enables the discovery of the correct lemma even if the input Part-of-Speech information is inaccurate. The BioLemmatizer achieves an accuracy of 97.5% in lemmatizing an evaluation set prepared from the CRAFT corpus, a collection of full-text biomedical articles, and an accuracy of 97.6% on the LLL05 corpus. The contribution of the BioLemmatizer to accuracy improvement of a practical information extraction task is further demonstrated when it is used as a component in a biomedical text mining system. Conclusions The BioLemmatizer outperforms other tools when compared with eight existing lemmatizers. The BioLemmatizer is released as an open source software and can be downloaded from http://biolemmatizer.sourceforge.net. PMID:22464129

  4. Signal processing methods for MFE plasma diagnostics

    SciTech Connect

    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.

  5. Electronics Signal Processing for Medical Imaging

    NASA Astrophysics Data System (ADS)

    Turchetta, Renato

    This paper describes the way the signal coming from a radiation detector is conditioned and processed to produce images useful for medical applications. First of all, the small signal produce by the radiation is processed by analogue electronics specifically designed to produce a good signal-over-noise ratio. The optimised analogue signal produced at this stage can then be processed and transformed into digital information that is eventually stored in a computer, where it can be further processed as required. After an introduction to the general requirements of the processing electronics, we will review the basic building blocks that process the `tiny' analogue signal coming from a radiation detector. We will in particular analyse how it is possible to optimise the signal-over-noise ratio of the electronics. Some exercises, developed in the tutorial, will help to understand this fundamental part. The blocks needed to process the analogue signal and transform it into a digital code will be described. The description of electronics systems used for medical imaging systems will conclude the lecture.

  6. 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. PMID:27243208

  7. Multiwavelet design for cardiac signal processing.

    PubMed

    Peelers, R L M; Karel, J M H; Westra, R L; Haddad, S A P; Serdijn, W A

    2006-01-01

    An approach for designing multiwavelets is introduced, for use in cardiac signal processing. The parameterization of the class of multiwavelets is in terms of associated FIR polyphase all-pass filters. Orthogonality and a balanced vanishing moment of order 1 are built into the parameterization. An optimization criterion is developed to associate the wavelets with different meaningful segments of a signal. This approach is demonstrated on the simultaneous detection of QRS-complexes and T-peaks in ECG signals. PMID:17946917

  8. Optical Profilometers Using Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Hall, Gregory A.; Youngquist, Robert; Mikhael, Wasfy

    2006-01-01

    A method of adaptive signal processing has been proposed as the basis of a new generation of interferometric optical profilometers for measuring surfaces. The proposed profilometers would be portable, hand-held units. Sizes could be thus reduced because the adaptive-signal-processing method would make it possible to substitute lower-power coherent light sources (e.g., laser diodes) for white light sources and would eliminate the need for most of the optical components of current white-light profilometers. The adaptive-signal-processing method would make it possible to attain scanning ranges of the order of decimeters in the proposed profilometers.

  9. Biomedical application of wavelets: analysis of electroencephalograph signals for monitoring depth of anesthesia

    NASA Astrophysics Data System (ADS)

    Abbate, Agostino; Nayak, A.; Koay, J.; Roy, R. J.; Das, Pankaj K.

    1996-03-01

    The wavelet transform (WT) has been used to study the nonstationary information in the electroencephalograph (EEG) as an aid in determining the anesthetic depth. A complex analytic mother wavelet is utilized to obtain the time evolution of the various spectral components of the EEG signal. The technique is utilized for the detection and spectral analysis of transient and background processes in the awake and asleep states. It can be observed that the response of both states before the application of the stimulus is similar in amplitude but not in spectral contents, which suggests a background activity of the brain. The brain reacts to the external stimulus in two different modes depending on the state of consciousness of the subject. In the case of awake state, there is an evident increase in response, while for the sleep state a reduction in this activity is observed. This analysis seems to suggest that the brain has an ongoing background process that monitors external stimulus in both the sleep and awake states.

  10. Sparse representation in speech signal processing

    NASA Astrophysics Data System (ADS)

    Lee, Te-Won; Jang, Gil-Jin; Kwon, Oh-Wook

    2003-11-01

    We review the sparse representation principle for processing speech signals. A transformation for encoding the speech signals is learned such that the resulting coefficients are as independent as possible. We use independent component analysis with an exponential prior to learn a statistical representation for speech signals. This representation leads to extremely sparse priors that can be used for encoding speech signals for a variety of purposes. We review applications of this method for speech feature extraction, automatic speech recognition and speaker identification. Furthermore, this method is also suited for tackling the difficult problem of separating two sounds given only a single microphone.

  11. Signal processing by the endosomal system.

    PubMed

    Villaseñor, Roberto; Kalaidzidis, Yannis; Zerial, Marino

    2016-04-01

    Cells need to decode chemical or physical signals from their environment in order to make decisions on their fate. In the case of signalling receptors, ligand binding triggers a cascade of chemical reactions but also the internalization of the activated receptors in the endocytic pathway. Here, we highlight recent studies revealing a new role of the endosomal network in signal processing. The diversity of entry pathways and endosomal compartments is exploited to regulate the kinetics of receptor trafficking, and interactions with specific signalling adaptors and effectors. By governing the spatio-temporal distribution of signalling molecules, the endosomal system functions analogously to a digital-analogue computer that regulates the specificity and robustness of the signalling response. PMID:26921695

  12. Digital signal processor and programming system for parallel signal processing

    SciTech Connect

    Van den Bout, D.E.

    1987-01-01

    This thesis describes an integrated assault upon the problem of designing high-throughput, low-cost digital signal-processing systems. The dual prongs of this assault consist of: (1) the design of a digital signal processor (DSP) which efficiently executes signal-processing algorithms in either a uniprocessor or multiprocessor configuration, (2) the PaLS programming system which accepts an arbitrary algorithm, partitions it across a group of DSPs, synthesizes an optimal communication link topology for the DSPs, and schedules the partitioned algorithm upon the DSPs. The results of applying a new quasi-dynamic analysis technique to a set of high-level signal-processing algorithms were used to determine the uniprocessor features of the DSP design. For multiprocessing applications, the DSP contains an interprocessor communications port (IPC) which supports simple, flexible, dataflow communications while allowing the total communication bandwidth to be incrementally allocated to achieve the best link utilization. The net result is a DSP with a simple architecture that is easy to program for both uniprocessor and multi-processor modes of operation. The PaLS programming system simplifies the task of parallelizing an algorithm for execution upon a multiprocessor built with the DSP.

  13. 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. PMID:2180633

  14. [Anesthesia in the Signal Processing Methods].

    PubMed

    Gu, Jiajun; Huang, Yan; Ye, Jilun; Wang, Kaijun; Zhang, Meimei

    2015-09-01

    Anesthesia plays an essential role in clinical operations. Guiding anesthesia by EEG signals is one of the most promising methods at present and it has obtained good results. The analysis and process of the EEG signals in anesthesia can provide clean signal for further research. This paper used variance threshold method to remove the mutation fast and large interfering signals; and used notch filter to remove frequency interference, smoothing filter to remove baseline drift and Butterworth low-pass filter to remove high frequency noise at the same time. In addition to this, the translation invariant wavelet method to remove interference noise on the signals which was after the classical filter and retained non-stationary characteristics was used to evaluate parameter calculation. By comparing the calculated parameters from treated signal using this paper's methods and untreated signal and standard signal, the standard deviation and correlation has been improved, particularly the major parameters BetaR, which provides better signal for integration of multi-parameter to evaluate depth of anesthesia index for the latter. PMID:26904870

  15. Intelligent Signal Processing for Detection System Optimization

    SciTech Connect

    Fu, C Y; Petrich, L I; Daley, P F; Burnham, A K

    2004-06-18

    A wavelet-neural network signal processing method has demonstrated approximately tenfold improvement in the detection limit of various nitrogen and phosphorus compounds over traditional signal-processing methods in analyzing the output of a thermionic detector attached to the output of a gas chromatograph. A blind test was conducted to validate the lower detection limit. All fourteen of the compound spikes were detected when above the estimated threshold, including all three within a factor of two above. In addition, two of six were detected at levels 1/2 the concentration of the nominal threshold. We would have had another two correct hits if we had allowed human intervention to examine the processed data. One apparent false positive in five nulls was traced to a solvent impurity, whose presence was identified by running a solvent aliquot evaporated to 1% residual volume, while the other four nulls were properly classified. We view this signal processing method as broadly applicable in analytical chemistry, and we advocate that advanced signal processing methods be applied as directly as possible to the raw detector output so that less discriminating preprocessing and post-processing does not throw away valuable signal.

  16. Intelligent Signal Processing for Detection System Optimization

    SciTech Connect

    Fu, C Y; Petrich, L I; Daley, P F; Burnham, A K

    2004-12-05

    A wavelet-neural network signal processing method has demonstrated approximately tenfold improvement over traditional signal-processing methods for the detection limit of various nitrogen and phosphorus compounds from the output of a thermionic detector attached to a gas chromatograph. A blind test was conducted to validate the lower detection limit. All fourteen of the compound spikes were detected when above the estimated threshold, including all three within a factor of two above the threshold. In addition, two of six spikes were detected at levels of 1/2 the concentration of the nominal threshold. Another two of the six would have been detected correctly if we had allowed human intervention to examine the processed data. One apparent false positive in five nulls was traced to a solvent impurity, whose presence was subsequently identified by analyzing a solvent aliquot evaporated to 1% residual volume, while the other four nulls were properly classified. We view this signal processing method as broadly applicable in analytical chemistry, and we advocate that advanced signal processing methods should be applied as directly as possible to the raw detector output so that less discriminating preprocessing and post-processing does not throw away valuable signal.

  17. Haotic, Fractal, and Nonlinear Signal Processing. Proceedings

    SciTech Connect

    Katz, R.A.

    1996-10-01

    These proceedings include papers presented at the Third Technical Conference on Nonlinear Dynamics and Full{minus}Spectrum Processing held in Mystic, Connecticut. The Conference focus was on the latest advances in chaotic, fractal and nonlinear signal processing methods. Topics of discussion covered in the Conference include: mathematical frontiers; predictability and control of chaos, detection and classification with applications in acoustics; advanced applied signal processing methods(linear and nonlinear); stochastic resonance; machinery diagnostics; turbulence; geophysics; medicine; and recent novel approaches to modeling nonlinear systems. There were 58 papers in the conference and all have been abstracted for the Energy Science and Technology database. (AIP)

  18. Group-normalized wavelet packet signal processing

    NASA Astrophysics Data System (ADS)

    Shi, Zhuoer; Bao, Zheng

    1997-04-01

    Since the traditional wavelet and wavelet packet coefficients do not exactly represent the strength of signal components at the very time(space)-frequency tilling, group- normalized wavelet packet transform (GNWPT), is presented for nonlinear signal filtering and extraction from the clutter or noise, together with the space(time)-frequency masking technique. The extended F-entropy improves the performance of GNWPT. For perception-based image, soft-logic masking is emphasized to remove the aliasing with edge preserved. Lawton's method for complex valued wavelets construction is extended to generate the complex valued compactly supported wavelet packets for radar signal extraction. This kind of wavelet packets are symmetry and unitary orthogonal. Well-defined wavelet packets are chosen by the analysis remarks on their time-frequency characteristics. For real valued signal processing, such as images and ECG signal, the compactly supported spline or bi- orthogonal wavelet packets are preferred for perfect de- noising and filtering qualities.

  19. Time domain cyclostationarity signal-processing tools

    NASA Astrophysics Data System (ADS)

    Léonard, François

    2015-10-01

    This paper proposes four different time-domain tools to estimate first-order time cyclostationary signals without the need of a keyphasor signal. Applied to gearbox signals, these tacho-less methods appear intuitively simple, offer user-friendly graphic interfaces to visualize a pattern and allow the retrieval and removal of the selected cyclostationarity components in order to process higher-order spectra. Two of these tools can deal with time-varying operating conditions since they use an adaptive resampled signal driven by the vibration signal itself for order tracking. Three coherency indicators are proposed, one for every sample of the time pattern, one for each impact (tooth shock) observed in the gear mesh pattern, and one for the whole pattern. These indicators are used to detect a cyclostationarity and analyze the pattern repeatability. A gear mesh graph is also proposed to illustrate the cyclostationarity in 3D.

  20. Complexity of Receptor Tyrosine Kinase Signal Processing

    PubMed Central

    Volinsky, Natalia; Kholodenko, Boris N.

    2013-01-01

    Our knowledge of molecular mechanisms of receptor tyrosine kinase (RTK) signaling advances with ever-increasing pace. Yet our understanding of how the spatiotemporal dynamics of RTK signaling control specific cellular outcomes has lagged behind. Systems-centered experimental and computational approaches can help reveal how overlapping networks of signal transducers downstream of RTKs orchestrate specific cell-fate decisions. We discuss how RTK network regulatory structures, which involve the immediate posttranslational and delayed transcriptional controls by multiple feed forward and feedback loops together with pathway cross talk, adapt cells to the combinatorial variety of external cues and conditions. This intricate network circuitry endows cells with emerging capabilities for RTK signal processing and decoding. We illustrate how mathematical modeling facilitates our understanding of RTK network behaviors by unraveling specific systems properties, including bistability, oscillations, excitable responses, and generation of intricate landscapes of signaling activities. PMID:23906711

  1. Complexity of EEG-signal in Time Domain - Possible Biomedical Application

    NASA Astrophysics Data System (ADS)

    Klonowski, Wlodzimierz; Olejarczyk, Elzbieta; Stepien, Robert

    2002-07-01

    Human brain is a highly complex nonlinear system. So it is not surprising that in analysis of EEG-signal, which represents overall activity of the brain, the methods of Nonlinear Dynamics (or Chaos Theory as it is commonly called) can be used. Even if the signal is not chaotic these methods are a motivating tool to explore changes in brain activity due to different functional activation states, e.g. different sleep stages, or to applied therapy, e.g. exposure to chemical agents (drugs) and physical factors (light, magnetic field). The methods supplied by Nonlinear Dynamics reveal signal characteristics that are not revealed by linear methods like FFT. Better understanding of principles that govern dynamics and complexity of EEG-signal can help to find `the signatures' of different physiological and pathological states of human brain, quantitative characteristics that may find applications in medical diagnostics.

  2. Signal processing in cryogenic particle detection

    NASA Astrophysics Data System (ADS)

    Yuryev, Y. N.; Jang, Y. S.; Kim, S. K.; Lee, K. B.; Lee, M. K.; Lee, S. J.; Yoon, W. S.; Kim, Y. H.

    2011-04-01

    We describe a signal-processing program for a data acquisition system for cryogenic particle detectors. The program is based on an optimal-filtering method for high-resolution measurement of calorimetric signals with a significant amount of noise of unknown origin and non-stationary behavior. The program was applied to improve the energy resolution of the alpha particle spectrum of an 241Am source.

  3. Discrete Signal Processing on Graphs: Sampling Theory

    NASA Astrophysics Data System (ADS)

    Chen, Siheng; Varma, Rohan; Sandryhaila, Aliaksei; Kovacevic, Jelena

    2015-12-01

    We propose a sampling theory for signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory. We show that perfect recovery is possible for graph signals bandlimited under the graph Fourier transform. The sampled signal coefficients form a new graph signal, whose corresponding graph structure preserves the first-order difference of the original graph signal. For general graphs, an optimal sampling operator based on experimentally designed sampling is proposed to guarantee perfect recovery and robustness to noise; for graphs whose graph Fourier transforms are frames with maximal robustness to erasures as well as for Erd\\H{o}s-R\\'enyi graphs, random sampling leads to perfect recovery with high probability. We further establish the connection to the sampling theory of finite discrete-time signal processing and previous work on signal recovery on graphs. To handle full-band graph signals, we propose a graph filter bank based on sampling theory on graphs. Finally, we apply the proposed sampling theory to semi-supervised classification on online blogs and digit images, where we achieve similar or better performance with fewer labeled samples compared to previous work.

  4. New Optical Methods for Signal Processing

    NASA Astrophysics Data System (ADS)

    Zhang, Yan

    This doctoral thesis studies the optical implementations of various new algorithms and methods for large bandwidth signal and image processing. Among the schemes to be studied are the long data stream convolution/correlation, the Gabor and the wavelet transforms, and their applications to system failure prediction, dense target signal processing and image coding. Based on the Chinese remainder theorem, optically implementable algorithms are described, which convert the convolution/correlation of long data streams to relatively small scale linear operations such as a group of short -term vector-matrix multiplications or short-term convolutions/correlations. The proposed algorithms can be realized by using the existing optical analog data processors. Simulations were performed to prove their validity. Technical problems and fundamental limitations of the above schemes are studied. Following the consideration of the above time domain operations, signal's representations in joint time -frequency (scale) domain are then considered. An opto -electronic Gabor coefficient processor is designed to perform the Gabor transform on short one-dimensional (1-D) signals in real-time. Some experimental results are presented to confirm the operational principle of the system. As an application of this processor, Gabor transform based transient signal detection is studied. Other schemes for implementing Gabor transform of long 1-D signals based on the long data stream convolver, and 2-D signals are also investigated. Following the study of the Gabor transform, the newly suggested wavelet transform is considered for its optical implementation. Using commercially available opto-electronic components, an optical wavelet processor is designed and built to perform the wavelet transforms on short 1-D signals in real-time. As an extension, architectures for 2-D optical wavelet transform are also described and computer simulated with the consideration of their technical problems of optical

  5. A unified approach to sparse signal processing

    NASA Astrophysics Data System (ADS)

    Marvasti, Farokh; Amini, Arash; Haddadi, Farzan; Soltanolkotabi, Mahdi; Khalaj, Babak Hossein; Aldroubi, Akram; Sanei, Saeid; Chambers, Janathon

    2012-12-01

    A unified view of the area of sparse signal processing is presented in tutorial form by bringing together various fields in which the property of sparsity has been successfully exploited. For each of these fields, various algorithms and techniques, which have been developed to leverage sparsity, are described succinctly. The common potential benefits of significant reduction in sampling rate and processing manipulations through sparse signal processing are revealed. The key application domains of sparse signal processing are sampling, coding, spectral estimation, array processing, component analysis, and multipath channel estimation. In terms of the sampling process and reconstruction algorithms, linkages are made with random sampling, compressed sensing, and rate of innovation. The redundancy introduced by channel coding in finite and real Galois fields is then related to over-sampling with similar reconstruction algorithms. The error locator polynomial (ELP) and iterative methods are shown to work quite effectively for both sampling and coding applications. The methods of Prony, Pisarenko, and MUltiple SIgnal Classification (MUSIC) are next shown to be targeted at analyzing signals with sparse frequency domain representations. Specifically, the relations of the approach of Prony to an annihilating filter in rate of innovation and ELP in coding are emphasized; the Pisarenko and MUSIC methods are further improvements of the Prony method under noisy environments. The iterative methods developed for sampling and coding applications are shown to be powerful tools in spectral estimation. Such narrowband spectral estimation is then related to multi-source location and direction of arrival estimation in array processing. Sparsity in unobservable source signals is also shown to facilitate source separation in sparse component analysis; the algorithms developed in this area such as linear programming and matching pursuit are also widely used in compressed sensing. Finally

  6. 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

  7. Designer cell signal processing circuits for biotechnology.

    PubMed

    Bradley, Robert W; Wang, Baojun

    2015-12-25

    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

  8. 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.

  9. Array algebra estimation in signal processing

    NASA Astrophysics Data System (ADS)

    Rauhala, U. A.

    A general theory of linear estimators called array algebra estimation is interpreted in some terms of multidimensional digital signal processing, mathematical statistics, and numerical analysis. The theory has emerged during the past decade from the new field of a unified vector, matrix and tensor algebra called array algebra. The broad concepts of array algebra and its estimation theory cover several modern computerized sciences and technologies converting their established notations and terminology into one common language. Some concepts of digital signal processing are adopted into this language after a review of the principles of array algebra estimation and its predecessors in mathematical surveying sciences.

  10. Processing Oscillatory Signals by Incoherent Feedforward Loops.

    PubMed

    Zhang, Carolyn; Tsoi, Ryan; Wu, Feilun; You, Lingchong

    2016-09-01

    From the timing of amoeba development to the maintenance of stem cell pluripotency, many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression. While the networks underlying this signal decoding are diverse, many are built around a common motif, the incoherent feedforward loop (IFFL), where an input simultaneously activates an output and an inhibitor of the output. With appropriate parameters, this motif can exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input signals with varying temporal profiles. Here, we use quantitative modeling to examine another property of IFFLs-the ability to process oscillatory signals. Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints. The kinetics of the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal "counting". We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose. PMID:27623175

  11. Processing oscillatory signals by incoherent feedforward loops

    NASA Astrophysics Data System (ADS)

    Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

    From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

  12. Processing of New Materials by Additive Manufacturing: Iron-Based Alloys Containing Silver for Biomedical Applications

    NASA Astrophysics Data System (ADS)

    Niendorf, Thomas; Brenne, Florian; Hoyer, Peter; Schwarze, Dieter; Schaper, Mirko; Grothe, Richard; Wiesener, Markus; Grundmeier, Guido; Maier, Hans Jürgen

    2015-07-01

    In the biomedical sector, production of bioresorbable implants remains challenging due to improper dissolution rates or deficient strength of many candidate alloys. Promising materials for overcoming the prevalent drawbacks are iron-based alloys containing silver. However, due to immiscibility of iron and silver these alloys cannot be manufactured based on conventional processing routes. In this study, iron-manganese-silver alloys were for the first time synthesized by means of additive manufacturing. Based on combined mechanical, microscopic, and electrochemical studies, it is shown that silver particles well distributed in the matrix can be obtained, leading to cathodic sites in the composite material. Eventually, this results in an increased dissolution rate of the alloy. Stress-strain curves showed that the incorporation of silver barely affects the mechanical properties.

  13. Laser induced micro plasma processing of polymer substrates for biomedical implant applications

    NASA Astrophysics Data System (ADS)

    French, P. W.; Rosowski, A.; Murphy, M.; Irving, M.; Sharp, M. C.

    2015-07-01

    This paper reports the experimental results of a new hybrid laser processing technique; Laser Induced Micro Plasma Processing (LIMP2). A transparent substrate is placed on top of a medium that will interact with the laser beam and create a plasma. The plasma and laser beam act in unison to ablate material and create micro-structuring on the "backside" of the substrate. We report the results of a series of experiments on a new laser processing technique that will use the same laser-plasma interaction to micromachining structures into glass and polymer substrates on the "topside" of the substrate and hence machine non-transparent material. This new laser processing technique is called Laser Induced Micro Plasma Processing (LIMP2). Micromachining of biomedical implants is proving an important enabling technology in controlling cell growth on a macro-scale. This paper discusses LIMP2 structuring of transparent substrate such as glasses and polymers for this application. Direct machining of these materials by lasers in the near infrared is at present impossible. Laser Induced Micro Plasma Processing (LIMP2) is a technique that allows laser operating at 1064 nm to machine microstructures directly these transparent substrates.

  14. Stimulus Contrast and Retinogeniculate Signal Processing

    PubMed Central

    Rathbun, Daniel L.; Alitto, Henry J.; Warland, David K.; Usrey, W. Martin

    2016-01-01

    Neuronal signals conveying luminance contrast play a key role in nearly all aspects of perception, including depth perception, texture discrimination, and motion perception. Although much is known about the retinal mechanisms responsible for encoding contrast information, relatively little is known about the relationship between stimulus contrast and the processing of neuronal signals between visual structures. Here, we describe simultaneous recordings from monosynaptically connected retinal ganglion cells and lateral geniculate nucleus (LGN) neurons in the cat to determine how stimulus contrast affects the communication of visual signals between the two structures. Our results indicate that: (1) LGN neurons typically reach their half-maximal response at lower contrasts than their individual retinal inputs and (2) LGN neurons exhibit greater contrast-dependent phase advance (CDPA) than their retinal inputs. Further analyses suggests that increased sensitivity relies on spatial convergence of multiple retinal inputs, while increased CDPA is achieved, in part, on temporal summation of arriving signals. PMID:26924964

  15. Stimulus Contrast and Retinogeniculate Signal Processing.

    PubMed

    Rathbun, Daniel L; Alitto, Henry J; Warland, David K; Usrey, W Martin

    2016-01-01

    Neuronal signals conveying luminance contrast play a key role in nearly all aspects of perception, including depth perception, texture discrimination, and motion perception. Although much is known about the retinal mechanisms responsible for encoding contrast information, relatively little is known about the relationship between stimulus contrast and the processing of neuronal signals between visual structures. Here, we describe simultaneous recordings from monosynaptically connected retinal ganglion cells and lateral geniculate nucleus (LGN) neurons in the cat to determine how stimulus contrast affects the communication of visual signals between the two structures. Our results indicate that: (1) LGN neurons typically reach their half-maximal response at lower contrasts than their individual retinal inputs and (2) LGN neurons exhibit greater contrast-dependent phase advance (CDPA) than their retinal inputs. Further analyses suggests that increased sensitivity relies on spatial convergence of multiple retinal inputs, while increased CDPA is achieved, in part, on temporal summation of arriving signals. PMID:26924964

  16. FPGA implementation of a ZigBee wireless network control interface to transmit biomedical signals

    NASA Astrophysics Data System (ADS)

    Gómez López, M. A.; Goy, C. B.; Bolognini, P. C.; Herrera, M. C.

    2011-12-01

    In recent years, cardiac hemodynamic monitors have incorporated new technologies based on wireless sensor networks which can implement different types of communication protocols. More precisely, a digital conductance catheter system recently developed adds a wireless ZigBee module (IEEE 802.15.4 standards) to transmit cardiac signals (ECG, intraventricular pressure and volume) which would allow the physicians to evaluate the patient's cardiac status in a noninvasively way. The aim of this paper is to describe a control interface, implemented in a FPGA device, to manage a ZigBee wireless network. ZigBee technology is used due to its excellent performance including simplicity, low-power consumption, short-range transmission and low cost. FPGA internal memory stores 8-bit signals with which the control interface prepares the information packets. These data were send to the ZigBee END DEVICE module that receives and transmits wirelessly to the external COORDINATOR module. Using an USB port, the COORDINATOR sends the signals to a personal computer for displaying. Each functional block of control interface was assessed by means of temporal diagrams. Three biological signals, organized in packets and converted to RS232 serial protocol, were sucessfully transmitted and displayed in a PC screen. For this purpose, a custom-made graphical software was designed using LabView.

  17. Cross-frequency Doppler sensitive signal processing

    NASA Astrophysics Data System (ADS)

    Wagstaff, Ronald A.

    2005-04-01

    When there is relative motion between an acoustic source and a receiver, a signal can be Doppler shifted in frequency and enter or leave the processing bins of the conventional signal processor. The amount of the shift is determined by the frequency and the rate of change in the distance between the source and the receiver. This frequency Doppler shifting can cause severe reductions in the processors performance. Special cross-frequency signal processing algorithms have recently been developed to mitigate the effects of Doppler. They do this by using calculation paths that cut across frequency bins in order to follow signals during frequency shifting. Cross-frequency spectral grams of a fast-flying sound source were compared to conventional grams, to evaluate the performance of this new signal processing method. The Doppler shifts in the data ranged up to 70 contiguous frequency bins. The resulting cross-frequency grams showed that three paths provided small to no improvement. Four paths showed improvements for either up-frequency or down-frequency shifting, but not for both. Two paths showed substantial improvement for both up-frequency and down-frequency shifting. The cross-frequency paths will be defined, and comparisons between conventional and cross-frequency grams will be presented. [Work supported by Miltec Corporation.

  18. Visual signal processing, speechreading, and related issues

    NASA Astrophysics Data System (ADS)

    Levitt, Harry

    2003-06-01

    People with hearing loss make use of visual speech cues to supplement the impoverished speech signal. This process, known as speechreading (or lipreading) can be very effective because of the complementary nature of auditory and visual speech cues. Despite the importance of visual speech cues (for both normal-hearing and hearing-impaired people) research on the visual characteristics of speech has lagged behind research on the acoustic characteristics of speech. The field of acoustic phonetics benefited substantially from the availability of powerful techniques for acoustic signal analysis. The substantial, recent advances in optical signal processing have opened up new vistas for visual speech analysis analogous to the way technological innovation revolutionized the field of acoustic phonetics. This paper describes several experiments in the emerging field of optic phonetics.

  19. 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.

  20. Tracking rhythmicity in nonstationary quasi-periodic biomedical signals using adaptive time-varying covariance.

    PubMed

    Li, Dan; Jung, Ranu

    2002-07-01

    A time-varying covariance method for detecting and quantifying the evolution of rhythmicity (frequency) in persistently varying quasi-periodic nonstationary signals is presented. The basic method, evaluated using chirp signals, utilizes a shifting window of fixed length. A substantial reduction in estimation bias and variability are obtained by utilizing an adaptive window whose length is dependent on past frequency estimates. The adaptive window yields estimates that are comparable in accuracy to those obtained using high-resolution time-frequency representation but with lower computation requirements and the potential for on-line application. Finally, an example of the application of the method for analyzing a neural recording is also illustrated. PMID:11931864

  1. Displays, memories, and signal processing: A compilation

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Articles on electronics systems and techniques were presented. The first section is on displays and other electro-optical systems; the second section is devoted to signal processing. The third section presented several new memory devices for digital equipment, including articles on holographic memories. The latest patent information available is also given.

  2. Signal processing aspects of windshear detection

    NASA Technical Reports Server (NTRS)

    Aalfs, David D.; Baxa, Ernest G., Jr.; Bracalente, Emedio M.

    1993-01-01

    Low-altitude windshear (LAWS) has been identified as a major hazard to aircraft, particularly during takeoff and landing. The Federal Aviation Administration (FAA) has been involved with developing technology to detect LAWS. A key element in this technology is high resolution pulse Doppler weather radar equipped with signal and data processing to provide timely information about possible hazardous conditions.

  3. Efficient multiprocessor architecture for digital signal processing

    SciTech Connect

    Auguin, M.; Boeri, F.

    1982-01-01

    There is a continuing pressure of better processing performances in numerical signal processing. Effective utilization of LSI semiconductor technology allows the consideration of multiprocessor architectures. The problem of interconnecting the components of the architecture arises. The authors describe a control algorithm of the Benes interconnection network in a asynchronous multiprocessor system. A simulation study of the time-shared bus, of the omega network, of the benes network and of the crossbar network gives a comparison of performances. 8 references.

  4. Signal processing of ultrasonic tomographic data

    NASA Astrophysics Data System (ADS)

    Tsihrintzis, George A.; Devaney, Anthony J.

    1992-12-01

    We process a set of data measured with a prototype ultrasonic scanner developed by the Norwegian company Norwave Development AS, Oslo, Norway in collaboration with the American company A.J. Devaney Associates, Boston, Massachusetts. In particular, we apply signal processing algorithms, recently developed by the authors to locate known test objects in a fluid background. Possible applications of the research include locating and identifying cancerous tumors in human tissue. These and other avenues for future research are discussed in the paper.

  5. Stepped-frequency radar signal processing

    NASA Astrophysics Data System (ADS)

    Seyfried, Daniel; Schoebel, Joerg

    2015-01-01

    Stepped-frequency radar is a prominent example of the class of continuous-wave radar systems. Since raw data are recorded in frequency-domain direct investigations referring to the frequency content can be done on the raw data. However, a transformation of these data is required in order to obtain a time-domain representation of the targets illuminated by the radar. In this paper we present different ways of arranging the raw data which then are processed by means of the inverse fast Fourier transform. On the basis of the time-domain result we discuss strengths and weaknesses of each of these data structures. Furthermore, we investigate the influence of phase noise on the time-domain signal by means of an appropriate model implemented in our simulation tool. We also demonstrate the effects of commonly known techniques of digital signal processing, such as windowing and zero-padding of frequency-domain data. Finally we present less commonly known methods, such as the processing gain of the (inverse) fast Fourier transform by means of which the signal to noise ratio of the time-domain signal can be increased.

  6. Signal processing in impulsive electromagnetic interference

    NASA Astrophysics Data System (ADS)

    Zabin, Serena M.

    1991-06-01

    Statistical signal processing functions such as signal detection, estimating, and identification play a key role in the development of effective communications, radar, and sonar systems. For example, advanced statistical methods are emerging as being particularly important in digital communications systems operating in channels corrupted by interference from such phenomena as multiple-access noise, intentional jamming, and impulsive noise sources. Conventional demodulation methods, such as coherent matched filtering, often suffer serious performance degradation when subjected to interference of these types; however, this degradation can frequently be eliminated through the use of more sophisticated signal processing techniques. A central issue in the design of effective signal processing procedures for system operating in channels such as those noted above is that of channel identification. Although certain aspects of channel identification have been studied extensively, one area in which there is a pressing need for further research is that of identification of impulsive channels. Communication systems are seldom interfered with by white Gaussian noise alone, yet receiving systems in general use are those which are optimum for white Gaussian noise.

  7. Digital signal processing for ionospheric propagation diagnostics

    NASA Astrophysics Data System (ADS)

    Rino, Charles L.; Groves, Keith M.; Carrano, Charles S.; Gunter, Jacob H.; Parris, Richard T.

    2015-08-01

    For decades, analog beacon satellite receivers have generated multifrequency narrowband complex data streams that could be processed directly to extract total electron content (TEC) and scintillation diagnostics. With the advent of software-defined radio, modern digital receivers generate baseband complex data streams that require intermediate processing to extract the narrowband modulation imparted to the signal by ionospheric structure. This paper develops and demonstrates a processing algorithm for digital beacon satellite data that will extract TEC and scintillation components. For algorithm evaluation, a simulator was developed to generate noise-limited multifrequency complex digital signal realizations with representative orbital dynamics and propagation disturbances. A frequency-tracking procedure is used to capture the slowly changing frequency component. Dynamic demodulation against the low-frequency estimate captures the scintillation. The low-frequency reference can be used directly for dual-frequency TEC estimation.

  8. Wireless biomedical signal monitoring device on wheelchair using noncontact electro-mechanical film sensor.

    PubMed

    Kim, Jong-Myoung; Hong, Joo-Hyun; Cho, Myeong-Chan; Cha, Eun-Jong; Lee, Tae-Soo

    2007-01-01

    The present study purposed to measure the BCG (Ballistocardiogram) of subjects on a wheelchair using a noncontact electro-mechanical film sensor (EMFi sensor) and detect the respiratory rate from BCG in real-time while the subjects are moving. In order to measure wirelessly the BCG of subjects moving on a wheelchair, we made a seat-type noncontact EMFi sensor and developed a transmitter and a receiver using Zigbee wireless RF communication technology. The sensor is embedded with a 3-axis accelerometer to remove the noise of wheelchair vibration from BCG signal. Signal obtained from each sensor goes through the A/D converter and is recorded in the SD (Secure Digital) card in PDA (Personal Digital Assistance) with a receiving part. We also developed a PC (Personal Computer) data analysis program, analyzed data recorded in the SD card using the program, and presented the results in graph. Lastly, this study demonstrated that a warning message can be sent from PDA to the remote server via a CDMA (Code Division Multiple Access) network in case the person on wheelchair falls in emergency. Our experiment was carried out with healthy male and female adults in their 20s who volunteered to help this research. The results of analyzing collected data will show that the respiratory rate can be measured in real-time on a moving wheelchair. PMID:18002021

  9. Parallel digital signal processing architectures for image processing

    NASA Astrophysics Data System (ADS)

    Kshirsagar, Shirish P.; Hartley, David A.; Harvey, David M.; Hobson, Clifford A.

    1994-10-01

    This paper describes research into a high speed image processing system using parallel digital signal processors for the processing of electro-optic images. The objective of the system is to reduce the processing time of non-contact type inspection problems including industrial and medical applications. A single processor can not deliver sufficient processing power required for the use of applications hence, a MIMD system is designed and constructed to enable fast processing of electro-optic images. The Texas Instruments TMS320C40 digital signal processor is used due to its high speed floating point CPU and the support for the parallel processing environment. A custom designed VISION bus is provided to transfer images between processors. The system is being applied for solder joint inspection of high technology printed circuit boards.

  10. Processing Electromyographic Signals to Recognize Words

    NASA Technical Reports Server (NTRS)

    Jorgensen, C. C.; Lee, D. D.

    2009-01-01

    A recently invented speech-recognition method applies to words that are articulated by means of the tongue and throat muscles but are otherwise not voiced or, at most, are spoken sotto voce. This method could satisfy a need for speech recognition under circumstances in which normal audible speech is difficult, poses a hazard, is disturbing to listeners, or compromises privacy. The method could also be used to augment traditional speech recognition by providing an additional source of information about articulator activity. The method can be characterized as intermediate between (1) conventional speech recognition through processing of voice sounds and (2) a method, not yet developed, of processing electroencephalographic signals to extract unspoken words directly from thoughts. This method involves computational processing of digitized electromyographic (EMG) signals from muscle innervation acquired by surface electrodes under a subject's chin near the tongue and on the side of the subject s throat near the larynx. After preprocessing, digitization, and feature extraction, EMG signals are processed by a neural-network pattern classifier, implemented in software, that performs the bulk of the recognition task as described.

  11. Signal Subspace Processing Of Experimental Radio Data

    NASA Astrophysics Data System (ADS)

    Martin, Gordon E.

    1988-02-01

    The research related to this paper was concerned with the application of EigenVector EigenValue ( EVEV ) signal processing techniques to experimental data. The signal subspace methods of Schmidt (called MUSIC), Johnson, and Pisarenko were considered and compared with results of conventional beamformers. Almost all oral and written papers regarding these EVEV processors involve theoretical studies, possibly using simulated data and incoherent noise, but not experimental data. Contrary to that trend, we have reported behavior of EVEV processors using experimental data in this and other papers. The data used here are predominantly due to an HF radio experiment, but the distribution of eigenvalues is also reported for acoustic data. The paper emphasizes two general subtopics of signal subspace processing. First, the eigenvalues of sampled covariance matrices are examined and related to those of incoherent noise. These results include actual data, all of which we found were not Gaussian incoherent noise. A new test related to the ratio of eigenvalues is developed. The MDL and AIC criteria give misleading results with actual noise. Second, directional responses of EVEV and conventional processors are compared using HF radio data that has high signal-to-noise ratio in the non-Gaussian noise. MUSIC is found to have very favorable directional characteristics.

  12. Macrocell design for concurrent signal processing

    SciTech Connect

    Pope, S.P.; Brodersen, R.W.

    1983-01-01

    Macrocells serve as subsystems at the top level of the hardware design hierarchy. The authors present the macrocell design technique as applied to the implementation of real-time, sampled-data signal processing functions. The design of such circuits is particularly challenging due to the computationally intensive nature of signal-processing algorithms and the constraints of real-time operation. The most efficient designs make use of a high degree of concurrency-a property facilitated by the microcell approach. Two circuit projects whose development resulted largely from the macrocell methodology described are used as examples throughout the report: a linear-predictive vocoder circuit, and a front-end filter-bank chip for a speech recognition system. Both are monolithic multiprocessor implementations: the lpc vocoder circuit contains three processors, the filter-bank chip two processors. 10 references.

  13. PROBLEM-BASED LEARNING FOR PROFESSIONALISM AND ETHICS TRAINING OF BIOMEDICAL GRADUATE STUDENTS: PROCESS EVALUATION

    PubMed Central

    Jones, Nancy L.; Peiffer, Ann M.; Lambros, Ann; Eldridge, J. Charles

    2013-01-01

    Purpose A process evaluation was conducted to assess whether the newly developed Problem-Based Learning (PBL) curriculum designed to teach professionalism and ethics to biomedical graduate students was achieving its objectives. The curriculum was chosen to present realistic cases and issues in the practice of science, to promote skill development and to acculturate students to professional norms of science. Method The perception to which the objectives for the curriculum and courses were being reached was assessed using 5-step Likert-scaled questions, open-ended questions and interviews of students and facilitators. Results Process evaluation indicated that both facilitators and students perceived course objectives were being met. For example, active learning was preferred over lectures; both faculty and students percieved that the curriculum increased their understanding of norms, role obligations, and responsibilities of professional scientists; their ability to identify ethical situations was increased; skills in moral reasoning and effective group work were developed. Conclusions Information gathered was used to improve course implementation and instructional material. For example, a negative perception as an “ethics” course was addressed by redesigning case debriefing activities that reinforced learning objectives and important skills. Cases were refined to be more engaging and relevant for students, and facilitators were given more specific training and resources for each case. The PBL small group strategy can stimulate an environment more aware of ethical implications of science and increase socialization and open communication about professional behavior. PMID:20663754

  14. Surface energy modification for biomedical material by corona streamer plasma processing to mitigate bacterial adhesion

    NASA Astrophysics Data System (ADS)

    Alhamarneh, Ibrahim; Pedrow, Patrick

    2011-10-01

    Bacterial adhesion initiates biofouling of biomedical material but the processes can be reduced by adjusting the material's surface energy. The surface of surgical-grade 316L stainless steel (316L SS) had its hydrophilic property enhanced by processing in a corona streamer plasma reactor using atmospheric pressure Ar mixed with O2. Reactor excitation was 60 Hz ac high-voltage (<= 10 kV RMS) applied to a multi-needle-to-grounded-torus electrode configuration. Applied voltage and streamer current pulses were monitored with a broadband sensor system. When Ar/O2 plasma was used, the surface energy was enhanced more than with Ar plasma alone. Composition of the surface before and after plasma treatment was characterized by XPS. As the hydrophilicity of the treated surface increased so did percent of oxygen on the surface thus we concluded that reduction in contact angle was mainly due to new oxygen-containing functionalities. FTIR was used to identify oxygen containing groups on the surface. The aging effect that accompanies surface free energy adjustments was also observed.

  15. Analysis of biomedical time signals for characterization of cutaneous diabetic micro-angiopathy

    NASA Astrophysics Data System (ADS)

    Kraitl, Jens; Ewald, Hartmut

    2007-02-01

    Photo-plethysmography (PPG) is frequently used in research on microcirculation of blood. It is a non-invasive procedure and takes minimal time to be carried out. Usually PPG time series are analyzed by conventional linear methods, mainly Fourier analysis. These methods may not be optimal for the investigation of nonlinear effects of the hearth circulation system like vasomotion, autoregulation, thermoregulation, breathing, heartbeat and vessels. The wavelet analysis of the PPG time series is a specific, sensitive nonlinear method for the in vivo identification of hearth circulation patterns and human health status. This nonlinear analysis of PPG signals provides additional information which cannot be detected using conventional approaches. The wavelet analysis has been used to study healthy subjects and to characterize the health status of patients with a functional cutaneous microangiopathy which was associated with diabetic neuropathy. The non-invasive in vivo method is based on the radiation of monochromatic light through an area of skin on the finger. A Photometrical Measurement Device (PMD) has been developed. The PMD is suitable for non-invasive continuous online monitoring of one or more biologic constituent values and blood circulation patterns.

  16. Digital signal processing in acoustics. I

    NASA Astrophysics Data System (ADS)

    Davies, H.; McNeil, D. J.

    1985-11-01

    Digital signal processing techniques have gained steadily in importance over the past few years in many areas of science and engineering and have transformed the character of instrumentation used in laboratory and plant. This is particularly marked in acoustics, which has both benefited from the developments in signal processing and provided significant stimulus for these developments. As a result acoustical techniques are now used in a very wide range of applications and acoustics is one area in which digital signal processing is exploited to its limits. For example, the development of fast algorithms for computing Fourier transforms and the associated developments in hardware have led to remarkable advances in the use of spectral analysis as a means of investigating the nature and characteristics of acoustic sources. Speech research has benefited considerably in this respect, and, in a rather more technological application, spectral analysis of machinery noise provides information about changes in machine condition which may indicate imminent failure. More recently the observation that human and animal muscles emit low intensity noise suggests that spectral analysis of this noise may yield information about muscle structure and performance.

  17. Using Seismic Signals to Forecast Volcanic Processes

    NASA Astrophysics Data System (ADS)

    Salvage, R.; Neuberg, J. W.

    2012-04-01

    Understanding seismic signals generated during volcanic unrest have the ability to allow scientists to more accurately predict and understand active volcanoes since they are intrinsically linked to rock failure at depth (Voight, 1988). In particular, low frequency long period signals (LP events) have been related to the movement of fluid and the brittle failure of magma at depth due to high strain rates (Hammer and Neuberg, 2009). This fundamentally relates to surface processes. However, there is currently no physical quantitative model for determining the likelihood of an eruption following precursory seismic signals, or the timing or type of eruption that will ensue (Benson et al., 2010). Since the beginning of its current eruptive phase, accelerating LP swarms (< 10 events per hour) have been a common feature at Soufriere Hills volcano, Montserrat prior to surface expressions such as dome collapse or eruptions (Miller et al., 1998). The dynamical behaviour of such swarms can be related to accelerated magma ascent rates since the seismicity is thought to be a consequence of magma deformation as it rises to the surface. In particular, acceleration rates can be successfully used in collaboration with the inverse material failure law; a linear relationship against time (Voight, 1988); in the accurate prediction of volcanic eruption timings. Currently, this has only been investigated for retrospective events (Hammer and Neuberg, 2009). The identification of LP swarms on Montserrat and analysis of their dynamical characteristics allows a better understanding of the nature of the seismic signals themselves, as well as their relationship to surface processes such as magma extrusion rates. Acceleration and deceleration rates of seismic swarms provide insights into the plumbing system of the volcano at depth. The application of the material failure law to multiple LP swarms of data allows a critical evaluation of the accuracy of the method which further refines current

  18. Biomedical ultrasonoscope

    NASA Technical Reports Server (NTRS)

    Lee, R. D. (Inventor)

    1979-01-01

    The combination of a "C" mode scan electronics in a portable, battery powered biomedical ultrasonoscope having "A" and "M" mode scan electronics, the latter including a clock generator for generating clock pulses, a cathode ray tube having X, Y and Z axis inputs, a sweep generator connected between the clock generator and the X axis input of the cathode ray tube for generating a cathode ray sweep signal synchronized by the clock pulses, and a receiver adapted to be connected to the Z axis input of the cathode ray tube. The "C" mode scan electronics comprises a plurality of transducer elements arranged in a row and adapted to be positioned on the skin of the patient's body for converting a pulsed electrical signal to a pulsed ultrasonic signal, radiating the ultrasonic signal into the patient's body, picking up the echoes reflected from interfaces in the patient's body and converting the echoes to electrical signals; a plurality of transmitters, each transmitter being coupled to a respective transducer for transmitting a pulsed electrical signal thereto and for transmitting the converted electrical echo signals directly to the receiver, a sequencer connected between the clock generator and the plurality of transmitters and responsive to the clock pulses for firing the transmitters in cyclic order; and a staircase voltage generator connected between the clock generator and the Y axis input of the cathode ray tube for generating a staircase voltage having steps synchronized by the clock pulses.

  19. Signal processing for ION mobility spectrometers

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  20. C language algorithms for digital signal processing

    SciTech Connect

    Embree, P.M.; Kimble, B.

    1991-01-01

    The use of the C programming language to construct digital signal-processing (DSP) algorithms for operation on high-performance personal computers is described in a textbook for engineering students. Chapters are devoted to the fundamental principles of DSP, basic C programming techniques, user-interface and disk-storage routines, filtering routines, discrete Fourier transforms, matrix and vector routines, and image-processing routines. Also included is a floppy disk containing a library of standard C mathematics, character-string, memory-allocation, and I/O functions; a library of DSP functions; and several sample DSP programs. 83 refs.

  1. NOVEL SIGNAL PROCESSING WITH NONLINEAR TRANSMISSION LINES

    SciTech Connect

    D. REAGOR; ET AL

    2000-08-01

    Nonlinear dielectrics offer uniquely strong and tunable nonlinearities that make them attractive for current devices (for example, frequency-agile microwave filters) and for future signal-processing technologies. The goal of this project is to understand pulse propagation on nonlinear coplanar waveguide prototype devices. We have performed time-domain and frequency-domain experimental studies of simple waveguide structures and pursued a theoretical understanding of the propagation of signals on these nonlinear waveguides. To realistically assess the potential applications, we used a time-domain measurement and analysis technique developed during this project to perform a broadband electrodynamics characterization in terms of nonlinear, dispersive, and dissipative effects. We completed a comprehensive study of coplanar waveguides made from high-temperature superconducting thin-film YBa{sub 2}Cu{sub 3}O{sub 7{minus}{delta}} electrodes on nonlinear dielectric single-crystal SrTiO{sub 3} substrates. By using parameters determined from small-signal (linear) transmission characteristics of the waveguides, we develop a model equation that successfully predicts and describes large-signal (nonlinear) behavior.

  2. Radar transponder apparatus and signal processing technique

    SciTech Connect

    Axline, R.M. Jr.; Sloan, G.R.; Spalding, R.E.

    1994-12-31

    An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance tile transponder`s echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag, through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR.

  3. Signal processing in impulsive electromagnetic interference

    NASA Astrophysics Data System (ADS)

    Zabin, Serena M.

    1993-06-01

    Statistical signal processing functions such as signal detection, estimation, and identification play a key role in the development of effective communications, radar, and sonar systems. For example, advanced statistical methods are emerging as being particularly important in digital communications systems operating in channels corrupted by interference from such phenomena as multiple-access noise, intentional jamming, and impulsive noise sources. Conventional demodulation methods, such as coherent matched filtering, often suffer serious performance degradation when subject to interference of these types; however, this degradation can frequently be eliminated through the use of more sophisticated signal processing techniques. During this reporting period, the focus of our work has been on the problem of obtaining optimum and efficient identification and detection procedures for impulsive channels. Of particular interest is the Middleton Class A noise model, which is a widely-accepted statistical-physical model for impulsive interference superimposed on a Gaussian background. The model has two basic parameters that can be adjusted to fit a wide variety of impulsive noise phenomena occurring in practice.

  4. Radar transponder apparatus and signal processing technique

    DOEpatents

    Axline, R.M. Jr.; Sloan, G.R.; Spalding, R.E.

    1996-01-23

    An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance the transponder`s echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR. 4 figs.

  5. Radar transponder apparatus and signal processing technique

    DOEpatents

    Axline, Jr., Robert M.; Sloan, George R.; Spalding, Richard E.

    1996-01-01

    An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance the transponder's echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR.

  6. Optical signal processing at Essex Corporation

    NASA Astrophysics Data System (ADS)

    Franklin, William R.

    1996-02-01

    The most current research and development in optical signal processing and its application at Essex Corporation is summarized. In progress for more than a decade, this work has evolved from the development of highly specialized algorithms for the intelligence community to more general domains embracing such diverse areas as radar signal processing, medical ultrasound and magnetic resonance imaging, acoustic tomography, and cellular and satellite communications. Essex develops algorithms and designs, fabricates, and tests breadboard designs and transforms these into rugged, compact products for use in harsh environments. Descriptions of the most important investigations in these areas are presented. An image synthesizer called ImSynTM is described that forms images from the measured spatial Fourier components of the object to be imaged. Applications to synthetic aperture radar, acoustic tomography, medical resonance imaging, and synthetic aperture microscopy are shown. An acousto-optic radar signal processor is described that can produce high-resolution, high-dynamic-range range Doppler maps from instantaneous wideband radar returns. A design for a fiber optic true-time delay beamformer is presented. Finally, an optoelectronic telecommunications switch is discussed.

  7. Automatic generation of signal processing integrated circuits

    SciTech Connect

    Pope, S.P.

    1985-01-01

    A system for the automated design of signal processing integrated circuits is described in this thesis. The system is based on a library of circuit cells, and a software package that can configure the cells into complete integrated circuits. The architecture of the cell library is optimized for low and medium bandwidth digital signal processing applications. Circuits designed with the system use a multiprocessor architecture. Input to the system is a design file written in a specialized programming language. Software emulation from the design file is used to verify performance. A two-pass silicon compiler is used to translate the design file into a mask-level description of an integrated circuit. A major goal of the project is to make the system useable by those with little or no formal training in integrated circuits. A second goal is to reduce the time and cost associated with performing an integrated circuit design, while still producing designs which are reasonably efficient in their use of the technology. Development of the system was guided by basic research on appropriate architectures and circuit constructs for signal processors. As part of this research an integrated circuit was designed which performs speech analysis and synthesis. This vocoder circuit is intended for use in low-bit-rate digital speech transmission systems.

  8. An intelligent, onboard signal processing payload concept

    SciTech Connect

    Shriver, P. M.; Harikumar, J.; Briles, S. C.; Gokhale, M.

    2003-01-01

    Our approach to onboard processing will enable a quicker return and improved quality of processed data from small, remote-sensing satellites. We describe an intelligent payload concept which processes RF lightning signal data onboard the spacecraft in a power-aware manner. Presently, onboard processing is severely curtailed due to the conventional management of limited resources and power-unaware payload designs. Delays of days to weeks are commonly experienced before raw data is received, processed into a human-usable format, and finally transmitted to the end-user. We enable this resource-critical technology of onboard processing through the concept of Algorithm Power Modulation (APM). APM is a decision process used to execute a specific software algorithm, from a suite of possible algorithms, to make the best use of the available power. The suite of software algorithms chosen for our application is intended to reduce the probability of false alarms through postprocessing. Each algorithm however also has a cost in energy usage. A heuristic decision tree procedure is used which selects an algorithm based on the available power, time allocated, algorithm priority, and algorithm performance. We demonstrate our approach to power-aware onboard processing through a preliminary software simulation.

  9. Laser microfabrication of biomedical devices: time-resolved microscopy of the printing process

    NASA Astrophysics Data System (ADS)

    Serra, P.; Patrascioiu, A.; Fernández-Pradas, J. M.; Morenza, J. L.

    2013-04-01

    Laser printing constitutes an interesting alternative to more conventional printing techniques in the microfabrication of biomedical devices. The principle of operation of most laser printing techniques relies on the highly localized absorption of strongly focused laser pulses in the close proximity of the free surface of the liquid to be printed. This leads to the generation of a cavitation bubble which further expansion results in the ejection of a small fraction of the liquid, giving place to the deposition of a well-defined droplet onto a collector substrate. Laser printing has proved feasible for printing biological materials, from single-stranded DNA to proteins, and even living cells and microorganisms, with high degrees of resolution and reproducibility. In consequence, laser printing appears to be an excellent candidate for the fabrication of biological microdevices, such as DNA and protein microarrays, or miniaturized biosensors. The optimization of the performances of laser printing techniques requires a detailed knowledge of the dynamics of liquid transfer. Time-resolved microscopy techniques play a crucial role in this concern, since they allow tracking the evolution of the ejected material with excellent time and spatial resolution. Investigations carried out up to date have shown that liquid ejection proceeds through the formation of long, thin and stable liquid jets. In this work the different approaches used so far for monitoring liquid ejection during laser printing are considered, and it is shown how these techniques make possible to understand the complex dynamics involved in the process.

  10. Composite film fabricated on biomedical material with corona streamer plasma processing to mitigate bacterial adhesion

    NASA Astrophysics Data System (ADS)

    Alhamarneh, Ibrahim; Pedrow, Patrick; Eskhan, Asma; Abu-Lail, Nehal

    2011-10-01

    Composite films might control bacterial adhesion and concomitant biofouling that afflicts biomedical materials. Different size molecules of polyethylene glycol (PEG) with nominal molecular weights 600, 2000, and 20000 g/mol were used to synthesize composite films with plasma processing and dip-coating procedures on surgical-grade 316L stainless steel. Before dip-coating, the substrate was pre-coated with plasma-polymerized di(ethylene glycol) vinyl ether (pp-EO2V) in an atmospheric pressure corona streamer plasma reactor. The PEG dip-coating step followed immediately in the same chamber due to the finite lifetime of radicals associated with freshly deposited pp-EO2V. Morphology of the composite film was investigated with an ESEM. FTIR confirmed incorporation of pp-EO2V and PEG species into the composite film. More investigations on the composite film were conducted by XPS measurements. Adhesion of the composite film was evaluated with a standard peel-off test. Stability of the composite film in buffer solution was evaluated by AFM. AFM was also used to measure the film roughness and thickness. Polar and non-polar contact angle measurements were included.

  11. Signal processing electronics for a capacitive microsensor

    NASA Astrophysics Data System (ADS)

    Amendola, Gilles; Lu, Guo N.

    2000-04-01

    An interface circuit in a 0.8-micrometers CMOS process for the on- chip integration of a capacitive micro-sensor used as a microphone is presented. In order to circumvent 1/f noise contributions and to improve the signal/noise ratio, a synchronous modulation-demodulation technique has been applied. For the implementation of this technique, we have studied and designed several functional block, such as modulator with signal conversion, low-noise amplifier, demodulator, etc. To deal with problems related to dispersion of intrinsic capacitance of the sensor, a feedback compensating solution is suggested. The designed circuit has a sensibility of 1200 V/pF, with a minimum detectable capacitance variation of 2 10-6 pF.

  12. FPGA-Based Filterbank Implementation for Parallel Digital Signal Processing

    NASA Technical Reports Server (NTRS)

    Berner, Stephan; DeLeon, Phillip

    1999-01-01

    One approach to parallel digital signal processing decomposes a high bandwidth signal into multiple lower bandwidth (rate) signals by an analysis bank. After processing, the subband signals are recombined into a fullband output signal by a synthesis bank. This paper describes an implementation of the analysis and synthesis banks using (Field Programmable Gate Arrays) FPGAs.

  13. 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

  14. 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

  15. Measurement of OH, NO, O and N atoms in helium plasma jet for ROS/RNS controlled biomedical processes

    NASA Astrophysics Data System (ADS)

    Yonemori, Seiya; Kamakura, Taku; Ono, Ryo

    2014-10-01

    Atmospheric-pressure plasmas are of emerging interest for new plasma applications such as cancer treatment, cell activation and sterilization. In those biomedical processes, reactive oxygen/nitrogen species (ROS/RNS) are said that they play significant role. It is though that active species give oxidative stress and induce biomedical reactions. In this study, we measured OH, NO, O and N atoms using laser induced fluorescence (LIF) measurement and found that voltage polarity affect particular ROS. When negative high voltage was applied to the plasma jet, O atom density was tripled compared to the case of positive applied voltage. In that case, O atom density was around 3 × 1015 [cm-3] at maximum. In contrast, OH and NO density did not change their density depending on the polarity of applied voltage, measured as in order of 1013 and 1014 [cm-3] at maximum, respectively. From ICCD imaging measurement, it could be seen that negative high voltage enhanced secondary emission in plasma bullet propagation and it can affect the effective production of particular ROS. Since ROS/RNS dose can be a quantitative criterion to control plasma biomedical application, those measurement results is able to be applied for in vivo and in vitro plasma biomedical experiments. This study is supported by the Grant-in-Aid for Science Research by the Ministry of Education, Culture, Sport, Science and Technology.

  16. Digital signal processing for radioactive decay studies

    SciTech Connect

    Miller, D.; Madurga, M.; Paulauskas, S. V.; Ackermann, D.; Heinz, S.; Hessberger, F. P.; Hofmann, S.; Grzywacz, R.; Miernik, K.; Rykaczewski, K.; Tan, H.

    2011-11-30

    The use of digital acquisition system has been instrumental in the investigation of proton and alpha emitting nuclei. Recent developments extend the sensitivity and breadth of the application. The digital signal processing capabilities, used predominately by UT/ORNL for decay studies, include digitizers with decreased dead time, increased sampling rates, and new innovative firmware. Digital techniques and these improvements are furthermore applicable to a range of detector systems. Improvements in experimental sensitivity for alpha and beta-delayed neutron emitters measurements as well as the next generation of superheavy experiments are discussed.

  17. Inertial processing of vestibulo-ocular signals

    NASA Technical Reports Server (NTRS)

    Hess, B. J.; Angelaki, D. E.

    1999-01-01

    New evidence for a central resolution of gravito-inertial signals has been recently obtained by analyzing the properties of the vestibulo-ocular reflex (VOR) in response to combined lateral translations and roll tilts of the head. It is found that the VOR generates robust compensatory horizontal eye movements independent of whether or not the interaural translatory acceleration component is canceled out by a gravitational acceleration component due to simultaneous roll-tilt. This response property of the VOR depends on functional semicircular canals, suggesting that the brain uses both otolith and semicircular canal signals to estimate head motion relative to inertial space. Vestibular information about dynamic head attitude relative to gravity is the basis for computing head (and body) angular velocity relative to inertial space. Available evidence suggests that the inertial vestibular system controls both head attitude and velocity with respect to a gravity-centered reference frame. The basic computational principles underlying the inertial processing of otolith and semicircular canal afferent signals are outlined.

  18. Three-dimensional image signals: processing methods

    NASA Astrophysics Data System (ADS)

    Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru

    2010-11-01

    Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.

  19. Computational problems and signal processing in SETI

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

  20. GLAST Burst Monitor Signal Processing System

    SciTech Connect

    Bhat, P. Narayana; Briggs, Michael; Connaughton, Valerie; Paciesas, William; Preece, Robert; Diehl, Roland; Greiner, Jochen; Kienlin, Andreas von; Lichti, Giselher; Steinle, Helmut; Fishman, Gerald; Kouveliotou, Chryssa; Meegan, Charles; Wilson-Hodge, Colleen; Kippen, R. Marc; Persyn, Steven

    2007-07-12

    The onboard Data Processing Unit (DPU), designed and built by Southwest Research Institute, performs the high-speed data acquisition for GBM. The analog signals from each of the 14 detectors are digitized by high-speed multichannel analog data acquisition architecture. The streaming digital values resulting from a periodic (period of 104.2 ns) sampling of the analog signal by the individual ADCs are fed to a Field-Programmable Gate Array (FPGA). Real-time Digital Signal Processing (DSP) algorithms within the FPGA implement functions like filtering, thresholding, time delay and pulse height measurement. The spectral data with a 12-bit resolution are formatted according to the commandable look-up-table (LUT) and then sent to the High-Speed Science-Date Bus (HSSDB, speed=1.5 MB/s) to be telemetered to ground. The DSP offers a novel feature of a commandable and constant event deadtime. The ADC non-linearities have been calibrated so that the spectral data can be corrected during analysis. The best temporal resolution is 2 {mu}s for the pre-burst and post-trigger time-tagged events (TTE) data. The time resolution of the binned data types is commandable from 64 msec to 1.024 s for the CTIME data (8 channel spectral resolution) and 1.024 to 32.768 s for the CSPEC data (128 channel spectral resolution). The pulse pile-up effects have been studied by Monte Carlo simulations. For a typical GRB, the possible shift in the Epeak value at high-count rates ({approx}100 kHz) is {approx}1% while the change in the single power-law index could be up to 5%.

  1. Digital Signal Processing in the GRETINA Spectrometer

    NASA Astrophysics Data System (ADS)

    Cromaz, Mario

    2015-10-01

    Developments in the segmentation of large-volume HPGe crystals has enabled the development of high-efficiency gamma-ray spectrometers which have the ability to track the path of gamma-rays scattering through the detector volume. This technology has been successfully implemented in the GRETINA spectrometer whose high efficiency and ability to perform precise event-by-event Doppler correction has made it an important tool in nuclear spectroscopy. Tracking has required the spectrometer to employ a fully digital signal processing chain. Each of the systems 1120 channels are digitized by 100 Mhz, 14-bit flash ADCs. Filters that provide timing and high-resolution energies are implemented on local FPGAs acting on the ADC data streams while interaction point locations and tracks, derived from the trace on each detector segment, are calculated in real time on a computing cluster. In this presentation we will give a description of GRETINA's digital signal processing system, the impact of design decisions on system performance, and a discussion of possible future directions as we look towards soon developing larger spectrometers such as GRETA with full 4 π solid angle coverage. This work was supported by the Office of Science in the Department of Energy under grant DE-AC02-05CH11231.

  2. Digital signal processing using virtual instruments

    NASA Astrophysics Data System (ADS)

    Anderson, James A.; Korrapati, Raghu; Swain, Nikunja K.

    2000-08-01

    The area of test and measurement is changing rapidly because of the recent developments in software and hardware. The test and measurement systems are increasingly becoming PC based. Most of these PC based systems use graphical programming language to design test and measurement modules called virtual instruments (Vis). These Vis provide visual representation of dat or models, and make understanding of abstract concepts and algorithms easier. This allows users to express their ideas in a concise manner. One such virtual instruments package is LabVIEW from National Instruments Corporation at Austin, Texas. This software package is one of the first graphical programming products and is currently used in number of academic institutions, industries, Department of Defense graphical programming products and is currently sued in number of academic institutions, industries, Department of Defense, Department of Energy, and National Aeronautics and Space Administration for various test, measurement, and control applications. LabVIEW has an extensive built-in VI library that can be used to design and develop solutions for different applications. Besides using the built-in VI library that can be used to design and develop solutions for different applications. Besides using the built-in VI modules in LabVIEW, the user can design new VI modules easily. This paper discusses the use of LabVIEW to design and develop digital signal processing VI modules such as Fourier Analysis and Windowing. Instructors can use these modules to teach some of the signal processing concepts effectively.

  3. Signal processing and analyzing works of art

    NASA Astrophysics Data System (ADS)

    Johnson, Don H.; Johnson, C. Richard, Jr.; Hendriks, Ella

    2010-08-01

    In examining paintings, art historians use a wide variety of physico-chemical methods to determine, for example, the paints, the ground (canvas primer) and any underdrawing the artist used. However, the art world has been little touched by signal processing algorithms. Our work develops algorithms to examine x-ray images of paintings, not to analyze the artist's brushstrokes but to characterize the weave of the canvas that supports the painting. The physics of radiography indicates that linear processing of the x-rays is most appropriate. Our spectral analysis algorithms have an accuracy superior to human spot-measurements and have the advantage that, through "short-space" Fourier analysis, they can be readily applied to entire x-rays. We have found that variations in the manufacturing process create a unique pattern of horizontal and vertical thread density variations in the bolts of canvas produced. In addition, we measure the thread angles, providing a way to determine the presence of cusping and to infer the location of the tacks used to stretch the canvas on a frame during the priming process. We have developed weave matching software that employs a new correlation measure to find paintings that share canvas weave characteristics. Using a corpus of over 290 paintings attributed to Vincent van Gogh, we have found several weave match cliques that we believe will refine the art historical record and provide more insight into the artist's creative processes.

  4. Bio-Swarm-Pipeline: A Light-Weight, Extensible Batch Processing System for Efficient Biomedical Data Processing

    PubMed Central

    Cheng, Xi; Pizarro, Ricardo; Tong, Yunxia; Zoltick, Brad; Luo, Qian; Weinberger, Daniel R.; Mattay, Venkata S.

    2009-01-01

    A streamlined scientific workflow system that can track the details of the data processing history is critical for the efficient handling of fundamental routines used in scientific research. In the scientific workflow research community, the information that describes the details of data processing history is referred to as “provenance” which plays an important role in most of the existing workflow management systems. Despite its importance, however, provenance modeling and management is still a relatively new area in the scientific workflow research community. The proper scope, representation, granularity and implementation of a provenance model can vary from domain to domain and pose a number of challenges for an efficient pipeline design. This paper provides a case study on structured provenance modeling and management problems in the neuroimaging domain by introducing the Bio-Swarm-Pipeline. This new model, which is evaluated in the paper through real world scenarios, systematically addresses the provenance scope, representation, granularity, and implementation issues related to the neuroimaging domain. Although this model stems from applications in neuroimaging, the system can potentially be adapted to a wide range of bio-medical application scenarios. PMID:19847314

  5. Question processing and clustering in INDOC: a biomedical question answering system.

    PubMed

    Sondhi, Parikshit; Raj, Purushottam; Kumar, V Vinod; Mittal, Ankush

    2007-01-01

    The exponential growth in the volume of publications in the biomedical domain has made it impossible for an individual to keep pace with the advances. Even though evidence-based medicine has gained wide acceptance, the physicians are unable to access the relevant information in the required time, leaving most of the questions unanswered. This accentuates the need for fast and accurate biomedical question answering systems. In this paper we introduce INDOC--a biomedical question answering system based on novel ideas of indexing and extracting the answer to the questions posed. INDOC displays the results in clusters to help the user arrive the most relevant set of documents quickly. Evaluation was done against the standard OHSUMED test collection. Our system achieves high accuracy and minimizes user effort. PMID:18274647

  6. Active voltammetric microsensors with neural signal processing.

    SciTech Connect

    Vogt, M. C.

    1998-12-11

    Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical ''signatures'' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration, the calibration, sensing, and processing methods of these active voltammetric microsensors can detect, recognize, and

  7. Linearly-Constrained Adaptive Signal Processing Methods

    NASA Astrophysics Data System (ADS)

    Griffiths, Lloyd J.

    1988-01-01

    In adaptive least-squares estimation problems, a desired signal d(n) is estimated using a linear combination of L observation values samples xi (n), x2(n), . . . , xL-1(n) and denoted by the vector X(n). The estimate is formed as the inner product of this vector with a corresponding L-dimensional weight vector W. One particular weight vector of interest is Wopt which minimizes the mean-square between d(n) and the estimate. In this context, the term `mean-square difference' is a quadratic measure such as statistical expectation or time average. The specific value of W which achieves the minimum is given by the prod-uct of the inverse data covariance matrix and the cross-correlation between the data vector and the desired signal. The latter is often referred to as the P-vector. For those cases in which time samples of both the desired and data vector signals are available, a variety of adaptive methods have been proposed which will guarantee that an iterative weight vector Wa(n) converges (in some sense) to the op-timal solution. Two which have been extensively studied are the recursive least-squares (RLS) method and the LMS gradient approximation approach. There are several problems of interest in the communication and radar environment in which the optimal least-squares weight set is of interest and in which time samples of the desired signal are not available. Examples can be found in array processing in which only the direction of arrival of the desired signal is known and in single channel filtering where the spectrum of the desired response is known a priori. One approach to these problems which has been suggested is the P-vector algorithm which is an LMS-like approximate gradient method. Although it is easy to derive the mean and variance of the weights which result with this algorithm, there has never been an identification of the corresponding underlying error surface which the procedure searches. The purpose of this paper is to suggest an alternative

  8. 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.

  9. Ultrasonic signal processing and tissue characterization

    NASA Astrophysics Data System (ADS)

    Mu, Zhiping

    Ultrasound imaging has become one of the most widely used diagnostic tools in medicine. While it has advantages, compared with other modalities, in terms of safety, low-cost, accessibility, portability and capability of real-time imaging, it has limitations. One of the major disadvantages of ultrasound imaging is the relatively low image quality, especially the low signal-to-noise ratio (SNR) and the low spatial resolution. Part of this dissertation is dedicated to the development of digital ultrasound signal and image processing methods to improve ultrasound image quality. Conventional B-mode ultrasound systems display the demodulated signals, i.e., the envelopes, in the images. In this dissertation, I introduce the envelope matched quadrature filtering (EMQF) technique, which is a novel demodulation technique generating optimal performance in envelope detection. In ultrasonography, the echo signals are the results of the convolution of the pulses and the medium responses, and the finite pulse length is a major source of the degradation of the image resolution. Based on the more appropriate complex-valued medium response assumption rather than the real-valued assumption used by many researchers, a nonparametric iterative deconvolution method, the Least Squares method with Point Count regularization (LSPC), is proposed. This method was tested using simulated and experimental data, and has produced excellent results showing significant improvements in resolution. During the past two decades, ultrasound tissue characterization (UTC) has emerged as an active research field and shown potentials of applications in a variety of clinical areas. Particularly interesting to me is a group of methods characterizing the scatterer spatial distribution. For resolvable regular structures, a deconvolution based method is proposed to estimate parameters characterizing such structures, including mean scatterer spacing, and has demonstrated superior performance when compared to

  10. System for monitoring non-coincident, nonstationary process signals

    DOEpatents

    Gross, Kenneth C.; Wegerich, Stephan W.

    2005-01-04

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

  11. A Novel Approach for Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Chen, Ya-Chin; Juang, Jer-Nan

    1998-01-01

    Adaptive linear predictors have been used extensively in practice in a wide variety of forms. In the main, their theoretical development is based upon the assumption of stationarity of the signals involved, particularly with respect to the second order statistics. On this basis, the well-known normal equations can be formulated. If high- order statistical stationarity is assumed, then the equivalent normal equations involve high-order signal moments. In either case, the cross moments (second or higher) are needed. This renders the adaptive prediction procedure non-blind. A novel procedure for blind adaptive prediction has been proposed and considerable implementation has been made in our contributions in the past year. The approach is based upon a suitable interpretation of blind equalization methods that satisfy the constant modulus property and offers significant deviations from the standard prediction methods. These blind adaptive algorithms are derived by formulating Lagrange equivalents from mechanisms of constrained optimization. In this report, other new update algorithms are derived from the fundamental concepts of advanced system identification to carry out the proposed blind adaptive prediction. The results of the work can be extended to a number of control-related problems, such as disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. The applications implemented are speech processing, such as coding and synthesis. Simulations are included to verify the novel modelling method.

  12. Signal processing of aircraft flyover noise

    NASA Technical Reports Server (NTRS)

    Kelly, Jeffrey J.

    1991-01-01

    A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a uniform level flyover is considered but the code can accept more general flight profiles. The effects of spectral smearing and its removal is discussed. Using data acquired from XV-15 tilt rotor flyover test comparisons are made showing the measured and corrected spectra. Frequency shifts are accurately accounted for by the method. It is shown that correcting for spherical spreading, Doppler amplitude, and frequency can give some idea about source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.

  13. Ultrasound perfusion signal processing for tumor detection

    NASA Astrophysics Data System (ADS)

    Kim, MinWoo; Abbey, Craig K.; Insana, Michael F.

    2016-04-01

    Enhanced blood perfusion in a tissue mass is an indication of neo-vascularity and a sign of a potential malignancy. Ultrasonic pulsed-Doppler imaging is a preferred modality for noninvasive monitoring of blood flow. However, the weak blood echoes and disorganized slow flow make it difficult to detect perfusion using standard methods without the expense and risk of contrast enhancement. Our research measures the efficiency of conventional power-Doppler (PD) methods at discriminating flow states by comparing measurement performance to that of an ideal discriminator. ROC analysis applied to the experimental results shows that power Doppler methods are just 30-50 % efficient at perfusion flows less than 1ml/min, suggesting an opportunity to improve perfusion assessment through signal processing. A new perfusion estimator is proposed by extending the statistical discriminator approach. We show that 2-D perfusion color imaging may be enhanced using this approach.

  14. Signal Processing Issues in Fourier Transform Spectrometers

    NASA Astrophysics Data System (ADS)

    Hayes, Monson H.

    2002-12-01

    There are a number of interesting and challenging signal processing problems related to the design of a Fourier Transform Spectrometer (FTS). In this project, we look at a few of these problems in two different types of spectrometers-the Geostationary Imaging Fourier Transform Spectrometer (GIFTS), and a Far Infrared (FIR) FTS. One of the si nal processing challenges in GIFTS is the reduction of the massive data rate (2.4 x 109 bps) to an affordable telemetry rate of less than 60 Mbps. Since the GIFTS interferograms are heavily over-sampled, the first step is to decimate (down-sample) the interferograms with minimal distortion while keeping the signal processing algorithms simple enough to be implemented in the GIFTS hardware. Therefore, the first problem we looked at was the design of the decimation filters. Specifically, we performed a detailed analysis of two competing approaches that were being considered. The first, proposed by the Space Dynamics Lab (SDL), was to use a double sideband (real) band-pass filter. The second, proposed by Lincoln Laboratories (LL), was to use a single sideband (complex) band-pass filter. What the study showed was that a complex filter (LL approach) results in a savings of about 25% in the filtering requirements for the long-wave band, while in the mid-wave band the savings are approximately 50%. As a result, the decision was made to use a complex filter. Once the decision to use a complex filter had been made, we looked at some of the consequences of this decision. The most significant of these was the discovery that, with a complex filter, it is possible to extend the long-wave IR band beyond the folding frequency of 1174/cm and recover the SO2 line at 1176.5/cm. What this requires is the design of a band-pass decimation filter with a wider passband, and consequently of higher order. Specifically, it was shown that with about 25% more filter operations, the elusive SO2 line, believed to be irretrievable, could in fact be recovered

  15. Materials processing towards development of rapid prototyping technology for manufacturing biomedical implants

    NASA Astrophysics Data System (ADS)

    Pekin, Senol

    2000-10-01

    Materials processing towards development of fused deposition of materials (FDM) method for manufacturing biomedical implants has been studied experimentally. Main processing steps consisted of thermoplastic binder development in the ethylene vinyl acetate (EVA)-microcrystalline wax system, feedstock extrusion, characterization and optimization of binder degradation, and sintering of calcium deficient hydroxyapatite. Differential scanning calorimetry (DSC) revealed that the melting index (MI) of the copolymer affects the temperature location of the solidification exotherm, whereas the effect on the temperature location of the melting endotherm was negligible. Nonisothermal measurement of viscosity of different blends as a function of VA content of the EVA component revealed that the microcrystalline wax is compatible with 25--14% VA-containing EVA grades. Further DSC analysis revealed that co-crystallization leads to compatible EVA-microcrystalline wax blends. A typical binder formulation that was developed in the present work has a viscosity of about 700 cP at 140°C, a compressive yield strength of 6 MPa and an elastic modulus of about 600 MPa, and contained 15--20% EVA and 80--85% microcrystalline wax. Various filaments with a nominal diameter of 1.8 mm were extruded by using such a binder, and calcium pyro-phosphate powder that had a distribution modulus of about 0.37. Measurement of physical dimensions of the filament revealed that fluid state can be achieved in the filaments. Simultaneous thermal analysis of degradation characteristics of the typical binder formulations revealed that degradation sequence is oxidation of the hydrocarbons, evaporation of the hydrocarbons, degradation of the vinyl acetate, and degradation of the ethylene chain. A rate controlled binder removal system was developed and used in order to optimize the binder removal schedule. Sintering of gel-cast calcium hydroxyapatite was studied by means of thermal analysis, XRD, mechanical

  16. Tunable signal processing through modular control of transcription factor translocation

    PubMed Central

    Hao, Nan; Budnik, Bogdan A.; Gunawardena, Jeremy; O’Shea, Erin K.

    2013-01-01

    Signaling pathways can induce different dynamics of transcription factor (TF) activation. We explored how TFs process signaling inputs to generate diverse dynamic responses. The budding yeast general stress responsive TF Msn2 acted as a tunable signal processor that could track, filter, or integrate signals in an input dependent manner. This tunable signal processing appears to originate from dual regulation of both nuclear import and export by phosphorylation, as mutants with one form of regulation sustained only one signal processing function. Versatile signal processing by Msn2 is crucial for generating distinct dynamic responses to different natural stresses. Our findings reveal how complex signal processing functions are integrated into a single molecule and provide a guide for the design of TFs with “programmable” signal processing functions. PMID:23349292

  17. An ECG signal processing algorithm based on removal of wave deflections in time domain.

    PubMed

    Kim, Jungkuk; Kim, Minkyu; Won, Injae; Yang, Seungyhul; Lee, Kiyoung; Huh, Woong

    2009-01-01

    This paper introduces a new approach to process biomedical signals by surgically removing wave deflections in time domain. The method first determines the epochs of high frequency deflections, cuts out them from the signal, and then connects the two disconnected points. To determine the epoch of a deflection to be removed, four slope trace waves are used to isolate the deflection based on signal characteristics of amplitude, slope, duration, and distance from neighboring deflections. The method has been applied to simulated data and MIT-BIH arrhythmia database to show its practical efficacy in the case of baseline wandering removal. It is found that the method has the capability to identify and remove high frequency deflections appropriately, leaving low frequency deflection such as baseline drifting. PMID:19963498

  18. Advances in white-light optical signal processing

    NASA Technical Reports Server (NTRS)

    Yu, F. T. S.

    1984-01-01

    A technique that permits signal processing operations which can be carried out by white light source is described. The method performs signal processing that obeys the concept of coherent light rather than incoherent optics. Since the white light source contains all the color wavelengths of the visible light, the technique is very suitable for color signal processing.

  19. Dynamic range control of audio signals by digital signal processing

    NASA Astrophysics Data System (ADS)

    Gilchrist, N. H. C.

    It is often necessary to reduce the dynamic range of musical programs, particularly those comprising orchestral and choral music, for them to be received satisfactorily by listeners to conventional FM and AM broadcasts. With the arrival of DAB (Digital Audio Broadcasting) a much wider dynamic range will become available for radio broadcasting, although some listeners may prefer to have a signal with a reduced dynamic range. This report describes a digital processor developed by the BBC to control the dynamic range of musical programs in a manner similar to that of a trained Studio Manager. It may be used prior to transmission in conventional broadcasting, replacing limiters or other compression equipment. In DAB, it offers the possibility of providing a dynamic range control signal to be sent to the receiver via an ancillary data channel, simultaneously with the uncompressed audio, giving the listener the option of the full dynamic range or a reduced dynamic range.

  20. DLP switched blaze grating: the heart of optical signal processing

    NASA Astrophysics Data System (ADS)

    Duncan, Walter M.; Lee, Benjamin L.; Rancuret, Paul; Sawyers, Bryce D.; Endsley, Lynn; Powell, Donald

    2003-01-01

    We have developed an approach for processing communication signals in the optical domain using a DLP digital mirror array driven by a Digital Signal Processor (DSP). In optical communication systems, modulation rates of 10 GB/s and above are common, hence, direct processing of Dense Wavelength Division Multiplexed (DWDM) optical signals without undergoing Optical to Electrical conversion has become a key requirement for cost effective deployment of dynamic optical networks. This work will discuss primarily applications of Optical Signal Processing (OSP) to coherent DWDM signals. Optical Signal Processing has also found applications in spectroscopy, microscopy, sensing, optical correlation, and testing.

  1. Signal processing schemes for optical voltage transducer

    NASA Astrophysics Data System (ADS)

    Chen, Jinling; Xie, Delin; Chen, Hongbin; Xie, Latang; Song, Jianhe; Luo, Xiaoni

    2006-02-01

    This paper describes an optical voltage transducer(OVT) for a 35kV system based on Pockels effect in a BGO(Bi 4Ge 3O 12) crystal. OVT used to measure the voltage of power are superior to conventional electromagnet-induced voltage transducer in many aspects, thus it has great potential to applications. It has some advantages. These advantages are: 1)Optics provides total galvanic separation between the measuring point at high voltage (HV) potential and the measuring equipment at ground potential. 2)Transmission of measuring signals in optical fibers is immune to induced electromagnetic noise even in EMI-environment of switchyards and other high voltage installations. 3)Optics and especially optical fibers make the insulation costs independent of voltage levels thus giving an economical advantage at voltage levels above 100kV. 4)The use of optics is expected to reduce the weight of the transducers. 5)Optical transducers are expected to have a large bandwidth than conventional transducers. 6)The output-signals from an optical transducer are easily interfaced with computers and electronically operated equipment such as digital relays. New techniques developed in electronics and optical field including fiber optic technology bring new contributions to the measurement of voltage and electric field. A Pockels voltage sensor has been widely introduced to electrical power transmission and distribution systems and some advantage of the optical voltage measuring techniques are reported. In this paper, a brief summary of electro-optic effects and the principle of OVT is proposed. The signal processing schemes of different optical path and features are analyzed. The basic principle of OVT is to modulate the irradiance of the light-directed to OVT by an optical fiber-according to the potential difference between the HV-line and the ground potential. The modulation of the light is accomplished by placing a material-that has an optical property (the birefringence), which is

  2. Processing and Characterization of Functionally Graded Hydroxyapatite Coatings for Biomedical Implants

    NASA Astrophysics Data System (ADS)

    Bai, Xiao

    Hydroxyapatite [Ca10(PO4)6(OH) 2, HA] has been widely applied as a coating on various biomedical bone/dental implants to improve biocompatibility and bioactivity. It has been observed that primary reasons leading to implantation failure of commercial HA coated implants processed by plasma spraying are the poor mechanical properties of coatings and infections accompanied by implantation. It has been also reported an ideal coating should be able to stimulate new bone growth at the initial stage of implantation and stay stable both mechanically and chemically thereafter. This research has investigated a functionally graded hydroxyapatite (FGHA) coating that is capable of improving the stability of implants, facilitating recovery, and preventing infections after implantation. A series of FGHA coatings with incorporated Ag 0 ˜ 13.53 wt. % has been deposited onto Ti substrate using ion beam assisted deposition (IBAD) with in-situ heat treatment. The compositional, microstructural, mechanical, and biological properties of coatings have been analyzed via various tests. The relationship among processing parameters, coating properties and biological behaviors has been established and the processing parameters for processing FGHA coatings with/without incorporated Ag have been optimized. Microstructure observations of coating cross section via transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) for set temperature coatings deposited at 450°C ˜ 750°C reveals that in-situ substrate temperature is the primary factor controlling the crystallinity of the coatings. The microstructure observation of cross section via TEM/STEM for both FGHA coatings with/without incorporated Ag has shown that coatings are dense and have a gradually decreased crystallinity from substrate/coating interface to top surface. In particular, the interface has an atomically intermixed structure; the region near the interface has a columnar grain structure whereas

  3. Pedagogical reforms of digital signal processing education

    NASA Astrophysics Data System (ADS)

    Christensen, Michael

    The future of the engineering discipline is arguably predicated heavily upon appealing to the future generation, in all its sensibilities. The greatest burden in doing so, one might rightly believe, lies on the shoulders of the educators. In examining the causal means by which the profession arrived at such a state, one finds that the technical revolution, precipitated by global war, had, as its catalyst, institutions as expansive as the government itself to satisfy the demand for engineers, who, as a result of such an existential crisis, were taught predominantly theoretical underpinnings to address a finite purpose. By contrast, the modern engineer, having expanded upon this vision and adapted to an evolving society, is increasingly placed in the proverbial role of the worker who must don many hats: not solely a scientist, yet often an artist; not a businessperson alone, but neither financially naive; not always a representative, though frequently a collaborator. Inasmuch as change then serves as the only constancy in a global climate, therefore, the educational system - if it is to mimic the demands of the industry - is left with an inherent need for perpetual revitalization to remain relevant. This work aims to serve that end. Motivated by existing research in engineering education, an epistemological challenge is molded into the framework of the electrical engineer with emphasis on digital signal processing. In particular, it is investigated whether students are better served by a learning paradigm that tolerates and, when feasible, encourages error via a medium free of traditional adjudication. Through the creation of learning modules using the Adobe Captivate environment, a wide range of fundamental knowledge in signal processing is challenged within the confines of existing undergraduate courses. It is found that such an approach not only conforms to the research agenda outlined for the engineering educator, but also reflects an often neglected reality

  4. Issues in collecting, processing and storing human tissues and associated information to support biomedical research

    PubMed Central

    Grizzle, William E.; Bell, Walter C.; Sexton, Katherine C.

    2012-01-01

    The availability of human tissues to support biomedical research is critical to advance translational research focused on identifying and characterizing approaches to individualized (personalized) medical care. Providing such tissues relies on three acceptable models – a tissue banking model, a prospective collection model and a combination of these two models. An unacceptable model is the “catch as catch can” model in which tissues are collected, processed and stored without goals or a plan or without standard operating procedures, i.e., portions of tissues are collected as available and processed and stored when time permits. In the tissue banking model, aliquots of tissues are collected according to SOPs. Usually specific sizes and types of tissues are collected and processed (e.g., 0.1 gm of breast cancer frozen in OCT). Using the banking model, tissues may be collected that may not be used and/or do not meet specific needs of investigators; however, at the time of an investigator request, tissues are readily available as is clinical information including clinical outcomes. In the model of prospective collection, tissues are collected based upon investigator requests including specific requirements of investigators. For example, the investigator may request that two 0.15 gm matching aliquots of breast cancer be minced while fresh, put in RPMI media with and without fetal calf serum, cooled to 4°C and shipped to the investigator on wet ice. Thus, the tissues collected prospectively meet investigator needs, all collected specimens are utilized and storage of specimens is minimized; however, investigators must wait until specimens are collected, and if needed, for clinical outcome. The operation of any tissue repository requires well trained and dedicated personnel. A quality assurance program is required which provides quality control information on the diagnosis of a specimen that is matched specifically to the specimen provided to an investigator instead

  5. User's manual SIG: a general-purpose signal processing program

    SciTech Connect

    Lager, D.; Azevedo, S.

    1983-10-25

    SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Many of the basic operations one would perform on digitized data are contained in the core SIG package. Out of these core commands, more powerful signal processing algorithms may be built. Many different operations on time- and frequency-domain signals can be performed by SIG. They include operations on the samples of a signal, such as adding a scalar to each sample, operations on the entire signal such as digital filtering, and operations on two or more signals such as adding two signals. Signals may be simulated, such as a pulse train or a random waveform. Graphics operations display signals and spectra.

  6. Spatial acoustic signal processing for immersive communication

    NASA Astrophysics Data System (ADS)

    Atkins, Joshua

    Computing is rapidly becoming ubiquitous as users expect devices that can augment and interact naturally with the world around them. In these systems it is necessary to have an acoustic front-end that is able to capture and reproduce natural human communication. Whether the end point is a speech recognizer or another human listener, the reduction of noise, reverberation, and acoustic echoes are all necessary and complex challenges. The focus of this dissertation is to provide a general method for approaching these problems using spherical microphone and loudspeaker arrays.. In this work, a theory of capturing and reproducing three-dimensional acoustic fields is introduced from a signal processing perspective. In particular, the decomposition of the spatial part of the acoustic field into an orthogonal basis of spherical harmonics provides not only a general framework for analysis, but also many processing advantages. The spatial sampling error limits the upper frequency range with which a sound field can be accurately captured or reproduced. In broadband arrays, the cost and complexity of using multiple transducers is an issue. This work provides a flexible optimization method for determining the location of array elements to minimize the spatial aliasing error. The low frequency array processing ability is also limited by the SNR, mismatch, and placement error of transducers. To address this, a robust processing method is introduced and used to design a reproduction system for rendering over arbitrary loudspeaker arrays or binaurally over headphones. In addition to the beamforming problem, the multichannel acoustic echo cancellation (MCAEC) issue is also addressed. A MCAEC must adaptively estimate and track the constantly changing loudspeaker-room-microphone response to remove the sound field presented over the loudspeakers from that captured by the microphones. In the multichannel case, the system is overdetermined and many adaptive schemes fail to converge to

  7. Microwave photonic delay line signal processing.

    PubMed

    Diehl, John F; Singley, Joseph M; Sunderman, Christopher E; Urick, Vincent J

    2015-11-01

    This paper provides a path for the design of state-of-the-art fiber-optic delay lines for signal processing. The theoretical forms for various radio-frequency system performance metrics are derived for four modulation types: X- and Z-cut Mach-Zehnder modulators, a phase modulator with asymmetric Mach-Zehnder interferometer, and a polarization modulator with control waveplate and polarizing beam splitter. Each modulation type is considered to cover the current and future needs for ideal system designs. System gain, compression point, and third-order output intercept point are derived from the transfer matrices for each modulation type. A discussion of optical amplifier placement and fiber-effect mitigation is offered. The paper concludes by detailing two high-performance delay lines, built for unique applications, that exhibit performance levels an order of magnitude better than commercial delay lines. This paper should serve as a guide to maximizing the performance of future systems and offer a look into current and future research being done to further improve photonics technologies. PMID:26560620

  8. Signal processing of aircraft flyover noise

    NASA Technical Reports Server (NTRS)

    Kelly, J. J.

    1993-01-01

    A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a level uniform flyover is considered in the study, but the code can accept more general flight profiles. The effects of spectral smearing and its removal are discussed. Using test data acquired from an XV-15 tilt-rotor flyover, comparisons are made between the measured and corrected spectra. Frequency shifts are accurately accounted for by the de-Dopplerization procedure. It is shown that by correcting for spherical spreading and Doppler amplitude, along with frequency, can give some idea about noise source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.

  9. Closed orbit feedback with digital signal processing

    SciTech Connect

    Chung, Y.; Kirchman, J.; Lenkszus, F.

    1994-08-01

    The closed orbit feedback experiment conducted on the SPEAR using the singular value decomposition (SVD) technique and digital signal processing (DSP) is presented. The beam response matrix, defined as beam motion at beam position monitor (BPM) locations per unit kick by corrector magnets, was measured and then analyzed using SVD. Ten BPMs, sixteen correctors, and the eight largest SVD eigenvalues were used for closed orbit correction. The maximum sampling frequency for the closed loop feedback was measured at 37 Hz. Using the proportional and integral (PI) control algorithm with the gains Kp = 3 and K{sub I} = 0.05 and the open-loop bandwidth corresponding to 1% of the sampling frequency, a correction bandwidth ({minus}3 dB) of approximately 0.8 Hz was achieved. Time domain measurements showed that the response time of the closed loop feedback system for 1/e decay was approximately 0.25 second. This result implies {approximately} 100 Hz correction bandwidth for the planned beam position feedback system for the Advanced Photon Source storage ring with the projected 4-kHz sampling frequency.

  10. Optical signal processing using photonic reservoir computing

    NASA Astrophysics Data System (ADS)

    Salehi, Mohammad Reza; Dehyadegari, Louiza

    2014-10-01

    As a new approach to recognition and classification problems, photonic reservoir computing has such advantages as parallel information processing, power efficient and high speed. In this paper, a photonic structure has been proposed for reservoir computing which is investigated using a simple, yet, non-partial noisy time series prediction task. This study includes the application of a suitable topology with self-feedbacks in a network of SOA's - which lends the system a strong memory - and leads to adjusting adequate parameters resulting in perfect recognition accuracy (100%) for noise-free time series, which shows a 3% improvement over previous results. For the classification of noisy time series, the rate of accuracy showed a 4% increase and amounted to 96%. Furthermore, an analytical approach was suggested to solve rate equations which led to a substantial decrease in the simulation time, which is an important parameter in classification of large signals such as speech recognition, and better results came up compared with previous works.

  11. Processing Motion Signals in Complex Environments

    NASA Technical Reports Server (NTRS)

    Verghese, Preeti

    2000-01-01

    Motion information is critical for human locomotion and scene segmentation. Currently we have excellent neurophysiological models that are able to predict human detection and discrimination of local signals. Local motion signals are insufficient by themselves to guide human locomotion and to provide information about depth, object boundaries and surface structure. My research is aimed at understanding the mechanisms underlying the combination of motion signals across space and time. A target moving on an extended trajectory amidst noise dots in Brownian motion is much more detectable than the sum of signals generated by independent motion energy units responding to the trajectory segments. This result suggests that facilitation occurs between motion units tuned to similar directions, lying along the trajectory path. We investigated whether the interaction between local motion units along the motion direction is mediated by contrast. One possibility is that contrast-driven signals from motion units early in the trajectory sequence are added to signals in subsequent units. If this were the case, then units later in the sequence would have a larger signal than those earlier in the sequence. To test this possibility, we compared contrast discrimination thresholds for the first and third patches of a triplet of sequentially presented Gabor patches, aligned along the motion direction. According to this simple additive model, contrast increment thresholds for the third patch should be higher than thresholds for the first patch.The lack of a measurable effect on contrast thresholds for these various manipulations suggests that the pooling of signals along a trajectory is not mediated by contrast-driven signals. Instead, these results are consistent with models that propose that the facilitation of trajectory signals is achieved by a second-level network that chooses the strongest local motion signals and combines them if they occur in a spatio-temporal sequence consistent

  12. Biologically-based signal processing system applied to noise removal for signal extraction

    DOEpatents

    Fu, Chi Yung; Petrich, Loren I.

    2004-07-13

    The method and system described herein use a biologically-based signal processing system for noise removal for signal extraction. A wavelet transform may be used in conjunction with a neural network to imitate a biological system. The neural network may be trained using ideal data derived from physical principles or noiseless signals to determine to remove noise from the signal.

  13. Statistical signal processing in sensor networks

    NASA Astrophysics Data System (ADS)

    Guerriero, Marco

    In this dissertation we focus on decentralized signal processing in Sensor Networks (SN). Four topics are studied: (i) Direction of Arrival (DOA) estimation using a Wireless Sensor network (WSN), (ii) multiple target tracking in large SN, (iii) decentralized target detection in SN and (iv) decentralized sequential detection in SN with communication constraints. The first topic of this thesis addresses the problem of estimating the DOA of an acoustic wavefront using a a WSN made of isotropic (hence individually useless) sensors. The WSN was designed according to the SENMA (SEnsor Network with Mobile Agents) architecture with a mobile agent (MA) that successively queries the sensors lying inside its field of view. We propose both fast/simple and optimal DOA-estimation schemes, and an optimization of the MAs observation management is also carried out, with the surprising finding that the MA ought to orient itself at an oblique angle to the expected DOA, rather than directly toward it. We also consider the extension to multiple sources; intriguingly, per-source DOA accuracy is higher when there is more than one source. In all cases, performance is investigated by simulation and compared, when appropriate, with asymptotic bounds; these latter are usually met after a moderate number of MA dwells. In the second topic, we study the problem of tracking multiple targets in large SN. While these networks hold significant potential for surveillance, it is of interest to address fundamental limitations in large-scale implementations. We first introduce a simple analytical tracker performance model. Analysis of this model suggests that scan-based tracking performance improves with increasing numbers of sensors, but only to a certain point beyond which degradation is observed. Correspondingly, we address model-based optimization of the local sensor detection threshold and the number of sensors. Next, we propose a two-stage tracking approach (fuse-before-track) as a possible

  14. Microwave signal processing with photorefractive dynamic holography

    NASA Astrophysics Data System (ADS)

    Fotheringham, Edeline B.

    Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that

  15. Basic concepts in the processing of SARSAT signals

    NASA Astrophysics Data System (ADS)

    Chung, T.; Carter, C. R.

    1987-03-01

    Search and rescue satellite-aided tracking (SARSAT) involves the use of satellites in low-polar orbits which relay the emergency signals of distressed vehicles to an earth station for signal analysis. In this paper, some basic concepts and a theoretical analysis of the spectra produced by coherent and noncoherent emergency locator transmitter signals are presented. It is shown that coherent signals can be easily processed using linear spectral analysis. Noncoherent signals, however, require more advanced methods.

  16. 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.

  17. Camera systems in human motion analysis for biomedical applications

    NASA Astrophysics Data System (ADS)

    Chin, Lim Chee; Basah, Shafriza Nisha; Yaacob, Sazali; Juan, Yeap Ewe; Kadir, Aida Khairunnisaa Ab.

    2015-05-01

    Human Motion Analysis (HMA) system has been one of the major interests among researchers in the field of computer vision, artificial intelligence and biomedical engineering and sciences. This is due to its wide and promising biomedical applications, namely, bio-instrumentation for human computer interfacing and surveillance system for monitoring human behaviour as well as analysis of biomedical signal and image processing for diagnosis and rehabilitation applications. This paper provides an extensive review of the camera system of HMA, its taxonomy, including camera types, camera calibration and camera configuration. The review focused on evaluating the camera system consideration of the HMA system specifically for biomedical applications. This review is important as it provides guidelines and recommendation for researchers and practitioners in selecting a camera system of the HMA system for biomedical applications.

  18. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

    cortex by the application of lateral interactions during the learning phase. The organization of the mature network is compared to that found in the macaque monkey by several analytical tests. The capacity of the network to process images is investigated. By a method of reconstructing the input images in terms of V1 activities, the simulations show that images can be faithfully represented in V1 by the proposed network. The signal-to-noise ratio of the image is improved by the representation, and compression ratios of well over two-hundred are possible. Lateral interactions between V1 neurons sharpen their orientational tuning. We further study the dynamics of the processing, showing that the rate of decrease of the error of the reconstruction is maximized for the receptive fields used. Lastly, we employ a Fokker-Planck equation for a more detailed prediction of the error value vs. time. The Fokker-Planck equation for an underdamped system with a driving force is derived, yielding an energy-dependent diffusion coefficient which is the integral of the spectral densities of the force and the velocity of the system. The theory is applied to correlated noise activation and resonant activation. Simulation results for the error of the network vs time are compared to the solution of the Fokker-Planck equation.

  19. Multichannel heterodyning for wideband interferometry, correlation and signal processing

    DOEpatents

    Erskine, D.J.

    1999-08-24

    A method is disclosed of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized. 50 figs.

  20. Multichannel heterodyning for wideband interferometry, correlation and signal processing

    DOEpatents

    Erskine, David J.

    1999-01-01

    A method of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized.

  1. Statistical Signal Processing Methods in Scattering and Imaging

    NASA Astrophysics Data System (ADS)

    Zambrano Nunez, Maytee

    This Ph.D. dissertation project addresses two related topics in wave-based signal processing: 1) Cramer-Rao bound (CRB) analysis of scattering systems formed by pointlike scatterers in one-dimensional (1D) and three-dimensional (3D) spaces. 2) Compressive optical coherent imaging, based on the incorporation of sparsity priors in the reconstructions. The first topic addresses for wave scattering systems in 1D and 3D spaces the information content about scattering parameters, in particular, the targets' positions and strengths, and derived quantities, that is contained in scattering data corresponding to reflective, transmissive, and more general sensing modalities. This part of the dissertation derives the Cramer-Rao bound (CRB) for the estimation of parameters of scalar wave scattering systems formed by point scatterers. The results shed light on the fundamental difference between the approximate Born approximation model for weak scatterers and the more general multiple scattering model, and facilitate the identification of regions in parameter space where multiple scattering facilitates or obstructs the estimation of parameters from scattering data, as well as of sensing configurations giving maximal or minimal information about the parameters. The derived results are illustrated with numerical examples, with particular emphasis on the imaging resolution which we quantify via a relative resolution index borrowed from a previous paper. Additionally, this work investigates fundamental limits of estimation performance for the localization of the targets and the inverse scattering problem. The second topic of the effort describes a novel compressive-sensing-based technique for optical imaging with a coherent single-detector system. This hybrid opto-micro-electromechanical, coherent single-detector imaging system applies the latest developments in the nascent field of compressive sensing to the problem of computational imaging of wavefield intensity from a small number

  2. Optimizing signal and image processing applications using Intel libraries

    NASA Astrophysics Data System (ADS)

    Landré, Jérôme; Truchetet, Frédéric

    2007-01-01

    This paper presents optimized signal and image processing libraries from Intel Corporation. Intel Performance Primitives (IPP) is a low-level signal and image processing library developed by Intel Corporation to optimize code on Intel processors. Open Computer Vision library (OpenCV) is a high-level library dedicated to computer vision tasks. This article describes the use of both libraries to build flexible and efficient signal and image processing applications.

  3. Development of an Ontology-Directed Signal Processing Toolbox

    SciTech Connect

    Stephen W. Lang

    2011-05-27

    This project was focused on the development of tools for the automatic configuration of signal processing systems. The goal is to develop tools that will be useful in a variety of Government and commercial areas and useable by people who are not signal processing experts. In order to get the most benefit from signal processing techniques, deep technical expertise is often required in order to select appropriate algorithms, combine them into a processing chain, and tune algorithm parameters for best performance on a specific problem. Therefore a significant benefit would result from the assembly of a toolbox of processing algorithms that has been selected for their effectiveness in a group of related problem areas, along with the means to allow people who are not signal processing experts to reliably select, combine, and tune these algorithms to solve specific problems. Defining a vocabulary for problem domain experts that is sufficiently expressive to drive the configuration of signal processing functions will allow the expertise of signal processing experts to be captured in rules for automated configuration. In order to test the feasibility of this approach, we addressed a lightning classification problem, which was proposed by DOE as a surrogate for problems encountered in nuclear nonproliferation data processing. We coded a toolbox of low-level signal processing algorithms for extracting features of RF waveforms, and demonstrated a prototype tool for screening data. We showed examples of using the tool for expediting the generation of ground-truth metadata, for training a signal recognizer, and for searching for signals with particular characteristics. The public benefits of this approach, if successful, will accrue to Government and commercial activities that face the same general problem - the development of sensor systems for complex environments. It will enable problem domain experts (e.g. analysts) to construct signal and image processing chains without

  4. Information processing in multi-step signaling pathways

    NASA Astrophysics Data System (ADS)

    Ganesan, Ambhi; Hamidzadeh, Archer; Zhang, Jin; Levchenko, Andre

    Information processing in complex signaling networks is limited by a high degree of variability in the abundance and activity of biochemical reactions (biological noise) operating in living cells. In this context, it is particularly surprising that many signaling pathways found in eukaryotic cells are composed of long chains of biochemical reactions, which are expected to be subject to accumulating noise and delayed signal processing. Here, we challenge the notion that signaling pathways are insulated chains, and rather view them as parts of extensively branched networks, which can benefit from a low degree of interference between signaling components. We further establish conditions under which this pathway organization would limit noise accumulation, and provide evidence for this type of signal processing in an experimental model of a calcium-activated MAPK cascade. These results address the long-standing problem of diverse organization and structure of signaling networks in live cells.

  5. Nonlinear filtering for robust signal processing

    SciTech Connect

    Palmieri, F.

    1987-01-01

    A generalized framework for the description and design of a large class of nonlinear filters is proposed. Such a family includes, among others, the newly defined Ll-estimators, that generalize the order statistic filters (L-filters) and the nonrecursive linear filters (FIR). Such estimators are particularly efficient in filtering signals that do not follow gaussian distributions. They can be designed to restore signals and images corrupted by noise of impulsive type. Such filters are very appealing since they are suitable for being made robust against perturbations on the assumed model, or insensitive to the presence of spurious outliers in the data. The linear part of the filter is used to characterize their essential spectral behavior. It can be constrained to a given shape to obtain nonlinear filters that combine given frequency characteristics and noise immunity. The generalized nonlinear filters can also be used adaptively with the coefficients computed dynamically via LMS or RLS algorithms.

  6. Moving source localization using seismic signal processing

    NASA Astrophysics Data System (ADS)

    Asgari, Shadnaz; Stafsudd, Jing Z.; Hudson, Ralph E.; Yao, Kung; Taciroglu, Ertugrul

    2015-01-01

    Accurate localization of a seismic source in a near-field scenario where the distances between sensors and the source are less than a few wavelengths of the generated signal has shown to be a challenging task. Conventional localization algorithms often prove to be ineffective, as near-field seismic signals exhibit characteristics different from the well-studied far-field signals. The current work is aimed at the employment of a seismic sensor array for the localization and tracking of a near-field wideband moving source. In this paper, the mathematical derivation of a novel DOA estimation algorithm-dubbed the Modified Kirlin Method-has been presented in details. The estimated DOAs are then combined using a least-squares optimization method for source localization. The performance of the proposed method has been evaluated in a field experiment to track a moving truck. We also compare the DOA estimation and source localization results of the proposed method with those of two other existing methods originally developed for localization of a stationary wideband source; Covariance Matrix Analysis and the Surface Wave Analysis. Our results indicate that both the Surface Wave Analysis and the Modified Kirlin Methods are effective in locating and tracking a moving truck.

  7. An Analog Circuit Approximation of the Discrete Wavelet Transform for Ultra Low Power Signal Processing in Wearable Sensor Nodes.

    PubMed

    Casson, Alexander J

    2015-01-01

    Ultra low power signal processing is an essential part of all sensor nodes, and particularly so in emerging wearable sensors for biomedical applications. Analog signal processing has an important role in these low power, low voltage, low frequency applications, and there is a key drive to decrease the power consumption of existing analog domain signal processing and to map more signal processing approaches into the analog domain. This paper presents an analog domain signal processing circuit which approximates the output of the Discrete Wavelet Transform (DWT) for use in ultra low power wearable sensors. Analog filters are used for the DWT filters and it is demonstrated how these generate analog domain DWT-like information that embeds information from Butterworth and Daubechies maximally flat mother wavelet responses. The Analog DWT is realised in hardware via g(m)C circuits, designed to operate from a 1.3 V coin cell battery, and provide DWT-like signal processing using under 115 nW of power when implemented in a 0.18 μm CMOS process. Practical examples demonstrate the effective use of the new Analog DWT on ECG (electrocardiogram) and EEG (electroencephalogram) signals recorded from humans. PMID:26694414

  8. An Analog Circuit Approximation of the Discrete Wavelet Transform for Ultra Low Power Signal Processing in Wearable Sensor Nodes

    PubMed Central

    Casson, Alexander J.

    2015-01-01

    Ultra low power signal processing is an essential part of all sensor nodes, and particularly so in emerging wearable sensors for biomedical applications. Analog signal processing has an important role in these low power, low voltage, low frequency applications, and there is a key drive to decrease the power consumption of existing analog domain signal processing and to map more signal processing approaches into the analog domain. This paper presents an analog domain signal processing circuit which approximates the output of the Discrete Wavelet Transform (DWT) for use in ultra low power wearable sensors. Analog filters are used for the DWT filters and it is demonstrated how these generate analog domain DWT-like information that embeds information from Butterworth and Daubechies maximally flat mother wavelet responses. The Analog DWT is realised in hardware via gmC circuits, designed to operate from a 1.3 V coin cell battery, and provide DWT-like signal processing using under 115 nW of power when implemented in a 0.18 μm CMOS process. Practical examples demonstrate the effective use of the new Analog DWT on ECG (electrocardiogram) and EEG (electroencephalogram) signals recorded from humans. PMID:26694414

  9. Artificial intelligence applied to process signal analysis

    NASA Technical Reports Server (NTRS)

    Corsberg, Dan

    1988-01-01

    Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

  10. Digital signal processing in the radio science stability analyzer

    NASA Technical Reports Server (NTRS)

    Greenhall, C. A.

    1995-01-01

    The Telecommunications Division has built a stability analyzer for testing Deep Space Network installations during flight radio science experiments. The low-frequency part of the analyzer operates by digitizing wave signals with bandwidths between 80 Hz and 45 kHz. Processed outputs include spectra of signal, phase, amplitude, and differential phase; time series of the same quantities; and Allan deviation of phase and differential phase. This article documents the digital signal-processing methods programmed into the analyzer.

  11. Uncovering brain–heart information through advanced signal and image processing

    PubMed Central

    Toschi, Nicola; Barbieri, Riccardo

    2016-01-01

    Through their dynamical interplay, the brain and the heart ensure fundamental homeostasis and mediate a number of physiological functions as well as their disease-related aberrations. Although a vast number of ad hoc analytical and computational tools have been recently applied to the non-invasive characterization of brain and heart dynamic functioning, little attention has been devoted to combining information to unveil the interactions between these two physiological systems. This theme issue collects contributions from leading experts dealing with the development of advanced analytical and computational tools in the field of biomedical signal and image processing. It includes perspectives on recent advances in 7 T magnetic resonance imaging as well as electroencephalogram, electrocardiogram and cerebrovascular flow processing, with the specific aim of elucidating methods to uncover novel biological and physiological correlates of brain–heart physiology and physiopathology. PMID:27044995

  12. Uncovering brain-heart information through advanced signal and image processing.

    PubMed

    Valenza, Gaetano; Toschi, Nicola; Barbieri, Riccardo

    2016-05-13

    Through their dynamical interplay, the brain and the heart ensure fundamental homeostasis and mediate a number of physiological functions as well as their disease-related aberrations. Although a vast number of ad hoc analytical and computational tools have been recently applied to the non-invasive characterization of brain and heart dynamic functioning, little attention has been devoted to combining information to unveil the interactions between these two physiological systems. This theme issue collects contributions from leading experts dealing with the development of advanced analytical and computational tools in the field of biomedical signal and image processing. It includes perspectives on recent advances in 7 T magnetic resonance imaging as well as electroencephalogram, electrocardiogram and cerebrovascular flow processing, with the specific aim of elucidating methods to uncover novel biological and physiological correlates of brain-heart physiology and physiopathology. PMID:27044995

  13. Signal processing at the Poker Flat MST radar

    NASA Technical Reports Server (NTRS)

    Carter, D. A.

    1983-01-01

    Signal processing for Mesosphere-Stratosphere-Troposphere (MST) radar is carried out by a combination of hardware in high-speed, special-purpose devices and software in a general-purpose, minicomputer/array processor. A block diagram of the signal processing system is presented, and the steps in the processing pathway are described. The current processing capabilities are given, and a system offering greater coherent integration speed is advanced which hinges upon a high speed preprocessor.

  14. Signal processing and electronic noise in LZ

    NASA Astrophysics Data System (ADS)

    Khaitan, D.

    2016-03-01

    The electronics of the LUX-ZEPLIN (LZ) experiment, the 10-tonne dark matter detector to be installed at the Sanford Underground Research Facility (SURF), consists of low-noise dual-gain amplifiers and a 100-MHz, 14-bit data acquisition system for the TPC PMTs. Pre-prototypes of the analog amplifiers and the 32-channel digitizers were tested extensively with simulated pulses that are similar to the prompt scintillation light and the electroluminescence signals expected in LZ. These studies are used to characterize the noise and to measure the linearity of the system. By increasing the amplitude of the test signals, the effect of saturating the amplifier and the digitizers was studied. The RMS ADC noise of the digitizer channels was measured to be 1.19± 0.01 ADCC. When a high-energy channel of the amplifier is connected to the digitizer, the measured noise remained virtually unchanged, while the noise added by a low-energy channel was estimated to be 0.38 ± 0.02 ADCC (46 ± 2 μV). A test facility is under construction to study saturation, mitigate noise and measure the performance of the LZ electronics and data acquisition chain.

  15. Safety Assessment of Commonly Used Nanoparticles in Biomedical Applications: Impact on Inflammatory Processes

    NASA Astrophysics Data System (ADS)

    Alnasser, Yossef

    Nanotechnology offers great promise in the biomedical field. Current knowledge of nanoparticles' (NPs) safety and possible mechanisms of various particle types' toxicity is insufficient. The role of particle properties and the route of particles administration in toxic reactions remain unexplored. In this thesis, we aimed to inspect the interrelationship between particle size, chemical composition and toxicological effects of four candidate NPs for drug delivery systems: gold (Au), chitosan, silica, and poly (lactide-co-glycolide) (PLGA). Mice model was combined with in vitro study to explore NPs' safety. We investigated mice survival, weight, behavior, and pro-inflammatory changes. NF-kappaB induction was assessed in vitro using the Luciferase Assay System. As observed in mice, Au NPs had a higher toxicity profile at a shorter duration than the other NPs. This was significantly in concordance with pro-inflammatory changes which may be the key routes of Au NPs toxicity. Although silica NPs induced NF-kappaB, they were less toxic to the mice than Au NPs and did not lead to the pro-inflammatory changes. Chitosan NPs were toxic to the mice but failed to cause significant NF-kappaB induction and pro-inflammatory changes. These findings indicate that chitosan NPs might not have the same pathophysiologic mechanism as the Au NPs. Comparative analysis in this model demonstrated that PLGA NPs is the safest drug delivery candidate to be administered subcutaneously.

  16. [Dynamic Pulse Signal Processing and Analyzing in Mobile System].

    PubMed

    Chou, Yongxin; Zhang, Aihua; Ou, Jiqing; Qi, Yusheng

    2015-09-01

    In order to derive dynamic pulse rate variability (DPRV) signal from dynamic pulse signal in real time, a method for extracting DPRV signal was proposed and a portable mobile monitoring system was designed. The system consists of a front end for collecting and wireless sending pulse signal and a mobile terminal. The proposed method is employed to extract DPRV from dynamic pulse signal in mobile terminal, and the DPRV signal is analyzed both in the time domain and the frequency domain and also with non-linear method in real time. The results show that the proposed method can accurately derive DPRV signal in real time, the system can be used for processing and analyzing DPRV signal in real time. PMID:26904868

  17. Statistical mechanics and visual signal processing

    NASA Astrophysics Data System (ADS)

    Potters, Marc; Bialek, William

    1994-11-01

    We show how to use the language of statistical field theory to address and solve problems in which one must estimate some aspect of the environnent from the data in an array of sensors. In the field theory formulation the optimal estimator can be written as an expectation value in an ensemble where the input data act as external field. Problems at low signal-to-noise ratio can be solved in perturbation theory, while high signal-to-noise ratios are treated with a saddle-point approximation. These ideas are illustrated in detail by an example of visual motion estimation which is chosen to model a problem solved by the fly's brain. The optimal estimator bas a rich structure, adapting to various parameters of the environnent such as the mean-square contrast and the corrélation time of contrast fluctuations. This structure is in qualitative accord with existing measurements on motion sensitive neurons in the fly's brain, and the adaptive properties of the optimal estimator may help resolve conficts among different interpretations of these data. Finally we propose some crucial direct tests of the adaptive behavior. Nous montrons comment employer le langage de la théorie statistique des champs pour poser et résoudre des problèmes où l'on doit estimer une caractéristique de l'environnement à l'aide de données provenant d'un ensemble de détecteurs. Dans ce formalisme, l'estimateur optimal peut être écrit comme la valeur moyenne d'un opérateur, l'ensemble des données d'entrée agissant comme un champ externe. Les problèmes à faible rapport signal-bruit sont résolus par la théorie des perturbations. La méthode du col est employée pour ceux à haut rapport signal-bruit. Ces idées sont illustrées en détails sur un modèle d'estimation visuelle du mouvement basé sur un problème résolu par la mouche. L'estimateur optimal a une structure très riche, s'adaptant à divers paramètres de l'environnement tels la variance du contraste et le temps de corr

  18. Time reversal signal processing for communication.

    SciTech Connect

    Young, Derek P.; Jacklin, Neil; Punnoose, Ratish J.; Counsil, David T.

    2011-09-01

    Time-reversal is a wave focusing technique that makes use of the reciprocity of wireless propagation channels. It works particularly well in a cluttered environment with associated multipath reflection. This technique uses the multipath in the environment to increase focusing ability. Time-reversal can also be used to null signals, either to reduce unintentional interference or to prevent eavesdropping. It does not require controlled geometric placement of the transmit antennas. Unlike existing techniques it can work without line-of-sight. We have explored the performance of time-reversal focusing in a variety of simulated environments. We have also developed new algorithms to simultaneously focus at a location while nulling at an eavesdropper location. We have experimentally verified these techniques in a realistic cluttered environment.

  19. Neuromorphic opto-electronic integrated circuits for optical signal processing

    NASA Astrophysics Data System (ADS)

    Romeira, B.; Javaloyes, J.; Balle, S.; Piro, O.; Avó, R.; Figueiredo, J. M. L.

    2014-08-01

    The ability to produce narrow optical pulses has been extensively investigated in laser systems with promising applications in photonics such as clock recovery, pulse reshaping, and recently in photonics artificial neural networks using spiking signal processing. Here, we investigate a neuromorphic opto-electronic integrated circuit (NOEIC) comprising a semiconductor laser driven by a resonant tunneling diode (RTD) photo-detector operating at telecommunication (1550 nm) wavelengths capable of excitable spiking signal generation in response to optical and electrical control signals. The RTD-NOEIC mimics biologically inspired neuronal phenomena and possesses high-speed response and potential for monolithic integration for optical signal processing applications.

  20. A comb filter based signal processing method to effectively reduce motion artifacts from photoplethysmographic signals.

    PubMed

    Peng, Fulai; Liu, Hongyun; Wang, Weidong

    2015-10-01

    A photoplethysmographic (PPG) signal can provide very useful information about a subject's cardiovascular status. Motion artifacts (MAs), which usually deteriorate the waveform of a PPG signal, severely obstruct its applications in the clinical diagnosis and healthcare area. To reduce the MAs from a PPG signal, in the present study we present a comb filter based signal processing method. Firstly, wavelet de-noising was implemented to preliminarily suppress a part of the MAs. Then, the PPG signal in the time domain was transformed into the frequency domain by a fast Fourier transform (FFT). Thirdly, the PPG signal period was estimated from the frequency domain by tracking the fundamental frequency peak of the PPG signal. Lastly, the MAs were removed by the comb filter which was designed based on the obtained PPG signal period. Experiments with synthetic and real-world datasets were implemented to validate the performance of the method. Results show that the proposed method can effectively restore the PPG signals from the MA corrupted signals. Also, the accuracy of blood oxygen saturation (SpO2), calculated from red and infrared PPG signals, was significantly improved after the MA reduction by the proposed method. Our study demonstrates that the comb filter can effectively reduce the MAs from a PPG signal provided that the PPG signal period is obtained. PMID:26334000

  1. Conflicting interests involved in the process of publishing in biomedical journals.

    PubMed

    Igi, Rajko

    2015-01-01

    This short discussion on conflicting interests in publishing is designed to help all participants (authors, editors and peer reviewers) in the publication of biomedical papers. Authors who submit manuscripts to a journal are responsible for the overall quality and integrity of the paper. The main goal of the editor is to provide readers with the most relevant information by insuring proper presentation and interpretation of scientific data. The editor informs readers on potential conflicting interests of the authors to enable the reader to judge a paper in a more informative way. However, the editor must also consider potential conflicting interests of peer reviewers. If a peer reviewer has a potential conflicting interest in evaluating a manuscript, he/she should not accept the job of reviewing it. If the editor or any member of the executive board has a similar conflict of interest for an article under consideration, including an editorial for this journal, such persons should not participate in the vote to endorse the article, and the journal should publish a note to that effect. When an article is published in the local language for a "small scientific community" there is always a risk that peer review could reflect personal relationships and animosities. Blinding the reviewer to the author(s) might eliminate a reviewer's conflict of interests, but this is not always possible or even desirable. A better solution would be to have the journal publish all scientific articles in English. This would provide both wider readership and a larger group of international reviewers. To gain better reviewers, the journal staff could educate young local investigators by publishing educational articles. Advantages and disadvantages of publishing a statement on conflicting interests are discussed. PMID:26537088

  2. New signal processing technique for density profile reconstruction using reflectometry

    SciTech Connect

    Clairet, F.; Bottereau, C.; Ricaud, B.; Briolle, F.; Heuraux, S.

    2011-08-15

    Reflectometry profile measurement requires an accurate determination of the plasma reflected signal. Along with a good resolution and a high signal to noise ratio of the phase measurement, adequate data analysis is required. A new data processing based on time-frequency tomographic representation is used. It provides a clearer separation between multiple components and improves isolation of the relevant signals. In this paper, this data processing technique is applied to two sets of signals coming from two different reflectometer devices used on the Tore Supra tokamak. For the standard density profile reflectometry, it improves the initialization process and its reliability, providing a more accurate profile determination in the far scrape-off layer with density measurements as low as 10{sup 16} m{sup -1}. For a second reflectometer, which provides measurements in front of a lower hybrid launcher, this method improves the separation of the relevant plasma signal from multi-reflection processes due to the proximity of the plasma.

  3. New signal processing technique for density profile reconstruction using reflectometry.

    PubMed

    Clairet, F; Ricaud, B; Briolle, F; Heuraux, S; Bottereau, C

    2011-08-01

    Reflectometry profile measurement requires an accurate determination of the plasma reflected signal. Along with a good resolution and a high signal to noise ratio of the phase measurement, adequate data analysis is required. A new data processing based on time-frequency tomographic representation is used. It provides a clearer separation between multiple components and improves isolation of the relevant signals. In this paper, this data processing technique is applied to two sets of signals coming from two different reflectometer devices used on the Tore Supra tokamak. For the standard density profile reflectometry, it improves the initialization process and its reliability, providing a more accurate profile determination in the far scrape-off layer with density measurements as low as 10(16) m(-1). For a second reflectometer, which provides measurements in front of a lower hybrid launcher, this method improves the separation of the relevant plasma signal from multi-reflection processes due to the proximity of the plasma. PMID:21895243

  4. Understanding the effects of pre-processing on extracted signal features from gait accelerometry signals.

    PubMed

    Millecamps, Alexandre; Lowry, Kristin A; Brach, Jennifer S; Perera, Subashan; Redfern, Mark S; Sejdić, Ervin

    2015-07-01

    Gait accelerometry is an important approach for gait assessment. Previous contributions have adopted various pre-processing approaches for gait accelerometry signals, but none have thoroughly investigated the effects of such pre-processing operations on the obtained results. Therefore, this paper investigated the influence of pre-processing operations on signal features extracted from gait accelerometry signals. These signals were collected from 35 participants aged over 65years: 14 of them were healthy controls (HC), 10 had Parkinson׳s disease (PD) and 11 had peripheral neuropathy (PN). The participants walked on a treadmill at preferred speed. Signal features in time, frequency and time-frequency domains were computed for both raw and pre-processed signals. The pre-processing stage consisted of applying tilt correction and denoising operations to acquired signals. We first examined the effects of these operations separately, followed by the investigation of their joint effects. Several important observations were made based on the obtained results. First, the denoising operation alone had almost no effects in comparison to the trends observed in the raw data. Second, the tilt correction affected the reported results to a certain degree, which could lead to a better discrimination between groups. Third, the combination of the two pre-processing operations yielded similar trends as the tilt correction alone. These results indicated that while gait accelerometry is a valuable approach for the gait assessment, one has to carefully adopt any pre-processing steps as they alter the observed findings. PMID:25935124

  5. Understanding the effects of pre-processing on extracted signal features from gait accelerometry signals

    PubMed Central

    Millecamps, Alexandre; Brach, Jennifer S.; Lowry, Kristin A.; Perera, Subashan; Redfern, Mark S.

    2015-01-01

    Gait accelerometry is an important approach for gait assessment. Previous contributions have adopted various pre-processing approaches for gait accelerometry signals, but none have thoroughly investigated the effects of such pre-processing operations on the obtained results. Therefore, this paper investigated the influence of pre-processing operations on signal features extracted from gait accelerometry signals. These signals were collected from 35 participants aged over 65 years-old: 14 of them were healthy controls (HC), 10 had Parkinson’s disease (PD) and 11 had peripheral neuropathy (PN). The participants walked on a treadmill at preferred speed. Signal features in time, frequency and time-frequency domains were computed for both raw and pre-processed signals. The pre-processing stage consisted of applying tilt correction and de-noising operations to acquired signals. We first examined the effects of these operations separately, followed by the investigation of their joint effects. Several important observations were made based on the obtained results. First, the denoising operation alone had almost no effects in comparison to the trends observed in the raw data. Second, the tilt correction affected the reported results to a certain degree, which could lead to a better discrimination between groups. Third, the combination of the two pre-processing operations yielded similar trends as the tilt correction alone. These results indicated that while gait accelerometry is a valuable approach for the gait assessment, one has to carefully adopt any pre-processing steps as they alter the observed findings. PMID:25935124

  6. Physics-based signal processing algorithms for micromachined cantilever arrays

    DOEpatents

    Candy, James V; Clague, David S; Lee, Christopher L; Rudd, Robert E; Burnham, Alan K; Tringe, Joseph W

    2013-11-19

    A method of using physics-based signal processing algorithms for micromachined cantilever arrays. The methods utilize deflection of a micromachined cantilever that represents the chemical, biological, or physical element being detected. One embodiment of the method comprises the steps of modeling the deflection of the micromachined cantilever producing a deflection model, sensing the deflection of the micromachined cantilever and producing a signal representing the deflection, and comparing the signal representing the deflection with the deflection model.

  7. 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. PMID:24321955

  8. Preliminary development of digital signal processing in microwave radiometers

    NASA Technical Reports Server (NTRS)

    Stanley, W. D.

    1980-01-01

    Topics covered involve a number of closely related tasks including: the development of several control loop and dynamic noise model computer programs for simulating microwave radiometer measurements; computer modeling of an existing stepped frequency radiometer in an effort to determine its optimum operational characteristics; investigation of the classical second order analog control loop to determine its ability to reduce the estimation error in a microwave radiometer; investigation of several digital signal processing unit designs; initiation of efforts to develop required hardware and software for implementation of the digital signal processing unit; and investigation of the general characteristics and peculiarities of digital processing noiselike microwave radiometer signals.

  9. Modeling laser velocimeter signals as triply stochastic Poisson processes

    NASA Technical Reports Server (NTRS)

    Mayo, W. T., Jr.

    1976-01-01

    Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

  10. Advanced Integrated Optical Signal Processing Components.

    NASA Astrophysics Data System (ADS)

    Rastani, Kasra

    This research was aimed at the development of advanced integrated optical components suitable for devices capable of processing multi-dimensional inputs. In such processors, densely packed waveguide arrays with low crosstalk are needed to provide dissection of the information that has been partially processed. Waveguide arrays also expand the information in the plane of the processor while maintaining its coherence. Rib waveguide arrays with low loss, high mode confinement and highly uniform surface quality (660 elements, 8 μm wide, 1 μm high, and 1 cm long with 2 mu m separations) were fabricated on LiNbO _3 substrates through the ion beam milling technique. A novel feature of the multi-dimensional IO processor architecture proposed herein is the implementation of large area uniform outcoupling (with low to moderate outcoupling efficiencies) from rib waveguide arrays in order to access the third dimension of the processor structure. As a means of outcoupling, uniform surface gratings (2 μm and 4 μm grating periods, 0.05 μm high and 1 mm long) with low outcoupling efficiencies (of approximately 2-18%/mm) were fabricated on the nonuniform surface of the rib waveguide arrays. As a practical technique of modulating the low outcoupling efficiencies of the surface gratings, it was proposed to alter the period of the grating as a function of position along each waveguide. Large aperture (2.5 mm) integrated lenses with short positive focal lengths (1.2-2.5 cm) were developed through a modification of the titanium-indiffused proton exchanged (TIPE) technique. Such integrated lenses were fabricated by increasing the refractive index of the slab waveguides by the TIPE process while maintaining the refractive index of the lenses at the lower level of Ti:LiNbO _3 waveguide. By means of curvature reversal of the integrated lenses, positive focal length lenses have been fabricated while providing high mode confinement for the slab waveguide. The above elements performed as

  11. HYMOSS signal processing for pushbroom spectral imaging

    NASA Technical Reports Server (NTRS)

    Ludwig, David E.

    1991-01-01

    The objective of the Pushbroom Spectral Imaging Program was to develop on-focal plane electronics which compensate for detector array non-uniformities. The approach taken was to implement a simple two point calibration algorithm on focal plane which allows for offset and linear gain correction. The key on focal plane features which made this technique feasible was the use of a high quality transimpedance amplifier (TIA) and an analog-to-digital converter for each detector channel. Gain compensation is accomplished by varying the feedback capacitance of the integrate and dump TIA. Offset correction is performed by storing offsets in a special on focal plane offset register and digitally subtracting the offsets from the readout data during the multiplexing operation. A custom integrated circuit was designed, fabricated, and tested on this program which proved that nonuniformity compensated, analog-to-digital converting circuits may be used to read out infrared detectors. Irvine Sensors Corporation (ISC) successfully demonstrated the following innovative on-focal-plane functions that allow for correction of detector non-uniformities. Most of the circuit functions demonstrated on this program are finding their way onto future IC's because of their impact on reduced downstream processing, increased focal plane performance, simplified focal plane control, reduced number of dewar connections, as well as the noise immunity of a digital interface dewar. The potential commercial applications for this integrated circuit are primarily in imaging systems. These imaging systems may be used for: security monitoring systems, manufacturing process monitoring, robotics, and for spectral imaging when used in analytical instrumentation.

  12. HYMOSS signal processing for pushbroom spectral imaging

    NASA Astrophysics Data System (ADS)

    Ludwig, David E.

    1991-06-01

    The objective of the Pushbroom Spectral Imaging Program was to develop on-focal plane electronics which compensate for detector array non-uniformities. The approach taken was to implement a simple two point calibration algorithm on focal plane which allows for offset and linear gain correction. The key on focal plane features which made this technique feasible was the use of a high quality transimpedance amplifier (TIA) and an analog-to-digital converter for each detector channel. Gain compensation is accomplished by varying the feedback capacitance of the integrate and dump TIA. Offset correction is performed by storing offsets in a special on focal plane offset register and digitally subtracting the offsets from the readout data during the multiplexing operation. A custom integrated circuit was designed, fabricated, and tested on this program which proved that nonuniformity compensated, analog-to-digital converting circuits may be used to read out infrared detectors. Irvine Sensors Corporation (ISC) successfully demonstrated the following innovative on-focal-plane functions that allow for correction of detector non-uniformities. Most of the circuit functions demonstrated on this program are finding their way onto future IC's because of their impact on reduced downstream processing, increased focal plane performance, simplified focal plane control, reduced number of dewar connections, as well as the noise immunity of a digital interface dewar. The potential commercial applications for this integrated circuit are primarily in imaging systems. These imaging systems may be used for: security monitoring systems, manufacturing process monitoring, robotics, and for spectral imaging when used in analytical instrumentation.

  13. Novel sonar signal processing tool using Shannon entropy

    SciTech Connect

    Quazi, A.H.

    1996-06-01

    Traditionally, conventional signal processing extracts information from sonar signals using amplitude, signal energy or frequency domain quantities obtained using spectral analysis techniques. The object is to investigate an alternate approach which is entirely different than that of traditional signal processing. This alternate approach is to utilize the Shannon entropy as a tool for the processing of sonar signals with emphasis on detection, classification, and localization leading to superior sonar system performance. Traditionally, sonar signals are processed coherently, semi-coherently, and incoherently, depending upon the a priori knowledge of the signals and noise. Here, the detection, classification, and localization technique will be based on the concept of the entropy of the random process. Under a constant energy constraint, the entropy of a received process bearing finite number of sample points is maximum when hypothesis H{sub 0} (that the received process consists of noise alone) is true and decreases when correlated signal is present (H{sub 1}). Therefore, the strategy used for detection is: (I) Calculate the entropy of the received data; then, (II) compare the entropy with the maximum value; and, finally, (III) make decision: H{sub 1} is assumed if the difference is large compared to pre-assigned threshold and H{sub 0} is otherwise assumed. The test statistics will be different between entropies under H{sub 0} and H{sub 1}. Here, we shall show the simulated results for detecting stationary and non-stationary signals in noise, and results on detection of defects in a Plexiglas bar using an ultrasonic experiment conducted by Hughes. {copyright} {ital 1996 American Institute of Physics.}

  14. Signal and image processing for early detection of coronary artery diseases: A review

    NASA Astrophysics Data System (ADS)

    Mobssite, Youness; Samir, B. Belhaouari; Mohamad Hani, Ahmed Fadzil B.

    2012-09-01

    Today biomedical signals and image based detection are a basic step to diagnose heart diseases, in particular, coronary artery diseases. The goal of this work is to provide non-invasive early detection of Coronary Artery Diseases relying on analyzing images and ECG signals as a combined approach to extract features, further classify and quantify the severity of DCAD by using B-splines method. In an aim of creating a prototype of screening biomedical imaging for coronary arteries to help cardiologists to decide the kind of treatment needed to reduce or control the risk of heart attack.

  15. Signal processing techniques for synchronization of wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Lee, Jaehan; Wu, Yik-Chung; Chaudhari, Qasim; Qaraqe, Khalid; Serpedin, Erchin

    2010-11-01

    Clock synchronization is a critical component in wireless sensor networks, as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and sleep wake-up scheduling, etc. Early studies on clock synchronization for wireless sensor networks mainly focus on protocol design. However, clock synchronization problem is inherently related to parameter estimation, and recently, studies of clock synchronization from the signal processing viewpoint started to emerge. In this article, a survey of latest advances on clock synchronization is provided by adopting a signal processing viewpoint. We demonstrate that many existing and intuitive clock synchronization protocols can be interpreted by common statistical signal processing methods. Furthermore, the use of advanced signal processing techniques for deriving optimal clock synchronization algorithms under challenging scenarios will be illustrated.

  16. Optical Signal Processing: Poisson Image Restoration and Shearing Interferometry

    NASA Technical Reports Server (NTRS)

    Hong, Yie-Ming

    1973-01-01

    Optical signal processing can be performed in either digital or analog systems. Digital computers and coherent optical systems are discussed as they are used in optical signal processing. Topics include: image restoration; phase-object visualization; image contrast reversal; optical computation; image multiplexing; and fabrication of spatial filters. Digital optical data processing deals with restoration of images degraded by signal-dependent noise. When the input data of an image restoration system are the numbers of photoelectrons received from various areas of a photosensitive surface, the data are Poisson distributed with mean values proportional to the illuminance of the incoherently radiating object and background light. Optical signal processing using coherent optical systems is also discussed. Following a brief review of the pertinent details of Ronchi's diffraction grating interferometer, moire effect, carrier-frequency photography, and achromatic holography, two new shearing interferometers based on them are presented. Both interferometers can produce variable shear.

  17. Synthetic aperture radar signal processing: Trends and technologies

    NASA Technical Reports Server (NTRS)

    Curlander, John C.

    1993-01-01

    An overview of synthetic aperture radar (SAR) technology is presented in vugraph form. The following topics are covered: an SAR ground data system; SAR signal processing algorithms; SAR correlator architectures; and current and future trends.

  18. 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.

  19. Comparative analysis of genomic signal processing for microarray data clustering.

    PubMed

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods. PMID:22157075

  20. The physics of bat echolocation: Signal processing techniques

    NASA Astrophysics Data System (ADS)

    Denny, Mark

    2004-12-01

    The physical principles and signal processing techniques underlying bat echolocation are investigated. It is shown, by calculation and simulation, how the measured echolocation performance of bats can be achieved.

  1. Functional description of signal processing in the Rogue GPS receiver

    NASA Technical Reports Server (NTRS)

    Thomas, J. B.

    1988-01-01

    Over the past year, two Rogue GPS prototype receivers have been assembled and successfully subjected to a variety of laboratory and field tests. A functional description is presented of signal processing in the Rogue receiver, tracing the signal from RF input to the output values of group delay, phase, and data bits. The receiver can track up to eight satellites, without time multiplexing among satellites or channels, simultaneously measuring both group delay and phase for each of three channels (L1-C/A, L1-P, L2-P). The Rogue signal processing described requires generation of the code for all three channels. Receiver functional design, which emphasized accuracy, reliability, flexibility, and dynamic capability, is summarized. A detailed functional description of signal processing is presented, including C/A-channel and P-channel processing, carrier-aided averaging of group delays, checks for cycle slips, acquistion, and distinctive features.

  2. 28. Perimeter acquisition radar building room #302, signal process and ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    28. Perimeter acquisition radar building room #302, signal process and analog receiver room - Stanley R. Mickelsen Safeguard Complex, Perimeter Acquisition Radar Building, Limited Access Area, between Limited Access Patrol Road & Service Road A, Nekoma, Cavalier County, ND

  3. A survey of the economics of materials processing in space. [accenting biomedical materials

    NASA Technical Reports Server (NTRS)

    Miller, B. P.

    1975-01-01

    A survey of the economics of space materials processing has been performed with the objectives of identifying those areas of space materials processing that give preliminary indication of significant economic potential, and to identify possible approaches to quantify the economic potential. It is concluded that limited economic studies have been performed to date, primarily in the area of the processing of inorganic materials, but that the economics of space processing of biological material has not received adequate attention. Specific studies are recommended to evaluate the economic impact of human lymphocyte subgroup separation on organ transplantation, and on the separation and concentration of urokinase producing cells.

  4. Relationships between digital signal processing and control and estimation theory

    NASA Technical Reports Server (NTRS)

    Willsky, A. S.

    1978-01-01

    Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.

  5. All-optical signal processing using dynamic Brillouin gratings

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    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.

  6. 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

  7. A Study on Signal Group Processing of AUTOSAR COM Module

    NASA Astrophysics Data System (ADS)

    Lee, Jeong-Hwan; Hwang, Hyun Yong; Han, Tae Man; Ahn, Yong Hak

    2013-06-01

    In vehicle, there are many ECU(Electronic Control Unit)s, and ECUs are connected to networks such as CAN, LIN, FlexRay, and so on. AUTOSAR COM(Communication) which is a software platform of AUTOSAR(AUTomotive Open System ARchitecture) in the international industry standards of automotive electronic software processes signals and signal groups for data communications between ECUs. Real-time and reliability are very important for data communications in the vehicle. Therefore, in this paper, we analyze functions of signals and signal groups used in COM, and represent that functions of signal group are more efficient than signals in real-time data synchronization and network resource usage between the sender and receiver.

  8. 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.

  9. Simplified signal processing for an airborne CO2 Doppler lidar

    NASA Technical Reports Server (NTRS)

    Schwiesow, R. L.; Spowart, M. P.

    1992-01-01

    In the development of the National Center for Atmospheric Research (NCAR) airborne infrared lidar system (NAILS), we have emphasized a simple, modular design to suit the instrument to its mission of providing measurements of atmospheric structure and dynamics from an aircraft platform. Based on our research to this point, we believe that a significant simplification of the signal processing approach compared to that now used is possible by using high speed digitization of the signal. The purpose here is to place signal processing in the context of the overall system design and to explore the basis of the alternative technique so that the community can comment on the approach.

  10. Signal-processing theory for the TurboRogue receiver

    NASA Technical Reports Server (NTRS)

    Thomas, J. B.

    1995-01-01

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

  11. A comparison of signal processing techniques for Intrinsic Optical Signal imaging in mice.

    PubMed

    Turley, Jordan A; Nilsson, Michael; Walker, Frederick Rohan; Johnson, Sarah J

    2015-08-01

    Intrinsic Optical Signal imaging is a technique which allows the visualisation and mapping of activity related changes within the brain with excellent spatial and temporal resolution. We analysed a variety of signal and image processing techniques applied to real mouse imaging data. The results were compared in an attempt to overcome the unique issues faced when performing the technique on mice and improve the understanding of post processing options available. PMID:26737728

  12. Biomedical digital assistant for ubiquitous healthcare.

    PubMed

    Lee, Tae-Soo; Hong, Joo-Hyun; Cho, Myeong-Chan

    2007-01-01

    The concept of ubiquitous healthcare service, which emerged as one of measures to solve healthcare problems in aged society, means that patients can receive services such as prevention, diagnosis, therapy and prognosis management at any time and in any place with the help of advanced information and communication technology. This service requires not only biomedical digital assistant that can monitor continuously the patients' health condition regardless of time and place, but also wired and wireless communication devices and telemedicine servers that provide doctors with data on patients' present health condition. In order to implement a biomedical digital assistant that is portable and wearable to patients, the present study developed a device that minimizes size, weight and power consumption, measures ECG and PPG signals, and even monitors moving patients' state. The biomedical sensor with the function of wireless communication was designed to be highly portable and wearable, to be operable 24 hours with small-size batteries, and to monitor the subject's heart rate, step count and respiratory rate in his daily life. The biomedical signal receiving device was implemented in two forms, PDA and cellular phone. The movement monitoring device embedded in the battery pack of a cellular phone does not have any problem in operating 24 hours, but the real-time biomedical signal receiving device implemented with PDA operated up to 6 hours due to the limited battery capacity of PDA. This problem is expected to be solved by reducing wireless communication load through improving the processing and storage functions of the sensor. The developed device can transmit a message on the patient's emergency to the remote server through the cellular phone network, and is expected to play crucial roles in the health management of chronic-aged patients in their daily life. PMID:18002325

  13. Signal processing method and system for noise removal and signal extraction

    DOEpatents

    Fu, Chi Yung; Petrich, Loren

    2009-04-14

    A signal processing method and system combining smooth level wavelet pre-processing together with artificial neural networks all in the wavelet domain for signal denoising and extraction. Upon receiving a signal corrupted with noise, an n-level decomposition of the signal is performed using a discrete wavelet transform to produce a smooth component and a rough component for each decomposition level. The n.sup.th level smooth component is then inputted into a corresponding neural network pre-trained to filter out noise in that component by pattern recognition in the wavelet domain. Additional rough components, beginning at the highest level, may also be retained and inputted into corresponding neural networks pre-trained to filter out noise in those components also by pattern recognition in the wavelet domain. In any case, an inverse discrete wavelet transform is performed on the combined output from all the neural networks to recover a clean signal back in the time domain.

  14. Process mapping of laser surface modification of AISI 316L stainless steel for biomedical applications

    NASA Astrophysics Data System (ADS)

    Chikarakara, Evans; Naher, Sumsun; Brabazon, Dermot

    2010-11-01

    A 1.5-kW CO2 laser in pulsed mode at 3 kHz was used to investigate the effects of varied laser process parameters and resulting morphology of AISI 316L stainless steel. Irradiance and residence time were varied between 7.9 to 23.6 MW/cm2 and 50 to 167 μs, respectively. A strong correlation between irradiance, residence time, depth of processing and roughness of processed steel was established. The high depth of altered microstructure and increased roughness were linked to higher levels of both irradiance and residence times. Energy fluence and surface temperature models were used to predict levels of melting occurring on the surface through the analysis of roughness and depth of the region processed. Microstructural images captured by the SEM revealed significant grain structure changes at higher irradiances, but due to increased residence times, limited to the laser in use, the hardness values were not improved.

  15. A corpus of full-text journal articles is a robust evaluation tool for revealing differences in performance of biomedical natural language processing tools

    PubMed Central

    2012-01-01

    Background We introduce the linguistic annotation of a corpus of 97 full-text biomedical publications, known as the Colorado Richly Annotated Full Text (CRAFT) corpus. We further assess the performance of existing tools for performing sentence splitting, tokenization, syntactic parsing, and named entity recognition on this corpus. Results Many biomedical natural language processing systems demonstrated large differences between their previously published results and their performance on the CRAFT corpus when tested with the publicly available models or rule sets. Trainable systems differed widely with respect to their ability to build high-performing models based on this data. Conclusions The finding that some systems were able to train high-performing models based on this corpus is additional evidence, beyond high inter-annotator agreement, that the quality of the CRAFT corpus is high. The overall poor performance of various systems indicates that considerable work needs to be done to enable natural language processing systems to work well when the input is full-text journal articles. The CRAFT corpus provides a valuable resource to the biomedical natural language processing community for evaluation and training of new models for biomedical full text publications. PMID:22901054

  16. Removing Background Noise with Phased Array Signal Processing

    NASA Technical Reports Server (NTRS)

    Podboy, Gary; Stephens, David

    2015-01-01

    Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

  17. Biomedical research

    NASA Technical Reports Server (NTRS)

    1981-01-01

    Biomedical problems encountered by man in space which have been identified as a result of previous experience in simulated or actual spaceflight include cardiovascular deconditioning, motion sickness, bone loss, muscle atrophy, red cell alterations, fluid and electrolyte loss, radiation effects, radiation protection, behavior, and performance. The investigations and the findings in each of these areas were reviewed. A description of how biomedical research is organized within NASA, how it is funded, and how it is being reoriented to meet the needs of future manned space missions is also provided.

  18. Simplified signal processing for impedance spectroscopy with spectrally sparse sequences

    NASA Astrophysics Data System (ADS)

    Annus, P.; Land, R.; Reidla, M.; Ojarand, J.; Mughal, Y.; Min, M.

    2013-04-01

    Classical method for measurement of the electrical bio-impedance involves excitation with sinusoidal waveform. Sinusoidal excitation at fixed frequency points enables wide variety of signal processing options, most general of them being Fourier transform. Multiplication with two quadrature waveforms at desired frequency could be easily accomplished both in analogue and in digital domains, even simplest quadrature square waves can be considered, which reduces signal processing task in analogue domain to synchronous switching followed by low pass filter, and in digital domain requires only additions. So called spectrally sparse excitation sequences (SSS), which have been recently introduced into bio-impedance measurement domain, are very reasonable choice when simultaneous multifrequency excitation is required. They have many good properties, such as ease of generation and good crest factor compared to similar multisinusoids. Typically, the usage of discrete or fast Fourier transform in signal processing step is considered so far. Usage of simplified methods nevertheless would reduce computational burden, and enable simpler, less costly and less energy hungry signal processing platforms. Accuracy of the measurement with SSS excitation when using different waveforms for quadrature demodulation will be compared in order to evaluate the feasibility of the simplified signal processing. Sigma delta modulated sinusoid (binary signal) is considered to be a good alternative for a synchronous demodulation.

  19. Assess sleep stage by modern signal processing techniques.

    PubMed

    Wu, Hau-tieng; Talmon, Ronen; Lo, Yu-Lun

    2015-04-01

    In this paper, two modern adaptive signal processing techniques, empirical intrinsic geometry and synchrosqueezing transform, are applied to quantify different dynamical features of the respiratory and electroencephalographic signals. We show that the proposed features are theoretically rigorously supported, as well as capture the sleep information hidden inside the signals. The features are used as input to multiclass support vector machines with the radial basis function to automatically classify sleep stages. The effectiveness of the classification based on the proposed features is shown to be comparable to human expert classification-the proposed classification of awake, REM, N1, N2, and N3 sleeping stages based on the respiratory signal (resp. respiratory and EEG signals) has the overall accuracy 81.7% (resp. 89.3%) in the relatively normal subject group. In addition, by examining the combination of the respiratory signal with the electroencephalographic signal, we conclude that the respiratory signal consists of ample sleep information, which supplements to the information stored in the electroencephalographic signal. PMID:25438301

  20. BioC: a minimalist approach to interoperability for biomedical text processing

    PubMed Central

    Comeau, Donald C.; Islamaj Doğan, Rezarta; Ciccarese, Paolo; Cohen, Kevin Bretonnel; Krallinger, Martin; Leitner, Florian; Lu, Zhiyong; Peng, Yifan; Rinaldi, Fabio; Torii, Manabu; Valencia, Alfonso; Verspoor, Karin; Wiegers, Thomas C.; Wu, Cathy H.; Wilbur, W. John

    2013-01-01

    A vast amount of scientific information is encoded in natural language text, and the quantity of such text has become so great that it is no longer economically feasible to have a human as the first step in the search process. Natural language processing and text mining tools have become essential to facilitate the search for and extraction of information from text. This has led to vigorous research efforts to create useful tools and to create humanly labeled text corpora, which can be used to improve such tools. To encourage combining these efforts into larger, more powerful and more capable systems, a common interchange format to represent, store and exchange the data in a simple manner between different language processing systems and text mining tools is highly desirable. Here we propose a simple extensible mark-up language format to share text documents and annotations. The proposed annotation approach allows a large number of different annotations to be represented including sentences, tokens, parts of speech, named entities such as genes or diseases and relationships between named entities. In addition, we provide simple code to hold this data, read it from and write it back to extensible mark-up language files and perform some sample processing. We also describe completed as well as ongoing work to apply the approach in several directions. Code and data are available at http://bioc.sourceforge.net/. Database URL: http://bioc.sourceforge.net/ PMID:24048470

  1. BioC: a minimalist approach to interoperability for biomedical text processing.

    PubMed

    Comeau, Donald C; Islamaj Doğan, Rezarta; Ciccarese, Paolo; Cohen, Kevin Bretonnel; Krallinger, Martin; Leitner, Florian; Lu, Zhiyong; Peng, Yifan; Rinaldi, Fabio; Torii, Manabu; Valencia, Alfonso; Verspoor, Karin; Wiegers, Thomas C; Wu, Cathy H; Wilbur, W John

    2013-01-01

    A vast amount of scientific information is encoded in natural language text, and the quantity of such text has become so great that it is no longer economically feasible to have a human as the first step in the search process. Natural language processing and text mining tools have become essential to facilitate the search for and extraction of information from text. This has led to vigorous research efforts to create useful tools and to create humanly labeled text corpora, which can be used to improve such tools. To encourage combining these efforts into larger, more powerful and more capable systems, a common interchange format to represent, store and exchange the data in a simple manner between different language processing systems and text mining tools is highly desirable. Here we propose a simple extensible mark-up language format to share text documents and annotations. The proposed annotation approach allows a large number of different annotations to be represented including sentences, tokens, parts of speech, named entities such as genes or diseases and relationships between named entities. In addition, we provide simple code to hold this data, read it from and write it back to extensible mark-up language files and perform some sample processing. We also describe completed as well as ongoing work to apply the approach in several directions. Code and data are available at http://bioc.sourceforge.net/. Database URL: http://bioc.sourceforge.net/ PMID:24048470

  2. Ablation processing of biomedical materials by ultrashort laser pulse ranging from 50 fs through 2 ps

    NASA Astrophysics Data System (ADS)

    Ozono, Kazue; Obara, Minoru; Sakuma, Jun

    2003-06-01

    In recent years, femtosecond laser processing of human hard/soft tissues has been studied. Here, we have demonstrated ablation etching of hydroxyapatite. Hydroxyapatite (Ca10(PO4)6(OH)2) is a key component of human tooth and human bone. The human bone is mainly made of hydroxyapatite oriented along the collagen. The micromachining of hydroxyapatite is highly required for orthopedics and dentistry. The important issue is to preserve the chemical property of the ablated surface. If chemical properties of hydroxyapatite change once, the human bone or tooth cannot grow again after laser processing. As for nanosecond laser ablation (for example excimer laser ablation), the relative content of calcium and phosphorus in (Ca10(PO4)6(OH)2) is found to change after laser ablation. We used here pulsewidth tunable output from 50 fs through 2 ps at 820 nm and 1 kpps. We measured calcium spectrum and phosphorus spectrum of the ablated surface of hydroxyapatite by XPS. As a result, the chemical content of calcium and phosphorus is kept unchanged before and after 50-fs - 2-ps laser ablation. We also demonstrated ablation processing of human tooth with Ti:sapphire laser, and precise ablation processing and microstructure fabrication are realized.

  3. Fatigue properties of a biomedical 316L steel processed by surface mechanical attrition

    NASA Astrophysics Data System (ADS)

    Sun, Z.; Chemkhi, M.; Kanoute, P.; Retraint, D.

    2014-08-01

    This work deals with the influence of surface mechanical attrition treatment (SMAT) on fatigue properties of a medical grade 316L stainless steel. Metallurgical parameters governed by SMAT such as micro-hardness and nanocrystalline layer are characterized using different techniques. Low cycle fatigue tests are performed to investigate the fatigue properties of untreated and SMAT-processed samples. The results show that the stress amplitude of SMAT- processed samples with two different treatment intensities is significantly enhanced compared to untreated samples, while the fatigue strength represented by the number of cycles to failure is not improved in the investigated strain range. The enhancement in the stress amplitude of treated samples can be attributed to the influence of the SMAT affected layer.

  4. Information processing and signal integration in bacterial quorum sensing

    PubMed Central

    Mehta, Pankaj; Goyal, Sidhartha; Long, Tao; Bassler, Bonnie L; Wingreen, Ned S

    2009-01-01

    Bacteria communicate using secreted chemical signaling molecules called autoinducers in a process known as quorum sensing. The quorum-sensing network of the marine bacterium Vibrio harveyi uses three autoinducers, each known to encode distinct ecological information. Yet how cells integrate and interpret the information contained within these three autoinducer signals remains a mystery. Here, we develop a new framework for analyzing signal integration on the basis of information theory and use it to analyze quorum sensing in V. harveyi. We quantify how much the cells can learn about individual autoinducers and explain the experimentally observed input–output relation of the V. harveyi quorum-sensing circuit. Our results suggest that the need to limit interference between input signals places strong constraints on the architecture of bacterial signal-integration networks, and that bacteria probably have evolved active strategies for minimizing this interference. Here, we analyze two such strategies: manipulation of autoinducer production and feedback on receptor number ratios. PMID:19920810

  5. Optimal and adaptive methods of processing hydroacoustic signals (review)

    NASA Astrophysics Data System (ADS)

    Malyshkin, G. S.; Sidel'nikov, G. B.

    2014-09-01

    Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

  6. Relationships between digital signal processing and control and estimation theory

    NASA Technical Reports Server (NTRS)

    Willsky, A. S.

    1978-01-01

    Research directions in the fields of digital signal processing and modern control and estimation theory are discussed. Stability theory, linear prediction and parameter identification, system synthesis and implementation, two-dimensional filtering, decentralized control and estimation, and image processing are considered in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the disciplines.

  7. Research on Signal Processing Algorithms in GPS Receivers

    NASA Astrophysics Data System (ADS)

    Cai, Fan; Yin, Yan; Zhang, Xiu-Zhong

    2007-03-01

    The modern standard satellite navigation receivers are commonly based on ASICs for signal processing and fast microprocessors for application calculations. The software satellite navigation receiver is also developed in recent years. The research on software receivers becomes one trend of satellite navigation receiver. For algorithms on signal processing play an important role in satellite navigation receivers, the paper illuminates the signal processing algorithms in detail. The GPS receiver is widely used at present. So the paper places emphasis on signal processing algorithms about GPS receiver. Signal processing algorithms include three aspects: the algorithm on signal acquisition, the algorithm on carrier tracking and the algorithm on PRN (pseudo random noise) code tracking. In the part of signal acquisition, the method of using FFT to get the result of circular correlation is introduced. The paper carefully researches the method and discusses the derivation process of the method. In the part of carrier tracking, the paper describes the principle of frequency locked loop (FLL) and phase locked loop (PLL) and analyzes the principle of loop filter. The method of transition from s-domain to z-domain is introduced. The computation of noise bandwidth of the loop filter are expatiated and the structures of one-step digital loop filter, two-step digital loop filter and three step are given. Other parameters of loop filters are also given. In the part of code tracking, delay-early locked loop (DLL) is introduced. Theoretical analysis and experiment results demonstrate the algorithms in the paper. Through the simulation testing, the performance of combination of PLL and FLL can be acknowledged.

  8. Signal processing techniques for atrial fibrillation source detection.

    PubMed

    Ambadkar, Minal; Leonelli, Fabio M; Sankar, Ravi

    2014-01-01

    In clinical practice, Atrial Fibrillation (AF) is the most common and critical cardiac arrhythmia encountered. The treatment that can ensure permanent AF removal is catheter ablation, where cardiologists destroy the affected cardiac muscle cells with RF or Laser. In this procedure it is necessary to know exactly from which part of the heart AF triggers are originated. Various signal processing algorithms provide a strong tool to track AF sources. This study proposes, signal processing techniques that can be exploited for characterization, analysis and source detection of AF signals. These algorithms are implemented on Electrocardiogram (ECG) and intracardiac signals which contain important information that allows the analysis of anatomic and physiologic aspects of the whole cardiac muscle. PMID:25570578

  9. SIG: a general-purpose signal processing program

    SciTech Connect

    Lager, D.; Azevedo, S.

    1986-02-01

    SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. It also accommodates other representations for data such as transfer function polynomials. Signal processing operations include digital filtering, auto/cross spectral density, transfer function/impulse response, convolution, Fourier transform, and inverse Fourier transform. Graphical operations provide display of signals and spectra, including plotting, cursor zoom, families of curves, and multiple viewport plots. SIG provides two user interfaces with a menu mode for occasional users and a command mode for more experienced users. Capability exits for multiple commands per line, command files with arguments, commenting lines, defining commands, automatic execution for each item in a repeat sequence, etc. SIG is presently available for VAX(VMS), VAX (BERKELEY 4.2 UNIX), SUN (BERKELEY 4.2 UNIX), DEC-20 (TOPS-20), LSI-11/23 (TSX), and DEC PRO 350 (TSX). 4 refs., 2 figs.

  10. 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.

  11. Application of homomorphic signal processing to stress wave factor analysis

    NASA Technical Reports Server (NTRS)

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

    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.

  12. GNSS-based bistatic SAR: a signal processing view

    NASA Astrophysics Data System (ADS)

    Antoniou, Michail; Cherniakov, Mikhail

    2013-12-01

    This article presents signal processing algorithms used as a new remote sensing tool, that is passive bistatic SAR with navigation satellites (e.g. GPS, GLONASS or Galileo) as transmitters of opportunity. Signal synchronisation and image formation algorithms are described for two system variants: one where the receiver is moving and one where it is fixed on the ground. The applicability and functionality of the algorithms described is demonstrated through experimental imagery that ultimately confirms the feasibility of the overall technology.

  13. Passive silicon photonic devices for microwave photonic signal processing

    NASA Astrophysics Data System (ADS)

    Wu, Jiayang; Peng, Jizong; Liu, Boyu; Pan, Ting; Zhou, Huanying; Mao, Junming; Yang, Yuxing; Qiu, Ciyuan; Su, Yikai

    2016-08-01

    We present our recent progress on microwave signal processing (MSP) using on-chip passive silicon photonic devices, including tunable microwave notch filtering/millimeter-wave (MMW) signal generation based on self-coupled micro-resonators (SCMRs), and tunable radio-frequency (RF) phase shifting implemented by a micro-disk resonator (MDR). These schemes can provide improved flexibility and performances of MSP. The experimental results are in good agreement with theoretical predictions, which validate the effectiveness of the proposed schemes.

  14. Digital signal processing for fiber-optic thermometers

    SciTech Connect

    Fernicola, V.; Crovini, L.

    1994-12-31

    A digital signal processing scheme for measurement of exponentially-decaying signals, such as those found in fluorescence, lifetime-based, fiber-optic sensors, is proposed. The instrument uses a modified digital phase-sensitive-detection technique with the phase locked to a fixed value and the modulation period tracking the measured lifetime. Typical resolution of the system is 0.05% for slow decay (>500 {mu}s) and 0.1% for fast decay.

  15. Array enhanced stochastic resonance: Implications for signal processing

    SciTech Connect

    Inchiosa, M.E.; Bulsara, A.R.; Lindner, J.F.; Meadows, B.K.; Ditto, W.L.

    1996-06-01

    In computer simulations, we enhance the response of a {open_quote}{open_quote}stochastic resonator{close_quote}{close_quote} by coupling it into an array of identical resonators. We relate this array enhanced stochastic resonance (AESR) to the global spatiotemporal dynamics of the array and show how noise and coupling cooperate to organize spatial order, temporal periodicity, and peak output signal-to-noise ratio. We consider the application of AESR to signal processing. {copyright} {ital 1996 American Institute of Physics.}

  16. Cellular phosphatases facilitate combinatorial processing of receptor-activated signals

    PubMed Central

    Kumar, Dhiraj; Dua, Raina; Srikanth, Ravichandran; Jayaswal, Shilpi; Siddiqui, Zaved; Rao, Kanury VS

    2008-01-01

    Background Although reciprocal regulation of protein phosphorylation represents a key aspect of signal transduction, a larger perspective on how these various interactions integrate to contribute towards signal processing is presently unclear. For example, a key unanswered question is that of how phosphatase-mediated regulation of phosphorylation at the individual nodes of the signaling network translates into modulation of the net signal output and, thereby, the cellular phenotypic response. Results To address the above question we, in the present study, examined the dynamics of signaling from the B cell antigen receptor (BCR) under conditions where individual cellular phosphatases were selectively depleted by siRNA. Results from such experiments revealed a highly enmeshed structure for the signaling network where each signaling node was linked to multiple phosphatases on the one hand, and each phosphatase to several nodes on the other. This resulted in a configuration where individual signaling intermediates could be influenced by a spectrum of regulatory phosphatases, but with the composition of the spectrum differing from one intermediate to another. Consequently, each node differentially experienced perturbations in phosphatase activity, yielding a unique fingerprint of nodal signals characteristic to that perturbation. This heterogeneity in nodal experiences, to a given perturbation, led to combinatorial manipulation of the corresponding signaling axes for the downstream transcription factors. Conclusion Our cumulative results reveal that it is the tight integration of phosphatases into the signaling network that provides the plasticity by which perturbation-specific information can be transmitted in the form of a multivariate output to the downstream transcription factor network. This output in turn specifies a context-defined response, when translated into the resulting gene expression profile. PMID:18798986

  17. Bicoid Signal Extraction with a Selection of Parametric and Nonparametric Signal Processing Techniques

    PubMed Central

    Ghodsi, Zara; Silva, Emmanuel Sirimal; Hassani, Hossein

    2015-01-01

    The maternal segmentation coordinate gene bicoid plays a significant role during Drosophila embryogenesis. The gradient of Bicoid, the protein encoded by this gene, determines most aspects of head and thorax development. This paper seeks to explore the applicability of a variety of signal processing techniques at extracting bicoid expression signal, and whether these methods can outperform the current model. We evaluate the use of six different powerful and widely-used models representing both parametric and nonparametric signal processing techniques to determine the most efficient method for signal extraction in bicoid. The results are evaluated using both real and simulated data. Our findings show that the Singular Spectrum Analysis technique proposed in this paper outperforms the synthesis diffusion degradation model for filtering the noisy protein profile of bicoid whilst the exponential smoothing technique was found to be the next best alternative followed by the autoregressive integrated moving average. PMID:26197438

  18. Bicoid signal extraction with a selection of parametric and nonparametric signal processing techniques.

    PubMed

    Ghodsi, Zara; Silva, Emmanuel Sirimal; Hassani, Hossein

    2015-06-01

    The maternal segmentation coordinate gene bicoid plays a significant role during Drosophila embryogenesis. The gradient of Bicoid, the protein encoded by this gene, determines most aspects of head and thorax development. This paper seeks to explore the applicability of a variety of signal processing techniques at extracting bicoid expression signal, and whether these methods can outperform the current model. We evaluate the use of six different powerful and widely-used models representing both parametric and nonparametric signal processing techniques to determine the most efficient method for signal extraction in bicoid. The results are evaluated using both real and simulated data. Our findings show that the Singular Spectrum Analysis technique proposed in this paper outperforms the synthesis diffusion degradation model for filtering the noisy protein profile of bicoid whilst the exponential smoothing technique was found to be the next best alternative followed by the autoregressive integrated moving average. PMID:26197438

  19. How cells process information: Quantification of spatiotemporal signaling dynamics

    PubMed Central

    Ganesan, Ambhighainath; Zhang, Jin

    2012-01-01

    Arguably, one of the foremost distinctions between life and non-living matter is the ability to sense environmental changes and respond appropriately—an ability that is invested in every living cell. Within a single cell, this function is largely carried out by networks of signaling molecules. However, the details of how signaling networks help cells make complicated decisions are still not clear. For instance, how do cells read graded, analog stress signals but convert them into digital live-or-die responses? The answer to such questions may originate from the fact that signaling molecules are not static but dynamic entities, changing in numbers and activity over time and space. In the past two decades, researchers have been able to experimentally monitor signaling dynamics and use mathematical techniques to quantify and abstract general principles of how cells process information. In this review, the authors first introduce and discuss various experimental and computational methodologies that have been used to study signaling dynamics. The authors then discuss the different types of temporal dynamics such as oscillations and bistability that can be exhibited by signaling systems and highlight studies that have investigated such dynamics in physiological settings. Finally, the authors illustrate the role of spatial compartmentalization in regulating cellular responses with examples of second-messenger signaling in cardiac myocytes. PMID:22573643

  20. All-optical signal processing technique for secure optical communication

    NASA Astrophysics Data System (ADS)

    Qian, Feng-chen; Su, Bing; Ye, Ya-lin; Zhang, Qian; Lin, Shao-feng; Duan, Tao; Duan, Jie

    2015-10-01

    Secure optical communication technologies are important means to solve the physical layer security for optical network. We present a scheme of secure optical communication system by all-optical signal processing technique. The scheme consists of three parts, as all-optical signal processing unit, optical key sequence generator, and synchronous control unit. In the paper, all-optical signal processing method is key technology using all-optical exclusive disjunction (XOR) gate based on optical cross-gain modulation effect, has advantages of wide dynamic range of input optical signal, simple structure and so on. All-optical XOR gate composed of two semiconductor optical amplifiers (SOA) is a symmetrical structure. By controlling injection current, input signal power, delay and filter bandwidth, the extinction ratio of XOR can be greater than 8dB. Finally, some performance parameters are calculated and the results are analyzed. The simulation and experimental results show that the proposed method can be achieved over 10Gbps optical signal encryption and decryption, which is simple, easy to implement, and error-free diffusion.

  1. Formal ontology for natural language processing and the integration of biomedical databases.

    PubMed

    Simon, Jonathan; Dos Santos, Mariana; Fielding, James; Smith, Barry

    2006-01-01

    The central hypothesis underlying this communication is that the methodology and conceptual rigor of a philosophically inspired formal ontology can bring significant benefits in the development and maintenance of application ontologies [A. Flett, M. Dos Santos, W. Ceusters, Some Ontology Engineering Procedures and their Supporting Technologies, EKAW2002, 2003]. This hypothesis has been tested in the collaboration between Language and Computing (L&C), a company specializing in software for supporting natural language processing especially in the medical field, and the Institute for Formal Ontology and Medical Information Science (IFOMIS), an academic research institution concerned with the theoretical foundations of ontology. In the course of this collaboration L&C's ontology, LinKBase, which is designed to integrate and support reasoning across a plurality of external databases, has been subjected to a thorough auditing on the basis of the principles underlying IFOMIS's Basic Formal Ontology (BFO) [B. Smith, Basic Formal Ontology, 2002. http://ontology.buffalo.edu/bfo]. The goal is to transform a large terminology-based ontology into one with the ability to support reasoning applications. Our general procedure has been the implementation of a meta-ontological definition space in which the definitions of all the concepts and relations in LinKBase are standardized in the framework of first-order logic. In this paper we describe how this principles-based standardization has led to a greater degree of internal coherence of the LinKBase structure, and how it has facilitated the construction of mappings between external databases using LinKBase as translation hub. We argue that the collaboration here described represents a new phase in the quest to solve the so-called "Tower of Babel" problem of ontology integration [F. Montayne, J. Flanagan, Formal Ontology: The Foundation for Natural Language Processing, 2003. http://www.landcglobal.com/]. PMID:16153885

  2. Parallel Signal Processing and System Simulation using aCe

    NASA Technical Reports Server (NTRS)

    Dorband, John E.; Aburdene, Maurice F.

    2003-01-01

    Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).

  3. Detectors and signal processing for high-energy physics

    SciTech Connect

    Rehak, P.

    1981-01-01

    Basic principles of the particle detection and signal processing for high-energy physics experiments are presented. It is shown that the optimum performance of a properly designed detector system is not limited by incidental imperfections, but solely by more fundamental limitations imposed by the quantum nature and statistical behavior of matter. The noise sources connected with the detection and signal processing are studied. The concepts of optimal filtering and optimal detector/amplifying device matching are introduced. Signal processing for a liquid argon calorimeter is analyzed in some detail. The position detection in gas counters is studied. Resolution in drift chambers for the drift coordinate measurement as well as the second coordinate measurement is discussed.

  4. Improvement of titanium alloy for biomedical applications by nitriding and carbonitriding processes under glow discharge conditions.

    PubMed

    Czarnowska, E; Wierzchoń, T; Maranda-Niedbała, A; Karczmarewicz, E

    2000-02-01

    Although titanium alloys are used in medicine, they present low wear resistance. In this paper we present the results of studies on surface layers produced by nitriding at three different temperatures, and by carbonitriding under glow discharge conditions in order to improve wear resistance, hardness, and to modulate microstructure and chemical composition of surface layers. A cell culture model using human fibroblasts was chosen to study the effect of such treatments on the cytocompatibility of these materials. The results showed that nitrided and carbonitrided surface layers were cytocompatible. Modulation of surface microstructure by temperature in the nitriding process and chemical composition of surface layers by carbonitriding led to differences in cellular behaviour. Cell proliferation appeared to be slightly reduced from the 6th day of culture on nitrided surfaces produced at 730 degrees C and 1000 degrees C, however after 12 days of culture, the best growth was on surface layers produced at 850 degrees C. The best viability was observed on the carbonitrided layer. The orientation and shape of the cells corresponded to surface topography. Nitriding and carbonitriding under glow discharge conditions may constitute interesting techniques allowing the formation of surface layers on parts with sophisticated shapes. They may also permit modulating surface topography in a way improving the features of titanium alloys for various applications in medicine. PMID:15348050

  5. Tailored ablation processing of advanced biomedical hydroxyapatite by femtosecond laser pulses

    NASA Astrophysics Data System (ADS)

    Ozono, K.; Obara, M.

    The micromachining of hydroxyapatite (HAp) is highly important for orthopedics and dentistry, since human bone and teeth consist mainly of HAp. We demonstrate ultrashort Ti:sapphire laser ablation of HAp, using pulse-widths of 50 fs, 500 fs, and 2 ps at a wavelength of 820 nm and at 1 kpps. The crucial medical issue is to preserve the chemical properties of the machined (ablated) surface. If the chemical properties of HAp change, the human bone or tooth cannot re-grow after laser processing. Using X-ray photoelectron spectroscopy, we observe chemical properties of HAp ablated in air. The HAp is ablated at laser fluences of 3.2 J/cm2 (6.4×1013 W/cm2 at 50 fs), 3.3 J/cm2 (6.6×1012 W/cm2 at 500 fs), and 9.6 J/cm2 (4.8×1012 W/cm2 at 2 ps), respectively. As a result it is found that the ablated surface is unchanged after laser ablation over the pulse-width range used in this experiment.

  6. 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.

  7. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center. PMID:25850092

  8. Using off-the-shelf medical devices for biomedical signal monitoring in a telemedicine system for emergency medical services.

    PubMed

    Thelen, Sebastian; Czaplik, Michael; Meisen, Philipp; Schilberg, Daniel; Jeschke, Sabina

    2015-01-01

    In order to study new methods of telemedicine usage in the context of emergency medical services, researchers need to prototype integrated telemedicine systems. To conduct a one-year trial phase-intended to study a new application of telemedicine in German emergency medical services-we used off-the-shelf medical devices and software to realize real-time patient monitoring within an integrated telemedicine system prototype. We demonstrate its feasibility by presenting the integrated real-time patient monitoring solution, by studying signal delay and transmission robustness regarding changing communication channel characteristics, and by evaluating issues reported by the physicians during the trial phase. Where standards like HL7 and the IEEE 11073 family are intended to enable interoperability of product grade medical devices, we show that research prototypes benefit from the use of web technologies and simple device interfaces, as they simplify product development for a manufacturer and ease integration efforts for research teams. Embracing this approach for the development of new medical devices eases the constraint to use off-the-shelf products for research trials investigating innovative use of telemedicine. PMID:25312967

  9. The Process of Installing REDCap, a Web Based Database Supporting Biomedical Research

    PubMed Central

    Mare, I.; Hazelhurst, S.; Kramer, B.

    2014-01-01

    Summary Background Clinical and research data are essential for patient care, research and healthcare system planning. REDCapTM is a web-based tool for research data curatorship developed at Vanderbilt University in Nashville, USA. The Faculty of Health Sciences at the University of the Witwatersrand, Johannesburg South Africa identified the need for a cost effective data management instrument. REDCap was installed as per the user agreement with Vanderbilt University in August 2012. Objectives In order to assist other institutions that may lack the in-house Information Technology capacity, this paper describes the installation and support of REDCap and incorporates an analysis of user uptake over the first year of use. Methods We reviewed the staffing requirements, costs of installation, process of installation and necessary infrastructure and end-user requests following the introduction of REDCap at Wits. The University Legal Office and Human Research Ethics Committee were consulted regarding the REDCap end-user agreement. Bi-monthly user meetings resulted in a training workshop in August 2013. We compared our REDCap software user numbers and records before and after the first training workshop. Results Human resources were recruited from existing staff. Installation costs were limited to servers and security certificates. The total costs to provide a functional REDCap platform was less than $9000. Eighty-one (81) users were registered in the first year. After the first training workshop the user numbers increased by 59 in one month and the total number of active users to 140 by the end of August 2013. Custom software applications for REDCap were created by collaboration between clinicians and software developers. Conclusion REDCap was installed and maintained at limited cost. A small number of people with defined skills can support multiple REDCap users in two to four hours a week. End user training increased in the number of users, number of projects created and

  10. Phosphorelays Provide Tunable Signal Processing Capabilities for the Cell

    PubMed Central

    Kothamachu, Varun B.; Feliu, Elisenda; Wiuf, Carsten; Cardelli, Luca; Soyer, Orkun S.

    2013-01-01

    Achieving a complete understanding of cellular signal transduction requires deciphering the relation between structural and biochemical features of a signaling system and the shape of the signal-response relationship it embeds. Using explicit analytical expressions and numerical simulations, we present here this relation for four-layered phosphorelays, which are signaling systems that are ubiquitous in prokaryotes and also found in lower eukaryotes and plants. We derive an analytical expression that relates the shape of the signal-response relationship in a relay to the kinetic rates of forward, reverse phosphorylation and hydrolysis reactions. This reveals a set of mathematical conditions which, when satisfied, dictate the shape of the signal-response relationship. We find that a specific topology also observed in nature can satisfy these conditions in such a way to allow plasticity among hyperbolic and sigmoidal signal-response relationships. Particularly, the shape of the signal-response relationship of this relay topology can be tuned by altering kinetic rates and total protein levels at different parts of the relay. These findings provide an important step towards predicting response dynamics of phosphorelays, and the nature of subsequent physiological responses that they mediate, solely from topological features and few composite measurements; measuring the ratio of reverse and forward phosphorylation rate constants could be sufficient to determine the shape of the signal-response relationship the relay exhibits. Furthermore, they highlight the potential ways in which selective pressures on signal processing could have played a role in the evolution of the observed structural and biochemical characteristic in phosphorelays. PMID:24244132

  11. Signal Processing For Chemical Sensing: Statistics or Biological Inspiration

    NASA Astrophysics Data System (ADS)

    Marco, Santiago

    2011-09-01

    Current analytical instrumentation and continuous sensing can provide huge amounts of data. Automatic signal processing and information evaluation is needed to overcome drowning in data. Today, statistical techniques are typically used to analyse and extract information from continuous signals. However, it is very interesting to note that biology (insects and vertebrates) has found alternative solutions for chemical sensing and information processing. This is a brief introduction to the developments in the European Project: Bio-ICT NEUROCHEM: Biologically Inspired Computation for Chemical Sensing (grant no. 216916) Fp7 project devoted to biomimetic olfactory systems.

  12. Digital signal processing utilizing a generic instruction set

    NASA Astrophysics Data System (ADS)

    Mosley, V. V. W.; Bronder, J.; Wenk, A.

    In order to maintain a degree of technological equivalence between software and hardware in advanced VLSI development efforts, a set of generic instructions has been defined in the form of Ada-callable procedures which invoke a complex sequence of events for the execution of vector instructions in signal processing modules. Attention is presently given to real time signal processing functions in the cases of fighter aircraft fire control radar, passive sonar surveillance, communications systems' FSK demodulation and bit regeneration, and electronic warfare support measures and countermeasures. Generalized examples of each application are given as data flow graphs.

  13. Optical signal acquisition and processing in future accelerator diagnostics

    SciTech Connect

    Jackson, G.P. ); Elliott, A. )

    1992-01-01

    Beam detectors such as striplines and wall current monitors rely on matched electrical networks to transmit and process beam information. Frequency bandwidth, noise immunity, reflections, and signal to noise ratio are considerations that require compromises limiting the quality of the measurement. Recent advances in fiber optics related technologies have made it possible to acquire and process beam signals in the optical domain. This paper describes recent developments in the application of these technologies to accelerator beam diagnostics. The design and construction of an optical notch filter used for a stochastic cooling system is used as an example. Conceptual ideas for future beam detectors are also presented.

  14. Optical signal acquisition and processing in future accelerator diagnostics

    SciTech Connect

    Jackson, G.P.; Elliott, A.

    1992-12-31

    Beam detectors such as striplines and wall current monitors rely on matched electrical networks to transmit and process beam information. Frequency bandwidth, noise immunity, reflections, and signal to noise ratio are considerations that require compromises limiting the quality of the measurement. Recent advances in fiber optics related technologies have made it possible to acquire and process beam signals in the optical domain. This paper describes recent developments in the application of these technologies to accelerator beam diagnostics. The design and construction of an optical notch filter used for a stochastic cooling system is used as an example. Conceptual ideas for future beam detectors are also presented.

  15. Using image processing techniques on proximity probe signals in rotordynamics

    NASA Astrophysics Data System (ADS)

    Diamond, Dawie; Heyns, Stephan; Oberholster, Abrie

    2016-06-01

    This paper proposes a new approach to process proximity probe signals in rotordynamic applications. It is argued that the signal be interpreted as a one dimensional image. Existing image processing techniques can then be used to gain information about the object being measured. Some results from one application is presented. Rotor blade tip deflections can be calculated through localizing phase information in this one dimensional image. It is experimentally shown that the newly proposed method performs more accurately than standard techniques, especially where the sampling rate of the data acquisition system is inadequate by conventional standards.

  16. Calcium Signals: The Lead Currency of Plant Information Processing

    PubMed Central

    Kudla, Jörg; Batistič, Oliver; Hashimoto, Kenji

    2010-01-01

    Ca2+ signals are core transducers and regulators in many adaptation and developmental processes of plants. Ca2+ signals are represented by stimulus-specific signatures that result from the concerted action of channels, pumps, and carriers that shape temporally and spatially defined Ca2+ elevations. Cellular Ca2+ signals are decoded and transmitted by a toolkit of Ca2+ binding proteins that relay this information into downstream responses. Major transduction routes of Ca2+ signaling involve Ca2+-regulated kinases mediating phosphorylation events that orchestrate downstream responses or comprise regulation of gene expression via Ca2+-regulated transcription factors and Ca2+-responsive promoter elements. Here, we review some of the remarkable progress that has been made in recent years, especially in identifying critical components functioning in Ca2+ signal transduction, both at the single-cell and multicellular level. Despite impressive progress in our understanding of the processing of Ca2+ signals during the past years, the elucidation of the exact mechanistic principles that underlie the specific recognition and conversion of the cellular Ca2+ currency into defined changes in protein–protein interaction, protein phosphorylation, and gene expression and thereby establish the specificity in stimulus response coupling remain to be explored. PMID:20354197

  17. Does Signal Degradation Affect Top-Down Processing of Speech?

    PubMed

    Wagner, Anita; Pals, Carina; de Blecourt, Charlotte M; Sarampalis, Anastasios; Başkent, Deniz

    2016-01-01

    Speech perception is formed based on both the acoustic signal and listeners' knowledge of the world and semantic context. Access to semantic information can facilitate interpretation of degraded speech, such as speech in background noise or the speech signal transmitted via cochlear implants (CIs). This paper focuses on the latter, and investigates the time course of understanding words, and how sentential context reduces listeners' dependency on the acoustic signal for natural and degraded speech via an acoustic CI simulation.In an eye-tracking experiment we combined recordings of listeners' gaze fixations with pupillometry, to capture effects of semantic information on both the time course and effort of speech processing. Normal-hearing listeners were presented with sentences with or without a semantically constraining verb (e.g., crawl) preceding the target (baby), and their ocular responses were recorded to four pictures, including the target, a phonological (bay) competitor and a semantic (worm) and an unrelated distractor.The results show that in natural speech, listeners' gazes reflect their uptake of acoustic information, and integration of preceding semantic context. Degradation of the signal leads to a later disambiguation of phonologically similar words, and to a delay in integration of semantic information. Complementary to this, the pupil dilation data show that early semantic integration reduces the effort in disambiguating phonologically similar words. Processing degraded speech comes with increased effort due to the impoverished nature of the signal. Delayed integration of semantic information further constrains listeners' ability to compensate for inaudible signals. PMID:27080670

  18. ISLE (Image and Signal Lisp Environment): A functional language interface for signal and image processing

    SciTech Connect

    Azevedo, S.G.; Fitch, J.P.

    1987-05-01

    Conventional software interfaces which utilize imperative computer commands or menu interactions are often restrictive environments when used for researching new algorithms or analyzing processed experimental data. We found this to be true with current signal processing software (SIG). Existing ''functional language'' interfaces provide features such as command nesting for a more natural interaction with the data. The Image and Signal Lisp Environment (ISLE) will be discussed as an example of an interpreted functional language interface based on Common LISP. Additional benefits include multidimensional and multiple data-type independence through dispatching functions, dynamic loading of new functions, and connections to artificial intelligence software.

  19. Biomedical Conferences

    NASA Technical Reports Server (NTRS)

    1976-01-01

    As a result of Biomedical Conferences, Vivo Metric Systems Co. has produced cardiac electrodes based on NASA technology. Frequently in science, one highly specialized discipline is unaware of relevant advances made in other areas. In an attempt to familiarize researchers in a variety of disciplines with medical problems and needs, NASA has sponsored conferences that bring together university scientists, practicing physicians and manufacturers of medical instruments.

  20. Respiratory rate detection algorithms by photoplethysmography signal processing.

    PubMed

    Lee, E M; Kim, N H; Trang, N T; Hong, J H; Cha, E J; Lee, T S

    2008-01-01

    Photoplethysmography (PPG) offers the clinically meaningful parameters, such as, heart rate, and respiratory rate. In this study, we presented three respiratory signal detection algorithms using photoplethysmography raw data generated from commercial PPG sensor: (1)Min-Max (2)Peak-to-Peak (3)Pulse Shape. As reference signal, nasal sensor signal was acquired simultaneously and compared and analyzed. We used two types of moving average filtering technique to process three PPG parameters. In laboratory experiment, 6 subjects' PPG signals were measured when they respire ten and fifteen, and arbitrary times per minute. From the results, following conclusions were drawn. Min-Max and Peak-to-Peak algorithms perform better than Pulse shape algorithm. They can be used to detect respiratory rate. But, Pulse Shape algorithm was accurate for subject 4 only. More experimental data is necessary to improve the accuracy and reliability. PMID:19162865

  1. Analysis of signal processing techniques in pulsed thermography

    NASA Astrophysics Data System (ADS)

    Lopez, Fernando; Ibarra-Castanedo, Clemente; Maldague, Xavier; de Paulo Nicolau, Vicente

    2013-05-01

    Pulsed Thermography (PT) is one of the most widely used approaches for the inspection of composites materials, being its main attraction the deployment in transient regime. However, due to the physical phenomena involved during the inspection, the signals acquired by the infrared camera are nearly always affected by external reflections and local emissivity variations. Furthermore, non-uniform heating at the surface and thermal losses at the edges of the material also represent constraints in the detection capability. For this reason, the thermographics signals should be processed in order to improve - qualitatively and quantitatively - the quality of the thermal images. Signal processing constitutes an important step in the chain of thermal image analysis, especially when defects characterization is required. Several of the signals processing techniques employed nowadays are based on the one-dimensional solution of Fourier's law of heat conduction. This investigation brings into discussion the three-most used techniques based on the 1D Fourier's law: Thermographic Signal Reconstruction (TSR), Differential Absolute Contrast (DAC) and Pulsed Phase Thermography (PPT), applied on carbon fiber laminated composites. It is of special interest to determine the detection capabilities of each technique, allowing in this way more reliable results when performing an inspection by PT.

  2. Fault Detection of Gearbox from Inverter Signals Using Advanced Signal Processing Techniques

    NASA Astrophysics Data System (ADS)

    Pislaru, C.; Lane, M.; Ball, A. D.; Gu, F.

    2012-05-01

    The gear faults are time-localized transient events so time-frequency analysis techniques (such as the Short-Time Fourier Transform, Wavelet Transform, motor current signature analysis) are widely used to deal with non-stationary and nonlinear signals. Newly developed signal processing techniques (such as empirical mode decomposition and Teager Kaiser Energy Operator) enabled the recognition of the vibration modes that coexist in the system, and to have a better understanding of the nature of the fault information contained in the vibration signal. However these methods require a lot of computational power so this paper presents a novel approach of gearbox fault detection using the inverter signals to monitor the load, rather than the motor current. The proposed technique could be used for continuous monitoring as well as on-line damage detection systems for gearbox maintenance.

  3. Thirty years of underwater acoustic signal processing in China

    NASA Astrophysics Data System (ADS)

    Li, Qihu

    2012-11-01

    Advances in technology and theory in 30 years of underwater acoustic signal processing and its applications in China are presented in this paper. The topics include research work in the field of underwater acoustic signal modeling, acoustic field matching, ocean waveguide and internal wave, the extraction and processing technique for acoustic vector signal information, the space/time correlation characteristics of low frequency acoustic channels, the invariant features of underwater target radiated noise, the transmission technology of underwater voice/image data and its anti-interference technique. Some frontier technologies in sonar design are also discussed, including large aperture towed line array sonar, high resolution synthetic aperture sonar, deep sea siren and deep sea manned subsea vehicle, diver detection sonar and demonstration projector of national ocean monitoring system in China, etc.

  4. 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.

  5. Multiple-channel optical signal processing with wavelength-waveform conversions, pulsewidth tunability, and signal regeneration.

    PubMed

    Nguyen Tan, Hung; Matsuura, Motoharu; Katafuchi, Tomoya; Kishi, Naoto

    2009-12-01

    A multiple-channel multiple-function optical signal processor (MCMF-OSP) including wavelength-waveform conversions, pulsewidth tunability, and signal regeneration is realized through AND logic gate based on optical parametric processing with a pulsewidth-tunable RZ clock pump. The proposed scheme simultaneously offers four signal processing functions which are useful in wavelength-division multiplexing (WDM) transmission systems, and at network nodes with the necessity for multiple-channel data processing. After the discussions on the concept of MCMF-OSP, a proof-of concept experiment is demonstrated on four 10 Gb/s nonreturn-to-zero (NRZ) data format channels using nonlinearities in semiconductor optical amplifier (SOA) and highly nonlinear fiber (HNLF). A wavelength and waveform conversions to return-to-zero (RZ) modulation format are obtained together with pulsewidth-tunable range from 20% to 80% duty cycles for all input signals. The converted signals inherit the timing and waveform of the RZ clock pump, thus resulting in a time regeneration and large tolerance to narrow-band optical filtering (NAOF) and fiber accumulated chromatic dispersion (CD). PMID:20052222

  6. Parallel Processing of Broad-Band PPM Signals

    NASA Technical Reports Server (NTRS)

    Gray, Andrew; Kang, Edward; Lay, Norman; Vilnrotter, Victor; Srinivasan, Meera; Lee, Clement

    2010-01-01

    A parallel-processing algorithm and a hardware architecture to implement the algorithm have been devised for timeslot synchronization in the reception of pulse-position-modulated (PPM) optical or radio signals. As in the cases of some prior algorithms and architectures for parallel, discrete-time, digital processing of signals other than PPM, an incoming broadband signal is divided into multiple parallel narrower-band signals by means of sub-sampling and filtering. The number of parallel streams is chosen so that the frequency content of the narrower-band signals is low enough to enable processing by relatively-low speed complementary metal oxide semiconductor (CMOS) electronic circuitry. The algorithm and architecture are intended to satisfy requirements for time-varying time-slot synchronization and post-detection filtering, with correction of timing errors independent of estimation of timing errors. They are also intended to afford flexibility for dynamic reconfiguration and upgrading. The architecture is implemented in a reconfigurable CMOS processor in the form of a field-programmable gate array. The algorithm and its hardware implementation incorporate three separate time-varying filter banks for three distinct functions: correction of sub-sample timing errors, post-detection filtering, and post-detection estimation of timing errors. The design of the filter bank for correction of timing errors, the method of estimating timing errors, and the design of a feedback-loop filter are governed by a host of parameters, the most critical one, with regard to processing very broadband signals with CMOS hardware, being the number of parallel streams (equivalently, the rate-reduction parameter).

  7. The Khoros software development environment for image and signal processing.

    PubMed

    Konstantinides, K; Rasure, J R

    1994-01-01

    Data flow visual language systems allow users to graphically create a block diagram of their applications and interactively control input, output, and system variables. Khoros is an integrated software development environment for information processing and visualization. It is particularly attractive for image processing because of its rich collection of tools for image and digital signal processing. This paper presents a general overview of Khoros with emphasis on its image processing and DSP tools. Various examples are presented and the future direction of Khoros is discussed. PMID:18291923

  8. An Evaluation of Two Signal-Processing Hearing Aids.

    ERIC Educational Resources Information Center

    Dempsey, James J.; Linzalone, Tanya G.

    1991-01-01

    This study, involving 15 older adults with hearing impairments, investigated the relationship between sentence recognition ability and two types of signal processing in hearing aids. Results indicated a significant improvement in sentence recognition when employing an instrument with adaptive compression versus an instrument with an adaptive…

  9. Signal processing for the TOPAZ Time Projection Chamber

    SciTech Connect

    Ikeda, H.; Iwasaki, H.; Iwata, S.; Kobayashi, M.; Matsuda, T.; Nakamura, K.; Yamauchi, M.; Aihara, H.; Enomoto, R.; Fujii, H.

    1987-02-01

    The signals from the TOPAZ Time Projection Chamber, after being processed by a low noise preamplifier and a shaper amplifier, are recorded by a CCD based digitizer system. The system achieved an integral operation in the environment of FASTBUS with Sector Sequencers and FPI.

  10. Keeping Signals Straight: How Cells Process Information and Make Decisions

    PubMed Central

    Laub, Michael T.

    2016-01-01

    As we become increasingly dependent on electronic information-processing systems at home and work, it’s easy to lose sight of the fact that our very survival depends on highly complex biological information-processing systems. Each of the trillions of cells that form the human body has the ability to detect and respond to a wide range of stimuli and inputs, using an extraordinary set of signaling proteins to process this information and make decisions accordingly. Indeed, cells in all organisms rely on these signaling proteins to survive and proliferate in unpredictable and sometimes rapidly changing environments. But how exactly do these proteins relay information within cells, and how do they keep a multitude of incoming signals straight? Here, I describe recent efforts to understand the fidelity of information flow inside cells. This work is providing fundamental insight into how cells function. Additionally, it may lead to the design of novel antibiotics that disrupt the signaling of pathogenic bacteria or it could help to guide the treatment of cancer, which often involves information-processing gone awry inside human cells. PMID:27427909

  11. Keeping Signals Straight: How Cells Process Information and Make Decisions.

    PubMed

    Laub, Michael T

    2016-07-01

    As we become increasingly dependent on electronic information-processing systems at home and work, it's easy to lose sight of the fact that our very survival depends on highly complex biological information-processing systems. Each of the trillions of cells that form the human body has the ability to detect and respond to a wide range of stimuli and inputs, using an extraordinary set of signaling proteins to process this information and make decisions accordingly. Indeed, cells in all organisms rely on these signaling proteins to survive and proliferate in unpredictable and sometimes rapidly changing environments. But how exactly do these proteins relay information within cells, and how do they keep a multitude of incoming signals straight? Here, I describe recent efforts to understand the fidelity of information flow inside cells. This work is providing fundamental insight into how cells function. Additionally, it may lead to the design of novel antibiotics that disrupt the signaling of pathogenic bacteria or it could help to guide the treatment of cancer, which often involves information-processing gone awry inside human cells. PMID:27427909

  12. Ultrafast lasers for coherent communications and signal processing (Invited Paper)

    NASA Astrophysics Data System (ADS)

    Gee, S.; Lee, W.; Ozharar, S.; Quinlan, F.; Izadpanah, H.; Delfyett, P. J.; Plant, J. J.; Juodawlkis, P. W.

    2005-05-01

    This paper discusses use of optical frequency combs generated by modelocked semiconductor lasers for coherent photonic signal processing applications. Key in our approach is a high Q cavity, supermode suppression and low spontaneous emission. Targeted applications of the stabilized optical frequency combs lie in areas of metrology, optical sampling, arbitrary waveform generation and communications using coherent detection.

  13. Signal processing in the cochlea: The structure equations

    PubMed Central

    2011-01-01

    Background Physical and physiological invariance laws, in particular time invariance and local symmetry, are at the outset of an abstract model. Harmonic analysis and Lie theory are the mathematical prerequisites for its deduction. Results The main result is a linear system of partial differential equations (referred to as the structure equations) that describe the result of signal processing in the cochlea. It is formulated for phase and for the logarithm of the amplitude. The changes of these quantities are the essential physiological observables in the description of signal processing in the auditory pathway. Conclusions The structure equations display in a quantitative way the subtle balance for processing information on the basis of phase versus amplitude. From a mathematical point of view, the linear system of equations is classified as an inhomogeneous - equation. In suitable variables the solutions can be represented as the superposition of a particular solution (determined by the system) and a holomorphic function (determined by the incoming signal). In this way, a global picture of signal processing in the cochlea emerges. PMID:22656650

  14. Signal processing techniques for clutter filtering and wind shear detection

    NASA Technical Reports Server (NTRS)

    Baxa, Ernest G., Jr.; Deshpande, Manohar D

    1991-01-01

    An extended Prony algorithm applicable to signal processing techniques for clutter filtering and windshear detection is discussed. The algorithm is based upon modelling the radar return as a time series, and appears to offer potential for improving hazard factor estimates in the presence of strong clutter returns.

  15. A robust sinusoidal signal processing method for interferometers

    NASA Astrophysics Data System (ADS)

    Wu, Xiang-long; Zhang, Hui; Tseng, Yang-Yu; Fan, Kuang-Chao

    2013-10-01

    Laser interferometers are widely used as a reference for length measurement. Reliable bidirectional optical fringe counting is normally obtained by using two orthogonally sinusoidal signals derived from the two outputs of an interferometer with path difference. These signals are subject to be disturbed by the geometrical errors of the moving target that causes the separation and shift of two interfering light spots on the detector. It results in typical Heydemann errors, including DC drift, amplitude variation and out-of-orthogonality of two sinusoidal signals that will seriously reduce the accuracy of fringe counting. This paper presents a robust sinusoidal signal processing method to correct the distorted waveforms by hardware. A corresponding circuit board has been designed. A linear stage equipped with a laser displacement interferometer and a height gauge equipped with a linear grating interferometer are used as the test beds. Experimental results show that, even with a seriously disturbed input waveform, the output Lissajous circle can always be stabilized after signal correction. This robust method increases the stability and reliability of the sinusoidal signals for data acquisition device to deal with pulse count and phase subdivision.

  16. Biomedical informatics and translational medicine

    PubMed Central

    2010-01-01

    Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams. PMID:20187952

  17. Modern Techniques in Acoustical Signal and Image Processing

    SciTech Connect

    Candy, J V

    2002-04-04

    Acoustical signal processing problems can lead to some complex and intricate techniques to extract the desired information from noisy, sometimes inadequate, measurements. The challenge is to formulate a meaningful strategy that is aimed at performing the processing required even in the face of uncertainties. This strategy can be as simple as a transformation of the measured data to another domain for analysis or as complex as embedding a full-scale propagation model into the processor. The aims of both approaches are the same--to extract the desired information and reject the extraneous, that is, develop a signal processing scheme to achieve this goal. In this paper, we briefly discuss this underlying philosophy from a ''bottom-up'' approach enabling the problem to dictate the solution rather than visa-versa.

  18. Toward optical signal processing using photonic reservoir computing.

    PubMed

    Vandoorne, Kristof; Dierckx, Wouter; Schrauwen, Benjamin; Verstraeten, David; Baets, Roel; Bienstman, Peter; Van Campenhout, Jan

    2008-07-21

    We propose photonic reservoir computing as a new approach to optical signal processing in the context of large scale pattern recognition problems. Photonic reservoir computing is a photonic implementation of the recently proposed reservoir computing concept, where the dynamics of a network of nonlinear elements are exploited to perform general signal processing tasks. In our proposed photonic implementation, we employ a network of coupled Semiconductor Optical Amplifiers (SOA) as the basic building blocks for the reservoir. Although they differ in many key respects from traditional software-based hyperbolic tangent reservoirs, we show using simulations that such a photonic reservoir can outperform traditional reservoirs on a benchmark classification task. Moreover, a photonic implementation offers the promise of massively parallel information processing with low power and high speed. PMID:18648434

  19. New challenges in signal processing in astrophysics: the SKA case

    NASA Astrophysics Data System (ADS)

    Faulkner, Andrew; Zarb-Adami, Kristian; Geralt Bij de Vaate, Jan

    2015-07-01

    Signal processing and communications are driving the latest generation of radio telescopes with major developments taking place for use on the Square Kilometre Array, SKA, the next generation low frequency radio telescope. The data rates and processing performance that can be achieved with currently available components means that concepts from the earlier days of radio astronomy, phased arrays, can be used at higher frequencies, larger bandwidths and higher numbers of beams. Indeed it has been argued that the use of dishes as a mechanical beamformer only gained strong acceptance to mitigate the processing load from phased array technology. The balance is changing and benefits in both performance and cost can be realised. In this paper we will mostly consider the signal processing implementation and control for very large phased arrays consisting of hundreds of thousands of antennas or even millions of antennas. They can use current technology for the initial deployments. These systems are very large extending to hundreds of racks with thousands of signal processing modules that link through high-speed, but commercially available data networking devices. There are major challenges to accurately calibrate the arrays, mitigate power consumption and make the system maintainable.

  20. A self-regulating biomolecular comparator for processing oscillatory signals.

    PubMed

    Agrawal, Deepak K; Franco, Elisa; Schulman, Rebecca

    2015-10-01

    While many cellular processes are driven by biomolecular oscillators, precise control of a downstream on/off process by a biochemical oscillator signal can be difficult: over an oscillator's period, its output signal varies continuously between its amplitude limits and spends a significant fraction of the time at intermediate values between these limits. Further, the oscillator's output is often noisy, with particularly large variations in the amplitude. In electronic systems, an oscillating signal is generally processed by a downstream device such as a comparator that converts a potentially noisy oscillatory input into a square wave output that is predominantly in one of two well-defined on and off states. The comparator's output then controls downstream processes. We describe a method for constructing a synthetic biochemical device that likewise produces a square-wave-type biomolecular output for a variety of oscillatory inputs. The method relies on a separation of time scales between the slow rate of production of an oscillatory signal molecule and the fast rates of intermolecular binding and conformational changes. We show how to control the characteristics of the output by varying the concentrations of the species and the reaction rates. We then use this control to show how our approach could be applied to process different in vitro and in vivo biomolecular oscillators, including the p53-Mdm2 transcriptional oscillator and two types of in vitro transcriptional oscillators. These results demonstrate how modular biomolecular circuits could, in principle, be combined to build complex dynamical systems. The simplicity of our approach also suggests that natural molecular circuits may process some biomolecular oscillator outputs before they are applied downstream. PMID:26378119

  1. Signal processing techniques for surveillance radar - An overview

    NASA Astrophysics Data System (ADS)

    Farina, A.; Galati, G.

    1985-06-01

    The present paper is concerned with a survey of the signal processing techniques presently employed in modern air defense and surveillance radars and those techniques likely to be applied in the future. Attention is given to the requirements for enhancing performance in surveillance radar, current processing techniques, advanced techniques, low probability of intercept (LPI) and anti-ARM (anti-radiation missile), anti-stealth, digital beamforming (DBF), adaptivity, high directivity and high resolution, multidimensional processing, target classification, and fieldability. Stealth is the term given to means of reducing the radar cross section of a target and the reduction of infrared emissions from the engine exhaust.

  2. Improved fundamental frequency coding in cochlear implant signal processing.

    PubMed

    Milczynski, Matthias; Wouters, Jan; van Wieringen, Astrid

    2009-04-01

    A new signal processing algorithm for improved pitch perception in cochlear implants is proposed. The algorithm realizes fundamental frequency (F0) coding by explicitly modulating the amplitude of the electrical stimulus. The proposed processing scheme is compared with the standard advanced combination encoder strategy in psychophysical music perception related tasks. Possible filter-bank and loudness cues between the strategies under study were minimized to predominantly focus on differences in temporal processing. The results demonstrate significant benefits provided by the new coding strategy for pitch ranking, melodic contour identification, and familiar melody identification. PMID:19354401

  3. Analysis of Wide-Band Signals Using Wavelet Array Processing

    NASA Astrophysics Data System (ADS)

    Nisii, V.; Saccorotti, G.

    2005-12-01

    Wavelets transforms allow for precise time-frequency localization in the analysis of non-stationary signals. In wavelet analysis the trade-off between frequency bandwidth and time duration, also known as Heisenberg inequality, is by-passed using a fully scalable modulated window which solves the signal-cutting problem of Windowed Fourier Transform. We propose a new seismic array data processing procedure capable of displaying the localized spatial coherence of the signal in both the time- and frequency-domain, in turn deriving the propagation parameters of the most coherent signals crossing the array. The procedure consists in: a) Wavelet coherence analysis for each station pair of the instruments array, aimed at retrieving the frequency- and time-localisation of coherent signals. To this purpose, we use the normalised wavelet cross- power spectrum, smoothed along the time and scale domains. We calculate different coherence spectra adopting smoothing windows of increasing lengths; a final, robust estimate of the time-frequency localisation of spatially-coherent signals is eventually retrieved from the stack of the individual coherence distribution. This step allows for a quick and reliable signal discrimination: wave groups propagating across the network will manifest as high-coherence patches spanning the corresponding time-scale region. b) Once the signals have been localised in the time and frequency domain,their propagation parameters are estimated using a modified MUSIC (MUltiple SIgnal Characterization) algorithm. We select the MUSIC approach as it demonstrated superior performances in the case of low SNR signals, more plane waves contemporaneously impinging at the array and closely separated sources. The narrow-band Coherent Signal Subspace technique is applied to the complex Continuous Wavelet Transform of multichannel data for improving the singularity of the estimated cross-covariance matrix and the accuracy of the estimated signal eigenvectors. Using

  4. A theoretical bound for the processing of SARSAT signals

    NASA Astrophysics Data System (ADS)

    Carter, C. R.

    1986-01-01

    A theoretical bound is calculated for a matched filter receiver for search and rescue satellite-aided tracking (SARSAT) signals. The processor is assumed to give the best possible performance when a single signal is immersed in noise. A solution in closed form is deduced, and values are calculated for several different cases. The results show that, for a processing duration of 125 ms, an emergency locator transmitter signal can be detected within + or - 8 Hz when the carrier-to-noise density ratio is only 15 dB-Hz. The bound can be used to evaluate the performance of more practical implementations, although it may also be possible to realize the matched filter in certain cases.

  5. Compensatory neurofuzzy model for discrete data classification in biomedical

    NASA Astrophysics Data System (ADS)

    Ceylan, Rahime

    2015-03-01

    Biomedical data is separated to two main sections: signals and discrete data. So, studies in this area are about biomedical signal classification or biomedical discrete data classification. There are artificial intelligence models which are relevant to classification of ECG, EMG or EEG signals. In same way, in literature, many models exist for classification of discrete data taken as value of samples which can be results of blood analysis or biopsy in medical process. Each algorithm could not achieve high accuracy rate on classification of signal and discrete data. In this study, compensatory neurofuzzy network model is presented for classification of discrete data in biomedical pattern recognition area. The compensatory neurofuzzy network has a hybrid and binary classifier. In this system, the parameters of fuzzy systems are updated by backpropagation algorithm. The realized classifier model is conducted to two benchmark datasets (Wisconsin Breast Cancer dataset and Pima Indian Diabetes dataset). Experimental studies show that compensatory neurofuzzy network model achieved 96.11% accuracy rate in classification of breast cancer dataset and 69.08% accuracy rate was obtained in experiments made on diabetes dataset with only 10 iterations.

  6. Synthetic aperture radar signal processing on the MPP

    NASA Technical Reports Server (NTRS)

    Ramapriyan, H. K.; Seiler, E. J.

    1987-01-01

    Satellite-borne Synthetic Aperture Radars (SAR) sense areas of several thousand square kilometers in seconds and transmit phase history signal data several tens of megabits per second. The Shuttle Imaging Radar-B (SIR-B) has a variable swath of 20 to 50 km and acquired data over 100 kms along track in about 13 seconds. With the simplification of separability of the reference function, the processing still requires considerable resources; high speed I/O, large memory and fast computation. Processing systems with regular hardware take hours to process one Seasat image and about one hour for a SIR-B image. Bringing this processing time closer to acquisition times requires an end-to-end system solution. For the purpose of demonstration, software was implemented on the present Massively Parallel Processor (MPP) configuration for processing Seasat and SIR-B data. The software takes advantage of the high processing speed offered by the MPP, the large Staging Buffer, and the high speed I/O between the MPP array unit and the Staging Buffer. It was found that with unoptimized Parallel Pascal code, the processing time on the MPP for a 4096 x 4096 sample subset of signal data ranges between 18 and 30.2 seconds depending on options.

  7. Digital signal processing algorithms for automatic voice recognition

    NASA Technical Reports Server (NTRS)

    Botros, Nazeih M.

    1987-01-01

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

  8. Signal Processing in Periodically Forced Gradient Frequency Neural Networks

    PubMed Central

    Kim, Ji Chul; Large, Edward W.

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

  9. 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.

  10. The high speed low noise multi-data processing signal process circuit research of remote sensing

    NASA Astrophysics Data System (ADS)

    Su, Lei; Jiang, Haibin; Dong, Wang

    2013-08-01

    The high speed, low noise and integration characteristic are the main technology and the main development directions on the signal process circuit of the image sensor, especially in high resolution remote sensing. With these developments, the high noise limiting circuits, high speed data transfer system and the integrated design of the signal process circuit become more and more important. Therefore the requirement of the circuit system simulation is more and more important during the system design and PCB board design process. A CCD signal process circuit system which has the high speed, low noise and several selectable operate modes function was designed and certificated in this paper, during the CCD signal process circuit system design, simulation was made which include the signal integrity and the power integrity. The important devices such as FPGA and the DDR2 device were simulated, using the power integrity simulation the sensitive power planes of the FPGA on the PCB was modified to make the circuit operate more stabilize on a higher frequency. The main clock path and the high speed data path of the PCB board were simulated with the signal integrity. All the simulation works make the signal process circuit system's image's SNR value get higher and make the circuit system could operate well on higher frequency. In the board testing process, the PCB time diagrams were listed on the testing chapter and the wave's parameter meets the request. The real time diagram and the simulated result of the PCB board was listed respectively. The CCD signal process circuit system's images' SNR (Signal Noise Ratio) value, the 14bit AFE slew rate and the data transfer frequency is listed in the paper respective.

  11. Biological signal processing with a genetic toggle switch.

    PubMed

    Hillenbrand, Patrick; Fritz, Georg; Gerland, Ulrich

    2013-01-01

    Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems. PMID:23874595

  12. Task effects on BOLD signal correlates of implicit syntactic processing.

    PubMed

    Caplan, David

    2010-07-01

    BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed. PMID:20671983

  13. 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. PMID:26831487

  14. Task effects on BOLD signal correlates of implicit syntactic processing

    PubMed Central

    Caplan, David

    2010-01-01

    BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed. PMID:20671983

  15. Deterring watermark collusion attacks using signal processing techniques

    NASA Astrophysics Data System (ADS)

    Lemma, Aweke N.; van der Veen, Michiel

    2007-02-01

    Collusion attack is a malicious watermark removal attack in which the hacker has access to multiple copies of the same content with different watermarks and tries to remove the watermark using averaging. In the literature, several solutions to collusion attacks have been reported. The main stream solutions aim at designing watermark codes that are inherently resistant to collusion attacks. The other approaches propose signal processing based solutions that aim at modifying the watermarked signals in such a way that averaging multiple copies of the content leads to a significant degradation of the content quality. In this paper, we present signal processing based technique that may be deployed for deterring collusion attacks. We formulate the problem in the context of electronic music distribution where the content is generally available in the compressed domain. Thus, we first extend the collusion resistance principles to bit stream signals and secondly present experimental based analysis to estimate a bound on the maximum number of modified versions of a content that satisfy good perceptibility requirement on one hand and destructive averaging property on the other hand.

  16. Biological Signal Processing with a Genetic Toggle Switch

    PubMed Central

    Hillenbrand, Patrick; Fritz, Georg; Gerland, Ulrich

    2013-01-01

    Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems. PMID:23874595

  17. Communications, Signal Processing, and Telemetering Research Program Review

    NASA Technical Reports Server (NTRS)

    1999-01-01

    A Communications, Signal Processing, and Telemetering Research Program Review was held on February 23, 1999. Research conducted under the grant was presented and reviewed, for progress, and for possible technology transfers. The research reviewed was in the following areas: (1) Bandwidth-efficient Modulation and nonlinear equalization; (2) Investigation of an architecture for parallel signal processing applicable to communications problems; (3)Coded partial response over satellites; (4) synchronization at Low SNR; (5) Serial concatenated convolutional codes and some implementation issues on high rate turbo codes; (6) Flight experiments; (7) Real time doppler tracking; (8) Space protocol testing; (9) Lightweight optical communications without carrying a laser in space. The presentations are given by the graduate students who performed the research.

  18. Signal processing methodologies for an acoustic fetal heart rate monitor

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  19. Signal processing software for ground penetrating radar, user's manual

    NASA Astrophysics Data System (ADS)

    Liem, Ronnie; Davis, Thomas J.

    1988-03-01

    This is the user's manual for the signal processing software for reducing ground penetrating radar (GPR) data. The manual provides background information and instructions for operating the computer program. The developed program is based on the synthetic aperture focusing technique. Input data to the program consists of digitized sequential GPR scans from a linear survey. The format for the input data is specified in Appendix C. The output of the program are two-dimensional plots of the ground profile showing the stations and depth of the objects identified by the program. Features of the program include utilities to determine the velocity of propagation of the GPR signal and the location of the ground surface as well as semi-automatic and automatic processing of the data. The program is designed to operate on an IBM PC or compatible computer. Other hardware and supporting software requirements for operating the program are specified in Appendix B.

  20. Nonlinear Signal Processing Using Fiber-Optics Neurograms

    NASA Astrophysics Data System (ADS)

    Szu, Harold

    1986-02-01

    A novel optical device for nonlinear signal processing is described based upon the following observations: (a) A phase space for signal processing is identified with a time-frequency joint representation (TFJR) that appears almost everywhere naturally, for example in bats, in music, etc. (b) A sudden slow down mechanism is responsible for the transition from a phase coherent-to-incoherent wavefront and provides us the sharpest tone transduction from a Bekesy traveling wave in a model of the inner ear. The cause of the slowdown is physically identified to be due to three forces. This has been used to derive a cubic deceleration polynomial responsible for a cusp bifurcation phenomenon which occur for every tone transducted along the nonuniform elastic membrane. The liquid-filled inner ear cochlea channel is divided by the membrane into an upper duct that has hair cells for the forward sound-generated flow and the lower duct for the backward balance-return flow.

  1. Flash Signal Processing and NAND/ReRAM SSD

    NASA Astrophysics Data System (ADS)

    Takeuchi, K.

    The widespread use of NAND Flash memories in SSDs has unleashed new avenues of innovation for the enterprise and client computing. System-wide architectural changes are required to make full use of the advantages of SSDs in terms of performance, reliability and power. Signal processing technologies are becoming more and more popular to countermeasure all the parasitic effects of a Flash NAND array: the first part of this chapter deals with such techniques.

  2. Programmable rate modem utilizing digital signal processing techniques

    NASA Technical Reports Server (NTRS)

    Naveh, Arad

    1992-01-01

    The need for a Programmable Rate Digital Satellite Modem capable of supporting both burst and continuous transmission modes with either Binary Phase Shift Keying (BPSK) or Quadrature Phase Shift Keying (QPSK) modulation is discussed. The preferred implementation technique is an all digital one which utilizes as much digital signal processing (DSP) as possible. The design trade-offs in each portion of the modulator and demodulator subsystem are outlined.

  3. Developments in signal processing and interpretation in laser tapping

    NASA Astrophysics Data System (ADS)

    Perton, M.; Neron, C.; Blouin, A.; Monchalin, J.-P.

    2013-01-01

    A novel technique, called laser-tapping, based on the thermoelastic excitation by laser like laser-ultrasonics has been previously introduced for inspecting honeycomb and foam core structures. If the top skin is delaminated or detached from the substrate, the detached layer is driven into vibration. The interpretation of the vibrations in terms of Lamb wave resonances is first discussed for a flat bottom hole configuration and then used to determine appropriate signal processing for samples such as honeycomb structures.

  4. Adaptive control technique for accelerators using digital signal processing

    SciTech Connect

    Eaton, L.; Jachim, S.; Natter, E.

    1987-01-01

    The use of present Digital Signal Processing (DSP) techniques can drastically reduce the residual rf amplitude and phase error in an accelerating rf cavity. Accelerator beam loading contributes greatly to this residual error, and the low-level rf field control loops cannot completely absorb the fast transient of the error. A feedforward technique using DSP is required to maintain the very stringent rf field amplitude and phase specifications. 7 refs.

  5. Digital signal processor and processing method for GPS receivers

    NASA Technical Reports Server (NTRS)

    Thomas, Jr., Jess B. (Inventor)

    1989-01-01

    A digital signal processor and processing method therefor for use in receivers of the NAVSTAR/GLOBAL POSITIONING SYSTEM (GPS) employs a digital carrier down-converter, digital code correlator and digital tracking processor. The digital carrier down-converter and code correlator consists of an all-digital, minimum bit implementation that utilizes digital chip and phase advancers, providing exceptional control and accuracy in feedback phase and in feedback delay. Roundoff and commensurability errors can be reduced to extremely small values (e.g., less than 100 nanochips and 100 nanocycles roundoff errors and 0.1 millichip and 1 millicycle commensurability errors). The digital tracking processor bases the fast feedback for phase and for group delay in the C/A, P.sub.1, and P.sub.2 channels on the L.sub.1 C/A carrier phase thereby maintaining lock at lower signal-to-noise ratios, reducing errors in feedback delays, reducing the frequency of cycle slips and in some cases obviating the need for quadrature processing in the P channels. Simple and reliable methods are employed for data bit synchronization, data bit removal and cycle counting. Improved precision in averaged output delay values is provided by carrier-aided data-compression techniques. The signal processor employs purely digital operations in the sense that exactly the same carrier phase and group delay measurements are obtained, to the last decimal place, every time the same sampled data (i.e., exactly the same bits) are processed.

  6. Nonlinear signal processing using neural networks: Prediction and system modelling

    SciTech Connect

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  7. Signal processing of microbolometer infrared focal-plane arrays

    NASA Astrophysics Data System (ADS)

    Zhang, Junju; Qian, Yunsheng; Chang, Benkang; Xing, Suxia; Sun, Lianjun

    2005-01-01

    A 320×240-uncooled-microbolometer-based signal processing circuit for infrared focal-plane arrays is presented, and the software designs of this circuit system are also discussed in details. This signal processing circuit comprises such devices as FPGA, D/A, A/D, SRAM, Flash, DSP, etc., among which, FPGA is the crucial part, which realizing the generation of drive signals for infrared focal-plane, nonuniformity correction, image enhancement and video composition. The device of DSP, mainly offering auxiliary functions, carries out communication with PC and loads data when power-up. The phase locked loops (PLL) is used to generate high-quality clocks with low phase dithering and multiple clocks are to used satisfy the demands of focal-plane arrays, A/D, D/A and FPGA. The alternate structure is used to read or write SRAM in order to avoid the contradiction between different modules. FIFO embedded in FPGA not only makes full use of the resources of FPGA but acts as the channel between different modules which have different-speed clocks. What's more, working conditions, working process, physical design and management of the circuit are discussed. In software designing, all the function modules realized by FPGA and DSP devices, which are mentioned in the previous part, are discussed explicitly. Particularly to the nonuniformity correction module, the pipeline structure is designed to improve the working frequency and the ability to realize more complex algorithm.

  8. Nonlinear fiber applications for ultrafast all-optical signal processing

    NASA Astrophysics Data System (ADS)

    Kravtsov, Konstantin

    In the present dissertation different aspects of all-optical signal processing, enabled by the use of nonlinear fibers, are studied. In particular, we focus on applications of a novel heavily GeO2-doped (HD) nonlinear fiber, that appears to be superior to many other types of nonlinear fibers because of its high nonlinearity and suitability for the use in nonlinear optical loop mirrors (NOLMs). Different functions, such as all-optical switching, thresholding, and wavelength conversion, are demonstrated with the HD fibers in the NOLM configuration. These basic functions are later used for realization of ultrafast time-domain demultiplexers, clock recovery, detectors of short pulses in stealth communications, and primitive elements for analog computations. Another important technology that benefits from the use of nonlinear fiber-based signal processing is optical code-division multiple access (CDMA). It is shown in both theory and experiment that all-optical thresholding is a unique way of improving existing detection methods for optical CDMA. Also, it is the way of implementation of true asynchronous optical spread-spectrum networks, which allows full realization of optical CDMA potential. Some aspects of quantum signal processing and manipulation of quantum states are also studied in this work. It is shown that propagation and collisions of Thirring solitons lead to a substantial squeezing of quantum states, which may find applications for generation of squeezed light.

  9. Cellular defense processes regulated by pathogen-elicited receptor signaling

    NASA Astrophysics Data System (ADS)

    Wu, Rongcong; Goldsipe, Arthur; Schauer, David B.; Lauffenburger, Douglas A.

    2011-06-01

    Vertebrates are constantly threatened by the invasion of microorganisms and have evolved systems of immunity to eliminate infectious pathogens in the body. Initial sensing of microbial agents is mediated by the recognition of pathogens by means of molecular structures expressed uniquely by microbes of a given type. So-called 'Toll-like receptors' are expressed on host epithelial barrier cells play an essential role in the host defense against microbial pathogens by inducing cell responses (e.g., proliferation, death, cytokine secretion) via activation of intracellular signaling networks. As these networks, comprising multiple interconnecting dynamic pathways, represent highly complex multi-variate "information processing" systems, the signaling activities particularly critical for governing the host cell responses are poorly understood and not easily ascertained by a priori theoretical notions. We have developed over the past half-decade a "data-driven" computational modeling approach, on a 'cue-signal-response' combined experiment/computation paradigm, to elucidate key multi-variate signaling relationships governing the cell responses. In an example presented here, we study how a canonical set of six kinase pathways combine to effect microbial agent-induced apoptotic death of a macrophage cell line. One modeling technique, partial least-squares regression, yielded the following key insights: {a} signal combinations most strongly correlated to apoptotic death are orthogonal to those most strongly correlated with release of inflammatory cytokines; {b} the ratio of two key pathway activities is the most powerful predictor of microbe-induced macrophage apoptotic death; {c} the most influential time-window of this signaling activity ratio is surprisingly fast: less than one hour after microbe stimulation.

  10. Data processing of fundamental frequency data in telephonic signals

    NASA Astrophysics Data System (ADS)

    Masserano, G.

    1980-12-01

    Voice fundamental frequency data obtained using an average magnitude difference function are further processed to reduce the evaluation error, in particular the double pitch error. Three algorithms are described and compared. An experimental assessment of the proposed algorithms is presented given a digitized male voice signal sampled at 10 kHz. One of the algorithms which simply eliminates the anomalous values of the fundamental frequency is found to be the best suited for error reduction. The simplicity of this algorithm, which allows for fast data processing, is emphasized.

  11. Interactions between visceral afferent signaling and stimulus processing

    PubMed Central

    Critchley, Hugo D.; Garfinkel, Sarah N.

    2015-01-01

    Visceral afferent signals to the brain influence thoughts, feelings and behavior. Here we highlight the findings of a set of empirical investigations in humans concerning body-mind interaction that focus on how feedback from states of autonomic arousal shapes cognition and emotion. There is a longstanding debate regarding the contribution of the body to mental processes. Recent theoretical models broadly acknowledge the role of (autonomically-mediated) physiological arousal to emotional, social and motivational behaviors, yet the underlying mechanisms are only partially characterized. Neuroimaging is overcoming this shortfall; first, by demonstrating correlations between autonomic change and discrete patterns of evoked, and task-independent, neural activity; second, by mapping the central consequences of clinical perturbations in autonomic response and; third, by probing how dynamic fluctuations in peripheral autonomic state are integrated with perceptual, cognitive and emotional processes. Building on the notion that an important source of the brain's representation of physiological arousal is derived from afferent information from arterial baroreceptors, we have exploited the phasic nature of these signals to show their differential contribution to the processing of emotionally-salient stimuli. This recent work highlights the facilitation at neural and behavioral levels of fear and threat processing that contrasts with the more established observations of the inhibition of central pain processing during baroreceptors activation. The implications of this body-brain-mind axis are discussed. PMID:26379481

  12. Hybrid integrated optic modules for real-time signal processing

    NASA Technical Reports Server (NTRS)

    Tsai, C. S.

    1984-01-01

    The most recent progress on four relatively new hybrid integrated optic device modules in LiNbO3 waveguides and one in YIG/GGG waveguide that are currently being studied are discussed. The five hybrid modules include a time-integrating acoustooptic correlator, a channel waveguide acoustooptic frequency shifter/modulator, an electrooptic channel waveguide total internal reflection moculator/switch, an electrooptic analog-to-digital converter using a Fabry-Perot modulator array, and a noncollinear magnetooptic modulator using magnetostatic surface waves. All of these devices possess the desirable characteristics of very large bandwidth (GHz or higher), very small substrate size along the optical path (typically 1.5 cm or less), single-mode optical propagation, and low drive power requirement. The devices utilize either acoustooptic, electrooptic or magnetooptic effects in planar or channel waveguides and, therefore, act as efficient interface devices between a light wave and temporal signals. Major areas of application lie in wideband multichannel optical real-time signal processing and communications. Some of the specific applications include spectral analysis and correlation of radio frequency (RF) signals, fiber-optic sensing, optical computing and multiport switching/routing, and analog-to-digital conversion of wide RF signals.

  13. Signal processing techniques for stepped frequency ultra-wideband radar

    NASA Astrophysics Data System (ADS)

    Nguyen, Lam

    2014-05-01

    The U.S. Army Research Laboratory (ARL) has developed the impulse-based, ground vehicle-based, forward-looking ultra-wideband (UWB), synthetic aperture radar (SAR) to detect concealed targets. Although the impulse-based architecture offers its own advantages, one of the important challenges is that when using this architecture it is very difficult to transmit a radar signal with an arbitrary bandwidth and shape. This feature is crucial for the radar to be compliant with the local frequency authority. In addition, being able to transmit signals with an arbitrary spectral shape is an important step in creating the next generation of smart (cognitive) radars. Therefore, we have designed a next-generation prototype radar to take advantage of the stepped frequency architecture. The design and building of the radar hardware is underway. In this paper, we study the radar transmit and acquisition scheme; the trade-offs between SAR image performance and various key radar parameters; and data reconstruction techniques for radar signals with an arbitrary spectrum. This study demonstrates performance, provides some guidelines for the radar design, and serves as a foundation for the signal and image processing stage.

  14. Analog signal processing for the Time Projection Chamber

    SciTech Connect

    Jared, R.C.; Landis, D.A.; Goulding, F.S.

    1981-10-01

    The Time Projection Chamber (TPC) is a large gas filled cylindrical detector designed to provide 3-D images of tracks radiating from the center of the detector where e/sup +/e/sup -/ collisions occur. Ionization along the tracks is drifted in an electric field to the end planes which are equipped with a large array of proportional wires and position pads (17,000 channels). The wire signals are used to derive radial data while the pad signals provide the azmuthal information. The axial dimension is determined using the drift time of the ionization. Preamplifiers mounted in the ends of the chamber feed the signals to remote amplifiers whose outputs drive Charge Coupled Devices (CCD). The CCDs are normally clocked at 10 MHz and hold a 45.5 ..mu..s history (445 CCD buckets) of analog drift information from the TPC. During readout the clock is changed to 20 KHz and 17,000 CCD outputs are digitized (9 bits) in parallel. The non-zero data is then transferred to buffer memories associated with the digitizers. This paper emphasizes the analog signal processing part of the system.

  15. Mouse submandibular gland morphogenesis: a paradigm for embryonic signal processing.

    PubMed

    Melnick, M; Jaskoll, T

    2000-01-01

    Signal processing is the sine qua non of embryogenesis. At its core, any single signal transduction pathway may be understood as classic Information Theory, adapted as an open system such that, because of networking, the "receiver" is presented with more information than was initially signaled by the "source". Over 40 years ago, Waddington presented his "Epigenetic Landscape" as a metaphor for the hierarchical nature of embryogenesis. Mathematically, Waddington's landscape may be modeled as a neural net. The "black box" of the neural net is an interacting network of signal transduction pathways (using hormones, growth factors, cytokines, neurotransmitters, and others) which inform the Boolean logic gates. An emerging theme in developmental biology is that defined sets of epigenetic circuits are used in multiple places, at multiple times, for similar and sometimes different purposes during organogenesis. As we show here, submandibular gland embryonic and fetal development is a splendid paradigm of these epigenetic circuits and their phenotypic outcomes, such as branching and lumen formation. PMID:12002815

  16. Dynamic tracking down-conversion signal processing method based on reference signal for grating heterodyne interferometer

    NASA Astrophysics Data System (ADS)

    Wang, Guochao; Yan, Shuhua; Zhou, Weihong; Gu, Chenhui

    2012-08-01

    Traditional displacement measurement systems by grating, which purely make use of fringe intensity to implement fringe count and subdivision, have rigid demands for signal quality and measurement condition, so they are not easy to realize measurement with nanometer precision. Displacement measurement with the dual-wavelength and single-grating design takes advantage of the single grating diffraction theory and the heterodyne interference theory, solving quite well the contradiction between large range and high precision in grating displacement measurement. To obtain nanometer resolution and nanometer precision, high-power subdivision of interference fringes must be realized accurately. A dynamic tracking down-conversion signal processing method based on the reference signal is proposed. Accordingly, a digital phase measurement module to realize high-power subdivision on field programmable gate array (FPGA) was designed, as well as a dynamic tracking down-conversion module using phase-locked loop (PLL). Experiments validated that a carrier signal after down-conversion can constantly maintain close to 100 kHz, and the phase-measurement resolution and phase precision are more than 0.05 and 0.2 deg, respectively. The displacement resolution and the displacement precision, corresponding to the phase results, are 0.139 and 0.556 nm, respectively.

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

    PubMed Central

    Dudik, Joshua M.; Coyle, James L.

    2015-01-01

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

  18. Micro/Nanostructured Films and Adhesives for Biomedical Applications.

    PubMed

    Lee, Jungkyu K; Kang, Sung Min; Yang, Sung Ho; Cho, Woo Kyung

    2015-12-01

    The advanced technologies available for micro/nanofabrication have opened new avenues for interdisciplinary approaches to solve the unmet medical needs of regenerative medicine and biomedical devices. This review highlights the recent developments in micro/nanostructured adhesives and films for biomedical applications, including waterproof seals for wounds or surgery sites, drug delivery, sensing human body signals, and optical imaging of human tissues. We describe in detail the fabrication processes required to prepare the adhesives and films, such as tape-based adhesives, nanofilms, and flexible and stretchable film-based electronic devices. We also discuss their biomedical functions, performance in vitro and in vivo, and the future research needed to improve the current systems. PMID:26510305

  19. Signal detection in FDA AERS database using Dirichlet process.

    PubMed

    Hu, Na; Huang, Lan; Tiwari, Ram C

    2015-08-30

    In the recent two decades, data mining methods for signal detection have been developed for drug safety surveillance, using large post-market safety data. Several of these methods assume that the number of reports for each drug-adverse event combination is a Poisson random variable with mean proportional to the unknown reporting rate of the drug-adverse event pair. Here, a Bayesian method based on the Poisson-Dirichlet process (DP) model is proposed for signal detection from large databases, such as the Food and Drug Administration's Adverse Event Reporting System (AERS) database. Instead of using a parametric distribution as a common prior for the reporting rates, as is the case with existing Bayesian or empirical Bayesian methods, a nonparametric prior, namely, the DP, is used. The precision parameter and the baseline distribution of the DP, which characterize the process, are modeled hierarchically. The performance of the Poisson-DP model is compared with some other models, through an intensive simulation study using a Bayesian model selection and frequentist performance characteristics such as type-I error, false discovery rate, sensitivity, and power. For illustration, the proposed model and its extension to address a large amount of zero counts are used to analyze statin drugs for signals using the 2006-2011 AERS data. PMID:25924820

  20. Decoding signal processing in thalamo-hippocampal circuitry: implications for theories of memory and spatial processing.

    PubMed

    Tsanov, Marian; O'Mara, Shane M

    2015-09-24

    A major tool in understanding how information is processed in the brain is the analysis of neuronal output at each hierarchical level through which neurophysiological signals are propagated. Since the experimental brain operation performed on Henry Gustav Molaison (known as patient H.M.) in 1953, the hippocampal formation has gained special attention, resulting in a very large number of studies investigating signals processed by the hippocampal formation. One of the main information streams to the hippocampal formation, vital for episodic memory formation, arises from thalamo-hippocampal projections, as there is extensive connectivity between these structures. This connectivity is sometimes overlooked by theories of memory formation by the brain, in favour of theories with a strong cortico-hippocampal flavour. In this review, we attempt to address some of the complexity of the signals processed within the thalamo-hippocampal circuitry. To understand the signals encoded by the anterior thalamic nuclei in particular, we review key findings from electrophysiological, anatomical, behavioural and computational studies. We include recent findings elucidating the integration of different signal modalities by single thalamic neurons; we focus in particular on the propagation of two prominent signals: head directionality and theta rhythm. We conclude that thalamo-hippocampal processing provides a centrally important, substantive, and dynamic input modulating and moderating hippocampal spatial and mnemonic processing. This article is part of a Special Issue entitled SI: Brain and Memory. PMID:25498107

  1. Time Reversal Signal Processing in Communications - A Feasibility Study

    SciTech Connect

    Meyer, A W; Candy, J V; Poggio, A J

    2002-01-30

    A typical communications channel is subjected to a variety of signal distortions, including multipath, that corrupt the information being transmitted and reduce the effective channel capacity. The mitigation of the multipath interference component is an ongoing concern for communication systems operating in complex environments such as might be experienced inside buildings, urban environments, and hilly or heavily wooded areas. Communications between mobile units and distributed sensors, so important to national security, are dependent upon flawless conveyance of information in complex environments. The reduction of this multipath corruption necessitates better channel equalization, i.e., the removal of channel distortion to extract the transmitted information. But, the current state of the art in channel equalization either requires a priori knowledge of the channel or the use of a known training sequence and adaptive filtering. If the ''assumed'' model within the equalization processor does not at least capture the dominant characteristics of the channel, then the received information may still be highly distorted and possibly useless. Also, the processing required for classical equalization is demanding in computational resources. To remedy this situation, many techniques have been investigated to replace classical equalization. Such a technique, the subject of this feasibility study, is Time Reversal Signal Processing (TRSP). Multipath is particularly insidious and a major factor in the deterioration of communication channels. Unlike most other characteristics that corrupt a communications channel, the detrimental effects of multipath cannot be overcome by merely increasing the transmitted power. Although the power in a signal diminishes as a function of the distance between the transmitter and receiver, multipath further degrades a signal by creating destructive interference that results in a loss of received power in a very localized area, a loss often

  2. Gallium arsenide enhances digital signal processing in electronic warfare

    NASA Astrophysics Data System (ADS)

    Hoffman, B.; Apte, D.

    1985-07-01

    The higher electron mobility and velocity of GaAs digital signal processing IC devices for electronic warfare (EW) allow operation times that are several times faster than those of ICs based on silicon. Particular benefits are foreseen for the response time and broadband capability of ECM systems. Many data manipulation methods can be implemented in emitter-coupled logic (ECL) GaAs devices, and digital GaAs RF memories are noted to show great promise for improved ECM system performance while encompassing microwave frequency and chirp signal synthesis, repeater jamming, and multiple false target generation. EW digital frequency synthesizers are especially in need of GaAS IC technology, since bandwidth and resolution have been limited by ECL technology to about 250 MHz.

  3. A rapid signal processing technique to remove the effect of dispersion from guided wave signals.

    PubMed

    Wilcox, Paul D

    2003-04-01

    Guided acoustic and ultrasonic waves have been utilized in various manners for non-destructive evaluation and testing. If a guided wave mode is dispersive, a pulse of energy will spread out in space and time as it propagates. For a long-range guided wave inspection application, this constrains the choice of operating point to regions on the dispersion curves where dispersion effects are small. A signal processing technique is presented that enables this constraint on operating point to be relaxed. The technique makes use of a priori knowledge of the dispersion characteristics of a guided wave mode to map signals from the time to distance domains. In the mapping process, dispersed signals are compressed to their original shape. The theoretical basis of the technique is described and an efficient numerical implementation is presented. The robustness of the technique to inaccuracies in the dispersion data is also addressed. The application of the technique to experimental data is shown and the resulting improvement in spatial resolution is demonstrated. The implications of using dispersion compensation in practical systems are briefly discussed. PMID:12744398

  4. Bunyamwera orthobunyavirus glycoprotein precursor is processed by cellular signal peptidase and signal peptide peptidase

    PubMed Central

    Shi, Xiaohong; Botting, Catherine H.; Li, Ping; Niglas, Mark; Brennan, Benjamin; Shirran, Sally L.; Szemiel, Agnieszka M.; Elliott, Richard M.

    2016-01-01

    The M genome segment of Bunyamwera virus (BUNV)—the prototype of both the Bunyaviridae family and the Orthobunyavirus genus—encodes the glycoprotein precursor (GPC) that is proteolytically cleaved to yield two viral structural glycoproteins, Gn and Gc, and a nonstructural protein, NSm. The cleavage mechanism of orthobunyavirus GPCs and the host proteases involved have not been clarified. In this study, we investigated the processing of BUNV GPC and found that both NSm and Gc proteins were cleaved at their own internal signal peptides (SPs), in which NSm domain I functions as SPNSm and NSm domain V as SPGc. Moreover, the domain I was further processed by a host intramembrane-cleaving protease, signal peptide peptidase, and is required for cell fusion activities. Meanwhile, the NSm domain V (SPGc) remains integral to NSm, rendering the NSm topology as a two-membrane-spanning integral membrane protein. We defined the cleavage sites and boundaries between the processed proteins as follows: Gn, from residue 17–312 or nearby residues; NSm, 332–477; and Gc, 478–1433. Our data clarified the mechanism of the precursor cleavage process, which is important for our understanding of viral glycoprotein biogenesis in the genus Orthobunyavirus and thus presents a useful target for intervention strategies. PMID:27439867

  5. Approaches to Chemical and Biochemical Information and Signal Processing

    NASA Astrophysics Data System (ADS)

    Privman, Vladimir

    2012-02-01

    We outline models and approaches for error control required to prevent buildup of noise when ``gates'' and other ``network elements'' based on (bio)chemical reaction processes are utilized to realize stable, scalable networks for information and signal processing. We also survey challenges and possible future research. [4pt] [1] Control of Noise in Chemical and Biochemical Information Processing, V. Privman, Israel J. Chem. 51, 118-131 (2010).[0pt] [2] Biochemical Filter with Sigmoidal Response: Increasing the Complexity of Biomolecular Logic, V. Privman, J. Halamek, M. A. Arugula, D. Melnikov, V. Bocharova and E. Katz, J. Phys. Chem. B 114, 14103-14109 (2010).[0pt] [3] Towards Biosensing Strategies Based on Biochemical Logic Systems, E. Katz, V. Privman and J. Wang, in: Proc. Conf. ICQNM 2010 (IEEE Comp. Soc. Conf. Publ. Serv., Los Alamitos, California, 2010), pages 1-9.

  6. Coherent detection and digital signal processing for fiber optic communications

    NASA Astrophysics Data System (ADS)

    Ip, Ezra

    The drive towards higher spectral efficiency in optical fiber systems has generated renewed interest in coherent detection. We review different detection methods, including noncoherent, differentially coherent, and coherent detection, as well as hybrid detection methods. We compare the modulation methods that are enabled and their respective performances in a linear regime. An important system parameter is the number of degrees of freedom (DOF) utilized in transmission. Polarization-multiplexed quadrature-amplitude modulation maximizes spectral efficiency and power efficiency as it uses all four available DOF contained in the two field quadratures in the two polarizations. Dual-polarization homodyne or heterodyne downconversion are linear processes that can fully recover the received signal field in these four DOF. When downconverted signals are sampled at the Nyquist rate, compensation of transmission impairments can be performed using digital signal processing (DSP). Software based receivers benefit from the robustness of DSP, flexibility in design, and ease of adaptation to time-varying channels. Linear impairments, including chromatic dispersion (CD) and polarization-mode dispersion (PMD), can be compensated quasi-exactly using finite impulse response filters. In practical systems, sampling the received signal at 3/2 times the symbol rate is sufficient to enable an arbitrary amount of CD and PMD to be compensated for a sufficiently long equalizer whose tap length scales linearly with transmission distance. Depending on the transmitted constellation and the target bit error rate, the analog-to-digital converter (ADC) should have around 5 to 6 bits of resolution. Digital coherent receivers are naturally suited for the implementation of feedforward carrier recovery, which has superior linewidth tolerance than phase-locked loops, and does not suffer from feedback delay constraints. Differential bit encoding can be used to prevent catastrophic receiver failure due

  7. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    NASA Astrophysics Data System (ADS)

    Si, Qian

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

  8. Improved effectiveness of GPS RAIM through ridge regression signal processing

    NASA Technical Reports Server (NTRS)

    Kelly, Robert J.; Van Graas, Frank; Kuhl, Mark R.

    1989-01-01

    A measurement processing method has been developed which markedly improves the GPS Receiver Autonomous Integrity Monitoring (RAIM) software-based algorithm system's effectiveness in detecting satellite signal failures. Detection is via the consistency of a redundant set of pseudorange measurements. When five satellites are in view, five different subsolutions can be calculated; the integrity alarm is triggered on the basis of subsolution comparisons. Because a poor distribution of the satellites also causes RAIM subsolution scattering, a methodology for selecting the covariance matrix is presented which incorporates ridge regression into a Kalman filter.

  9. 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.

  10. Photonics for microwave systems and ultra-wideband signal processing

    NASA Astrophysics Data System (ADS)

    Ng, W.

    2016-08-01

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

  11. A Random Walk into Optical Signal Processing and Integrated Optofluidics

    NASA Astrophysics Data System (ADS)

    Baylor, Martha-Elizabeth

    2013-04-01

    As a young child, I knew that I wanted to be a paleontologist. My parents, both artists, did their best to encourage me in my quest to dig for dinosaurs. However, decisions during my late high school and early college years serendipitously shifted my path so that I ended up pursuing a career in applied physics. In particular, my career path has been centered in optics with an emphasis on holography and signal processing. This talk will discuss my research in the areas of opto-electronic blind source separation and holographic photopolymers as well as the non-linear path that has gotten me to this point.

  12. Signal Processing System for the CASA Integrated Project I Radars

    SciTech Connect

    Bharadwaj, Nitin; Chandrasekar, V.; Junyent, Francesc

    2010-09-01

    This paper describes the waveform design space and signal processing system for dual-polarization Doppler weather radar operating at X band. The performance of the waveforms is presented with ground clutter suppression capability and mitigation of range velocity ambiguity. The operational waveform is designed based on operational requirements and system/hardware requirements. A dual Pulse Repetition Frequency (PRF) waveform was developed and implemented for the first generation X-band radars deployed by the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This paper presents an evaluation of the performance of the waveforms based on simulations and data collected by the first-generation CASA radars during operations.

  13. Real-time fractal signal processing in the time domain

    NASA Astrophysics Data System (ADS)

    Hartmann, András; Mukli, Péter; Nagy, Zoltán; Kocsis, László; Hermán, Péter; Eke, András

    2013-01-01

    Fractal analysis has proven useful for the quantitative characterization of complex time series by scale-free statistical measures in various applications. The analysis has commonly been done offline with the signal being resident in memory in full length, and the processing carried out in several distinct passes. However, in many relevant applications, such as monitoring or forecasting, algorithms are needed to capture changes in the fractal measure real-time. Here we introduce real-time variants of the Detrended Fluctuation Analysis (DFA) and the closely related Signal Summation Conversion (SSC) methods, which are suitable to estimate the fractal exponent in one pass. Compared to offline algorithms, the precision is the same, the memory requirement is significantly lower, and the execution time depends on the same factors but with different rates. Our tests show that dynamic changes in the fractal parameter can be efficiently detected. We demonstrate the applicability of our real-time methods on signals of cerebral hemodynamics acquired during open-heart surgery.

  14. Signal transduction and information processing in mammalian taste buds

    PubMed Central

    2013-01-01

    The molecular machinery for chemosensory transduction in taste buds has received considerable attention within the last decade. Consequently, we now know a great deal about sweet, bitter, and umami taste mechanisms and are gaining ground rapidly on salty and sour transduction. Sweet, bitter, and umami tastes are transduced by G-protein-coupled receptors. Salty taste may be transduced by epithelial Na channels similar to those found in renal tissues. Sour transduction appears to be initiated by intracellular acidification acting on acid-sensitive membrane proteins. Once a taste signal is generated in a taste cell, the subsequent steps involve secretion of neurotransmitters, including ATP and serotonin. It is now recognized that the cells responding to sweet, bitter, and umami taste stimuli do not possess synapses and instead secrete the neurotransmitter ATP via a novel mechanism not involving conventional vesicular exocytosis. ATP is believed to excite primary sensory afferent fibers that convey gustatory signals to the brain. In contrast, taste cells that do have synapses release serotonin in response to gustatory stimulation. The postsynaptic targets of serotonin have not yet been identified. Finally, ATP secreted from receptor cells also acts on neighboring taste cells to stimulate their release of serotonin. This suggests that there is important information processing and signal coding taking place in the mammalian taste bud after gustatory stimulation. PMID:17468883

  15. Social signal processing for studying parent–infant interaction

    PubMed Central

    Avril, Marie; Leclère, Chloë; Viaux, Sylvie; Michelet, Stéphane; Achard, Catherine; Missonnier, Sylvain; Keren, Miri; Cohen, David; Chetouani, Mohamed

    2014-01-01

    Studying early interactions is a core issue of infant development and psychopathology. Automatic social signal processing theoretically offers the possibility to extract and analyze communication by taking an integrative perspective, considering the multimodal nature and dynamics of behaviors (including synchrony). This paper proposes an explorative method to acquire and extract relevant social signals from a naturalistic early parent–infant interaction. An experimental setup is proposed based on both clinical and technical requirements. We extracted various cues from body postures and speech productions of partners using the IMI2S (Interaction, Multimodal Integration, and Social Signal) Framework. Preliminary clinical and computational results are reported for two dyads (one pathological in a situation of severe emotional neglect and one normal control) as an illustration of our cross-disciplinary protocol. The results from both clinical and computational analyzes highlight similar differences: the pathological dyad shows dyssynchronic interaction led by the infant whereas the control dyad shows synchronic interaction and a smooth interactive dialog. The results suggest that the current method might be promising for future studies. PMID:25540633

  16. TOPICAL REVIEW: A survey of signal processing algorithms in brain computer interfaces based on electrical brain signals

    NASA Astrophysics Data System (ADS)

    Bashashati, Ali; Fatourechi, Mehrdad; Ward, Rabab K.; Birch, Gary E.

    2007-06-01

    Brain computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?

  17. Model-Based Signal Processing: Correlation Detection With Synthetic Seismograms

    SciTech Connect

    Rodgers, A; Harris, D; Pasyanos, M; Blair, S; Matt, R

    2006-08-30

    Recent applications of correlation methods to seismological problems illustrate the power of coherent signal processing applied to seismic waveforms. Examples of these applications include detection of low amplitude signals buried in ambient noise and cross-correlation of sets of waveforms to form event clusters and accurately measure delay times for event relocation and/or earth structure. These methods rely on the exploitation of the similarity of individual waveforms and have been successfully applied to large sets of empirical observations. However, in cases with little or no empirical event data, such as aseismic regions or exotic event types, correlation methods with observed seismograms will not be possible due to the lack of previously observed similar waveforms. This study uses model-based signals computed for three-dimensional (3D) Earth models to form the basis for correlation detection. Synthetic seismograms are computed for fully 3D models estimated from the Markov Chain Monte-Carlo (MCMC) method. MCMC uses stochastic sampling to fit multiple seismological data sets. Rather than estimate a single ''optimal'' model, MCMC results in a suite of models that sample the model space and incorporates uncertainty through variability of the models. The variability reflects our ignorance of Earth structure, due to limited resolution, data and modeling errors, and produces variability in the seismic waveform response. Model-based signals are combined using a subspace method where the synthetic signals are decomposed into an orthogonal basis by singular-value decomposition (SVD) and the observed waveforms are represented with a linear combination of a sub-set of eigenvectors (signals) associated with the most significant eigenvalues. We have demonstrated the method by modeling long-period (80-10 seconds) regional seismograms for a moderate (M{approx}5) earthquake near the China-North Korea border. Synthetic seismograms are computed with the Spectral Element Method

  18. The Accuratre Signal Model and Imaging Processing in Geosynchronous SAR

    NASA Astrophysics Data System (ADS)

    Hu, Cheng

    With the development of synthetic aperture radar (SAR) application, the disadvantage of low earth orbit (LEO) SAR becomes more and more apparent. The increase of orbit altitude can shorten the revisit time and enlarge the coverage area in single look, and then satisfy the application requirement. The concept of geosynchronous earth orbit (GEO) SAR system is firstly presented and deeply discussed by K.Tomiyasi and other researchers. A GEO SAR, with its fine temporal resolution, would overcome the limitations of current imaging systems, allowing dense interpretation of transient phenomena as GPS time-series analysis with a spatial density several orders of magnitude finer. Until now, the related literatures about GEO SAR are mainly focused in the system parameter design and application requirement. As for the signal characteristic, resolution calculation and imaging algorithms, it is nearly blank in the related literatures of GEO SAR. In the LEO SAR, the signal model analysis adopts the `Stop-and-Go' assumption in general, and this assumption can satisfy the imaging requirement in present advanced SAR system, such as TerraSAR, Radarsat2 and so on. However because of long propagation distance and non-negligible earth rotation, the `Stop-and-Go' assumption does not exist and will cause large propagation distance error, and then affect the image formation. Furthermore the long propagation distance will result in the long synthetic aperture time such as hundreds of seconds, therefore the linear trajectory model in LEO SAR imaging will fail in GEO imaging, and the new imaging model needs to be proposed for the GEO SAR imaging processing. In this paper, considering the relative motion between satellite and earth during signal propagation time, the accurate analysis method for propagation slant range is firstly presented. Furthermore, the difference between accurate analysis method and `Stop-and-Go' assumption is analytically obtained. Meanwhile based on the derived

  19. 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.

  20. Gravity Influences Top-Down Signals in Visual Processing

    PubMed Central

    Cheron, Guy; Leroy, Axelle; Palmero-Soler, Ernesto; De Saedeleer, Caty; Bengoetxea, Ana; Cebolla, Ana-Maria; Vidal, Manuel; Dan, Bernard; Berthoz, Alain; McIntyre, Joseph

    2014-01-01

    Visual perception is not only based on incoming visual signals but also on information about a multimodal reference frame that incorporates vestibulo-proprioceptive input and motor signals. In addition, top-down modulation of visual processing has previously been demonstrated during cognitive operations including selective attention and working memory tasks. In the absence of a stable gravitational reference, the updating of salient stimuli becomes crucial for successful visuo-spatial behavior by humans in weightlessness. Here we found that visually-evoked potentials triggered by the image of a tunnel just prior to an impending 3D movement in a virtual navigation task were altered in weightlessness aboard the International Space Station, while those evoked by a classical 2D-checkerboard were not. Specifically, the analysis of event-related spectral perturbations and inter-trial phase coherency of these EEG signals recorded in the frontal and occipital areas showed that phase-locking of theta-alpha oscillations was suppressed in weightlessness, but only for the 3D tunnel image. Moreover, analysis of the phase of the coherency demonstrated the existence on Earth of a directional flux in the EEG signals from the frontal to the occipital areas mediating a top-down modulation during the presentation of the image of the 3D tunnel. In weightlessness, this fronto-occipital, top-down control was transformed into a diverging flux from the central areas toward the frontal and occipital areas. These results demonstrate that gravity-related sensory inputs modulate primary visual areas depending on the affordances of the visual scene. PMID:24400069

  1. Gravity influences top-down signals in visual processing.

    PubMed

    Cheron, Guy; Leroy, Axelle; Palmero-Soler, Ernesto; De Saedeleer, Caty; Bengoetxea, Ana; Cebolla, Ana-Maria; Vidal, Manuel; Dan, Bernard; Berthoz, Alain; McIntyre, Joseph

    2014-01-01

    Visual perception is not only based on incoming visual signals but also on information about a multimodal reference frame that incorporates vestibulo-proprioceptive input and motor signals. In addition, top-down modulation of visual processing has previously been demonstrated during cognitive operations including selective attention and working memory tasks. In the absence of a stable gravitational reference, the updating of salient stimuli becomes crucial for successful visuo-spatial behavior by humans in weightlessness. Here we found that visually-evoked potentials triggered by the image of a tunnel just prior to an impending 3D movement in a virtual navigation task were altered in weightlessness aboard the International Space Station, while those evoked by a classical 2D-checkerboard were not. Specifically, the analysis of event-related spectral perturbations and inter-trial phase coherency of these EEG signals recorded in the frontal and occipital areas showed that phase-locking of theta-alpha oscillations was suppressed in weightlessness, but only for the 3D tunnel image. Moreover, analysis of the phase of the coherency demonstrated the existence on Earth of a directional flux in the EEG signals from the frontal to the occipital areas mediating a top-down modulation during the presentation of the image of the 3D tunnel. In weightlessness, this fronto-occipital, top-down control was transformed into a diverging flux from the central areas toward the frontal and occipital areas. These results demonstrate that gravity-related sensory inputs modulate primary visual areas depending on the affordances of the visual scene. PMID:24400069

  2. Large-Array Signal Processing for Deep-Space Applications

    NASA Astrophysics Data System (ADS)

    Lee, C. H.; Vilnrotter, V.; Satorius, E.; Ye, Z.; Fort, D.; Cheung, K.-M.

    2002-04-01

    This article develops the mathematical models needed to describe the key issues in using an array of antennas for receiving spacecraft signals for DSN applications. The detrimental effects of nearby interfering sources, such as other spacecraft transmissions or natural radio sources within the array's field of view, on signal-to noise ratio (SNR) are determined, atmospheric effects relevant to the arraying problem developed, and two classes of algorithms (multiple signal classification (MUSIC) plus beam forming, and an eigen-based solution) capable of phasing up the array with maximized SNR in the presence of realistic disturbances are evaluated. It is shown that, when convolutionally encoded binary-phase shift keying (BPSK) data modulation is employed on the spacecraft signal, previously developed data pre-processing techniques that partially reconstruct the carrier can be of great benefit to array performance, particularly when strong interfering sources are present. Since this article is concerned mainly with demonstrating the required capabilities for operation under realistic conditions, no attempt has been made to reduce algorithm complexity; the design and evaluation of less complex algorithms with similar capabilities will be addressed in a future article. The performances of the candidate algorithms discussed in this article have been evaluated in terms of the number of symbols needed to achieve a given level of combining loss for different numbers of array elements, and compared on this common basis. It is shown that even the best algorithm requires approximately 25,000 symbols to achieve a combining loss of less than 0.5 dB when 128 antenna elements are employed, but generally 50,000 or more symbols are needed. This is not a serious impediment to successful arraying with high data-rate transmission, but may be of some concern with missions exploring near the edge of our solar system or beyond, where lower data rates may be required.

  3. Signal processing for passive detection and classification of underwater acoustic signals

    NASA Astrophysics Data System (ADS)

    Chung, Kil Woo

    2011-12-01

    This dissertation examines signal processing for passive detection, classification and tracking of underwater acoustic signals for improving port security and the security of coastal and offshore operations. First, we consider the problem of passive acoustic detection of a diver in a shallow water environment. A frequency-domain multi-band matched-filter approach to swimmer detection is presented. The idea is to break the frequency contents of the hydrophone signals into multiple narrow frequency bands, followed by time averaged (about half of a second) energy calculation over each band. Then, spectra composed of such energy samples over the chosen frequency bands are correlated to form a decision variable. The frequency bands with highest Signal/Noise ratio are used for detection. The performance of the proposed approach is demonstrated for experimental data collected for a diver in the Hudson River. We also propose a new referenceless frequency-domain multi-band detector which, unlike other reference-based detectors, does not require a diver specific signature. Instead, our detector matches to a general feature of the diver spectrum in the high frequency range: the spectrum is roughly periodic in time and approximately flat when the diver exhales. The performance of the proposed approach is demonstrated by using experimental data collected from the Hudson River. Moreover, we present detection, classification and tracking of small vessel signals. Hydroacoustic sensors can be applied for the detection of noise generated by vessels, and this noise can be used for vessel detection, classification and tracking. This dissertation presents recent improvements aimed at the measurement and separation of ship DEMON (Detection of Envelope Modulation on Noise) acoustic signatures in busy harbor conditions. Ship signature measurements were conducted in the Hudson River and NY Harbor. The DEMON spectra demonstrated much better temporal stability compared with the full ship

  4. 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.

  5. Tunable photonic filters: a digital signal processing design approach.

    PubMed

    Binh, Le Nguyen

    2009-05-20

    Digital signal processing techniques are used for synthesizing tunable optical filters with variable bandwidth and centered reference frequency including the tunability of the low-pass, high-pass, bandpass, and bandstop optical filters. Potential applications of such filters are discussed, and the design techniques and properties of recursive digital filters are outlined. The basic filter structures, namely, the first-order all-pole optical filter (FOAPOF) and the first-order all-zero optical filter (FOAZOF), are described, and finally the design process of tunable optical filters and the designs of the second-order Butterworth low-pass, high-pass, bandpass, and bandstop tunable optical filters are presented. Indeed, we identify that the all-zero and all-pole networks are equivalent with well known principles of optics of interference and resonance, respectively. It is thus very straightforward to implement tunable optical filters, which is a unique feature. PMID:19458728

  6. Guest Editorial: Two-Dimensional Optical Signal Processing

    NASA Astrophysics Data System (ADS)

    Kooij, Theo; Ludman, Jacques E.; Stilwell, P. D., Jr.

    1982-10-01

    When some optical processing systems firms proposed to the Defense Advanced Research Project Agency (DARPA) and the U.S. Navy some years ago that they could beat the ILLIAC-IV-that venerable supercomputer, which until recently was the world's largest by at least a factor of 100, it sounded too good to be true. But they were right, and they did not even have to try hard. The problem was a two-dimensional (2-D) processing task of generating ambiguity surfaces to test whether two received signals came from a common origin, with unknown time and Doppler shifts. The ILLIAC, going all out as an in-line processor for the Acoustic Research Center near San Francisco, California, could just make a handful of such surfaces per second; the optical processors made hundreds, literally sucking their digital inputs dry.

  7. Analog signal processing for optical coherence imaging systems

    NASA Astrophysics Data System (ADS)

    Xu, Wei

    Optical coherence tomography (OCT) and optical coherence microscopy (OCM) are non-invasive optical coherence imaging techniques, which enable micron-scale resolution, depth resolved imaging capability. Both OCT and OCM are based on Michelson interferometer theory. They are widely used in ophthalmology, gastroenterology and dermatology, because of their high resolution, safety and low cost. OCT creates cross sectional images whereas OCM obtains en face images. In this dissertation, the design and development of three increasingly complicated analog signal processing (ASP) solutions for optical coherence imaging are presented. The first ASP solution was implemented for a time domain OCT system with a Rapid Scanning Optical Delay line (RSOD)-based optical signal modulation and logarithmic amplifier (Log amp) based demodulation. This OCT system can acquire up to 1600 A-scans per second. The measured dynamic range is 106dB at 200A-scan per second. This OCT signal processing electronics includes an off-the-shelf filter box with a Log amp circuit implemented on a PCB board. The second ASP solution was developed for an OCM system with synchronized modulation and demodulation and compensation for interferometer phase drift. This OCM acquired micron-scale resolution, high dynamic range images at acquisition speeds up to 45,000 pixels/second. This OCM ASP solution is fully custom designed on a perforated circuit board. The third ASP solution was implemented on a single 2.2 mm x 2.2 mm complementary metal oxide semiconductor (CMOS) chip. This design is expandable to a multiple channel OCT system. A single on-chip CMOS photodetector and ASP channel was used for coherent demodulation in a time domain OCT system. Cross-sectional images were acquired with a dynamic range of 76dB (limited by photodetector responsivity). When incorporated with a bump-bonded InGaAs photodiode with higher responsivity, the expected dynamic range is close to 100dB.

  8. Vibrotactile identification of signal-processed sounds from environmental events.

    PubMed

    Ranjbar, Parivash; Stranneby, Dag; Borg, Erik

    2009-01-01

    This study compared three different signal-processing principles (eight basic algorithms)-transposing, modulating, and filtering-to find the principle(s)/algorithm(s) that resulted in the best tactile identification of environmental sounds. The subjects were 19 volunteers (9 female/10 male) who were between 18 and 50 years old and profoundly hearing impaired. We processed sounds produced by 45 representative environmental events with the different algorithms and presented them to subjects as tactile stimuli using a wide-band stationary vibrator. We compared eight algorithms based on the three principles (one unprocessed, as reference). The subjects identified the stimuli by choosing among 10 alternatives drawn from the 45 events. We found that algorithm and subject were significant factors affecting the results (repeated measures analysis of variance, p < 0.001). We also found large differences between individuals regarding which algorithm was best. The test-retest variability was small (mean +/- 95% confidence interval = 8 +/- 3 percentage units), and no correlation was noted between identification score and individual vibratory thresholds. One transposing algorithm and two modulating algorithms led to significantly better results than did the unprocessed signals (p < 0.05). Thus, the two principles of transposing and modulating were appropriate, whereas filtering was unsuccessful. In future work, the two transposing algorithms and the modulating algorithm will be used in tests with a portable vibrator for people with dual sensory impairment (hearing and vision). PMID:20157859

  9. Single sensor processing to obtain high resolution color component signals

    NASA Technical Reports Server (NTRS)

    Glenn, William E. (Inventor)

    2010-01-01

    A method for generating color video signals representative of color images of a scene includes the following steps: focusing light from the scene on an electronic image sensor via a filter having a tri-color filter pattern; producing, from outputs of the sensor, first and second relatively low resolution luminance signals; producing, from outputs of the sensor, a relatively high resolution luminance signal; producing, from a ratio of the relatively high resolution luminance signal to the first relatively low resolution luminance signal, a high band luminance component signal; producing, from outputs of the sensor, relatively low resolution color component signals; and combining each of the relatively low resolution color component signals with the high band luminance component signal to obtain relatively high resolution color component signals.

  10. Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

    NASA Technical Reports Server (NTRS)

    Kenny, R. Jeremy; Lee, Erik; Hulka, James R.; Casiano, Matthew

    2011-01-01

    The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response

  11. Ocean acoustic signal processing: A model-based approach

    SciTech Connect

    Candy, J.V. ); Sullivan, E.J. )

    1992-12-01

    A model-based approach is proposed to solve the ocean acoustic signal processing problem that is based on a state-space representation of the normal-mode propagation model. It is shown that this representation can be utilized to spatially propagate both modal (depth) and range functions given the basic parameters (wave numbers, etc.) developed from the solution of the associated boundary value problem. This model is then generalized to the stochastic case where an approximate Gauss--Markov model evolves. The Gauss--Markov representation, in principle, allows the inclusion of stochastic phenomena such as noise and modeling errors in a consistent manner. Based on this framework, investigations are made of model-based solutions to the signal enhancement, detection and related parameter estimation problems. In particular, a modal/pressure field processor is designed that allows {ital in} {ital situ} recursive estimation of the sound velocity profile. Finally, it is shown that the associated residual or so-called innovation sequence that ensues from the recursive nature of this formulation can be employed to monitor the model's fit to the data and also form the basis of a sequential detector.

  12. Developments in cardiovascular ultrasound: Part 1: Signal processing and instrumentation.

    PubMed

    Fish, P J; Hoskins, P R; Moran, C; McDicken, W N

    1997-11-01

    One of the major contributions to the improvement of spectral Doppler and colour flow imaging instruments has been the development of advanced signal-processing techniques made possible by increasing computing power. Model-based or parametric spectral estimators, time-frequency transforms, station-arising algorithms and spectral width correction techniques have been investigated as possible improvements on the FFT-based estimators currently used for real-time spectral estimation of Doppler signals. In colour flow imaging some improvement on velocity estimation accuracy has been achieved by the use of new algorithms but at the expense of increased computational complexity compared with the conventional autocorrelation method. Polynomial filters have been demonstrated to have some advantages over IIR filters for stationary echo cancellation. Several methods of velocity vector estimation to overcome the problem of angle dependence have been studied, including 2D feature tracking, two and three beam approaches and the use of spectral width in addition to mean frequency. 3D data acquisition and display and Doppler power imaging have also been investigated. The use of harmonic imaging, using the second harmonic generated by encapsulated bubble contrast media, seems promising particularly for imaging slow flow. Parallel image data acquisition using non-sequential scanning or broad beam transmission, followed by simultaneous reception along a number of beams, has been studied to speed up 'real-time' imaging. PMID:9538529

  13. Dispersion-engineered multicore fibers for distributed radiofrequency signal processing.

    PubMed

    García, Sergi; Gasulla, Ivana

    2016-09-01

    We report a trench-assisted heterogeneous multicore fiber optimized in terms of higher-order dispersion and crosstalk for radiofrequency true time delay operation. The analysis of the influence of the core refractive index profile on the dispersion slope and effective index reveals a tradeoff between the behavior of the crosstalk against fiber curvatures and the linearity of the propagation group delay. We investigate the optimization of the multicore fiber in the framework of this tradeoff and present a design that features a group delay relative error below 5% for an optical wavelength range up to 100 nm and a crosstalk level below -80 dB for bending radii larger than 103 mm. The performance of the true time delay line is validated in the context of microwave signal filtering and optical beamforming for phased array antennas. This work opens the way towards the development of compact fiber-integrated solutions that enable the implementation of a variety of distributed signal processing functionalities that will be key in future fiber-wireless communications networks and systems. PMID:27607668

  14. Regulation of amyloid precursor protein processing by serotonin signaling.

    PubMed

    Pimenova, Anna A; Thathiah, Amantha; De Strooper, Bart; Tesseur, Ina

    2014-01-01

    Proteolytic processing of the amyloid precursor protein (APP) by the β- and γ-secretases releases the amyloid-β peptide (Aβ), which deposits in senile plaques and contributes to the etiology of Alzheimer's disease (AD). The α-secretase cleaves APP in the Aβ peptide sequence to generate soluble APPα (sAPPα). Upregulation of α-secretase activity through the 5-hydroxytryptamine 4 (5-HT4) receptor has been shown to reduce Aβ production, amyloid plaque load and to improve cognitive impairment in transgenic mouse models of AD. Consequently, activation of 5-HT4 receptors following agonist stimulation is considered to be a therapeutic strategy for AD treatment; however, the signaling cascade involved in 5-HT4 receptor-stimulated proteolysis of APP remains to be determined. Here we used chemical and siRNA inhibition to identify the proteins which mediate 5-HT4d receptor-stimulated α-secretase activity in the SH-SY5Y human neuronal cell line. We show that G protein and Src dependent activation of phospholipase C are required for α-secretase activity, while, unexpectedly, adenylyl cyclase and cAMP are not involved. Further elucidation of the signaling pathway indicates that inositol triphosphate phosphorylation and casein kinase 2 activation is also a prerequisite for α-secretase activity. Our findings provide a novel route to explore the treatment of AD through 5-HT4 receptor-induced α-secretase activation. PMID:24466315

  15. Ultrafast Optical Signal Processing Based Upon Space-Time Dualities

    NASA Astrophysics Data System (ADS)

    van Howe, James; Xu, Chris

    2006-07-01

    The last two decades have seen a wealth of optical instrumentation based upon the concepts of space-time duality. A historical overview of how this beautiful framework has been exploited to develop instruments for optical signal processing is presented. The power of this framework is then demonstrated by reviewing four devices in detail based upon space-time dualities that have been experimentally demonstrated: 1) a time-lens timing-jitter compensator for ultralong-haul dense-wavelength-division-multiplexed dispersion-managed soliton transmission, 2) a multiwavelength pulse generator using time-lens compression, 3) a programmable ultrafast optical delay line by use of a time-prism pair, and 4) an enhanced ultrafast optical delay line by use of soliton propagation between a time-prism pair.

  16. Signal processing of jet noise from flyover test data

    NASA Technical Reports Server (NTRS)

    Kelly, Jeffrey J.; Wilson, Mark R.

    1993-01-01

    Narrow-band spectra characterizing jet noise are constructed from flyover acoustic measurements. Radar and c-band tracking systems provided the aircraft position histories which enabled directivity and smear angles from the aircraft to each microphone to be computed. These angles are based on source emission time and thus give some idea about the directivity of the radiated sound field due to jet noise. Simulated spectra are included in the paper to demonstrate spectral broadening due to smear angle. The acoustic data described in the study has application to community noise analysis, noise source characterization and validation of prediction models. Both broadband-shock noise and turbulent mixing noise are observed in the spectra. A detailed description of the signal processing procedures is provided.

  17. 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.

  18. Neurological Tremor: Sensors, Signal Processing and Emerging Applications

    PubMed Central

    Grimaldi, Giuliana; Manto, Mario

    2010-01-01

    Neurological tremor is the most common movement disorder, affecting more than 4% of elderly people. Tremor is a non linear and non stationary phenomenon, which is increasingly recognized. The issue of selection of sensors is central in the characterization of tremor. This paper reviews the state-of-the-art instrumentation and methods of signal processing for tremor occurring in humans. We describe the advantages and disadvantages of the most commonly used sensors, as well as the emerging wearable sensors being developed to assess tremor instantaneously. We discuss the current limitations and the future applications such as the integration of tremor sensors in BCIs (brain-computer interfaces) and the need for sensor fusion approaches for wearable solutions. PMID:22205874

  19. Very large scale integration (VLSI) architectures for video signal processing

    NASA Astrophysics Data System (ADS)

    Pirsch, Peter; Gehrke, Winfried

    1995-04-01

    The paper presents an overview on architectures for VLSI implementations of video compression schemes as specified by standardization committees of the ITU and ISO, focussing on programmable architectures. Programmable video signal processors are classified and specified as homogeneous and heterogeneous processor architectures. Architectures are presented for reported design examples for the literature. Heterogenous processors outperform homogeneous processors because of adaptation to the requirements of special subtasks by dedicated modules. The majority of heterogenous processors incorporate dedicated modules for high performance subtasks of high regularity as DCT and block matching. By normalization to a fictive 1.0 micron CMOS process typical linear relationships between silicon area and through-put rate have been determined for the different architectural styles. This relationship indicated a figure of merit for silicon efficiency.

  20. Digital Signal Processing for the Event Horizon Telescope

    NASA Astrophysics Data System (ADS)

    Weintroub, Jonathan

    2015-08-01

    A broad international collaboration is building the Event Horizon Telescope (EHT). The aim is to test Einstein’s theory of General Relativity in one of the very few places it could break down: the strong gravity regime right at the edge of a black hole. The EHT is an earth-size VLBI array operating at the shortest radio wavelengths, that has achieved unprecedented angular resolution of a few tens of μarcseconds. For nearby super massive black holes (SMBH) this size scale is comparable to the Schwarzschild Radius, and emission in the immediate neighborhood of the event horizon can be directly observed. We give an introduction to the science behind the CASPER-enabled EHT, and outline technical developments, with emphasis on the secret sauce of high speed signal processing.

  1. Digital signal processing techniques for coherent optical communication

    NASA Astrophysics Data System (ADS)

    Goldfarb, Gilad

    Coherent detection with subsequent digital signal processing (DSP) is developed, analyzed theoretically and numerically and experimentally demonstrated in various fiber-optic transmission scenarios. The use of DSP in conjunction with coherent detection unleashes the benefits of coherent detection which rely on the preservaton of full information of the incoming field. These benefits include high receiver sensitivity, the ability to achieve high spectral-efficiency and the use of advanced modulation formats. With the immense advancements in DSP speeds, many of the problems hindering the use of coherent detection in optical transmission systems have been eliminated. Most notably, DSP alleviates the need for hardware phase-locking and polarization tracking, which can now be achieved in the digital domain. The complexity previously associated with coherent detection is hence significantly diminished and coherent detection is once gain considered a feasible detection alternative. In this thesis, several aspects of coherent detection (with or without subsequent DSP) are addressed. Coherent detection is presented as a means to extend the dispersion limit of a duobinary signal using an analog decision-directed phase-lock loop. Analytical bit-error ratio estimation for quadrature phase-shift keying signals is derived. To validate the promise for high spectral efficiency, the orthogonal-wavelength-division multiplexing scheme is suggested. In this scheme the WDM channels are spaced at the symbol rate, thus achieving the spectral efficiency limit. Theory, simulation and experimental results demonstrate the feasibility of this approach. Infinite impulse response filtering is shown to be an efficient alternative to finite impulse response filtering for chromatic dispersion compensation. Theory, design considerations, simulation and experimental results relating to this topic are presented. Interaction between fiber dispersion and nonlinearity remains the last major challenge

  2. Digital Signal Processing System for Active Noise Reduction

    NASA Astrophysics Data System (ADS)

    Edmonson, William W.; Tucker, Jerry

    2002-12-01

    different adaptive noise cancellation algorithms and provide an operational prototype to understand the behavior of the system under test. DSP software was required to interface the processor with the data converters using interrupt routines. The goal is to build a complete ANC system that can be placed on a flexible circuit with added memory circuitry that also contains the power supply, sensors and actuators. This work on the digital signal processing system for active noise reduction was completed in collaboration with another ASEE Fellow, Dr. Jerry Tucker from Virginia Commonwealth University, Richmond, VA.

  3. A nonlinear optoelectronic filter for electronic signal processing

    PubMed Central

    Loh, William; Yegnanarayanan, Siva; Ram, Rajeev J.; Juodawlkis, Paul W.

    2014-01-01

    The conversion of electrical signals into modulated optical waves and back into electrical signals provides the capacity for low-loss radio-frequency (RF) signal transfer over optical fiber. Here, we show that the unique properties of this microwave-photonic link also enable the manipulation of RF signals beyond what is possible in conventional systems. We achieve these capabilities by realizing a novel nonlinear filter, which acts to suppress a stronger RF signal in the presence of a weaker signal independent of their separation in frequency. Using this filter, we demonstrate a relative suppression of 56 dB for a stronger signal having a 1-GHz center frequency, uncovering the presence of otherwise undetectable weaker signals located as close as 3.5 Hz away. The capabilities of the optoelectronic filter break the conventional limits of signal detection, opening up new possibilities for radar and communication systems, and for the field of precision frequency metrology. PMID:24402418

  4. Signal processing using artificial neural network for BOTDA sensor system.

    PubMed

    Azad, Abul Kalam; Wang, Liang; Guo, Nan; Tam, Hwa-Yaw; Lu, Chao

    2016-03-21

    We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy. PMID:27136863

  5. 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.

  6. Attosecond metrology: from electron capture to future signal processing

    NASA Astrophysics Data System (ADS)

    Krausz, Ferenc; Stockman, Mark I.

    2014-03-01

    The accurate measurement of time lies at the heart of experimental science, and is relevant to everyday life. Extending chronoscopy to ever shorter timescales has been the key to gaining real-time insights into microscopic phenomena, ranging from vital biological processes to the dynamics underlying high technologies. The generation of isolated attosecond pulses in 2001 allowed the fastest of all motions outside the nucleus -- electron dynamics in atomic systems -- to be captured. Attosecond metrology has provided access to several hitherto immeasurably fast electron phenomena in atoms, molecules and solids. The fundamental importance of electron processes for the physical and life sciences, technology and medicine has rendered the young field of attosecond science one of the most dynamically expanding research fields of the new millennium. Here, we review the basic concepts underlying attosecond measurement and control techniques. Among their many potential applications, we focus on the exploration of the fundamental speed limit of electronic signal processing. This endeavour relies on ultimate-speed electron metrology, as provided by attosecond technology.

  7. Quantifying process heterogeneity: Signal propagation in hydrological systems

    NASA Astrophysics Data System (ADS)

    Lischeid, G.; Merz, C.; Schindler, U.; Schulz, R.; Steidl, J.; Tauschke, R.

    2009-04-01

    Natural hydrological systems are characterized by heterogeneous structures. The typical length scale of the relevant structures is smaller than the resolution of area-covering methods that are available at the catchment-scale. On the other hand these structures are too large to be treated as random effects and are often related to hydrological behaviour in a non-linear way. Consequently, model results, risk assessments etc. are prone to substantial uncertainties. This is often addressed by random realizations of the structures based on given probability density functions and geostatistical properties, and then analysing the resulting effects on hydrological behaviour, e.g., discharge or groundwater table fluctuations, using process-based models. In this study an alternative approach was followed. Hydrological systems usually act as low-pass filters: An input signal (precipitation, groundwater recharge, tracer application, etc.) is damped and delayed during its passage through the system. This study aimed at characterizing the damping behaviour in a quantitative way. Large perturbations usually are transmitted at much higher velocities compared to small perturbations, thus hindering a spectrum analysis based approach. Instead, time series of soil water content, groundwater level and catchment runoff from the Uckermark region in North Germany were analysed using a principal component analysis. In all cases, the first component depicted the mean behaviour, and the second component explained a large fraction of the deviations from the mean behaviour. The loadings of the first two components could be used as an index of the mean damping behaviour for the given time period. Results of the soil water content data showed a linear increase of damping with depth at most sites. However, different sites differed substantially even for backfilled lysimeters that were considered to be homogeneous. There was no clear relationship between clay content and damping behaviour. The

  8. From Bursts to Back-Projection: Signal Processing Techniques for Earth and Planetary Observing Radars

    NASA Technical Reports Server (NTRS)

    Rosen, Paul A.

    2012-01-01

    Discusses: (1) JPL Radar Overview and Historical Perspective (2) Signal Processing Needs in Earth and Planetary Radars (3) Examples of Current Systems and techniques (4) Future Perspectives in signal processing for radar missions

  9. Special Issue on Signal Processing for Mechanical Systems in Honor of Professor Simon Braun

    NASA Astrophysics Data System (ADS)

    Fassois, Spilios D.

    2016-06-01

    This Special Issue is in honor of a pioneer of the area of Signal Processing for Mechanical Systems and, at the same time, Founding Editor of the Journal of Mechanical Systems and Signal Processing (MSSP), Professor Simon Braun.

  10. Fabrication of low-cost beta-type Ti-Mn alloys for biomedical applications by metal injection molding process and their mechanical properties.

    PubMed

    Santos, Pedro Fernandes; Niinomi, Mitsuo; Liu, Huihong; Cho, Ken; Nakai, Masaaki; Itoh, Yoshinori; Narushima, Takayuki; Ikeda, Masahiko

    2016-06-01

    Titanium and its alloys are suitable for biomedical applications owing to their good mechanical properties and biocompatibility. Beta-type Ti-Mn alloys (8-17 mass% Mn) were fabricated by metal injection molding (MIM) as a potential low cost material for use in biomedical applications. The microstructures and mechanical properties of the alloys were evaluated. For up to 13 mass% Mn, the tensile strength (1162-938MPa) and hardness (308-294HV) of the MIM fabricated alloys are comparable to those of Ti-Mn alloys fabricated by cold crucible levitation melting. Ti-9Mn exhibits the best balance of ultimate tensile strength (1046MPa) and elongation (4.7%) among the tested alloys, and has a Young's modulus of 89GPa. The observed low elongation of the alloys is attributed to the combined effects of high oxygen content, with the presence of interconnected pores and titanium carbides, the formation of which is due to carbon pickup during the debinding process. The elongation and tensile strength of the alloys decrease with increasing Mn content. The Ti-Mn alloys show good compressive properties, with Ti-17Mn showing a compressive 0.2% proof stress of 1034MPa, and a compressive strain of 50%. PMID:26999621

  11. The evaluation of vacuum venting and variotherm process for improving the replication by injection molding of high aspect ratio micro features for biomedical application

    NASA Astrophysics Data System (ADS)

    Sorgato, Marco; Lucchetta, Giovanni

    2015-05-01

    The aspect ratio achievable in replicating micro features is one of the most important process characteristics and it is a major manufacturing constraint in applying injection molding in a range of micro engineering applications. Vacuum venting has been reported to be an effective technique in replicating micro features by microinjection molding. High surface-to-volume ratio and reduced dimensions of micro parts promote the instantaneous drop of melt temperature and consequently lead to incomplete filling. This study aims to investigate the effects of variotherm process, cavity evacuation and their interaction on the production of a micro fluidic filter for biomedical applications. A low-viscosity polystyrene and a cyclic olefin copolymer were molded applying a combination of mold evacuation and a rapid mold temperature variation that keeps the cavity temperature above the glass transition temperature during the injection phase. The research revealed the importance of these molding technologies in enhancing part filling and the replication quality for high aspect ratio micro features.

  12. An information processing method for acoustic emission signal inspired from musical staff

    NASA Astrophysics Data System (ADS)

    Zheng, Wei; Wu, Chunxian

    2016-01-01

    This study proposes a musical-staff-inspired signal processing method for standard description expressions for discrete signals and describing the integrated characteristics of acoustic emission (AE) signals. The method maps various AE signals with complex environments into the normalized musical space. Four new indexes are proposed to comprehensively describe the signal. Several key features, such as contour, amplitude, and signal changing rate, are quantitatively expressed in a normalized musical space. The processed information requires only a small storage space to maintain high fidelity. The method is illustrated by using experiments on sandstones and computed tomography (CT) scanning to determine its validity for AE signal processing.

  13. Optical hybrid analog-digital signal processing based on spike processing in neurons

    NASA Astrophysics Data System (ADS)

    Fok, Mable P.; Tian, Yue; Rosenbluth, David; Deng, Yanhua; Prucnal, Paul R.

    2011-09-01

    Spike processing is one kind of hybrid analog-digital signal processing, which has the efficiency of analog processing and the robustness to noise of digital processing. When instantiated with optics, a hybrid analog-digital processing primitive has the potential to be scalable, computationally powerful, and have high operation bandwidth. These devices open up a range of processing applications for which electronic processing is too slow. Our approach is based on a hybrid analog/digital computational primitive that elegantly implements the functionality of an integrate-and-fire neuron using a Ge-doped non-linear optical fiber and off-the-shelf semiconductor devices. In this paper, we introduce our photonic neuron architecture and demonstrate the feasibility of implementing simple photonic neuromorphic circuits, including the auditory localization algorithm of the barn owl, which is useful for LIDAR localization, and the crayfish tail-flip escape response.

  14. Differential auditory signal processing in an animal model

    NASA Astrophysics Data System (ADS)

    Lim, Dukhwan; Kim, Chongsun; Chang, Sun O.

    2002-05-01

    Auditory evoked responses were collected in male zebra finches (Poephila guttata) to objectively determine differential frequency selectivity. First, the mating call of the animal was recorded and analyzed for its frequency components through the customized program. Then, auditory brainstem responses and cortical responses of each anesthetized animal were routinely recorded in response to tone bursts of 1-8 kHz derived from the corresponding mating call spectrum. From the results, most mating calls showed relatively consistent spectral structures. The upper limit of the spectrum was well under 10 kHz. The peak energy bands were concentrated in the region less than 5 kHz. The assessment of auditory brainstem responses and cortical evoked potentials showed differential selectivity with a series of characteristic scales. This system appears to be an excellent model to investigate complex sound processing and related language behaviors. These data could also be used in designing effective signal processing strategies in auditory rehabilitation devices such as hearing aids and cochlear implants. [Work supported by Brain Science & Engineering Program from Korean Ministry of Science and Technology.

  15. Optimal Signal Processing of Frequency-Stepped CW Radar Data

    NASA Technical Reports Server (NTRS)

    Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

    1995-01-01

    An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-851O network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

  16. Optimal Signal Processing of Frequency-Stepped CW Radar Data

    NASA Technical Reports Server (NTRS)

    Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

    1995-01-01

    An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the first two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-X510 network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

  17. Clay content evaluation in soils through GPR signal processing

    NASA Astrophysics Data System (ADS)

    Tosti, Fabio; Patriarca, Claudio; Slob, Evert; Benedetto, Andrea; Lambot, Sébastien

    2013-10-01

    The mechanical behavior of soils is partly affected by their clay content, which arises some important issues in many fields of employment, such as civil and environmental engineering, geology, and agriculture. This work focuses on pavement engineering, although the method applies to other fields of interest. Clay content in bearing courses of road pavement frequently causes damages and defects (e.g., cracks, deformations, and ruts). Therefore, the road safety and operability decreases, directly affecting the increase of expected accidents. In this study, different ground-penetrating radar (GPR) methods and techniques were used to non-destructively investigate the clay content in sub-asphalt compacted soils. Experimental layout provided the use of typical road materials, employed for road bearing courses construction. Three types of soils classified by the American Association of State Highway and Transportation Officials (AASHTO) as A1, A2, and A3 were used and adequately compacted in electrically and hydraulically isolated test boxes. Percentages of bentonite clay were gradually added, ranging from 2% to 25% by weight. Analyses were carried out for each clay content using two different GPR instruments. A pulse radar with ground-coupled antennae at 500 MHz centre frequency and a vector network analyzer spanning the 1-3 GHz frequency range were used. Signals were processed in both time and frequency domains, and the consistency of results was validated by the Rayleigh scattering method, the full-waveform inversion, and the signal picking techniques. Promising results were obtained for the detection of clay content affecting the bearing capacity of sub-asphalt layers.

  18. Neural Signaling of Food Healthiness Associated with Emotion Processing.

    PubMed

    Herwig, Uwe; Dhum, Matthias; Hittmeyer, Anna; Opialla, Sarah; Scherpiet, Sigrid; Keller, Carmen; Brühl, Annette B; Siegrist, Michael

    2016-01-01

    The ability to differentiate healthy from unhealthy foods is important in order to promote good health. Food, however, may have an emotional connotation, which could be inversely related to healthiness. The neurobiological background of differentiating healthy and unhealthy food and its relations to emotion processing are not yet well understood. We addressed the neural activations, particularly considering the single subject level, when one evaluates a food item to be of a higher, compared to a lower grade of healthiness with a particular view on emotion processing brain regions. Thirty-seven healthy subjects underwent functional magnetic resonance imaging while evaluating the healthiness of food presented as photographs with a subsequent rating on a visual analog scale. We compared individual evaluations of high and low healthiness of food items and also considered gender differences. We found increased activation when food was evaluated to be healthy in the left dorsolateral prefrontal cortex and precuneus in whole brain analyses. In ROI analyses, perceived and rated higher healthiness was associated with lower amygdala activity and higher ventral striatal and orbitofrontal cortex activity. Females exerted a higher activation in midbrain areas when rating food items as being healthy. Our results underline the close relationship between food and emotion processing, which makes sense considering evolutionary aspects. Actively evaluating and deciding whether food is healthy is accompanied by neural signaling associated with reward and self-relevance, which could promote salutary nutrition behavior. The involved brain regions may be amenable to mechanisms of emotion regulation in the context of psychotherapeutic regulation of food intake. PMID:26903859

  19. Neural Signaling of Food Healthiness Associated with Emotion Processing

    PubMed Central

    Herwig, Uwe; Dhum, Matthias; Hittmeyer, Anna; Opialla, Sarah; Scherpiet, Sigrid; Keller, Carmen; Brühl, Annette B.; Siegrist, Michael

    2016-01-01

    The ability to differentiate healthy from unhealthy foods is important in order to promote good health. Food, however, may have an emotional connotation, which could be inversely related to healthiness. The neurobiological background of differentiating healthy and unhealthy food and its relations to emotion processing are not yet well understood. We addressed the neural activations, particularly considering the single subject level, when one evaluates a food item to be of a higher, compared to a lower grade of healthiness with a particular view on emotion processing brain regions. Thirty-seven healthy subjects underwent functional magnetic resonance imaging while evaluating the healthiness of food presented as photographs with a subsequent rating on a visual analog scale. We compared individual evaluations of high and low healthiness of food items and also considered gender differences. We found increased activation when food was evaluated to be healthy in the left dorsolateral prefrontal cortex and precuneus in whole brain analyses. In ROI analyses, perceived and rated higher healthiness was associated with lower amygdala activity and higher ventral striatal and orbitofrontal cortex activity. Females exerted a higher activation in midbrain areas when rating food items as being healthy. Our results underline the close relationship between food and emotion processing, which makes sense considering evolutionary aspects. Actively evaluating and deciding whether food is healthy is accompanied by neural signaling associated with reward and self-relevance, which could promote salutary nutrition behavior. The involved brain regions may be amenable to mechanisms of emotion regulation in the context of psychotherapeutic regulation of food intake. PMID:26903859

  20. Chatter, process damping, and chip segmentation in turning: A signal processing approach

    NASA Astrophysics Data System (ADS)

    Taylor, Christopher M.; Turner, Sam; Sims, Neil D.

    2010-11-01

    An increasing number of aerospace components are manufactured from titanium and nickel alloys that are difficult to machine due to their thermal and mechanical properties. This limits the metal removal rates that can be achieved from the production process. However, under these machining conditions the phenomenon of process damping can be exploited to help avoid self-excited vibrations known as regenerative chatter. This means that greater widths of cut can be taken so as to increase the metal removal rate, and hence offset the cutting speed restrictions that are imposed by the thermo-mechanical properties of the material. However, there is little or no consensus as to the underlying mechanisms that cause process damping. The present study investigates two process damping mechanisms that have previously been proposed in the machining literature: the tool flank/workpiece interference effect, and the short regenerative effect. A signal processing procedure is employed to identify flank/workpiece interference from experimental data. Meanwhile, the short regenerative model is solved using a new frequency domain approach that yields additional insight into its stabilising effect. However, analysis and signal processing of the experimentally obtained data reveals that neither of these models can fully explain the increases in stability that are observed in practice. Meanwhile, chip segmentation effects were observed in a number of measurements, and it is suggested that segmentation could play an important role in the process-damped chatter stability of these materials.

  1. Integrated Optics for Planar imaging and Optical Signal Processing

    NASA Astrophysics Data System (ADS)

    Song, Qi

    Silicon photonics is a subject of growing interest with the potential of delivering planar electro-optical devices with chip scale integration. Silicon-on-insulator (SOI) technology has provided a marvelous platform for photonics industry because of its advantages in integration capability in CMOS circuit and countless nonlinearity applications in optical signal processing. This thesis is focused on the investigation of planar imaging techniques on SOI platform and potential applications in ultra-fast optical signal processing. In the first part, a general review and background introduction about integrated photonics circuit and planar imaging technique are provided. In chapter 2, planar imaging platform is realized by a silicon photodiode on SOI chip. Silicon photodiode on waveguide provides a high numerical aperture for an imaging transceiver pixel. An erbium doped Y2O3 particle is excited by 1550nm Laser and the fluorescent image is obtained with assistance of the scanning system. Fluorescence image is reconstructed by using image de-convolution technique. Under photovoltaic mode, we use an on-chip photodiode and an external PIN photodiode to realize similar resolution as 5μm. In chapter 3, a time stretching technique is developed to a spatial domain to realize a 2D imaging system as an ultrafast imaging tool. The system is evaluated based on theoretical calculation. The experimental results are shown for a verification of system capability to imaging a micron size particle or a finger print. Meanwhile, dynamic information for a moving object is also achieved by correlation algorithm. In chapter 4, the optical leaky wave antenna based on SOI waveguide has been utilized for imaging applications and extensive numerical studied has been conducted. and the theoretical explanation is supported by leaky wave theory. The highly directive radiation has been obtained from the broadside with 15.7 dB directivity and a 3dB beam width of ΔØ 3dB ≈ 1.65° in free space

  2. Hardware System for Real-Time EMG Signal Acquisition and Separation Processing during Electrical Stimulation.

    PubMed

    Hsueh, Ya-Hsin; Yin, Chieh; Chen, Yan-Hong

    2015-09-01

    The study aimed to develop a real-time electromyography (EMG) signal acquiring and processing device that can acquire signal during electrical stimulation. Since electrical stimulation output can affect EMG signal acquisition, to integrate the two elements into one system, EMG signal transmitting and processing method has to be modified. The whole system was designed in a user-friendly and flexible manner. For EMG signal processing, the system applied Altera Field Programmable Gate Array (FPGA) as the core to instantly process real-time hybrid EMG signal and output the isolated signal in a highly efficient way. The system used the power spectral density to evaluate the accuracy of signal processing, and the cross correlation showed that the delay of real-time processing was only 250 μs. PMID:26210898

  3. Medial nucleus tractus solitarius oxytocin receptor signaling and food intake control: the role of gastrointestinal satiation signal processing.

    PubMed

    Ong, Zhi Yi; Alhadeff, Amber L; Grill, Harvey J

    2015-05-01

    Central oxytocin (OT) administration reduces food intake and its effects are mediated, in part, by hindbrain oxytocin receptor (OT-R) signaling. The neural substrate and mechanisms mediating the intake inhibitory effects of hindbrain OT-R signaling are undefined. We examined the hypothesis that hindbrain OT-R-mediated feeding inhibition results from an interaction between medial nucleus tractus solitarius (mNTS) OT-R signaling and the processing of gastrointestinal (GI) satiation signals by neurons of the mNTS. Here, we demonstrated that mNTS or fourth ventricle (4V) microinjections of OT in rats reduced chow intake in a dose-dependent manner. To examine whether the intake suppressive effects of mNTS OT-R signaling is mediated by GI signal processing, rats were injected with OT to the 4V (1 μg) or mNTS (0.3 μg), followed by self-ingestion of a nutrient preload, where either treatment was designed to be without effect on chow intake. Results showed that the combination of mNTS OT-R signaling and GI signaling processing by preload ingestion reduced chow intake significantly and to a greater extent than either stimulus alone. Using enzyme immunoassay, endogenous OT content in mNTS-enriched dorsal vagal complex (DVC) in response to ingestion of nutrient preload was measured. Results revealed that preload ingestion significantly elevated endogenous DVC OT content. Taken together, these findings provide evidence that mNTS neurons are a site of action for hindbrain OT-R signaling in food intake control and that the intake inhibitory effects of hindbrain mNTS OT-R signaling are mediated by interactions with GI satiation signal processing by mNTS neurons. PMID:25740340

  4. Medial nucleus tractus solitarius oxytocin receptor signaling and food intake control: the role of gastrointestinal satiation signal processing

    PubMed Central

    Alhadeff, Amber L.; Grill, Harvey J.

    2015-01-01

    Central oxytocin (OT) administration reduces food intake and its effects are mediated, in part, by hindbrain oxytocin receptor (OT-R) signaling. The neural substrate and mechanisms mediating the intake inhibitory effects of hindbrain OT-R signaling are undefined. We examined the hypothesis that hindbrain OT-R-mediated feeding inhibition results from an interaction between medial nucleus tractus solitarius (mNTS) OT-R signaling and the processing of gastrointestinal (GI) satiation signals by neurons of the mNTS. Here, we demonstrated that mNTS or fourth ventricle (4V) microinjections of OT in rats reduced chow intake in a dose-dependent manner. To examine whether the intake suppressive effects of mNTS OT-R signaling is mediated by GI signal processing, rats were injected with OT to the 4V (1 μg) or mNTS (0.3 μg), followed by self-ingestion of a nutrient preload, where either treatment was designed to be without effect on chow intake. Results showed that the combination of mNTS OT-R signaling and GI signaling processing by preload ingestion reduced chow intake significantly and to a greater extent than either stimulus alone. Using enzyme immunoassay, endogenous OT content in mNTS-enriched dorsal vagal complex (DVC) in response to ingestion of nutrient preload was measured. Results revealed that preload ingestion significantly elevated endogenous DVC OT content. Taken together, these findings provide evidence that mNTS neurons are a site of action for hindbrain OT-R signaling in food intake control and that the intake inhibitory effects of hindbrain mNTS OT-R signaling are mediated by interactions with GI satiation signal processing by mNTS neurons. PMID:25740340

  5. Playback of beyond high definition video signal in holographic data storage system with wavefront compensation and parallel signal processing

    NASA Astrophysics Data System (ADS)

    Muroi, Tetsuhiko; Kinoshita, Nobuhiro; Ishii, Norihiko; Kamijo, Koji; Kikuchi, Hiroshi

    2014-09-01

    We have developed a holographic data storage system that can demonstrate real-time playback of beyond high definition video signals. In the proposed system, to increase the data-transfer rate of the reproduced data, we focused on improving the SNR of the reproduced data and on improving the signal processing speed, which the SNR of the reproduced data has a significant effect on. One of the factors that deteriorate the SNR is shrinkage in the medium. This shrinkage distorts recorded holograms and degrades the quality of the reproduced data. We investigated wavefront compensation as a means to improve the SNR of reproduced data degraded by hologram distortion and found that controlling the defocus component of the reference beam is effective. We have also been developing parallel signal processing to increase the data-transfer rate. We placed three GPUs in the signal processing unit: one for the reproduced data detection from the reconstructed image and two for the LDPC decoding for error correction of the reproduced data. The LDPC decoding required a lot more time than the data detection, so we designed a signal processing in which detected data in the GPU for the data detection were sent to the two GPUs for the LDPC decoding alternatively. We implemented wavefront compensation for the defocus component and developed parallel signal processing with three GPUs for our holographic data storage system. Using this system, we demonstrated real-time playback of beyond high definition video signals with 50 Mbps.

  6. Programmable rate modem utilizing digital signal processing techniques

    NASA Technical Reports Server (NTRS)

    Bunya, George K.; Wallace, Robert L.

    1989-01-01

    The engineering development study to follow was written to address the need for a Programmable Rate Digital Satellite Modem capable of supporting both burst and continuous transmission modes with either binary phase shift keying (BPSK) or quadrature phase shift keying (QPSK) modulation. The preferred implementation technique is an all digital one which utilizes as much digital signal processing (DSP) as possible. Here design tradeoffs in each portion of the modulator and demodulator subsystem are outlined, and viable circuit approaches which are easily repeatable, have low implementation losses and have low production costs are identified. The research involved for this study was divided into nine technical papers, each addressing a significant region of concern in a variable rate modem design. Trivial portions and basic support logic designs surrounding the nine major modem blocks were omitted. In brief, the nine topic areas were: (1) Transmit Data Filtering; (2) Transmit Clock Generation; (3) Carrier Synthesizer; (4) Receive AGC; (5) Receive Data Filtering; (6) RF Oscillator Phase Noise; (7) Receive Carrier Selectivity; (8) Carrier Recovery; and (9) Timing Recovery.

  7. Signal Processing for a Lunar Array: Minimizing Power Consumption

    NASA Technical Reports Server (NTRS)

    D'Addario, Larry; Simmons, Samuel

    2011-01-01

    Motivation for the study is: (1) Lunar Radio Array for low frequency, high redshift Dark Ages/Epoch of Reionization observations (z =6-50, f=30-200 MHz) (2) High precision cosmological measurements of 21 cm H I line fluctuations (3) Probe universe before first star formation and provide information about the Intergalactic Medium and evolution of large scale structures (5) Does the current cosmological model accurately describe the Universe before reionization? Lunar Radio Array is for (1) Radio interferometer based on the far side of the moon (1a) Necessary for precision measurements, (1b) Shielding from earth-based and solar RFI (12) No permanent ionosphere, (2) Minimum collecting area of approximately 1 square km and brightness sensitivity 10 mK (3)Several technologies must be developed before deployment The power needed to process signals from a large array of nonsteerable elements is not prohibitive, even for the Moon, and even in current technology. Two different concepts have been proposed: (1) Dark Ages Radio Interferometer (DALI) (2)( Lunar Array for Radio Cosmology (LARC)

  8. Integrated waveguide Bragg gratings for microwave photonics signal processing.

    PubMed

    Burla, Maurizio; Cortés, Luis Romero; Li, Ming; Wang, Xu; Chrostowski, Lukas; Azaña, José

    2013-10-21

    Integrated Microwave photonics (IMWP) signal processing using Photonic Integrated Circuits (PICs) has attracted a great deal of attention in recent years as an enabling technology for a number of functionalities not attainable by purely microwave solutions. In this context, integrated waveguide Bragg grating (WBG) devices constitute a particularly attractive approach thanks to their compactness and flexibility in producing arbitrarily defined amplitude and phase responses, by directly acting on coupling coefficient and perturbations of the grating profile. In this article, we review recent advances in the field of integrated WBGs applied to MWP, analyzing the advantages leveraged by an integrated realization. We provide a perspective on the exciting possibilities offered by the silicon photonics platform in the field of MWP, potentially enabling integration of highly-complex active and passive functionalities with high yield on a single chip, with a particular focus on the use of WBGs as basic building blocks for linear filtering operations. We demonstrate the versatility of WBG-based devices by proposing and experimentally demonstrating a novel, continuously-tunable, integrated true-time-delay (TTD) line based on a very simple dual phase-shifted WBG (DPS-WBG). PMID:24150355

  9. Cryogenic loss monitors with FPGA TDC signal processing

    SciTech Connect

    Warner, A.; Wu, J.; /Fermilab

    2011-09-01

    Radiation hard helium gas ionization chambers capable of operating in vacuum at temperatures ranging from 5K to 350K have been designed, fabricated and tested and will be used inside the cryostats at Fermilab's Superconducting Radiofrequency beam test facility. The chamber vessels are made of stainless steel and all materials used including seals are known to be radiation hard and suitable for operation at 5K. The chambers are designed to measure radiation up to 30 kRad/hr with sensitivity of approximately 1.9 pA/(Rad/hr). The signal current is measured with a recycling integrator current-to-frequency converter to achieve a required measurement capability for low current and a wide dynamic range. A novel scheme of using an FPGA-based time-to-digital converter (TDC) to measure time intervals between pulses output from the recycling integrator is employed to ensure a fast beam loss response along with a current measurement resolution better than 10-bit. This paper will describe the results obtained and highlight the processing techniques used.

  10. KATP channels process nucleotide signals in muscle thermogenic response

    PubMed Central

    Reyes, Santiago; Park, Sungjo; Terzic, Andre; Alekseev, Alexey E.

    2014-01-01

    Uniquely gated by intracellular adenine nucleotides, sarcolemmal ATP-sensitive K+ (KATP) channels have been typically assigned to protective cellular responses under severe energy insults. More recently, KATP channels have been instituted in the continuous control of muscle energy expenditure under non-stressed, physiological states. These advances raised the question of how KATP channels can process trends in cellular energetics within a milieu where each metabolic system is set to buffer nucleotide pools. Unveiling the mechanistic basis of the KATP channel-driven thermogenic response in muscles thus invites the concepts of intracellular compartmentalization of energy and proteins, along with nucleotide signaling over diffusion barriers. Furthermore, it requires gaining insight into the properties of reversibility of intrinsic ATPase activity associated with KATP channel complexes. Notwithstanding the operational paradigm, the homeostatic role of sarcolemmal KATP channels can be now broadened to a wider range of environmental cues affecting metabolic well-being. In this way, under conditions of energy deficit such as ischemic insult or adrenergic stress, the operation of KATP channel complexes would result in protective energy saving, safeguarding muscle performance and integrity. Under energy surplus, downregulation of KATP channel function may find potential implications in conditions of energy imbalance linked to obesity, cold intolerance and associated metabolic disorders. PMID:20925594

  11. Protein import into plant mitochondria: signals, machinery, processing, and regulation.

    PubMed

    Murcha, Monika W; Kmiec, Beata; Kubiszewski-Jakubiak, Szymon; Teixeira, Pedro F; Glaser, Elzbieta; Whelan, James

    2014-12-01

    The majority of more than 1000 proteins present in mitochondria are imported from nuclear-encoded, cytosolically synthesized precursor proteins. This impressive feat of transport and sorting is achieved by the combined action of targeting signals on mitochondrial proteins and the mitochondrial protein import apparatus. The mitochondrial protein import apparatus is composed of a number of multi-subunit protein complexes that recognize, translocate, and assemble mitochondrial proteins into functional complexes. While the core subunits involved in mitochondrial protein import are well conserved across wide phylogenetic gaps, the accessory subunits of these complexes differ in identity and/or function when plants are compared with Saccharomyces cerevisiae (yeast), the model system for mitochondrial protein import. These differences include distinct protein import receptors in plants, different mechanistic operation of the intermembrane protein import system, the location and activity of peptidases, the function of inner-membrane translocases in linking the outer and inner membrane, and the association/regulation of mitochondrial protein import complexes with components of the respiratory chain. Additionally, plant mitochondria share proteins with plastids, i.e. dual-targeted proteins. Also, the developmental and cell-specific nature of mitochondrial biogenesis is an aspect not observed in single-celled systems that is readily apparent in studies in plants. This means that plants provide a valuable model system to study the various regulatory processes associated with protein import and mitochondrial biogenesis. PMID:25324401

  12. Signal processing algorithms for staring single pixel hyperspectral sensors

    NASA Astrophysics Data System (ADS)

    Manolakis, Dimitris; Rossacci, Michael; O'Donnell, Erin; D'Amico, Francis M.

    2006-08-01

    Remote sensing of chemical warfare agents (CWA) with stand-off hyperspectral sensors has a wide range of civilian and military applications. These sensors exploit the spectral changes in the ambient photon flux produced thermal emission or absorption after passage through a region containing the CWA cloud. In this work we focus on (a) staring single-pixel sensors that sample their field of view at regular intervals of time to produce a time series of spectra and (b) scanning single or multiple pixel sensors that sample their FOV as they scan. The main objective of signal processing algorithms is to determine if and when a CWA enters the FOV of the sensor. We shall first develop and evaluate algorithms for staring sensors following two different approaches. First, we will assume that no threat information is available and we design an adaptive anomaly detection algorithm to detect a statistically-significant change in the observed spectrum. The algorithm processes the observed spectra sequentially-in-time, estimates adaptively the background, and checks whether the next spectrum differs significantly from the background based on the Mahalanobis distance or the distance from the background subspace. In the second approach, we will assume that we know the spectral signature of the CWA and develop sequential-in-time adaptive matched filter detectors. In both cases, we assume that the sensor starts its operation before the release of the CWA; otherwise, staring at a nearby CWA-free area is required for background estimation. Experimental evaluation and comparison of the proposed algorithms is accomplished using data from a long-wave infrared (LWIR) Fourier transform spectrometer.

  13. 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

  14. 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

  15. Signal Processor Development by Personnel of the JSC Signal Processing Section

    NASA Technical Reports Server (NTRS)

    Holland, S. Douglas

    1994-01-01

    The purpose of this paper is to describe systems and components of systems developed by personnel in the Signal Processing Section of the Tracking and Communications Division. The scope of this includes past developments which are in current use in NASA flight operations and future developments which are targeted for upcoming NASA applications. These projects specifically are: (1) NASA High Definition Television (HDTV) Project, (2) Video Codecs, (3) NASA Electronic Still Camera (ESC) Project, (4) Hercules Payload, (5) Ku-band Communications Adapter (KCA), (6) Windows Drivers for Satellite Interfacing to Commercial Equipment, and (7) Advanced Statistical Multiplexers. The methods used to determine what projects should be done in-house as opposed to which should not is based in NASA applications versus commercially available systems to meet those applications. If a commercial-off-the-shelf (COTS) component or system is available which meets the need, the first choice is to use COTS equipment. If it is not, and there is a NASA requirement, it is developed in-house. This results in technology which is being developed which otherwise was not available. Personnel involved in these projects have been contacted by many commercial companies interested in licensing or obtaining the NASA design.

  16. Digital Signal Processing Techniques for the GIFTS SM EDU

    NASA Technical Reports Server (NTRS)

    Tian, Jialin; Reisse, Robert A.; Gazarik, Michael J.

    2007-01-01

    The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiance using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three Focal Plane Arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes several digital signal processing (DSP) techniques involved in the development of the calibration model. In the first stage, the measured raw interferograms must undergo a series of processing steps that include filtering, decimation, and detector nonlinearity correction. The digital filtering is achieved by employing a linear-phase even-length FIR complex filter that is designed based on the optimum equiripple criteria. Next, the detector nonlinearity effect is compensated for using a set of pre-determined detector response characteristics. In the next stage, a phase correction algorithm is applied to the decimated interferograms. This is accomplished by first estimating the phase function from the spectral phase response of the windowed interferogram, and then correcting the entire interferogram based on the estimated phase function. In the calibration stage, we first compute the spectral responsivity based on the previous results and the ideal Planck blackbody spectra at the given temperatures, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. In the post-calibration stage, we estimate the Noise Equivalent Spectral Radiance (NESR) from the calibrated ABB and HBB spectra. The NESR is generally considered as a measure of the instrument noise performance, and can be estimated as

  17. Multivariate classification of animal communication signals: a simulation-based comparison of alternative signal processing procedures using electric fishes.

    PubMed

    Crampton, William G R; Davis, Justin K; Lovejoy, Nathan R; Pensky, Marianna

    2008-01-01

    Evolutionary studies of communication can benefit from classification procedures that allow individual animals to be assigned to groups (e.g. species) on the basis of high-dimension data representing their signals. Prior to classification, signals are usually transformed by a signal processing procedure into structural features. Applications of these signal processing procedures to animal communication have been largely restricted to the manual or semi-automated identification of landmark features from graphical representations of signals. Nonetheless, theory predicts that automated time-frequency-based digital signal processing (DSP) procedures can represent signals more efficiently (using fewer features) than can landmark procedures or frequency-based DSP - allowing more accurate classification. Moreover, DSP procedures are objective in that they require little previous knowledge of signal diversity, and are relatively free from potentially ungrounded assumptions of cross-taxon homology. Using a model data set of electric organ discharge waveforms from five sympatric species of the electric fish Gymnotus, we adopted an exhaustive simulation approach to investigate the classificatory performance of different signal processing procedures. We considered a landmark procedure, a frequency-based DSP procedure (the fast Fourier transform), and two kinds of time-frequency-based DSP procedures (a short-time Fourier transform, and several implementations of the discrete wavelet transform -DWT). The features derived from each of these signal processing procedures were then subjected to dimension reduction procedures to separate those features which permit the most effective discrimination among groups of signalers. We considered four alternative dimension reduction methods. Finally, each combination of reduced data was submitted to classification by linear discriminant analysis. Our results support theoretical predictions that time-frequency DSP procedures (especially DWT

  18. Processing of the Liquid Xenon calorimeter's signals for timing measurements

    NASA Astrophysics Data System (ADS)

    Epshteyn, L. B.; Yudin, Yu V.

    2014-09-01

    One of the goals of the Cryogenic Magnetic Detector at Budker Institute of Nuclear Physics SB RAS (Novosibirsk, Russia) is a study of nucleons production in electron-positron collisions near threshold. The neutron-antineutron pair production events can be detected only by the calorimeters. In the barrel calorimeter the antineutron annihilation typically occurs by 5 ns or later after beams crossing. For identification of such events it is necessary to measure the time of flight of particles to the LXe-calorimeter with accuracy of about 3 ns. The LXe-calorimeter consists of 14 layers of ionization chambers with anode and cathode readout. The duration of charge collection to the anodes is about 4.5 mks, while the required accuracy of measuring of the signal arrival time is less than 1/1000 of that. Besides, the signals' shapes differ substantially from event to event, so the signal arrival time is measured in two stages. At the first stage, the signal arrival time is determined with an accuracy of 1-2 discretization periods, and initial values of parameters for subsequent fitting procedure are calculated. At the second stage, the signal arrival time is determined with the required accuracy by means of fitting of the signal waveform with a template waveform. To implement that, a special electronics has been developed which performs waveform digitization and On-Line measurement of signals' arrival times and amplitudes.

  19. Design and programming of systolic array cells for signal processing

    SciTech Connect

    Smith, R.A.W.

    1989-01-01

    This thesis presents a new methodology for the design, simulation, and programming of systolic arrays in which the algorithms and architecture are simultaneously optimized. The algorithms determine the initial architecture, and simulation is used to optimize the architecture. The simulator provides a register-transfer level model of a complete systolic array computation. To establish the validity of this design methodology two novel programmable systolic array cells were designed and programmed. The cells were targeted for applications in high-speed signal processing and associated matrix computations. A two-chip programmable systolic array cell using a 16-bit multiplier-accumulator chip and a semi-custom VLSI controller chip was designed and fabricated. A low chip count allows large arrays to be constructed, but the cell is flexible enough to be a building-block for either one- or two-dimensional systolic arrays. Another more flexible and powerful cell using a 32-bit floating-point processor and a second VLSI controller chip was also designed. It contains several architectural features that are unique in a systolic array cell: (1) each instruction is 32 bits, yet all resources can be updated every cycle, (2) two on-chip interchangeable memories are used, and (3) one input port can be used as either a global or local port. The key issues involved in programming the cells are analyzed in detail. A set of modules is developed which can be used to construct large programs in an effective manner. The utility of this programming approach is demonstrated with several important examples.

  20. Diffraction tomographic signal processing algorithms for tunnel detection

    SciTech Connect

    Witten, A.J.

    1993-08-01

    Signal processing algorithms have been developed for wave based imaging using diffraction tomography. The basis for this image reconstruction procedure is the generalized projection slice theorem (GPST) which, for homogeneous waves, is an analytic relationship between the spatial Fourier transform of the acquired data and the spatial Fourier transform of the spatial profile (object function) of the object being imaged. Imaging within geophysical diffraction tomography when only homogeneous waves are considered can then be accomplished by inversion of the GPST using standard numerical techniques. In an attenuating background medium or when eddy currents or static fields are considered, a generalized GPST can be derived that involves both real and complex spatial frequencies. In this case, direct Fourier inversion is not possible because of the presence of the complex frequencies. Although direct inversion and, hence, complete imaging is not possible for such cases, the generalized CPST`S can be used to analytically shift the location of data templates matched to specified targets and these templates can, in turn, be correlated with acquired data to detect and estimate the location of the specified targets. Since GPST`s are used directly in the detection problem, there is no need to numerically invert the intergal transform of the object function. For this reason, target detection can be accomplished in a computationally efficient manner independent of the type of measurement or background geologic conditions. A number of GPST`s are derived and the use of GPST`s for both imaging and detection of subsurface voids is demonstrated in several recent applications.

  1. Auxiliary signal processing system for a multiparameter radar

    NASA Technical Reports Server (NTRS)

    Chandrasekar, V.; Gray, G. R.; Caylor, I. J.

    1993-01-01

    The design of an auxiliary signal processor for a multiparameter radar is described with emphasis on low cost, quick development, and minimum disruption of radar operations. The processor is based around a low-cost digital signal processor card and personal computer controller. With the use of such a concept, an auxiliary processor was implemented for the NCAR CP-2 radar during a 1991 summer field campaign and allowed measurement of additional polarimetric parameters, namely, the differential phase and the copolar cross correlation. Sample data are presented from both the auxiliary and existing radar signal processors.

  2. A CCD/CMOS process for integrated image acquisition and early vision signal processing

    NASA Astrophysics Data System (ADS)

    Keast, Craig L.; Sodini, Charles G.

    The development of technology which integrates a four phase, buried-channel CCD in an existing 1.75 micron CMOS process is described. The four phase clock is employed in the integrated early vision system to minimize process complexity. Signal corruption is minimized and lateral fringing fields are enhanced by burying the channel. The CMOS process for CCD enhancement is described, which highlights a new double-poly process and the buried channel, and the integration is outlined. The functionality and transfer efficiency of the process enhancement were appraised by measuring CCD shift registers at 100 kHz. CMOS measurement results are presented, which include threshold voltages, poly-to-poly capacitor voltage and temperature coefficients, and dark current. A CCD/CMOS processor is described which combines smoothing and segmentation operations. The integration of the CCD and the CMOS processes is found to function due to the enhancement-compatible design of the CMOS process and the thorough employment of CCD module baseline process steps.

  3. Tunable Signal Processing through a Kinase Control Cycle: the IKK Signaling Node

    PubMed Central

    Behar, Marcelo; Hoffmann, Alexander

    2013-01-01

    The transcription factor NFκB, a key component of the immune system, shows intricate stimulus-specific temporal dynamics. Those dynamics are thought to play a role in controlling the physiological response to cytokines and pathogens. Biochemical evidence suggests that the NFκB inducing kinase, IKK, a signaling hub onto which many signaling pathways converge, is regulated via a regulatory cycle comprising a poised, an active, and an inactive state. We hypothesize that it operates as a modulator of signal dynamics, actively reshaping the signals generated at the receptor proximal level. Here we show that a regulatory cycle can function in at least three dynamical regimes, tunable by regulating a single kinetic parameter. In particular, the simplest three-state regulatory cycle can generate signals with two well-defined phases, each with distinct coding capabilities in terms of the information they can carry about the stimulus. We also demonstrate that such a kinase cycle can function as a signal categorizer classifying diverse incoming signals into outputs with a limited set of temporal activity profiles. Finally, we discuss the extension of the results to other regulatory motifs that could be understood in terms of the regimes of the three-state cycle. PMID:23823243

  4. Higgs boson production at hadron colliders: Signal and background processes

    SciTech Connect

    David Rainwater; Michael Spira; Dieter Zeppenfeld

    2004-01-12

    We review the theoretical status of signal and background calculations for Higgs boson production at hadron colliders. Particular emphasis is given to missing NLO results, which will play a crucial role for the Tevatron and the LHC.

  5. Roles of phosphotase 2A in nociceptive signal processing

    PubMed Central

    2013-01-01

    Multiple protein kinases affect the responses of dorsal horn neurons through phosphorylation of synaptic receptors and proteins involved in intracellular signal transduction pathways, and the consequences of this modulation may be spinal central sensitization. In contrast, the phosphatases catalyze an opposing reaction of de-phosphorylation, which may also modulate the functions of crucial proteins in signaling nociception. This is an important mechanism in the regulation of intracellular signal transduction pathways in nociceptive neurons. Accumulated evidence has shown that phosphatase 2A (PP2A), a serine/threonine specific phosphatase, is implicated in synaptic plasticity of the central nervous system and central sensitization of nociception. Therefore, targeting protein phosphotase 2A may provide an effective and novel strategy for the treatment of clinical pain. This review will characterize the structure and functional regulation of neuronal PP2A and bring together recent advances on the modulation of PP2A in targeted downstream substrates and relevant multiple nociceptive signaling molecules. PMID:24010880

  6. Measuring Postural Stability: Strategies For Signal Acquisition And Processing

    NASA Astrophysics Data System (ADS)

    Riedel, Susan A.; Harris, Gerald F.

    1987-01-01

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

  7. Controlled metallic nanopillars for low impedance biomedical electrode.

    PubMed

    Gardner, Calvin J; Trisnadi, Jonathan; Kim, Tae Kyoung; Brammer, Karla; Reiss, Lina; Chen, Li-han; Jin, Sungho

    2014-05-01

    Radial metallic nanopillar/nanowire structures can be created by a controlled radiofrequency (RF) plasma processing technique on the surface of certain alloy wires, including important biomedical alloys such as MP35N (Co-Ni-Cr-Mo alloy), platinum-iridium and stainless steel. In electrode applications such as pacemakers or neural stimulators, the increase in surface area in elongated MP35N nanopillars allows for decreased surface impedance and greater current density. However, the nanopillar height on MP35N alloy tends to be self-limiting at ∼1-3μm. The objective of this study was to further elongate the radial nanopillars so as to reduce electrode impedance for biomedical electrode applications. Intelligent experimental design allowed for efficient investigation of processing parameters, including plasma material, process duration, power, pressure and repetition. It was found that multi-step repeated processing in the parameter-controlled RF environment could increase nanopillar height to ∼10μm, a 400% improvement, while the RF plasma processing with identical total duration but in a single step did not lead to desired nanopillar elongation. Measurement of electrode impedance in phosphate-buffered saline solution showed an associated decrease to one-fifth of the surface impedance of unprocessed wire for signals below 100Hz. For the purposes of this study, MP35N and Pt-Ir wires were characterized and demonstrated augmented surface impedance properties which, in combination with superior cell integration, enhanced biomedical electrode performance. PMID:24384124

  8. Signal simulation and signal processing for multiple reference optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Neuhaus, Kai; Subhash, Hrebesh; Dsouza, Roshan; Hogan, Josh; Wilson, Carol; Leahy, Martin

    2015-03-01

    The generation of a synthetic MR-OCT signal is presented and compared to a real acquired signal. Multiple reference optical coherence tomography (MR-OCT) is a novel time-domain interferometric system. The MR-OCT principle is adding a partial mirror to extend the axial scan range, which effectively extends the scan depth for imaging. The actuation of the scan mirror required for time-domain OCT, was demonstrated to operate with a low cost miniature voice coil, such as a speaker extracted from a smartphone or CD/DVD pick-up system. Building a compact and cost-effective optical imaging system will enable affordable medical diagnosis at low-resource setting applications. The partial mirror recirculates multiple reflections (orders) into the interferometric system and the increase of optical path delay does increase the beat frequency of the interference signal. The synthesis of such an interference signal using a numerical method is described in this manuscript.

  9. The use of digital signal processors (DSPs) in real-time processing of multi-parametric bioelectronic signals.

    PubMed

    Ressler, Johann; Dirscherl, Andreas; Grothe, Helmut; Wolf, Bernhard

    2007-02-01

    In many cases of bioanalytical measurement, calculation of large amounts of data, analysis of complex signal waveforms or signal speed can overwhelm the performance of microcontrollers, analog electronic circuits or even PCs. One method to obtain results in real time is to apply a digital signal processor (DSP) for the analysis or processing of measurement data. In this paper we show how DSP-supported multiplying and accumulating (MAC) operations, such as time/frequency transformation, pattern recognition by correlation, convolution or filter algorithms, can optimize the processing of bioanalytical data. Discrete integral calculations are applied to the acquisition of impedance values as part of multi-parametric sensor chips, to pH monitoring using light-addressable potentiometric sensors (LAPS) and to the analysis of rapidly changing signal shapes, such as action potentials of cultured neuronal networks, as examples of DSP capability. PMID:17313351

  10. Genomic Signal Processing: Predicting Basic Molecular Biological Principles

    NASA Astrophysics Data System (ADS)

    Alter, Orly

    2005-03-01

    Advances in high-throughput technologies enable acquisition of different types of molecular biological data, monitoring the flow of biological information as DNA is transcribed to RNA, and RNA is translated to proteins, on a genomic scale. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment and drug development. Recently we described data-driven models for genome-scale molecular biological data, which use singular value decomposition (SVD) and the comparative generalized SVD (GSVD). Now we describe an integrative data-driven model, which uses pseudoinverse projection (1). We also demonstrate the predictive power of these matrix algebra models (2). The integrative pseudoinverse projection model formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples, designated the ``basis'' set. The mathematical variables of this integrative model, the pseudoinverse correlation patterns that are uncovered in the data, represent independent processes and corresponding cellular states (such as observed genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measured samples in which these regulators or transcription factors are over- or underactive). Reconstruction of the data in the basis simulates experimental observation of only the cellular states manifest in the data that correspond to those of the basis. Classification of the data samples according to their reconstruction in the basis, rather than their overall measured profiles, maps the cellular states of the data onto those of the basis, and gives a global picture of the correlations and possibly also causal coordination of

  11. Contemporary ultrasonic signal processing approaches for nondestructive evaluation of multilayered structures

    NASA Astrophysics Data System (ADS)

    Zhang, Guang-Ming; Harvey, David M.

    2012-03-01

    Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some specific problems, such as penetration, echo overlap, high attenuation and low signal-to-noise ratio. The signals recorded from a multilayered structure are a class of very special signals comprised of limited echoes. Such signals can be assumed to have a sparse representation in a proper signal dictionary. Recently, a number of digital signal processing techniques have been developed by exploiting the sparse constraint. This paper presents a review of research to date, showing the up-to-date developments of signal processing techniques made in ultrasonic NDE. A few typical ultrasonic signal processing techniques used for NDE of multilayered structures are elaborated. The practical applications and limitations of different signal processing methods in ultrasonic NDE of multilayered structures are analysed.

  12. Rapid Prototyping of High Performance Signal Processing Applications

    NASA Astrophysics Data System (ADS)

    Sane, Nimish

    Advances in embedded systems for digital signal processing (DSP) are enabling many scientific projects and commercial applications. At the same time, these applications are key to driving advances in many important kinds of computing platforms. In this region of high performance DSP, rapid prototyping is critical for faster time-to-market (e.g., in the wireless communications industry) or time-to-science (e.g., in radio astronomy). DSP system architectures have evolved from being based on application specific integrated circuits (ASICs) to incorporate reconfigurable off-the-shelf field programmable gate arrays (FPGAs), the latest multiprocessors such as graphics processing units (GPUs), or heterogeneous combinations of such devices. We, thus, have a vast design space to explore based on performance trade-offs, and expanded by the multitude of possibilities for target platforms. In order to allow systematic design space exploration, and develop scalable and portable prototypes, model based design tools are increasingly used in design and implementation of embedded systems. These tools allow scalable high-level representations, model based semantics for analysis and optimization, and portable implementations that can be verified at higher levels of abstractions and targeted toward multiple platforms for implementation. The designer can experiment using such tools at an early stage in the design cycle, and employ the latest hardware at later stages. In this thesis, we have focused on dataflow-based approaches for rapid DSP system prototyping. This thesis contributes to various aspects of dataflow-based design flows and tools as follows: 1. We have introduced the concept of topological patterns, which exploits commonly found repetitive patterns in DSP algorithms to allow scalable, concise, and parameterizable representations of large scale dataflow graphs in high-level languages. We have shown how an underlying design tool can systematically exploit a high

  13. Falling Person Detection Using Multi-Sensor Signal Processing

    NASA Astrophysics Data System (ADS)

    Toreyin, B. Ugur; Soyer, A. Birey; Onaran, Ibrahim; Cetin, E. Enis

    2007-12-01

    Falls are one of the most important problems for frail and elderly people living independently. Early detection of falls is vital to provide a safe and active lifestyle for elderly. Sound, passive infrared (PIR) and vibration sensors can be placed in a supportive home environment to provide information about daily activities of an elderly person. In this paper, signals produced by sound, PIR and vibration sensors are simultaneously analyzed to detect falls. Hidden Markov Models are trained for regular and unusual activities of an elderly person and a pet for each sensor signal. Decisions of HMMs are fused together to reach a final decision.

  14. Brillouin amplification and processing of the Rayleigh scattered signal.

    PubMed

    Mermelstein, David; Shacham, Eliashiv; Biton, Moran; Sternklar, Shmuel

    2015-07-15

    Brillouin amplification of Rayleigh scattering is demonstrated using two different configurations. In the first technique, the Rayleigh scattering and amplification occurs simultaneously in the same fiber. In the second technique, the amplification takes place in a second fiber. The differences between the two techniques are delineated. Using the second technique, we demonstrate single-sideband off-resonant Brillouin amplification of the Rayleigh signal. This technique is shown to enhance the SNR of a signal that is due to vibration-induced strain on the fiber. PMID:26176464

  15. [A telemetery system for neural signal acquiring and processing].

    PubMed

    Wang, Min; Song, Yongji; Suen, Jiantao; Zhao, Yiliang; Jia, Aibin; Zhu, Jianping

    2011-02-01

    Recording and extracting characteristic brain signals in freely moving animals is the basic and significant requirement in the study of brain-computer interface (BCI). To record animal's behaving and extract characteristic brain signals simultaneously could help understand the complex behavior of neural ensembles. Here, a system was established to record and analyse extracellular discharge in freely moving rats for the study of BCI. It comprised microelectrode and micro-driver assembly, analog front end (AFE), programmer system on chip (PSoC), wireless communication and the LabVIEW used as the platform for the graphic user interface. PMID:21485182

  16. Reconfigurable Optical Signal Processing Based on a Distributed Feedback Semiconductor Optical Amplifier

    PubMed Central

    Li, Ming; Deng, Ye; Tang, Jian; Sun, Shuqian; Yao, Jianping; Azaña, José; Zhu, Ninghua

    2016-01-01

    All-optical signal processing has been considered a solution to overcome the bandwidth and speed limitations imposed by conventional electronic-based systems. Over the last few years, an impressive range of all-optical signal processors have been proposed, but few of them come with reconfigurability, a feature highly needed for practical signal processing applications. Here we propose and experimentally demonstrate an analog optical signal processor based on a phase-shifted distributed feedback semiconductor optical amplifier (DFB-SOA) and an optical filter. The proposed analog optical signal processor can be reconfigured to perform signal processing functions including ordinary differential equation solving and temporal intensity differentiation. The reconfigurability is achieved by controlling the injection currents. Our demonstration provitdes a simple and effective solution for all-optical signal processing and computing. PMID:26813252

  17. Reconfigurable Optical Signal Processing Based on a Distributed Feedback Semiconductor Optical Amplifier

    NASA Astrophysics Data System (ADS)

    Li, Ming; Deng, Ye; Tang, Jian; Sun, Shuqian; Yao, Jianping; Azaña, José; Zhu, Ninghua

    2016-01-01

    All-optical signal processing has been considered a solution to overcome the bandwidth and speed limitations imposed by conventional electronic-based systems. Over the last few years, an impressive range of all-optical signal processors have been proposed, but few of them come with reconfigurability, a feature highly needed for practical signal processing applications. Here we propose and experimentally demonstrate an analog optical signal processor based on a phase-shifted distributed feedback semiconductor optical amplifier (DFB-SOA) and an optical filter. The proposed analog optical signal processor can be reconfigured to perform signal processing functions including ordinary differential equation solving and temporal intensity differentiation. The reconfigurability is achieved by controlling the injection currents. Our demonstration provitdes a simple and effective solution for all-optical signal processing and computing.

  18. Reconfigurable Optical Signal Processing Based on a Distributed Feedback Semiconductor Optical Amplifier.

    PubMed

    Li, Ming; Deng, Ye; Tang, Jian; Sun, Shuqian; Yao, Jianping; Azaña, José; Zhu, Ninghua

    2016-01-01

    All-optical signal processing has been considered a solution to overcome the bandwidth and speed limitations imposed by conventional electronic-based systems. Over the last few years, an impressive range of all-optical signal processors have been proposed, but few of them come with reconfigurability, a feature highly needed for practical signal processing applications. Here we propose and experimentally demonstrate an analog optical signal processor based on a phase-shifted distributed feedback semiconductor optical amplifier (DFB-SOA) and an optical filter. The proposed analog optical signal processor can be reconfigured to perform signal processing functions including ordinary differential equation solving and temporal intensity differentiation. The reconfigurability is achieved by controlling the injection currents. Our demonstration provitdes a simple and effective solution for all-optical signal processing and computing. PMID:26813252

  19. Advanced study of video signal processing in low signal to noise environments

    NASA Technical Reports Server (NTRS)

    Carden, F.

    1973-01-01

    Conventional analytical techniques used to determine and optimize phase-lock loop (PLL) characteristics are most often based on a model which is valid only if the intermediate frequency (IF) filter bandwidth is large compared to the PLL bandwidth and the phase error is small. An improved model (called the quasi-linear model) is developed which takes into account small IF filter bandwidths and nonlinear effects associated with large phase errors. By comparison of theoretical and experimental results it is demonstrated that the quasi-linear model accurately predicts PLL characteristics. This is true even for small IF filter bandwidths and large phase errors where the conventional model is invalid. The theoretical and experimental results are used to draw conclusions concerning threshold, multiplier output variance, phase error variance, output signal-to-noise ratio, and signal distortion. The relationship between these characteristics and IF filter bandwidth, modulating signal spectrum, and rms deviation is also determined.

  20. Off-axis signal processing of cetacean biosonar

    NASA Astrophysics Data System (ADS)

    Zimmer, Walter M. X.

    2001-05-01

    Echolocation or biosonar plays a fundamental role for odontocetes to probe their environment, and their characteristics have been studied extensively for over 40 years. In summary, cetacean biosonar can be modeled as broadband transient-like signals radiating from a finite piston or aperture. The resulting sonar beam is directional, with a directivity index exceeding 25 dB for some species. The estimation of relevant sonar parameters is usually obtained from animals that are kept within a controlled and well-instrumented environment. This paper shows how measurements of opportunity from free-ranging odontocetes may be used to obtain their relevant biosonar parameters, in particular directivity index and source level. Frequently these measurements are made with a single hydrophone that is sufficiently deep so that surface-reflected echoes separate from the direct arrival of the echolocation clicks. Also, the received signal often fades in and out as the sonar beam of the scanning animal crosses the hydrophone. The presented technique exploits this scanning and the observation that broadband signals from a finite aperture will appear distorted when recorded off the acoustic axis, as the transfer function of the aperture modifies the spectrum of the transmitted signal.

  1. Wide-band array signal processing via spectral smoothing

    NASA Technical Reports Server (NTRS)

    Xu, Guanghan; Kailath, Thomas

    1989-01-01

    A novel algorithm for the estimation of direction-of-arrivals (DOA) of multiple wide-band sources via spectral smoothing is presented. The proposed algorithm does not require an initial DOA estimate or a specific signal model. The advantages of replacing the MUSIC search with an ESPRIT search are discussed.

  2. Biomedical real-time monitoring in restricted and safety-critical environments

    PubMed Central

    Astaras, A; Bamidis, P D; Kourtidou-Papadeli, C; Maglaveras, N

    2008-01-01

    Biomedical signal monitoring can counteract the risk of human operator error due to inattention or fatigue in safetycritical and restrictive environments, such as in aviation, space, automobile and heavy industrial machinery operation. Real-time biomedical data acquisition is changing through advances in microelectronics fabrication, bio-MEMS and power micro-generators. Such data acquisition and processing systems are becoming increasingly miniaturised, flexible and pervasive, while data is being collected from inside the human body as well as around it. In this paper we review two related research projects exploiting this technological convergence, discuss its implications and suggest future innovation prospects through further similar cross-disciplinary synergies. PMID:19048087

  3. 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.

  4. Biomedical sensor design using analog compressed sensing

    NASA Astrophysics Data System (ADS)

    Balouchestani, Mohammadreza; Krishnan, Sridhar

    2015-05-01

    The main drawback of current healthcare systems is the location-specific nature of the system due to the use of fixed/wired biomedical sensors. Since biomedical sensors are usually driven by a battery, power consumption is the most important factor determining the life of a biomedical sensor. They are also restricted by size, cost, and transmission capacity. Therefore, it is important to reduce the load of sampling by merging the sampling and compression steps to reduce the storage usage, transmission times, and power consumption in order to expand the current healthcare systems to Wireless Healthcare Systems (WHSs). In this work, we present an implementation of a low-power biomedical sensor using analog Compressed Sensing (CS) framework for sparse biomedical signals that addresses both the energy and telemetry bandwidth constraints of wearable and wireless Body-Area Networks (BANs). This architecture enables continuous data acquisition and compression of biomedical signals that are suitable for a variety of diagnostic and treatment purposes. At the transmitter side, an analog-CS framework is applied at the sensing step before Analog to Digital Converter (ADC) in order to generate the compressed version of the input analog bio-signal. At the receiver side, a reconstruction algorithm based on Restricted Isometry Property (RIP) condition is applied in order to reconstruct the original bio-signals form the compressed bio-signals with high probability and enough accuracy. We examine the proposed algorithm with healthy and neuropathy surface Electromyography (sEMG) signals. The proposed algorithm achieves a good level for Average Recognition Rate (ARR) at 93% and reconstruction accuracy at 98.9%. In addition, The proposed architecture reduces total computation time from 32 to 11.5 seconds at sampling-rate=29 % of Nyquist rate, Percentage Residual Difference (PRD)=26 %, Root Mean Squared Error (RMSE)=3 %.

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    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 linear 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 paper describes the algorithm paths applied to experimental data from ultrasonic signals as wax melts and explores different ways to display the results.

  6. Processing of Signals from Fiber Bragg Gratings Using Unbalanced Interferometers

    NASA Technical Reports Server (NTRS)

    Adamovsky, Grigory; Juergens, Jeff; Floyd, Bertram

    2005-01-01

    Fiber Bragg gratings (FBG) have become preferred sensory structures in fiber optic sensing system. High sensitivity, embedability, and multiplexing capabilities make FBGs superior to other sensor configurations. The main feature of FBGs is that they respond in the wavelength domain with the wavelength of the returned signal as the indicator of the measured parameter. The wavelength is then converted to optical intensity by a photodetector to detect corresponding changes in intensity. This wavelength-to-intensity conversion is a crucial part in any FBG-based sensing system. Among the various types of wavelength-to-intensity converters, unbalanced interferometers are especially attractive because of their small weight and volume, lack of moving parts, easy integration, and good stability. In this paper we investigate the applicability of unbalanced interferometers to analyze signals reflected from Bragg gratings. Analytical and experimental data are presented.

  7. Diverse and composite features for ECG signals processing.

    PubMed

    Ubeyli, Elif Derya

    2008-01-01

    The automated diagnostic systems employing diverse and composite features for electrocardiogram (ECG) signals were analyzed and their accuracies were determined. Because of the importance of making the right decision, classification procedures classifying the ECG signals with high accuracy were investigated. The classification accuracies of multilayer perceptron neural network (MLPNN), recurrent neural network (RNN), and mixture of experts (ME) trained on composite features and modified mixture of experts (MME) trained on diverse features were compared. The inputs of these automated diagnostic systems were composed of diverse or composite features (wavelet coefficients and power levels of the power spectral density estimates obtained by the eigenvector methods) and were chosen according to the network structures. The conclusions of this study demonstrated that the MME trained on diverse features achieved accuracy rates which were higher than that of the other automated diagnostic systems trained on composite features. PMID:18408257

  8. Advanced signal processing technique for damage detection in steel tubes

    NASA Astrophysics Data System (ADS)

    Amjad, Umar; Yadav, Susheel Kumar; Dao, Cac Minh; Dao, Kiet; Kundu, Tribikram

    2016-04-01

    In recent years, ultrasonic guided waves gained attention for reliable testing and characterization of metals and composites. Guided wave modes are excited and detected by PZT (Lead Zirconate Titanate) transducers either in transmission or reflection mode. In this study guided waves are excited and detected in the transmission mode and the phase change of the propagating wave modes are recorded. In most of the other studies reported in the literature, the change in the received signal strength (amplitude) is investigated with varying degrees of damage while in this study the change in phase is correlated with the extent of damage. Feature extraction techniques are used for extracting phase and time-frequency information. The main advantage of this approach is that the bonding condition between the transducer and the specimen does not affect the phase while it can affect the strength of recorded signal. Therefore, if the specimen is not damaged but the transducer-specimen bonding is deteriorated then the received signal strength is altered but the phase remains same and thus false positive predictions for damage can be avoided.

  9. TRAF4 restricts IL-17-mediated pathology and signaling processes

    PubMed Central

    Zepp, Jarod A.; Liu, Caini; Qian, Wen; Wu, Ling; Gulen, Muhammet F.; Kang, Zizhen; Li, Xiaoxia

    2013-01-01

    The effector T-cell subset, Th17, plays a significant role in the pathogenesis of multiple sclerosis as well as other autoimmune diseases. The signature cytokine, IL-17, engages the IL-17R and recruits the E3-ligase Act1 upon stimulation. In this study we examined the role of TRAF4 in IL-17 signaling and Th17-mediated autoimmune encephalomyelitis. Primary cells from TRAF4-deficient mice displayed markedly enhanced IL-17-activated signaling pathways and induction of chemokine mRNA. Adoptive transfer of MOG 35–55 specific wild-type Th17 cells into TRAF4-deficient recipient mice induced an earlier onset of disease. Mechanistically, we found that TRAF4 and TRAF6 utilized the same TRAF-binding sites on Act1, allowing the competition of TRAF4 with TRAF6 for the interaction with Act1. Taken together, this study reveals the necessity of a unique role of TRAF4 in restricting the effects of IL-17 signaling and Th17-mediated disease. PMID:22649194

  10. AMPylation of Rho GTPases Subverts Multiple Host Signaling Processes*

    PubMed Central

    Woolery, Andrew R.; Yu, Xiaobo; LaBaer, Joshua; Orth, Kim

    2014-01-01

    Rho GTPases are frequent targets of virulence factors as they are keystone signaling molecules. Herein, we demonstrate that AMPylation of Rho GTPases by VopS is a multifaceted virulence mechanism that counters several host immunity strategies. Activation of NFκB, Erk, and JNK kinase signaling pathways were inhibited in a VopS-dependent manner during infection with Vibrio parahaemolyticus. Phosphorylation and degradation of IKBα were inhibited in the presence of VopS as was nuclear translocation of the NFκB subunit p65. AMPylation also prevented the generation of superoxide by the phagocytic NADPH oxidase complex, potentially by inhibiting the interaction of Rac and p67. Furthermore, the interaction of GTPases with the E3 ubiquitin ligases cIAP1 and XIAP was hindered, leading to decreased degradation of Rac and RhoA during infection. Finally, we screened for novel Rac1 interactions using a nucleic acid programmable protein array and discovered that Rac1 binds to the protein C1QA, a protein known to promote immune signaling in the cytosol. Interestingly, this interaction was disrupted by AMPylation. We conclude that AMPylation of Rho Family GTPases by VopS results in diverse inhibitory consequences during infection beyond the most obvious phenotype, the collapse of the actin cytoskeleton. PMID:25301945

  11. Processing and Characterization of SrTiO₃-TiO₂ Nanoparticle-Nanotube Heterostructures on Titanium for Biomedical Applications.

    PubMed

    Wang, Yu; Zhang, Dongmei; Wen, Cuie; Li, Yuncang

    2015-07-29

    Surface properties such as physicochemical characteristics and topographical parameters of biomaterials, essentially determining the interaction between the biological cells and the biomaterial, are important considerations in the design of implant materials. In this study, a layer of SrTiO3-TiO2 nanoparticle-nanotube heterostructures on titanium has been fabricated via anodization combined with a hydrothermal process. Titanium was anodized to create a layer of titania (TiO2) nanotubes (TNTs), which was then decorated with a layer of SrTiO3 nanoparticles via hydrothermal processing. SrTiO3-TiO2 heterostructures with high and low volume fraction of SrTiO3 nanoparticle (denoted by 6.3-Sr/TNTs and 1.4-Sr/TNTs) were achieved by using a hydrothermal processing time of 12 and 3 h, respectively. The in vitro biocompatibility of the SrTiO3-TiO2 heterostructures was assessed by using osteoblast cells (SaOS2). Our results indicated that the SrTiO3-TiO2 heterostructures with different volume fractions of SrTiO3 nanoparticles exhibited different Sr ion release in cell culture media and different surface energies. An appropriate volume fraction of SrTiO3 in the heterostructures stimulated the secretion of cell filopodia, leading to enhanced biocompatibility in terms of cell attachment, anchoring, and proliferation on the heterostructure surface. PMID:26136139

  12. Biomedical technology transfer applications of NASA science and technology

    NASA Technical Reports Server (NTRS)

    1972-01-01

    The identification and solution of research and clinical problems in cardiovascular medicine which were investigated by means of biomedical data transfer are reported. The following are sample areas that were focused upon by the Stanford University Biomedical Technology Transfer Team: electrodes for hemiplegia research; vectorcardiogram computer analysis; respiration and phonation electrodes; radiotelemetry of intracranial pressure; and audiotransformation of the electrocardiographic signal. It is concluded that this biomedical technology transfer is significantly aiding present research in cardiovascular medicine.

  13. Quantitative assessment of the impact of biomedical image acquisition on the results obtained from image analysis and processing

    PubMed Central

    2014-01-01

    Introduction Dedicated, automatic algorithms for image analysis and processing are becoming more and more common in medical diagnosis. When creating dedicated algorithms, many factors must be taken into consideration. They are associated with selecting the appropriate algorithm parameters and taking into account the impact of data acquisition on the results obtained. An important feature of algorithms is the possibility of their use in other medical units by other operators. This problem, namely operator’s (acquisition) impact on the results obtained from image analysis and processing, has been shown on a few examples. Material and method The analysed images were obtained from a variety of medical devices such as thermal imaging, tomography devices and those working in visible light. The objects of imaging were cellular elements, the anterior segment and fundus of the eye, postural defects and others. In total, almost 200'000 images coming from 8 different medical units were analysed. All image analysis algorithms were implemented in C and Matlab. Results For various algorithms and methods of medical imaging, the impact of image acquisition on the results obtained is different. There are different levels of algorithm sensitivity to changes in the parameters, for example: (1) for microscope settings and the brightness assessment of cellular elements there is a difference of 8%; (2) for the thyroid ultrasound images there is a difference in marking the thyroid lobe area which results in a brightness assessment difference of 2%. The method of image acquisition in image analysis and processing also affects: (3) the accuracy of determining the temperature in the characteristic areas on the patient’s back for the thermal method - error of 31%; (4) the accuracy of finding characteristic points in photogrammetric images when evaluating postural defects – error of 11%; (5) the accuracy of performing ablative and non-ablative treatments in cosmetology - error of 18

  14. 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.

  15. Othering Processes and STS Curricula: From Nineteenth Century Scientific Discourse on Interracial Competition and Racial Extinction to Othering in Biomedical Technosciences

    NASA Astrophysics Data System (ADS)

    Arteaga, Juan Manuel Sánchez; El-Hani, Charbel N.

    2012-05-01

    This paper analyzes the debates on "interracial competition" and "racial extinction" in the biological discourse on human evolution during the second half of the nineteenth century. Our intention is to discuss the ideological function of these biological concepts as tools for the naturalization and scientific legitimation of racial hierarchies during that period. We argue that the examination of these scientific discussions about race from a historical perspective can play the role of a critical platform for students and teachers to think about the role of science in current othering processes, such as those related to biomedical technosciences. If they learn how biological ideas played an ideological function concerning interracial relationships in the past, they can be compelled to ask which ideological functions the biological knowledge they are teaching and learning might play now. If this is properly balanced, they can eventually both value scientific knowledge for its contributions and have a critical appraisal of some of its implications. We propose, here, a number of initial design principles for the construction of teaching sequences about scientific racism and science-technology-society relationships, yet to be empirically tested by iterative cycles of implementation in basic education and teacher education classrooms.

  16. Biomedical health assessments of the Florida manatee in Crystal River - providing opportunities for training during the capture, handling, and processing of this endangered aquatic mammal

    USGS Publications Warehouse

    Bonde, Robert K.; Garrett, Andrew; Belanger, Michael; Askin, Nesime; Tan, Luke; Wittnich, Carin

    2012-01-01

    Federal and state researchers have been involved in manatee (Trichechus manatus) biomedical health assessment programs for a couple of decades. These benchmark studies have provided a foundation for the development of consistent capture, handling, and processing techniques and protocols. Biologists have implemented training and encouraged multi-agency participation whenever possible to ensure reliable data acquisition, recording, sample collection, publication integrity, and meeting rigorous archival standards. Under a U.S. Fish and Wildlife Service wildlife research permit granted to the U.S. Geological Survey (USGS) Sirenia Project, federal biologists and collaborators are allowed to conduct research studies on wild and captive manatees detailing various aspects of their biology. Therefore, researchers with the project have been collaborating on numerous studies over the last several years. One extensive study, initiated in 2006 has focused on health and fitness of the winter manatee population located in Crystal River, Florida. During those health assessments, capture, handling, and work-up training has been afforded to many of the participants. That study has successfully captured and handled 123 manatees. The data gathered have provided baseline information on manatee health, reproductive status, and nutritional condition. This research initiative addresses concerns and priorities outlined in the Florida Manatee Recovery Plan. The assessment teams strive to continue this collaborative effort to help advance our understanding of health-related issues confronting manatees throughout their range and interlacing these findings with surrogate species concepts.

  17. Sublethal behavioral and physiological effects of the biomedical bleeding process on the American horseshoe crab, Limulus polyphemus.

    PubMed

    Anderson, Rebecca L; Watson, Winsor H; Chabot, Christopher C

    2013-12-01

    The hemolymph of the American horseshoe crab, Limulus polyphemus, is harvested from over 500,000 animals annually to produce Limulus amebocyte lysate (LAL), a medically important product used to detect pathogenic bacteria. Declining abundance of spawning Limulus females in heavily harvested regions suggests deleterious effects of this activity, and while mortality rates of the harvest process are known to be 10%-30%, sublethal behavioral and physiological effects are not known. In this study, we determined the impact of the harvest process on locomotion and hemocyanin levels of 28 female horseshoe crabs. While mortality rates after bleeding (18%) were similar to previous studies, we found significant decreases in the linear and angular velocity of freely moving animals, as well as changes in their activity levels and expression of circatidal behavioral rhythms. Further, we found reductions in hemocyanin levels, which may alter immune function and cuticle integrity. These previously unrecognized behavioral and physiological deficits suggest that the harvest of LAL may decrease female fitness, and thus may contribute to the current population decline. PMID:24445440

  18. Fourier analysis and signal processing by use of the Moebius inversion formula

    NASA Technical Reports Server (NTRS)

    Reed, Irving S.; Yu, Xiaoli; Shih, Ming-Tang; Tufts, Donald W.; Truong, T. K.

    1990-01-01

    A novel Fourier technique for digital signal processing is developed. This approach to Fourier analysis is based on the number-theoretic method of the Moebius inversion of series. The Fourier transform method developed is shown also to yield the convolution of two signals. A computer simulation shows that this method for finding Fourier coefficients is quite suitable for digital signal processing. It competes with the classical FFT (fast Fourier transform) approach in terms of accuracy, complexity, and speed.

  19. Earthquake early warning system using real-time signal processing

    SciTech Connect

    Leach, R.R. Jr.; Dowla, F.U.

    1996-02-01

    An earthquake warning system has been developed to provide a time series profile from which vital parameters such as the time until strong shaking begins, the intensity of the shaking, and the duration of the shaking, can be derived. Interaction of different types of ground motion and changes in the elastic properties of geological media throughout the propagation path result in a highly nonlinear function. We use neural networks to model these nonlinearities and develop learning techniques for the analysis of temporal precursors occurring in the emerging earthquake seismic signal. The warning system is designed to analyze the first-arrival from the three components of an earthquake signal and instantaneously provide a profile of impending ground motion, in as little as 0.3 sec after first ground motion is felt at the sensors. For each new data sample, at a rate of 25 samples per second, the complete profile of the earthquake is updated. The profile consists of a magnitude-related estimate as well as an estimate of the envelope of the complete earthquake signal. The envelope provides estimates of damage parameters, such as time until peak ground acceleration (PGA) and duration. The neural network based system is trained using seismogram data from more than 400 earthquakes recorded in southern California. The system has been implemented in hardware using silicon accelerometers and a standard microprocessor. The proposed warning units can be used for site-specific applications, distributed networks, or to enhance existing distributed networks. By producing accurate, and informative warnings, the system has the potential to significantly minimize the hazards of catastrophic ground motion. Detailed system design and performance issues, including error measurement in a simple warning scenario are discussed in detail.

  20. Speaker verification using combined acoustic and EM sensor signal processing

    SciTech Connect

    Ng, L C; Gable, T J; Holzrichter, J F

    2000-11-10

    Low Power EM radar-like sensors have made it possible to measure properties of the human speech production system in real-time, without acoustic interference. This greatly enhances the quality and quantity of information for many speech related applications. See Holzrichter, Burnett, Ng, and Lea, J. Acoustic. SOC. Am . 103 ( 1) 622 (1998). By combining the Glottal-EM-Sensor (GEMS) with the Acoustic-signals, we've demonstrated an almost 10 fold reduction in error rates from a speaker verification system experiment under a moderate noisy environment (-10dB).