Science.gov

Sample records for biomedical signal processing

  1. Design of experiments in Biomedical Signal Processing Course.

    PubMed

    Li, Ling; Li, Bin

    2008-01-01

    Biomedical Signal Processing is one of the most important major subjects in Biomedical Engineering. The contents of Biomedical Signal Processing include the theories of digital signal processing, the knowledge of different biomedical signals, physiology and the ability of computer programming. Based on our past five years teaching experiences, in order to let students master the signal processing algorithm well, we found that the design of experiments following algorithm was very important. In this paper we presented the ideas and aims in designing the experiments. The results showed that our methods facilitated the study of abstractive signal processing algorithms and made understanding of biomedical signals in a simple way.

  2. [A biomedical signal processing toolkit programmed by Java].

    PubMed

    Xie, Haiyuan

    2012-09-01

    According to the biomedical signal characteristics, a new biomedical signal processing toolkit is developed. The toolkit is programmed by Java. It is used in basic digital signal processing, random signal processing and etc. All the methods in toolkit has been tested, the program is robust. The feature of the toolkit is detailed explained, easy use and good practicability.

  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.

  4. 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

  5. Demystifying biomedical signals: a student centred approach to learning signal processing.

    PubMed

    Simpson, D M; De Stefano, A; Allen, R; Lutman, M E

    2005-09-01

    The processing and analysis of physiological signals has become firmly established in clinical medicine and biomedical research. Many of the users of this technology however do not come from an engineering or science background, and traditional approaches in teaching signal processing are thus not appropriate for them. We have therefore developed a series of modular courses that are aimed specifically at an audience with a background in medicine, health-care or the life-sciences. In these courses, we focus on the concepts, principles and rationale of applying signal processing methods, rather than the mathematical foundations of the techniques. Thus, we aim to remove some of the perceived 'mystery' often surrounding this subject. The very practical approach, with hands-on experience using the MATLAB software, has been well received, with strong evidence that students have learnt to apply their knowledge. This paper describes the learning and teaching approach taken, and some of the experience acquired. PMID:16046177

  6. 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

  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.

  8. Biomedical image processing

    SciTech Connect

    Huang, H.K.

    1981-01-01

    Biomedical image processing is a very broad field; it covers biomedical signal gathering, image forming, picture processing, and image display to medical diagnosis based on features extracted from images. This article reviews this topic in both its fundamentals and applications. In its fundamentals, some basic image processing techniques including outlining, deblurring, noise cleaning, filtering, search, classical analysis and texture analysis have been reviewed together with examples. The state-of-the-art image processing systems have been introduced and discussed in two categories: general purpose image processing systems and image analyzers. In order for these systems to be effective for biomedical applications, special biomedical image processing languages have to be developed. The combination of both hardware and software leads to clinical imaging devices. Two different types of clinical imaging devices have been discussed. There are radiological imagings which include radiography, thermography, ultrasound, nuclear medicine and CT. Among these, thermography is the most noninvasive but is limited in application due to the low energy of its source. X-ray CT is excellent for static anatomical images and is moving toward the measurement of dynamic function, whereas nuclear imaging is moving toward organ metabolism and ultrasound is toward tissue physical characteristics. Heart imaging is one of the most interesting and challenging research topics in biomedical image processing; current methods including the invasive-technique cineangiography, and noninvasive ultrasound, nuclear medicine, transmission, and emission CT methodologies have been reviewed.

  9. 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

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

    PubMed

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

    2013-11-05

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

  11. 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

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

    PubMed

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

    2011-12-01

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

  13. 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

  14. 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.

  15. A 16-Bit Microcomputer Based Biomedical Signal Processor

    PubMed Central

    Sarkady, Antal A.; Wallingford, Errol E.

    1979-01-01

    A versatile low-cost, two-channel signal processor was developed using a 16-bit microcomputer. The instrument can process biomedical signals in the time and frequency domains using a fast, fixed-point FFT algorithm. Many averaged signal processing functions and their estimates are computed efficiently on-line and in near real time using look-up tables and directives. The signal processing techniques were applied to phonocardiograms to develop a non-invasive technique to assess the severity of valvar aortic stenosis in children. A murmur power spectral analysis is presented which yields a statistically reliable spectrum. Envelograms are defined and found to be useful for timing cardiac events.

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

    PubMed

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

    2007-01-01

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

  17. 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

  18. 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

  19. Filter for biomedical imaging and image processing

    NASA Astrophysics Data System (ADS)

    Mondal, Partha P.; Rajan, K.; Ahmad, Imteyaz

    2006-07-01

    Image filtering techniques have numerous potential applications in biomedical imaging and image processing. The design of filters largely depends on the a priori, knowledge about the type of noise corrupting the image. This makes the standard filters application specific. Widely used filters such as average, Gaussian, and Wiener reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high-frequency details, making the image nonsmooth. An integrated general approach to design a finite impulse response filter based on Hebbian learning is proposed for optimal image filtering. This algorithm exploits the interpixel correlation by updating the filter coefficients using Hebbian learning. The algorithm is made iterative for achieving efficient learning from the neighborhood pixels. This algorithm performs optimal smoothing of the noisy image by preserving high-frequency as well as low-frequency features. Evaluation results show that the proposed finite impulse response filter is robust under various noise distributions such as Gaussian noise, salt-and-pepper noise, and speckle noise. Furthermore, the proposed approach does not require any a priori knowledge about the type of noise. The number of unknown parameters is few, and most of these parameters are adaptively obtained from the processed image. The proposed filter is successfully applied for image reconstruction in a positron emission tomography imaging modality. The images reconstructed by the proposed algorithm are found to be superior in quality compared with those reconstructed by existing PET image reconstruction methodologies.

  20. Acoustic Signal Processing

    NASA Astrophysics Data System (ADS)

    Hartmann, William M.; Candy, James V.

    Signal processing refers to the acquisition, storage, display, and generation of signals - also to the extraction of information from signals and the re-encoding of information. As such, signal processing in some form is an essential element in the practice of all aspects of acoustics. Signal processing algorithms enable acousticians to separate signals from noise, to perform automatic speech recognition, or to compress information for more efficient storage or transmission. Signal processing concepts are the building blocks used to construct models of speech and hearing. Now, in the 21st century, all signal processing is effectively digital signal processing. Widespread access to high-speed processing, massive memory, and inexpensive software make signal processing procedures of enormous sophistication and power available to anyone who wants to use them. Because advanced signal processing is now accessible to everybody, there is a need for primers that introduce basic mathematical concepts that underlie the digital algorithms. The present handbook chapter is intended to serve such a purpose.

  1. Optical signal processing

    NASA Technical Reports Server (NTRS)

    Casasent, D.

    1978-01-01

    The article discusses several optical configurations used for signal processing. Electronic-to-optical transducers are outlined, noting fixed window transducers and moving window acousto-optic transducers. Folded spectrum techniques are considered, with reference to wideband RF signal analysis, fetal electroencephalogram analysis, engine vibration analysis, signal buried in noise, and spatial filtering. Various methods for radar signal processing are described, such as phased-array antennas, the optical processing of phased-array data, pulsed Doppler and FM radar systems, a multichannel one-dimensional optical correlator, correlations with long coded waveforms, and Doppler signal processing. Means for noncoherent optical signal processing are noted, including an optical correlator for speech recognition and a noncoherent optical correlator.

  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. Signal Processing, Analysis, & Display

    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

  4. Digital signal processing: Handbook

    NASA Astrophysics Data System (ADS)

    Goldenberg, L. M.; Matiushkin, B. D.; Poliak, M. N.

    The fundamentals of the theory and design of systems and devices for the digital processing of signals are presented. Particular attention is given to algorithmic methods of synthesis and digital processing equipment in communication systems (e.g., selective digital filtering, spectral analysis, and variation of the signal discretization frequency). Programs for the computer-aided analysis of digital filters are described. Computational examples are presented, along with tables of transfer function coefficients for recursive and nonrecursive digital filters.

  5. Ultrahigh bandwidth signal processing

    NASA Astrophysics Data System (ADS)

    Oxenløwe, Leif Katsuo

    2016-04-01

    Optical time lenses have proven to be very versatile for advanced optical signal processing. Based on a controlled interplay between dispersion and phase-modulation by e.g. four-wave mixing, the processing is phase-preserving, and hence useful for all types of data signals including coherent multi-level modulation formats. This has enabled processing of phase-modulated spectrally efficient data signals, such as orthogonal frequency division multiplexed (OFDM) signals. In that case, a spectral telescope system was used, using two time lenses with different focal lengths (chirp rates), yielding a spectral magnification of the OFDM signal. Utilising such telescopic arrangements, it has become possible to perform a number of interesting functionalities, which will be described in the presentation. This includes conversion from OFDM to Nyquist WDM, compression of WDM channels to a single Nyquist channel and WDM regeneration. These operations require a broad bandwidth nonlinear platform, and novel photonic integrated nonlinear platforms like aluminum gallium arsenide nano-waveguides used for 1.28 Tbaud optical signal processing will be described.

  6. Surface electromyography signal processing and classification techniques.

    PubMed

    Chowdhury, Rubana H; Reaz, Mamun B I; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A A; Chellappan, K; Chang, T G

    2013-09-17

    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.

  7. 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

  8. 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.

  9. Characterization of sample entropy in the context of biomedical signal analysis.

    PubMed

    Aboy, Mateo; Cuesta-Frau, David; Austin, Daniel; Mico-Tormos, Pau

    2007-01-01

    Sample Entropy (SampEn) has been proposed as a method to overcome limitations associated with approximate entropy (ApEn). The initial paper describing the SampEn metric included a characterization study comparing both ApEn and SampEn against theoretical results and concluded that SampEn is both more consistent and agrees more closely with theory for known random processes than ApEn. SampEn has been used in several studies to analyze the regularity of clinical and experimental time series. However, questions regarding how to interpret SampEn in certain clinical situations and its relationship to classical signal parameters remain unanswered. In this paper we report the results of a characterization study intended to provide additional insights regarding the interpretability of SampEn in the context of biomedical signal analysis.

  10. [Required procedure for nominal data files processing in biomedical research].

    PubMed

    Chambon-Savanovitch, C; Dubray, C; Albuisson, E; Sauvant, M P

    2001-12-01

    To date, biomedical research using nominal data files for the data collection, data acquisition or data processing has had to comply with 2 French laws (Law of December, 20, 1988, modified, relating to the protection of patients participating in biomedical research, and the Law of January, 6, 1978, completed by the Law of July 1, 1994 n degrees 94-548, chapter V bis). This later law dictates rules not only for the establishment of nominal data files, but also confer individual rights to filed persons. These regulations concern epidemiological research, clinical trials, drug watch studies and economic health research. In this note, we describe the obligations and specific general and simplified procedure required for conducting biomedical research. Included in the requirements are an information and authorization procedure with the local and national consultative committees on data processing in biomedical research (CCTIRS, Comité Consultatif sur le Traitement de l'Information en Recherche Biomédicale, and CNIL, Commission Nationale Informatique et Libertés).

  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. 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

  13. Adaptive Signal Processing Testbed

    NASA Astrophysics Data System (ADS)

    Parliament, Hugh A.

    1991-09-01

    The design and implementation of a system for the acquisition, processing, and analysis of signal data is described. The initial application for the system is the development and analysis of algorithms for excision of interfering tones from direct sequence spread spectrum communication systems. The system is called the Adaptive Signal Processing Testbed (ASPT) and is an integrated hardware and software system built around the TMS320C30 chip. The hardware consists of a radio frequency data source, digital receiver, and an adaptive signal processor implemented on a Sun workstation. The software components of the ASPT consists of a number of packages including the Sun driver package; UNIX programs that support software development on the TMS320C30 boards; UNIX programs that provide the control, user interaction, and display capabilities for the data acquisition, processing, and analysis components of the ASPT; and programs that perform the ASPT functions including data acquisition, despreading, and adaptive filtering. The performance of the ASPT system is evaluated by comparing actual data rates against their desired values. A number of system limitations are identified and recommendations are made for improvements.

  14. 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

  15. Multidimensional digital signal processing

    NASA Astrophysics Data System (ADS)

    Lanfear, T. A.; Constantinides, A. G.

    1984-06-01

    The computer program SIMUL is intended to simulate the ALPS system architecture at a high level so as to answer such questions as: is a signal processing application feasible with a particular hardware configuration?; how fast can the processing be performed?; will the system degrade gracefully if some of the resources fail?; what is the effect upon system performance of changes to details such as the number of resources available, the execution time of a resource etc. This document should be read in conjunction with previous documentation for ALPS. The program takes as input data the following information: the number of nodes in the signal flow graph, the number of types of resources, the number of data busses, the time to transfer a block of data from one resource to another, the signal flow graph connectivity and edge prioritization in the form of an adjacency matrix, the number of each type of resource, the execution time of each resource and the type of resource associated with each graph node.

  16. 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.

  17. 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

  18. 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

  19. Heavy-tailed prediction error: a difficulty in predicting biomedical signals of 1/f noise type.

    PubMed

    Li, Ming; Zhao, Wei; Chen, Biao

    2012-01-01

    A fractal signal x(t) in biomedical engineering may be characterized by 1/f noise, that is, the power spectrum density (PSD) divergences at f = 0. According the Taqqu's law, 1/f noise has the properties of long-range dependence and heavy-tailed probability density function (PDF). The contribution of this paper is to exhibit that the prediction error of a biomedical signal of 1/f noise type is long-range dependent (LRD). Thus, it is heavy-tailed and of 1/f noise. Consequently, the variance of the prediction error is usually large or may not exist, making predicting biomedical signals of 1/f noise type difficult. PMID:23251226

  20. [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.

  1. 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.

  2. 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.

  3. 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.

  4. Signal and Image Processing Operations

    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. Bluetooth telemedicine processor for multichannel biomedical signal transmission via mobile cellular networks.

    PubMed

    Rasid, Mohd Fadlee A; Woodward, Bryan

    2005-03-01

    One of the emerging issues in m-Health is how best to exploit the mobile communications technologies that are now almost globally available. The challenge is to produce a system to transmit a patient's biomedical signals directly to a hospital for monitoring or diagnosis, using an unmodified mobile telephone. The paper focuses on the design of a processor, which samples signals from sensors on the patient. It then transmits digital data over a Bluetooth link to a mobile telephone that uses the General Packet Radio Service. The modular design adopted is intended to provide a "future-proofed" system, whose functionality may be upgraded by modifying the software.

  7. 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

  8. 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

  9. High resolution signal processing

    NASA Astrophysics Data System (ADS)

    Tufts, Donald W.

    1993-08-01

    Motivated by the goal of efficient, effective, high-speed integrated-circuit realization, we have discovered an algorithm for high speed Fourier analysis called the Arithmetic Fourier Transform (AFT). It is based on the number-theoretic method of Mobius inversion, a method that is well suited for integrated-circuit realization. The computation of the AFT can be carried out in parallel, pipelined channels, and the individual operations are very simple to execute and control. Except for a single scaling in each channel, all the operations are additions or subtractions. Thus, it can reduce the required power, volume, and cost. Also, analog switched-capacitor realizations of the AFT have been studied. We have also analyzed the performance of a broad and useful class of data adaptive signal estimation algorithms. This in turn has led to our proposed improvements in the methods. We have used perturbation analysis of the rank-reduced data matrix to calculate its statistical properties. The improvements made have been demonstrated by computer simulation as well as by comparison with the Cramer-Rao Bound.

  10. 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.

  11. Signal processing for semiconductor detectors

    SciTech Connect

    Goulding, F.S.; Landis, D.A.

    1982-02-01

    A balanced perspective is provided on the processing of signals produced by semiconductor detectors. The general problems of pulse shaping to optimize resolution with constraints imposed by noise, counting rate and rise time fluctuations are discussed.

  12. Model control of image processing for telerobotics and biomedical instrumentation

    NASA Astrophysics Data System (ADS)

    Nguyen, An Huu

    1993-06-01

    This thesis has model control of image processing (MCIP) as its major theme. By this it is meant that there is a top-down model approach which already knows the structure of the image to be processed. This top-down image processing under model control is used further as visual feedback to control robots and as feedforward information for biomedical instrumentation. The software engineering of the bioengineering instrumentation image processing is defined in terms of the task and the tools available. Early bottom-up image processing such as thresholding occurs only within the top-down control regions of interest (ROI's) or operating windows. Moment computation is an important bottom-up procedure as well as pyramiding to attain rapid computation, among other considerations in attaining programming efficiencies. A distinction is made between initialization procedures and stripped down run time operations. Even more detailed engineering design considerations are considered with respect to the ellipsoidal modeling of objects. Here the major axis orientation is an important additional piece of information, beyond the centroid moments. Careful analysis of various sources of errors and considerable benchmarking characterized the detailed considerations of the software engineering of the image processing procedures. Image processing for robotic control involves a great deal of 3D calibration of the robot working environment (RWE). Of special interest is the idea of adapting the machine scanpath to the current task. It was important to pay careful attention to the hardware aspects of the control of the toy robots that were used to demonstrate the general methodology. It was necessary to precalibrate the open loop gains for all motors so that after initialization the visual feedback, which depends on MCIP, would be able to supply enough information quickly enough to the control algorithms to govern the robots under a variety of control configurations and task operations

  13. [Signal processing in contour implants].

    PubMed

    Ormezzano, Y; Deleurme, C; Vormès, E; Frachet, B

    1990-01-01

    Signal processing by cochlear implants is aimed at transmitting all the acoustic information carried by the human voice, whether in its semantic, esthetic or affective aspects, as an electrical signal. The "translating" approach, which encodes the signal according to the characteristics of the sounds, can only be ideally used in multiple-canal implants. On the contrary, our experience with various single-canal prostheses shows that our patients choose one of these according to the comfort of the signal and to its reliability rather than to the complexity of signal processing: all prostheses produce approximately the same results, whatever the method implemented. The contour implant allows an easy, effective and well-tolerated fitting at low costs.

  14. 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

  15. 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.

  16. 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.

  17. Secure information embedding into 1D biomedical signals based on SPIHT.

    PubMed

    Rubio, Oscar J; Alesanco, Alvaro; García, José

    2013-08-01

    This paper proposes an encoding system for 1D biomedical signals that allows embedding metadata and provides security and privacy. The design is based on the analysis of requirements for secure and efficient storage, transmission and access to medical tests in e-health environment. This approach uses the 1D SPIHT algorithm to compress 1D biomedical signals with clinical quality, metadata embedding in the compressed domain to avoid extra distortion, digital signature to implement security and attribute-level encryption to support Role-Based Access Control. The implementation has been extensively tested using standard electrocardiogram and electroencephalogram databases (MIT-BIH Arrhythmia, MIT-BIH Compression and SCCN-EEG), demonstrating high embedding capacity (e.g. 3 KB in resting ECGs, 200 KB in stress tests, 30 MB in ambulatory ECGs), short delays (2-3.3s in real-time transmission) and compression of the signal (by ≃3 in real-time transmission, by ≃5 in offline operation) despite of the embedding of security elements and metadata to enable e-health services.

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Signal processing in eukaryotic chemotaxis

    NASA Astrophysics Data System (ADS)

    Segota, Igor; Rachakonda, Archana; Franck, Carl

    2013-03-01

    Unlike inanimate condensed matter, living cells depend upon the detection of chemical signals for their existence. First, we experimentally determined the chemotaxis response of eukaryotic Dictyostelium cells to static folic acid gradients and show that they can respond to gradients as shallow as 0.2% across the cell body. Second, using Shannon's information theory, we showed that the information cells receive about the gradient exceeds the theoretically predicted information at the receptor-ligand binding step, resulting in the violation of the data processing inequality. Finally, we analyzed how eukaryotic cells can affect the gradient signals by secreting enzymes that degrade the signal. We analyzed this effect with a focus on a well described Dictyostelium cAMP chemotaxis system where cAMP signals are affected by an extracellular cAMP phosphodiesterase (PDE) and its inhibitor (PDI). Using a reaction-diffusion model of this set of interactions in the extracellular space, we show that cells can effectively sense much steeper chemical gradients than naively expected (up to a factor of 12). We also found that the rough estimates of experimental PDE and PDI secretion rates are close to the optimal values for gradient sensing as predicted by our model.

  7. Signal processing in cellular clocks.

    PubMed

    Forger, Daniel B

    2011-03-15

    Many biochemical events within a cell need to be timed properly to occur at specific times of day, after other events have happened within the cell or in response to environmental signals. The cellular biochemical feedback loops that time these events have already received much recent attention in the experimental and modeling communities. Here, we show how ideas from signal processing can be applied to understand the function of these clocks. Consider two signals from the network s(t) and r(t), either two variables of a model or two experimentally measured time courses. We show how s(t) can be decomposed into two parts, the first being a function of r(t), and the second the derivative of a function of r(t). Geometric principles are then derived that can be used to understand when oscillations appear in biochemical feedback loops, the period of these oscillations, and their time course. Specific examples of this theory are provided that show how certain networks are prone or not prone to oscillate, how individual biochemical processes affect the period, and how oscillations in one chemical species can be deduced from oscillations in other parts of the network.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. A low power biomedical signal processor ASIC based on hardware software codesign.

    PubMed

    Nie, Z D; Wang, L; Chen, W G; Zhang, T; Zhang, Y T

    2009-01-01

    A low power biomedical digital signal processor ASIC based on hardware and software codesign methodology was presented in this paper. The codesign methodology was used to achieve higher system performance and design flexibility. The hardware implementation included a low power 32bit RISC CPU ARM7TDMI, a low power AHB-compatible bus, and a scalable digital co-processor that was optimized for low power Fast Fourier Transform (FFT) calculations. The co-processor could be scaled for 8-point, 16-point and 32-point FFTs, taking approximate 50, 100 and 150 clock circles, respectively. The complete design was intensively simulated using ARM DSM model and was emulated by ARM Versatile platform, before conducted to silicon. The multi-million-gate ASIC was fabricated using SMIC 0.18 microm mixed-signal CMOS 1P6M technology. The die area measures 5,000 microm x 2,350 microm. The power consumption was approximately 3.6 mW at 1.8 V power supply and 1 MHz clock rate. The power consumption for FFT calculations was less than 1.5 % comparing with the conventional embedded software-based solution.

  13. 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.

  14. Digital Signal Processing and Machine Learning

    NASA Astrophysics Data System (ADS)

    Li, Yuanqing; Ang, Kai Keng; Guan, Cuntai

    Any brain-computer interface (BCI) system must translate signals from the users brain into messages or commands (see Fig. 1). Many signal processing and machine learning techniques have been developed for this signal translation, and this chapter reviews the most common ones. Although these techniques are often illustrated using electroencephalography (EEG) signals in this chapter, they are also suitable for other brain signals.

  15. UMLS content views appropriate for NLP processing of the biomedical literature vs. clinical text.

    PubMed

    Demner-Fushman, Dina; Mork, James G; Shooshan, Sonya E; Aronson, Alan R

    2010-08-01

    Identification of medical terms in free text is a first step in such Natural Language Processing (NLP) tasks as automatic indexing of biomedical literature and extraction of patients' problem lists from the text of clinical notes. Many tools developed to perform these tasks use biomedical knowledge encoded in the Unified Medical Language System (UMLS) Metathesaurus. We continue our exploration of automatic approaches to creation of subsets (UMLS content views) which can support NLP processing of either the biomedical literature or clinical text. We found that suppression of highly ambiguous terms in the conservative AutoFilter content view can partially replace manual filtering for literature applications, and suppression of two character mappings in the same content view achieves 89.5% precision at 78.6% recall for clinical applications.

  16. An architecture for EEG signal processing and interpretation during sleep (ESPIS).

    PubMed

    Toussaint, M; Schaltenbrand, N; Paiva, T; Pollmacher, T; Pflieger, C; Luthringer, R; Macher, J P

    1994-10-01

    The project's aim is to develop a dedicated workstation in order to process multiple channels of electrophysiological signals in real-time during sleep. In ESPIS we are aiming to define both an architecture and an environment for EEG signal interpretation in medicine based on computer science gold standards (Unix, XWindow, Motif). Signal processing and pattern recognition analysis are provided by parallel processing on a specific developed acquisition architecture (DSP) based on transputers. The main result is a high performance prototype demonstrating signal interpretation during sleep which has already been tested in a medical environment. The overall specifications allow this biomedical device to be extended to other types of medical signals.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. 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".

  5. Process Dissociation and Mixture Signal Detection Theory

    ERIC Educational Resources Information Center

    DeCarlo, Lawrence T.

    2008-01-01

    The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely…

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

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

    PubMed

    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.

  14. Optical signal processing: Musical score for optical signals

    NASA Astrophysics Data System (ADS)

    Testorf, Markus

    2012-07-01

    Phase-space optics is an indispensable tool for optical imaging and sensing. New optical hardware for light-field photography and pupil engineering for imaging with extended depth of field promote the use of phase-space representations as the primary object of optical signal processing.

  15. 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.

  16. 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.

  17. Sonar signal processing using probabilistic signal and ocean environmental models.

    PubMed

    Culver, R Lee; Camin, H John

    2008-12-01

    Acoustic signals propagating through the ocean are refracted, scattered, and attenuated by the ocean volume and boundaries. Many aspects of how the ocean affects acoustic propagation are understood, such that the characteristics of a received signal can often be predicted with some degree of certainty. However, acoustic ocean parameters vary with time and location in a manner that is not, and cannot be, precisely known; some uncertainty will always remain. For this reason, the characteristics of the received signal can never be precisely predicted and must be described in probabilistic terms. A signal processing structure recently developed relies on knowledge of the ocean environment to predict the statistical characteristics of the received signal, and incorporates this description into the processor in order to detect and classify targets. Acoustic measurements at 250 Hz from the 1996 Strait of Gibraltar Acoustic Monitoring Experiment are used to illustrate how the processor utilizes environmental data to classify source depth and to underscore the importance of environmental model fidelity and completeness.

  18. [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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. Digital processing of signals from femtosecond combs

    NASA Astrophysics Data System (ADS)

    Čížek, Martin; Šmíd, Radek; Buchta, Zdeněk.; Mikel, Břetislav; Lazar, Josef; Číp, Ondrej

    2012-01-01

    The presented work is focused on digital processing of beat note signals from a femtosecond optical frequency comb. The levels of mixing products of single spectral components of the comb with CW laser sources are usually very low compared to products of mixing all the comb components together. RF counters are more likely to measure the frequency of the strongest spectral component rather than a weak beat note. Proposed experimental digital signal processing system solves this problem by analyzing the whole spectrum of the output RF signal and using software defined radio (SDR) algorithms. Our efforts concentrate in two main areas: Firstly, we are experimenting with digital signal processing of the RF beat note spectrum produced by f-2f 1 technique and with fully digital servo-loop stabilization of the fs comb. Secondly, we are using digital servo-loop techniques for locking free running continuous laser sources on single components of the fs comb spectrum. Software capable of computing and analyzing the beat-note RF spectrums using FFT and peak detection was developed. A SDR algorithm performing phase demodulation on the f- 2f signal is used as a regulation error signal source for a digital phase-locked loop stabilizing the offset and repetition frequencies of the fs comb.

  5. Chaotic signal processes and associated nonlinear filters

    NASA Astrophysics Data System (ADS)

    McCarty, Robert C.

    1997-04-01

    A chaotic signal process is generated by use of a continuous but nowhere differentiable Weierstrass function as a force function in Duffing's second-order nonlinear differential equation. In the particular cases where Duffing's equation represents the mechanical behavior of a simple pendulum where only the mass of the 'bob' changes in time, an analytical solution is obtained by the use of Hammerstein integrals. In the more-complicated case where the mass of the 'bob' and the length of the pendulum rod are both changing in time, the resulting solution is obtained numerically. In any detailed analysis of a chaotic signal process, nonlinear filters are used to determine the existence and nature of an attractor or repeller as discussed. By a simple change of parametric values in the Weierstrass function, other chaotic signal processes are easily generated.

  6. 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.

  7. 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

  8. Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images

    PubMed Central

    Lahmiri, Salim; Boukadoum, Mounir

    2013-01-01

    A new methodology for automatic feature extraction from biomedical images and subsequent classification is presented. The approach exploits the spatial orientation of high-frequency textural features of the processed image as determined by a two-step process. First, the two-dimensional discrete wavelet transform (DWT) is applied to obtain the HH high-frequency subband image. Then, a Gabor filter bank is applied to the latter at different frequencies and spatial orientations to obtain new Gabor-filtered image whose entropy and uniformity are computed. Finally, the obtained statistics are fed to a support vector machine (SVM) binary classifier. The approach was validated on mammograms, retina, and brain magnetic resonance (MR) images. The obtained classification accuracies show better performance in comparison to common approaches that use only the DWT or Gabor filter banks for feature extraction. PMID:27006906

  9. Engineering a material for biomedical applications with electric field assisted processing

    NASA Astrophysics Data System (ADS)

    Ahmad, Z.; Nangrejo, M.; Edirisinghe, M.; Stride, E.; Colombo, P.; Zhang, H. B.

    2009-10-01

    In this work, using multiple co-flows we demonstrate in-situ encapsulation of nano-particles, liquids and/or gases in different structural morphologies, which can also be deposited in a designated pattern by a direct write method and surface modification can be controlled to release encapsulated material. The range of possibilities offered by exposing a material solution to an applied electric field can result in a plethora of structures which can accommodate a whole host of biomedical applications from microfluidic devices (microchannels, loaded with various materials), printed 3D structures and patterns, lab-on-a-chip devices to encapsulated materials (capsules, tubes, fibres, dense multi-layered fibrous networks) for drug delivery and tissue engineering. The structures obtained in this way can vary in size from micrometer to the nanometer range and the processing is viable for all states of matter. The work shown demonstrates some novel structures and methodologies for processing a biomaterial.

  10. 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.

  11. 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.

  12. Processing Oscillatory Signals by Incoherent Feedforward Loops

    PubMed Central

    Zhang, Carolyn; You, Lingchong

    2016-01-01

    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

  13. 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

  14. 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).

  15. 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.

  16. Signal Processing Schemes for Doppler Global Velocimetry

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

    Two schemes for processing signals obtained from the Doppler global velocimeter are described. The analog approach is a simple, real time method for obtaining an RS-170 video signal containing the normalized intensity image. Pseudo colors are added using a monochromatic frame grabber producing a standard NTSC video signal that can be monitored and/or recorded. The digital approach is more complicated, but maintains the full resolution of the acquisition cameras with the capabilities to correct the signal image for pixel sensitivity variations and to remove of background light. Prototype circuits for each scheme are described and example results from the investigation of the vortical flow field above a 75-degree delta wing presented.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. A Virtual Laboratory for Digital Signal Processing

    ERIC Educational Resources Information Center

    Dow, Chyi-Ren; Li, Yi-Hsung; Bai, Jin-Yu

    2006-01-01

    This work designs and implements a virtual digital signal processing laboratory, VDSPL. VDSPL consists of four parts: mobile agent execution environments, mobile agents, DSP development software, and DSP experimental platforms. The network capability of VDSPL is created by using mobile agent and wrapper techniques without modifying the source code…

  3. Computer Aided Teaching of Digital Signal Processing.

    ERIC Educational Resources Information Center

    Castro, Ian P.

    1990-01-01

    Describes a microcomputer-based software package developed at the University of Surrey for teaching digital signal processing to undergraduate science and engineering students. Menu-driven software capabilities are explained, including demonstration of qualitative concepts and experimentation with quantitative data, and examples are given of…

  4. Impact of biomedical imaging and data visualization technology on the clinical development and regulatory review process

    NASA Astrophysics Data System (ADS)

    Conklin, James J.; Robbins, William L.

    1994-12-01

    The determination of whether a drug or medical device is safe and effective requires statistical proof of valid clinical trial information. Quantitative biostatistical measures from anatomic and functional medical images are now providing objective and reproducible measures of drug and device effects. These highly precise biostatistical measures can be used to quantitatively analyze the efficacy and occasionally the safety of these drugs and devices. Since medical imaging information is digital, or is readily digitized, it can be visualized and measured in a variety of ways to evaluate the validity of the data. Moreover, with advanced image processing and data visualization tools, this information can be electronically organized and submitted directly to the U.S. Food and Drug Administration reviewed. Biomedical imaging and computer-based data visualization technologies have the ability to substantially decrease the time required for clinical development and regulatory review while providing more valid data.

  5. 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.

  6. Signalling through mechanical inputs: a coordinated process.

    PubMed

    Zhang, Huimin; Labouesse, Michel

    2012-07-01

    There is growing awareness that mechanical forces - in parallel to electrical or chemical inputs - have a central role in driving development and influencing the outcome of many diseases. However, we still have an incomplete understanding of how such forces function in coordination with each other and with other signalling inputs in vivo. Mechanical forces, which are generated throughout the organism, can produce signals through force-sensitive processes. Here, we first explore the mechanisms through which forces can be generated and the cellular responses to forces by discussing several examples from animal development. We then go on to examine the mechanotransduction-induced signalling processes that have been identified in vivo. Finally, we discuss what is known about the specificity of the responses to different forces, the mechanisms that might stabilize cells in response to such forces, and the crosstalk between mechanical forces and chemical signalling. Where known, we mention kinetic parameters that characterize forces and their responses. The multi-layered regulatory control of force generation, force response and force adaptation should be viewed as a well-integrated aspect in the greater biological signalling systems.

  7. 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.

  8. Invariance algorithms for processing NDE signals

    NASA Astrophysics Data System (ADS)

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

    1996-11-01

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

  9. 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.

  10. Novel digital signal processing and detection techniques

    NASA Astrophysics Data System (ADS)

    Liu, B.

    1981-09-01

    In the area of narrowband signal processing, design rules are developed for optimum decimator and interpolator, a new efficient scheme using recursive filter for decimation/interpolation is proposed, and a novel approach to the computation of narrowband spectra is shown to yield substantial saving over conventional approaches. Results on the implementation of recursive filters with poles near the unit circle that produces significantly reduced roundoff error include a transformation technique, a scheme to modify the quantizer error spectrum, and a new computationally efficient low noise filter structure. In the area of nonclassical signal detection, several results were derived on nonparametric sequential procedures and on the quantization of signal for detection. In addition, a programmable charge transfer device filter is developed, several problems concerning ADPCM are investigated, results are obtained on FFT roundoff error including the prime factor algorithm, and an effective method of generating random sequences is studied.

  11. 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.

  12. 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.

  13. Nonlinear Cochlear Signal Processing and Phoneme Perception

    NASA Astrophysics Data System (ADS)

    Allen, Jont B.; Régnier, Marion; Phatak, Sandeep; Li, Feipeng

    2009-02-01

    The most important communication signal is human speech. It is helpful to think of speech communication in terms of Claude Shannon's information theory channel model. When thus viewed, it immediately becomes clear that the most complex part of speech communication channel is in auditory system (the receiver). In my opinion, even after years of work, relatively little is know about how the human auditory system decodes speech. Given cochlear damaged, speech scores are greatly reduced, even with tiny amounts of noise. The exact reasons for this SNR-loss presently remain unclear, but I speculate that the source of this must be cochlear outer hair cell temporal processing, not central processing. Specifically, "temporal edge enhancement" of the speech signal and forward masking could easily be modified in such ears, leading to SNR-Loss. What ever the reason, SNR-Loss is the key problem that needs to be fully researched.

  14. Array Signal Processing for Radio Astronomy

    NASA Astrophysics Data System (ADS)

    Veen, Alle Jan; Leshem, Amir; Boonstra, Albert Jan

    2004-06-01

    Radio astronomy forms an interesting application area for array signal processing techniques. Current synthesis imaging telescopes consist of a small number of identical dishes, which track a fixed patch in the sky and produce estimates of the time-varying spatial covariance matrix. The observations sometimes are distorted by interference, e.g., from radio, TV, radar or satellite transmissions. We describe some of the tools that array signal processing offers to filter out the interference, based on eigenvalue decompositions and factor analysis, which is a more general technique applicable to partially calibrated arrays. We consider detection of interference, spatial filtering techniques using projections, and discuss how a reference antenna pointed at the interferer can improve the performance. We also consider image formation and its relation to beamforming.

  15. Enhanced multistatic active sonar signal processing.

    PubMed

    Zhao, Kexin; Liang, Junli; Karlsson, Johan; Li, Jian

    2013-07-01

    Multistatic active sonar systems involve the transmission and reception of multiple probing sequences and can achieve significantly enhanced performance of target detection and localization through exploiting spatial diversity. This paper mainly focuses on two signal processing aspects of such systems, namely, enhanced range-Doppler imaging and improved target parameter estimation. The main contributions of this paper are (1) a hybrid dense-sparse method is proposed to generate range-Doppler images with both low sidelobe levels and high accuracy; (2) a generalized K-Means clustering (GKC) method for target association is developed to associate the range measurements from different transmitter-receiver pairs, which is actually a range fitting procedure; (3) the extended invariance principle-based weighted least-squares method is developed for accurate target position and velocity estimation. The effectiveness of the proposed multistatic active sonar signal processing techniques is verified using numerical examples.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. Processing of UHMWPE and HA/UHMWPE nanocomposite for biomedical applications

    NASA Astrophysics Data System (ADS)

    Fang, Liming

    Ultrahigh molecular weight polyethylene (UHMWPE) is an implant material for orthopedic implants because of its excellent mechanical properties. However, its applications were limited by the poor processability, particularly its use as matrix materials for bone-analogue. The objective of this work is to process UHMWPE and hydroxyapatite/UHMWPE (HA/UHMWPE) nanocomposites for biomedical applications. UHMWPE was processed by extrusion in a temperature window, in which a metastable polyethylene phase transformation was induced by the elongational flow. Compared with conventional methods, the flow resistance was reduced by the mobile mesophase and the fusion of powder became faster by the improved inter-particle chain diffusion. Pin-on-disc wear tests showed that the as-extruded UHMWPE exhibited less wear loss, smaller wear debris and smoother worn surface, suggesting it has higher wear resistance than conventional sample. HA/UHMWPE nanocomposite was processed by twin-screw extrusion of HA and UHMWPE powder mixture and swelling UHMWPE in a solvent to control the shear viscosity. Microstructure showed that aggregated HA powder was broken down to nano-sized primary particles and dispersed homogeneously by the intensive shear mixing in the extruder. The HA particles and UHMWPE fibrils were intimately contacted because swelling improved the chain mobility of UHMWPE. The composite stiffness was significantly enhanced attributed to the reinforcement effect of HA nano particles to UHMWPE fibrils, Since the toughness of UHMWPE was maintained in the composite, the composite was hot drawn to further increase the strength to that of cortical bone by aligning UHMWPE fibrils along the drawing direction. Biological evaluation indicated that the composite was biocompatible and very bioactive in simulated body fluid immersion. It was shown that the composite with 30% of HA by volume had optimal mechanical and biological properties.

  7. Advances in biomedical engineering and biotechnology during 2013-2014.

    PubMed

    Liu, Feng; Wang, Ying; Burkhart, Timothy A; González Penedo, Manuel Francisco; Ma, Shaodong

    2014-01-01

    The 3rd International Conference on Biomedical Engineering and Biotechnology (iCBEB 2014), held in Beijing from the 25th to the 28th of September 2014, is an annual conference that intends to provide an opportunity for researchers and practitioners around the world to present the most recent advances and future challenges in the fields of biomedical engineering, biomaterials, bioinformatics and computational biology, biomedical imaging and signal processing, biomechanical engineering and biotechnology, amongst others. The papers published in this issue are selected from this conference, which witnesses the advances in biomedical engineering and biotechnology during 2013-2014.

  8. 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

  9. 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.

  10. Digital signal processing methods for biosequence comparison.

    PubMed Central

    Benson, D C

    1990-01-01

    A method is discussed for DNA or protein sequence comparison using a finite field fast Fourier transform, a digital signal processing technique; and statistical methods are discussed for analyzing the output of this algorithm. This method compares two sequences of length N in computing time proportional to N log N compared to N2 for methods currently used. This method makes it feasible to compare very long sequences. An example is given to show that the method correctly identifies sites of known homology. PMID:2349096

  11. Focal-plane architectures and signal processing

    NASA Astrophysics Data System (ADS)

    Jayadev, T. S.

    1991-11-01

    This paper discusses the relationship of focal plane architectures and signal processing functions currently used in infrared sensors. It then discusses the development of an algorithm derived from the models developed by biologists to explain the functions of insect eyes and the hardware realization of this algorithm using commercially available silicon chips. The conclusion of this study is that there are important lessons to be learned from the architecture of biological sensors, which may lead to new techniques in electro-optic sensor design.

  12. 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.

  13. 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.

  14. Natural Ensembles and Sensory Signal Processing.

    NASA Astrophysics Data System (ADS)

    Ruderman, Daniel Lee

    In this thesis we explore the idea that sensory systems in biology are well matched to the natural signals they encode. This would imply that the optimal design of a sensory system depends on the statistical structure of its stimuli. Further, the interpretation of sensory data is a statistically defined task: The best signal reconstruction algorithm relies on the statistics of the stimuli and of the noise. We discuss a few instances from the broad class of statistical problems in sensory signal processing which depend on the statistics of natural stimuli. In formalizing these problems, we find that the methods of statistical mechanics are ideally suited toward their solution. First, we demonstrate the importance of prior statistical knowledge in signal reconstruction from an array of noisy detectors. Reconstruction error due to "aliasing," in which two or more Fourier components become confounded, is reduced when knowledge of the ensemble statistics is applied. Next, we consider which design of the visual system encodes the most information about natural images. Since information is a statistical concept, the structure of natural scenes plays a central role in the optimal visual system's design. To lowest order in the signal-to-noise ratio, the only important statistic is the ensemble power spectrum of natural scenes. The optimal linear visual filter is found to solve a Schroedinger equation whose potential is the power spectrum. We find that many of the qualitative features found in mammalian visual systems fall out of a simple linear model: multi -scale processing, orientation selectivity, and the qualitative change in filter shape as a function of signal-to-noise ratio. Finally, we explore the statistics of natural scenes themselves. For an ensemble we gather images from the woods in springtime. We find that they possess a very salient form of scale-invariance: the power spectrum is a power-law, and histograms of local quantities of a given length scale retain

  15. Writer Identification Using Inexpensive Signal Processing Techniques

    NASA Astrophysics Data System (ADS)

    Mokhov, Serguei A.; Song, Miao; Suen, Ching Y.

    We propose to use novel and classical audio and text signal-processing and otherwise techniques for “inexpensive” fast writer identification tasks of scanned hand-written documents “visually”. The “inexpensive” refers to the efficiency of the identification process in terms of CPU cycles while preserving decent accuracy for preliminary identification. This is a comparative study of multiple algorithm combinations in a pattern recognition pipeline implemented in Java around an open-source Modular Audio Recognition Framework (MARF) that can do a lot more beyond audio. We present our preliminary experimental findings in such an identification task. We simulate “visual” identification by “looking” at the hand-written document as a whole rather than trying to extract fine-grained features out of it prior classification.

  16. 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.

  17. 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.

  18. Image and Signal Processing LISP Environment (ISLE)

    SciTech Connect

    Azevedo, S.G.; Fitch, J.P.; Johnson, R.R.; Lager, D.L.; Searfus, R.M.

    1987-10-02

    We have developed a multidimensional signal processing software system called the Image and Signal LISP Environment (ISLE). It is a hybrid software system, in that it consists of a LISP interpreter (used as the command processor) combined with FORTRAN, C, or LISP functions (used as the processing and display routines). Learning the syntax for ISLE is relatively simple and has the additional benefit of introducing a subset of commands from the general-purpose programming language, Common LISP. Because Common LISP is a well-documented and complete language, users do not need to depend exclusively on system developers for a description of the features of the command language, nor do the developers need to generate a command parser that exhaustively satisfies all the user requirements. Perhaps the major reason for selecting the LISP environment is that user-written code can be added to the environment through a ''foreign function'' interface without recompiling the entire system. The ability to perform fast prototyping of new algorithms is an important feature of this environment. As currently implemented, ISLE requires a Sun color or monochrome workstation and a license to run Franz Extended Common LISP. 16 refs., 4 figs.

  19. Signal processing for imaging and mapping ladar

    NASA Astrophysics Data System (ADS)

    Grönwall, Christina; Tolt, Gustav

    2011-11-01

    The new generation laser-based FLASH 3D imaging sensors enable data collection at video rate. This opens up for realtime data analysis but also set demands on the signal processing. In this paper the possibilities and challenges with this new data type are discussed. The commonly used focal plane array based detectors produce range estimates that vary with the target's surface reflectance and target range, and our experience is that the built-in signal processing may not compensate fully for that. We propose a simple adjustment that can be used even if some sensor parameters are not known. The cost for the instantaneous image collection is, compared to scanning laser radar systems, lower range accuracy. By gathering range information from several frames the geometrical information of the target can be obtained. We also present an approach of how range data can be used to remove foreground clutter in front of a target. Further, we illustrate how range data enables target classification in near real-time and that the results can be improved if several frames are co-registered. Examples using data from forest and maritime scenes are shown.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. Nonlinear biochemical signal processing via noise propagation

    NASA Astrophysics Data System (ADS)

    Kim, Kyung Hyuk; Qian, Hong; Sauro, Herbert M.

    2013-10-01

    Single-cell studies often show significant phenotypic variability due to the stochastic nature of intra-cellular biochemical reactions. When the numbers of molecules, e.g., transcription factors and regulatory enzymes, are in low abundance, fluctuations in biochemical activities become significant and such "noise" can propagate through regulatory cascades in terms of biochemical reaction networks. Here we develop an intuitive, yet fully quantitative method for analyzing how noise affects cellular phenotypes based on identifying a system's nonlinearities and noise propagations. We observe that such noise can simultaneously enhance sensitivities in one behavioral region while reducing sensitivities in another. Employing this novel phenomenon we designed three biochemical signal processing modules: (a) A gene regulatory network that acts as a concentration detector with both enhanced amplitude and sensitivity. (b) A non-cooperative positive feedback system, with a graded dose-response in the deterministic case, that serves as a bistable switch due to noise-induced ultra-sensitivity. (c) A noise-induced linear amplifier for gene regulation that requires no feedback. The methods developed in the present work allow one to understand and engineer nonlinear biochemical signal processors based on fluctuation-induced phenotypes.

  8. 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.

  9. Nonlinear biochemical signal processing via noise propagation.

    PubMed

    Kim, Kyung Hyuk; Qian, Hong; Sauro, Herbert M

    2013-10-14

    Single-cell studies often show significant phenotypic variability due to the stochastic nature of intra-cellular biochemical reactions. When the numbers of molecules, e.g., transcription factors and regulatory enzymes, are in low abundance, fluctuations in biochemical activities become significant and such "noise" can propagate through regulatory cascades in terms of biochemical reaction networks. Here we develop an intuitive, yet fully quantitative method for analyzing how noise affects cellular phenotypes based on identifying a system's nonlinearities and noise propagations. We observe that such noise can simultaneously enhance sensitivities in one behavioral region while reducing sensitivities in another. Employing this novel phenomenon we designed three biochemical signal processing modules: (a) A gene regulatory network that acts as a concentration detector with both enhanced amplitude and sensitivity. (b) A non-cooperative positive feedback system, with a graded dose-response in the deterministic case, that serves as a bistable switch due to noise-induced ultra-sensitivity. (c) A noise-induced linear amplifier for gene regulation that requires no feedback. The methods developed in the present work allow one to understand and engineer nonlinear biochemical signal processors based on fluctuation-induced phenotypes.

  10. Detection and Processing Techniques of FECG Signal for Fetal Monitoring

    PubMed Central

    2009-01-01

    Fetal electrocardiogram (FECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during labor. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies are becoming very important requirements in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and developed algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature for fetal monitoring. A comparative study has been carried out to show the performance and accuracy of various methods of FECG signal analysis for fetal monitoring. Finally, this paper further focused some of the hardware implementations using electrical signals for monitoring the fetal heart rate. This paper opens up a passage for researchers, physicians, and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system. PMID:19495912

  11. Single-step colloidal processing of stable aqueous dispersions of ferroelectric nanoparticles for biomedical imaging

    NASA Astrophysics Data System (ADS)

    Zribi, Olena; Garbovskiy, Yuriy; Glushchenko, Anatoliy

    2014-12-01

    The biomedical applications of ferroelectric nanoparticles rely on the production of stable aqueous colloids. We report an implementation of the high energy ball milling method to produce and disperse ultrafine BaTiO3 nanoparticles in an aqueous media in a single step. This technique is low-cost, environmentally friendly and has the capability to control nanoparticle size and functionality with milling parameters. As a result, ultrafine nanoparticles with sizes as small as 6 nm can be produced. These nanoparticles maintain ferroelectricity and can be used as second harmonic generating nanoprobes for biomedical imaging. This technique can be generalized to produce aqueous nanoparticle colloids of other imaging materials.

  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 for beam position monitors

    NASA Astrophysics Data System (ADS)

    Vismara, Giuseppe

    2000-11-01

    At the first sight the problem to determine the beam position from the ratio of the induced charges of the opposite electrodes of a beam monitor seems trivial, but up to now no unique solution has been found that fits the various demands of all particle accelerators. The purpose of this paper is to help "instrumentalists" to choose the best processing system for their particular application, depending on the machine size, the input dynamic range, the required resolution and the acquisition speed. After a general introduction and an analysis of the electrical signals to be treated (frequency and time domain), the definition of the electronic specifications will be reviewed. The tutorial will present the different families in which the processing systems can be grouped. A general description of the operating principles with relative advantages and disadvantages for the most employed processing systems is presented. Special emphasis will be put on recent technological developments based on telecommunication circuitry. In conclusion, an application example will show how to choose the correct solution for a particular case.

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

    PubMed

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

    2013-01-25

    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.

  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. Signal processing at mammalian carotid body chemoreceptors.

    PubMed

    Nurse, Colin A; Piskuric, Nikol A

    2013-01-01

    Mammalian carotid bodies are richly vascularized chemosensory organs that sense blood levels of O(2), CO(2)/H(+), and glucose and maintain homeostatic regulation of these levels via the reflex control of ventilation. Carotid bodies consist of innervated clusters of type I (or glomus) cells in intimate association with glial-like type II cells. Carotid bodies make afferent connections with fibers from sensory neurons in the petrosal ganglia and receive efferent inhibitory innervation from parasympathetic neurons located in the carotid sinus and glossopharyngeal nerves. There are synapses between type I (chemosensory) cells and petrosal afferent terminals, as well as between neighboring type I cells. There is a broad array of neurotransmitters and neuromodulators and their ionotropic and metabotropic receptors in the carotid body. This allows for complex processing of sensory stimuli (e.g., hypoxia and acid hypercapnia) involving both autocrine and paracrine signaling pathways. This review summarizes and evaluates current knowledge of these pathways and presents an integrated working model on information processing in carotid bodies. Included in this model is a novel hypothesis for a potential role of type II cells as an amplifier for the release of a key excitatory carotid body neurotransmitter, ATP, via P2Y purinoceptors and pannexin-1 channels.

  18. 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.

  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. 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

  1. Meteor radar signal processing and error analysis

    NASA Astrophysics Data System (ADS)

    Kang, Chunmei

    Meteor wind radar systems are a powerful tool for study of the horizontal wind field in the mesosphere and lower thermosphere (MLT). While such systems have been operated for many years, virtually no literature has focused on radar system error analysis. The instrumental error may prevent scientists from getting correct conclusions on geophysical variability. The radar system instrumental error comes from different sources, including hardware, software, algorithms and etc. Radar signal processing plays an important role in radar system and advanced signal processing algorithms may dramatically reduce the radar system errors. In this dissertation, radar system error propagation is analyzed and several advanced signal processing algorithms are proposed to optimize the performance of radar system without increasing the instrument costs. The first part of this dissertation is the development of a time-frequency waveform detector, which is invariant to noise level and stable to a wide range of decay rates. This detector is proposed to discriminate the underdense meteor echoes from the background white Gaussian noise. The performance of this detector is examined using Monte Carlo simulations. The resulting probability of detection is shown to outperform the often used power and energy detectors for the same probability of false alarm. Secondly, estimators to determine the Doppler shift, the decay rate and direction of arrival (DOA) of meteors are proposed and evaluated. The performance of these estimators is compared with the analytically derived Cramer-Rao bound (CRB). The results show that the fast maximum likelihood (FML) estimator for determination of the Doppler shift and decay rate and the spatial spectral method for determination of the DOAs perform best among the estimators commonly used on other radar systems. For most cases, the mean square error (MSE) of the estimator meets the CRB above a 10dB SNR. Thus meteor echoes with an estimated SNR below 10dB are

  2. 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

  3. 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

  4. 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.

  5. Signal Processing Model for Radiation Transport

    SciTech Connect

    Chambers, D H

    2008-07-28

    This note describes the design of a simplified gamma ray transport model for use in designing a sequential Bayesian signal processor for low-count detection and classification. It uses a simple one-dimensional geometry to describe the emitting source, shield effects, and detector (see Fig. 1). At present, only Compton scattering and photoelectric absorption are implemented for the shield and the detector. Other effects may be incorporated in the future by revising the expressions for the probabilities of escape and absorption. Pair production would require a redesign of the simulator to incorporate photon correlation effects. The initial design incorporates the physical effects that were present in the previous event mode sequence simulator created by Alan Meyer. The main difference is that this simulator transports the rate distributions instead of single photons. Event mode sequences and other time-dependent photon flux sequences are assumed to be marked Poisson processes that are entirely described by their rate distributions. Individual realizations can be constructed from the rate distribution using a random Poisson point sequence generator.

  6. 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.

  7. Optimal signal processing for continuous qubit readout

    NASA Astrophysics Data System (ADS)

    Ng, Shilin; Tsang, Mankei

    2014-08-01

    The measurement of a quantum two-level system, or a qubit in modern terminology, often involves an electromagnetic field that interacts with the qubit, before the field is measured continuously and the qubit state is inferred from the noisy field measurement. During the measurement, the qubit may undergo spontaneous transitions, further obscuring the initial qubit state from the observer. Taking advantage of some well-known techniques in stochastic detection theory, here we propose a signal processing protocol that can infer the initial qubit state optimally from the measurement in the presence of noise and qubit dynamics. Assuming continuous quantum-nondemolition measurements with Gaussian or Poissonian noise and a classical Markov model for the qubit, we derive analytic solutions to the protocol in some special cases of interest using Itō calculus. Our method is applicable to multihypothesis testing for robust qubit readout and relevant to experiments on qubits in superconducting microwave circuits, trapped ions, nitrogen-vacancy centers in diamond, semiconductor quantum dots, or phosphorus donors in silicon.

  8. 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.

  9. 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

  10. 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.

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

    PubMed

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

    2010-01-01

    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 of an

  12. Neural mechanisms of spatiotemporal signal processing

    NASA Astrophysics Data System (ADS)

    Khanbabaie Shoub, Shaban (Reza)

    We have studied the synaptic, dendritic, and network mechanisms of spatiotemporal signal processing underlying the computation of visual motion in the avian tectum. Such mechanisms are critical for information processing in all vertebrates, but have been difficult to elucidate in mammals because of anatomical limitations. We have therefore developed a chick tectal slice preparation, which has features that help us circumvent these limitations. Using single-electrode multi-pulse synaptic stimulation experiments we found that the SGC-I cell responds to synaptic stimulation in a binary manner and its response is phasic in a time dependent probabilistic manner over large time scales. Synaptic inputs at two locations typically interact in a mutually exclusive manner when delivered within the "interaction time" of approximately 30 ms. Then we constructed a model of SGC-I cell and the retinal inputs to examine the role of the observed non-linear cellular properties in shaping the response of SGC-I neurons to assumed retinal representations of dynamic spatiotemporal visual stimuli. We found that by these properties, SGC-I cells can classify different stimuli. Especially without the phasic synaptic signal transfer the model SGC-I cell fails to distinguish between the static stationary stimuli and dynamic spatiotemporal stimuli. Based on one-site synaptic response probability and the assumption of independent neighboring dendritic endings we predicted the response probability of SGC-I cells to multiple synaptic inputs. We tested this independence-based model prediction and found that the independency assumption is not valid. The measured SGC-I response probability to multiple synaptic inputs does not increase with the number of synaptic inputs. The presence of GABAergic horizontal cells in layer 5 suggest an inhibitory effect of these cells on the SGC-I retino-tectal synaptic responses. In our experiment we found that the measured SGC-I response probability to multiple

  13. A comparison among different techniques for human ERG signals processing and classification.

    PubMed

    Barraco, R; Persano Adorno, D; Brai, M; Tranchina, L

    2014-02-01

    Feature detection in biomedical signals is crucial for deepening our knowledge about the involved physiological processes. To achieve this aim, many analytic approaches can be applied but only few are able to deal with signals whose time dependent features provide useful clinical information. Among the biomedical signals, the electroretinogram (ERG), that records the retinal response to a light flash, can improve our comprehension of the complex photoreceptoral activities. The present study is focused on the analysis of the early response of the photoreceptoral human system, known as a-wave ERG-component. This wave reflects the functional integrity of the photoreceptors, rods and cones, whose activation dynamics are not yet completely understood. Moreover, since in incipient photoreceptoral pathologies eventual anomalies in a-wave are not always detectable with a "naked eye" analysis of the traces, the possibility to discriminate pathologic from healthy traces, by means of appropriate analytical techniques, could help in clinical diagnosis. In the present paper, we discuss and compare the efficiency of various techniques of signal processing, such as Fourier analysis (FA), Principal Component Analysis (PCA), Wavelet Analysis (WA) in recognising pathological traces from the healthy ones. The investigated retinal pathologies are Achromatopsia, a cone disease and Congenital Stationary Night Blindness, affecting the photoreceptoral signal transmission. Our findings prove that both PCA and FA of conventional ERGs, don't add clinical information useful for the diagnosis of ocular pathologies, whereas the use of a more sophisticated analysis, based on the wavelet transform, provides a powerful tool for routine clinical examinations of patients. PMID:23590981

  14. 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.

  15. Proposal for Memristors in Signal Processing

    NASA Astrophysics Data System (ADS)

    Mouttet, B.

    Recently researchers at Hewlett-Packard have announced the discovery of a new material having resistance switching characteristics and which has been characterized as a fourth fundamental circuit component called the “memristor”[1]. It is proposed to combine such memristors with operational amplifier circuitry and fixed resistor elements so as to form a programmable signal processor capable of selective transmission and multiplexing of multiple signals for applications in communications and programmable drive waveform control.

  16. 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.

  17. 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.

  18. 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.

  19. [The alcoholization process in Latin America. Critical analysis of biomedical and sociological production, 1970-1980 (2)].

    PubMed

    Menéndez, E L

    1984-03-01

    This work analyses the bibliographical production in the sociological and biomedical fields on alcoholization generated within and for Latin America during the seventies. This production is characterized by a unilaterally "pathologizing" outlook, which contrasts with the outlook dominant in the socio-anthropological fields, and which was analysed in a previous work. Empirical and factorial outlook dominate, in both, theory and methodology. They stress again an approach whose serious limitations have already been shown. The dominant technical elements--the sociological and epidemiological inquest--keep on being utilized, in spite of the many criticisms which they have received. Data obtained not only bears little relevance on the problem, but also stresses facts at a level of depth which is not justified, and do not justify, the theoretical framework of analysis. In spite of the fact that unsystematized empirical data and specific research which has been undertaken in other regional areas have made reference to a continual deficit on the part of the health team for the diagnosis and treatment of the alcoholization process; we hardly have any research which can throw light on the scientific and ideological limitations of medical and paramedical actions. Besides, we do not have a systematic analysis of alternative therapeutic strategics. All bibliographical publications refers, in a very biased way, the process of alcoholization to the lower population strata, without any critical reflection on that association. The biomedical dimension, although it utilizes conceptions and viewpoints which have been taken from anthropological and sociological production, this appropiation has meant a modification, which, in fact, has caused a split between the two dominant productions in Latin America: the biomedical and the anthropological one. This split replicates the conflict between models, that operates within other national and international contexts. PMID:6741586

  20. Laser heterodyne interferometric signal processing method based on rising edge locking with high frequency clock signal.

    PubMed

    Zhang, Enzheng; Chen, Benyong; Yan, Liping; Yang, Tao; Hao, Qun; Dong, Wenjun; Li, Chaorong

    2013-02-25

    A novel phase measurement method composed of the rising-edge locked signal processing and the digital frequency mixing is proposed for laser heterodyne interferometer. The rising-edge locked signal processing, which employs a high frequency clock signal to lock the rising-edges of the reference and measurement signals, not only can improve the steepness of the rising-edge, but also can eliminate the error counting caused by multi-rising-edge phenomenon in fringe counting. The digital frequency mixing is realized by mixing the digital interference signal with a digital base signal that is different from conventional frequency mixing with analogue signals. These signal processing can improve the measurement accuracy and enhance anti-interference and measurement stability. The principle and implementation of the method are described in detail. An experimental setup was constructed and a series of experiments verified the feasibility of the method in large displacement measurement with high speed and nanometer resolution.

  1. 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.

  2. 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.

  3. Robust Signal Processing in Living Cells

    PubMed Central

    Steuer, Ralf; Waldherr, Steffen; Sourjik, Victor; Kollmann, Markus

    2011-01-01

    Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations. PMID:22215991

  4. Effects of Organizational Signals on Text-Processing Strategies.

    ERIC Educational Resources Information Center

    Lorch, Robert F., Jr.; Lorch, Elizabeth Pugzles

    1995-01-01

    Two hypotheses about how organizational signals influence text recall were tested with 274 college students who read and recalled a text with or without signals. Results are consistent with the hypothesis that organizational signals induce readers to change their text-processing strategies. (Author/SLD)

  5. Signal processing considerations for low signal to noise ratio laser Doppler and phase Doppler signals

    NASA Technical Reports Server (NTRS)

    Ibrahim, K. M.; Wertheimer, G. D.; Bachalo, William D.

    1991-01-01

    The relative performance of current methods used for estimating the phase and the frequency in LDV and phase Doppler applications in low signal to noise ratio conditions is analyzed. These methods include the Fourier analysis and the correlation techniques. Three methods that use the correlation function for frequency and phase estimations are evaluated in terms of accuracy and speed of processing. These methods include: (1) the frequency estimation using zero crossings counting of the auto-correlation function, (2) the Blackman-Tukey method, and (3) the AutoRegressive method (AR). The relative performance of these methods is evaluated and compared with the Fourier analysis method which provides the optimum performance in terms of the Maximum Likelihood (ML) criteria.

  6. 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

  7. 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.

  8. Signal processing for distributed readout using TESs

    NASA Astrophysics Data System (ADS)

    Smith, Stephen J.; Whitford, Chris H.; Fraser, George W.

    2006-04-01

    We describe optimal filtering algorithms for determining energy and position resolution in position-sensitive Transition Edge Sensor (TES) Distributed Read-Out Imaging Devices (DROIDs). Improved algorithms, developed using a small-signal finite-element model, are based on least-squares minimisation of the total noise power in the correlated dual TES DROID. Through numerical simulations we show that significant improvements in energy and position resolution are theoretically possible over existing methods.

  9. 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.

  10. Frequency domain laser velocimeter signal processor: A new signal processing scheme

    NASA Technical Reports Server (NTRS)

    Meyers, James F.; Clemmons, James I., Jr.

    1987-01-01

    A new scheme for processing signals from laser velocimeter systems is described. The technique utilizes the capabilities of advanced digital electronics to yield a smart instrument that is able to configure itself, based on the characteristics of the input signals, for optimum measurement accuracy. The signal processor is composed of a high-speed 2-bit transient recorder for signal capture and a combination of adaptive digital filters with energy and/or zero crossing detection signal processing. The system is designed to accept signals with frequencies up to 100 MHz with standard deviations up to 20 percent of the average signal frequency. Results from comparative simulation studies indicate measurement accuracies 2.5 times better than with a high-speed burst counter, from signals with as few as 150 photons per burst.

  11. 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.

  12. 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

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

    PubMed

    Casson, Alexander J

    2015-12-17

    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.

  14. 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

  15. 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.

  16. [Research progress of adventitious respiratory sound signal processing].

    PubMed

    Li, Zhenzhen; Wu, Xiaoming

    2013-10-01

    Adventitious respiratory sound signal processing has been an important researching topic in the field of computerized respiratory sound analysis system. In recent years, new progress has been achieved in adventitious respiratory sound signal analysis due to the applications of techniques of non-stationary random signal processing. Algorithm progress of adventitious respiratory sound detections is discussed in detail in this paper. Then the state of art of adventitious respiratory sound analysis is reviewed, and development directions of next phase are pointed out.

  17. Signal-driven computations in speech processing.

    PubMed

    Peña, Marcela; Bonatti, Luca L; Nespor, Marina; Mehler, Jacques

    2002-10-18

    Learning a language requires both statistical computations to identify words in speech and algebraic-like computations to discover higher level (grammatical) structure. Here we show that these computations can be influenced by subtle cues in the speech signal. After a short familiarization to a continuous speech stream, adult listeners are able to segment it using powerful statistics, but they fail to extract the structural regularities included in the stream even when the familiarization is greatly extended. With the introduction of subliminal segmentation cues, however, these regularities can be rapidly captured.

  18. 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.

  19. 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.

  20. 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

  1. [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.

  2. 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.

  3. Processing electrophysiological signals for the monitoring of alertness

    NASA Technical Reports Server (NTRS)

    Lai, D. C.

    1974-01-01

    Mathematical techniques are described for processing EEG signals associated with varying states of alertness. Fast algorithms for implementing real-time computations of alertness estimates were developed. A realization of the phase-distortionless digital filter is presented which approaches real-time filtering and a transform for EEG signals. This transform provides information for the alertness estimates and can be performed in real time. A statistical test for stationarity in EEG signals is being developed that will provide a method for determining the duration of the EEG signals necessary for estimating the short-time power or energy spectra for nonstationary analysis of EEG signals.

  4. 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.

  5. 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.

  6. 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

  7. 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.

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

    PubMed

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

    2012-01-01

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

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. The behavioral neuroscience of anuran social signal processing.

    PubMed

    Wilczynski, Walter; Ryan, Michael J

    2010-12-01

    Acoustic communication is the major component of social behavior in anuran amphibians (frogs and toads) and has served as a neuroethological model for the nervous system's processing of social signals related to mate choice decisions. The male's advertisement or mating call is its most conspicuous social signal, and the nervous system's analysis of the call is a progressive process. As processing proceeds through neural systems, response properties become more specific to the signal and, in addition, neural activity gradually shifts from representing sensory (auditory periphery and brainstem) to sensorimotor (diencephalon) to motor (forebrain) components of a behavioral response. A comparative analysis of many anuran species shows that the first stage in biasing responses toward conspecific signals over heterospecific signals, and toward particular features of conspecific signals, lies in the tuning of the peripheral auditory system. Biases in processing signals are apparent through the brainstem auditory system, where additional feature detection neurons are added by the time processing reaches the level of the midbrain. Recent work using immediate early gene expression as a marker of neural activity suggests that by the level of the midbrain and forebrain, the differential neural representation of conspecific and heterospecific signals involves both changes in mean activity levels across multiple subnuclei, and in the functional correlations among acoustically active areas. Our data show that in frogs the auditory midbrain appears to play an important role in controlling behavioral responses to acoustic social signals by acting as a regulatory gateway between the stimulus analysis of the brainstem and the behavioral and physiological control centers of the forebrain. We predict that this will hold true for other vertebrate groups such as birds and fish that produce acoustic social signals, and perhaps also in fish where electroreception or vibratory sensing

  14. 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.

  15. Processing of physiological signals in automotive research.

    PubMed

    Dambier, Michael; Altmüller, Tobias; Ladstätter, Ulrich

    2006-12-01

    The development of innovative driver assistance systems requires the evaluation of the predisposed hypotheses such as acceptance and driving safety. For this purpose, the conduction of experiments with end-users as subjects is necessary. Analysis and evaluation are based on the recording of numerous sensor values and system variables. Video, gaze and physiological data are recorded for the analysis of gaze distraction and emotional reactions of subjects to system behaviour. In this paper, a modular data streaming and processing architecture is suggested and a concept for this architecture is defined for consistent data evaluation, which integrates off-the-shelf products for data analysis and evaluation.

  16. 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.

  17. 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.

  18. 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.}

  19. 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.

  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. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Biomedical Telectrodes

    NASA Technical Reports Server (NTRS)

    Shepherd, C. K.

    1989-01-01

    Compact transmitters eliminate need for wires to monitors. Biomedical telectrode is small electronic package that attaches to patient in manner similar to small adhesive bandage. Patient wearing biomedical telectrodes moves freely, without risk of breaking or entangling wire connections. Especially beneficial to patients undergoing electrocardiographic monitoring in intensive-care units in hospitals. Eliminates nuisance of coping with wire connections while dressing and going to toilet.

  6. 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.

  7. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-12-31

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  8. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-01-01

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Variable-time-delay optical coherent transient signal processing.

    PubMed

    Merkel, K D; Babbitt, W R; Anderson, K E; Wagner, K H

    1999-10-15

    A technique is proposed and experimentally demonstrated that achieves simultaneous optical pattern waveform storage and programmable time delay for continuous real-time signal processing by use of optical coherent transient technology. We achieve variable-time-delay and broadband signal processing by frequency shifting of two chirped programming pulses, the chirp rate of one being twice that of the other, without using brief reference pulses and without changing the timing of the programming sequence. We demonstrate the technique experimentally in Tm(3+): YAG at 5 K for 40-MHz chirps by performing temporal signal convolution with true-time delays that vary over a 250-ns range.

  15. 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.

  16. 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

    2015-01-01

    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.

  17. New frontiers in biomedical science and engineering during 2014-2015.

    PubMed

    Liu, Feng; Lee, Dong-Hoon; Lagoa, Ricardo; Kumar, Sandeep

    2015-01-01

    The International Conference on Biomedical Engineering and Biotechnology (ICBEB) is an international meeting held once a year. This, the fourth International Conference on Biomedical Engineering and Biotechnology (ICBEB2015), will be held in Shanghai, China, during August 18th-21st, 2015. This annual conference intends to provide an opportunity for researchers and practitioners at home and abroad to present the most recent frontiers and future challenges in the fields of biomedical science, biomedical engineering, biomaterials, bioinformatics and computational biology, biomedical imaging and signal processing, biomechanical engineering and biotechnology, etc. The papers published in this issue are selected from this Conference, which witness the advances in biomedical engineering and biotechnology during 2014-2015.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Reaching for the cloud: on the lessons learned from grid computing technology transfer process to the biomedical community.

    PubMed

    Mohammed, Yassene; Dickmann, Frank; Sax, Ulrich; von Voigt, Gabriele; Smith, Matthew; Rienhoff, Otto

    2010-01-01

    Natural scientists such as physicists pioneered the sharing of computing resources, which led to the creation of the Grid. The inter domain transfer process of this technology has hitherto been an intuitive process without in depth analysis. Some difficulties facing the life science community in this transfer can be understood using the Bozeman's "Effectiveness Model of Technology Transfer". Bozeman's and classical technology transfer approaches deal with technologies which have achieved certain stability. Grid and Cloud solutions are technologies, which are still in flux. We show how Grid computing creates new difficulties in the transfer process that are not considered in Bozeman's model. We show why the success of healthgrids should be measured by the qualified scientific human capital and the opportunities created, and not primarily by the market impact. We conclude with recommendations that can help improve the adoption of Grid and Cloud solutions into the biomedical community. These results give a more concise explanation of the difficulties many life science IT projects are facing in the late funding periods, and show leveraging steps that can help overcoming the "vale of tears". PMID:20841902

  3. Reaching for the cloud: on the lessons learned from grid computing technology transfer process to the biomedical community.

    PubMed

    Mohammed, Yassene; Dickmann, Frank; Sax, Ulrich; von Voigt, Gabriele; Smith, Matthew; Rienhoff, Otto

    2010-01-01

    Natural scientists such as physicists pioneered the sharing of computing resources, which led to the creation of the Grid. The inter domain transfer process of this technology has hitherto been an intuitive process without in depth analysis. Some difficulties facing the life science community in this transfer can be understood using the Bozeman's "Effectiveness Model of Technology Transfer". Bozeman's and classical technology transfer approaches deal with technologies which have achieved certain stability. Grid and Cloud solutions are technologies, which are still in flux. We show how Grid computing creates new difficulties in the transfer process that are not considered in Bozeman's model. We show why the success of healthgrids should be measured by the qualified scientific human capital and the opportunities created, and not primarily by the market impact. We conclude with recommendations that can help improve the adoption of Grid and Cloud solutions into the biomedical community. These results give a more concise explanation of the difficulties many life science IT projects are facing in the late funding periods, and show leveraging steps that can help overcoming the "vale of tears".

  4. 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.

  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. Ultralow-power electronics for biomedical applications.

    PubMed

    Chandrakasan, Anantha P; Verma, Naveen; Daly, Denis C

    2008-01-01

    The electronics of a general biomedical device consist of energy delivery, analog-to-digital conversion, signal processing, and communication subsystems. Each of these blocks must be designed for minimum energy consumption. Specific design techniques, such as aggressive voltage scaling, dynamic power-performance management, and energy-efficient signaling, must be employed to adhere to the stringent energy constraint. The constraint itself is set by the energy source, so energy harvesting holds tremendous promise toward enabling sophisticated systems without straining user lifestyle. Further, once harvested, efficient delivery of the low-energy levels, as well as robust operation in the aggressive low-power modes, requires careful understanding and treatment of the specific design limitations that dominate this realm. We outline the performance and power constraints of biomedical devices, and present circuit techniques to achieve complete systems operating down to power levels of microwatts. In all cases, approaches that leverage advanced technology trends are emphasized.

  7. 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.

  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. 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.

  10. Synthesizing oncogenic signal-processing systems that function as both "signal counters" and "signal blockers" in cancer cells.

    PubMed

    Liu, Yuchen; Huang, Weiren; Zhou, Dexi; Han, Yonghua; Duan, Yonggang; Zhang, Xiaoyue; Zhang, Hu; Jiang, Zhimao; Gui, Yaoting; Cai, Zhiming

    2013-07-01

    RNA-protein interaction plays a significant role in regulating eukaryotic translation. This phenomenon raises questions about the ability of artificial biological systems to take the advantage of protein-RNA interaction. Here, we designed an oncogenic signal-processing system expressing both a Renilla luciferase reporter gene controlled by RNA-protein interaction in its 5'-untranslated region (5'-UTR) and a Firefly luciferase normalization gene. To test the ability of the designed system, we then constructed vectors targeting the nuclear factor-κB (NF-κB) or the β-catenin signal. We found that the inhibition (%) of luciferase expression was correlated to the targeted protein content, allowing quantitative measurement of oncogenic signal intensity in cancer cells. The systems inhibited the expression of oncogenic signal downstream genes and induced bladder cancer cell proliferation inhibition and apoptosis without affecting normal urothelial cells. Compared to traditional methods (ELISA and quantitative immunoblotting), the bio-systems provided highly accurate, consistent, and reproducible quantification of protein signals and were able to discriminate between cancerous and non-cancerous cells. In conclusion, the synthetic systems function as both "signal counters" and "signal blockers" in cancer cells. This approach provides a synthetic biology platform for oncogenic signal measurement and cancer treatment.

  11. Signal processing by its coil zipper domain activates IKKγ

    PubMed Central

    Bloor, Stuart; Ryzhakov, Grigor; Wagner, Sebastian; Butler, P. Jonathan G.; Smith, David L.; Krumbach, Rebekka; Dikic, Ivan; Randow, Felix

    2008-01-01

    NF-κB activation occurs upon degradation of its inhibitor I-κB and requires prior phosphorylation of the inhibitor by I-κB kinase (IKK). Activity of IKK is governed by its noncatalytic subunit IKKγ. Signaling defects due to missense mutations in IKKγ have been correlated to its inability to either become ubiquitylated or bind ubiquitin noncovalently. Because the relative contribution of these events to signaling had remained unknown, we have studied mutations in the coil-zipper (CoZi) domain of IKKγ that either impair signaling or cause constitutive NF-κB activity. Certain signaling-deficient alleles neither bound ubiquitin nor were they ubiquitylated by TRAF6. Introducing an activating mutation into those signaling-impaired alleles restored their ubiquitylation and created mutants constitutively activating NF-κB without repairing the ubiquitin-binding defect. Constitutive activity therefore arises downstream of ubiquitin binding but upstream of ubiquitylation. Such constitutive activity reveals a signal-processing function for IKKγ beyond that of a mere ubiquitin-binding adaptor. We propose that this signal processing may involve homophilic CoZi interactions as suggested by the enhanced affinity of CoZi domains from constitutively active IKKγ. PMID:18216269

  12. 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.

  13. 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.

  14. 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.

  15. Scanning near-field optical microscopy signal processing and resolution.

    PubMed

    Grosges, Thomas; Barchiesi, Dominique

    2007-04-20

    To increase the signal-to-noise ratio and to remove the spatially slow varying signals, a lock-in amplifier is often used in scanning probe microscopy. The signal reconstructed from the lock-in data contains the contributions of the evanescent and homogeneous waves that are mixed in the near-field zone (i.e., at a very short distance). The resolution is determined and a method is given to suppress the useless background information. Experimental images of nanoparticles are processed.

  16. 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.

  17. 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

  18. Research on mud pulse signal data processing in MWD

    NASA Astrophysics Data System (ADS)

    Tu, Bing; Li, De Sheng; Lin, En Huai; Ji, Miao Miao

    2012-12-01

    Wireless measure while drilling (MWD) transmits data by using mud pulse signal ; the ground decoding system collects the mud pulse signal and then decodes and displays the parameters under the down-hole according to the designed encoding rules and the correct detection and recognition of the ground decoding system towards the received mud pulse signal is one kind of the key technology of MWD. This paper introduces digit of Manchester encoding that transmits data and the format of the wireless transmission of data under the down-hole and develops a set of ground decoding systems. The ground decoding algorithm uses FIR (Finite impulse response) digital filtering to make de-noising on the mud pulse signal, then adopts the related base value modulating algorithm to eliminate the pump pulse base value of the denoised mud pulse signal, finally analyzes the mud pulse signal waveform shape of the selected Manchester encoding in three bits cycles, and applies the pattern similarity recognition algorithm to the mud pulse signal recognition. The field experiment results show that the developed device can make correctly extraction and recognition for the mud pulse signal with simple and practical decoding process and meet the requirements of engineering application.

  19. 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.

  20. Digital processing of RF signals from optical frequency combs

    NASA Astrophysics Data System (ADS)

    Cizek, Martin; Smid, Radek; Buchta, Zdeněk.; Mikel, Břetislav; Lazar, Josef; Cip, Ondřej

    2013-01-01

    The presented work is focused on digital processing of beat note signals from a femtosecond optical frequency comb. The levels of mixing products of single spectral components of the comb with CW laser sources are usually very low compared to products of mixing all the comb components together. RF counters are more likely to measure the frequency of the strongest spectral component rather than a weak beat note. Proposed experimental digital signal processing system solves this problem by analyzing the whole spectrum of the output RF signal and using software defined radio (SDR) algorithms. Our efforts concentrate in two main areas: Firstly, using digital servo-loop techniques for locking free running continuous laser sources on single components of the fs comb spectrum. Secondly, we are experimenting with digital signal processing of the RF beat note spectrum produced by f-2f 1 technique used for assessing the offset and repetition frequencies of the comb, resulting in digital servo-loop stabilization of the fs comb. Software capable of computing and analyzing the beat-note RF spectrums using FFT and peak detection was developed. A SDR algorithm performing phase demodulation on the f- 2f signal is used as a regulation error signal source for a digital phase-locked loop stabilizing the offset frequency of the fs comb.

  1. 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.

  2. 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

  3. Optimal Conditions for the Control Problem Associated to a Biomedical Process

    NASA Astrophysics Data System (ADS)

    Bundǎu, O.; Juratoni, A.; Chevereşan, A.

    2010-09-01

    This paper considers a mathematical model of infectious disease of SIS type. We will analyze the problem of minimizing the cost of diseases trough medical treatment. Mathematical modeling of this process leads to an optimal control problem with a finite horizon. The necessary conditions for optimality are given. Using the optimality conditions we prove the existence, uniqueness and stability of the steady state for a differential equations system.

  4. 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).

  5. 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.

  6. ISLE (Image and Signal Processing LISP Environment) reference manual

    SciTech Connect

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

    1990-01-01

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

  7. 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

  8. 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.

  9. 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.

  10. The Savant Hypothesis: is autism a signal-processing problem?

    PubMed

    Fabricius, Thomas

    2010-08-01

    Autism is being investigated through many different approaches. This paper suggests the genetic, perceptual, cognitive, and histological findings ultimately manifest themselves as variations of the same signal-processing problem of defective compression. The Savant Hypothesis is formulated from first principles of both mathematical signal-processing and primary neuroscience to reflect the failure of compression. The Savant Hypothesis is applied to the problem of autism in a surprisingly straightforward application. The enigma of the autistic savant becomes intuitive when observed from this approach.

  11. 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.

  12. 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.

  13. 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.

  14. Design of multichannel filter banks for subband coding of audio signals using multirate signal processing techniques

    NASA Astrophysics Data System (ADS)

    Goel, Aditya

    2007-09-01

    This paper presents a design technique for multi channel filter banks for subband coding of audio signal. In sub-band coding, the speech is first split into frequency bands using a bank of bandpass filters. The individual band pass signals are then decimated by a factor 'N' and encoded for transmission. A filter bank is a collection of bandpass filters, all processing the same input signal. The important parameters in sub-band coders are the number of frequency bands and the frequency range of the system, and the sub-band coding technique. The total number of filters required are 2N. The sub-band signals can be reconstructed perfectly with linear-phase FIR filters. The filter bank is designed so as to overcome the effect of non-ideal transition-band and stop-bands filtering. With real-world filters, the non-zero signal energy in the transition and stop bands is reflected back into the pass-band during the interpolation process at the receiver causing aliasing. This aliasing is canceled in the filter bank during reconstruction of the signal. This paper deals with the designing of 8 band filter banks and coding the subband signals at various bit rates using DPCM technique. In this we used a sampling rate of 44.1Khz. The first two bands are coded at 8 bits/sample, next three bands are coded at 4bits/sample and last 3 bands are coded at 2 bits/sample. Lower frequency spectrum is encoded at higher bit rate, as more energy is concentrated in the lower range. Simulated results using MATLAB Software shows that a compression ratio of 3.76:1 is achieved with perceptual quality. Beyond this we find that the signal quality degraded to reasonable extent, which is not recommended. There has to be a tradeoff between the compression ratio and Quality of transmitted signal.

  15. 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

  16. 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

  17. 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/].

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

    SciTech Connect

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

    1987-10-21

    Conventional software interfaces that use 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). As an alternative, ''functional language'' interfaces provide features such as command nesting for a more natural interaction with the data. The Image and Signal LISP Environment (ISLE) is an example of an interpreted functional language interface based on common LISP. Advantages of ISLE include multidimensional and multiple data-type independence through dispatching functions, dynamic loading of new functions, and connections to artificial intelligence (AI) software. 10 refs.

  19. 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.

  20. Rare-event detection and process control for a biomedical application

    NASA Astrophysics Data System (ADS)

    Kegelmeyer, Laura N.

    1990-05-01

    Medical researchers are seeking a method for detecting chromosomal abnormalities in unborn children without requiring invasive procedures such as anmiocentesis. Software has been developed to utilize a light microscope to detect fetal cells that occur with very low frequency in a sample of maternal blood. This rare event detection involves dividing a microscope slide containing a maternal blood sample into as many as 40,000 fields, automatically focusing on each field-of-view, and searching for fetal cells. Size and shape information is obtained by calculating a figure of merit through various binary operations and is used to discriminate fetal cells from noise and artifacts. Once the rare fetal cells are located, the slide is automatically rescanned to count the total number of cells on the slide. Binary operations and image processing hardware are used as much as possible to reduce the total amount of time to analyze one slide. Current runtime for scoring one full slide is about four hours, with motorized stage movement and focusing being the speed-limiting factors. Fetal cells occurring with a frequency of less than 1 in 200,000 maternal cells have been consistently found with this system.

  1. 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.

  2. Extraction of CYP chemical interactions from biomedical literature using natural language processing methods.

    PubMed

    Jiao, Dazhi; Wild, David J

    2009-02-01

    This paper proposes a system that automatically extracts CYP protein and chemical interactions from journal article abstracts, using natural language processing (NLP) and text mining methods. In our system, we employ a maximum entropy based learning method, using results from syntactic, semantic, and lexical analysis of texts. We first present our system architecture and then discuss the data set for training our machine learning based models and the methods in building components in our system, such as part of speech (POS) tagging, Named Entity Recognition (NER), dependency parsing, and relation extraction. An evaluation of the system is conducted at the end, yielding very promising results: The POS, dependency parsing, and NER components in our system have achieved a very high level of accuracy as measured by precision, ranging from 85.9% to 98.5%, and the precision and the recall of the interaction extraction component are 76.0% and 82.6%, and for the overall system are 68.4% and 72.2%, respectively.

  3. 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

  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. 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.

  6. 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.

  7. 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

  8. 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

  9. 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).

  10. Melt-processable hydrophobic acrylonitrile-based copolymer systems with adjustable elastic properties designed for biomedical applications.

    PubMed

    Cui, J; Trescher, K; Kratz, K; Jung, F; Hiebl, B; Lendlein, A

    2010-01-01

    Acrylonitrile-based polymer systems (PAN) are comprehensively explored as versatile biomaterials having various potential biomedical applications, such as membranes for extra corporal devices or matrixes for guided skin reconstruction. The surface properties (e.g. hydrophilicity or charges) of such materials can be tailored over a wide range by variation of molecular parameters such as different co-monomers or their sequence structure. Some of these materials show interesting biofunctionalities such as capability for selective cell cultivation. So far, the majority of AN-based copolymers, which were investigated in physiological environments, were processed from the solution (e.g. membranes), as these materials are thermo-sensitive and might degrade when heated. In this work we aimed at the synthesis of hydrophobic, melt-processable AN-based copolymers with adjustable elastic properties for preparation of model scaffolds with controlled pore geometry and size. For this purpose a series of copolymers from acrylonitrile and n-butyl acrylate (nBA) was synthesized via free radical copolymerisation technique. The content of nBA in the copolymer varied from 45 wt% to 70 wt%, which was confirmed by 1H-NMR spectroscopy. The glass transition temperatures (Tg) of the P(AN-co-nBA) copolymers determined by differential scanning calorimetry (DSC) decreased from 58 degrees C to 20 degrees C with increasing nBA-content, which was in excellent agreement with the prediction of the Gordon-Taylor equation based on the Tgs of the homopolymers. The Young's modulus obtained in tensile tests was found to decrease significantly with rising nBA-content from 1062 MPa to 1.2 MPa. All copolymers could be successfully processed from the melt with processing temperatures ranging from 50 degrees C to 170 degrees C, whereby thermally induced decomposition was only observed at temperatures higher than 320 degrees C in thermal gravimetric analysis (TGA). Finally, the melt processed P

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. Digital Signal Processing in Acoustics--Part 2.

    ERIC Educational Resources Information Center

    Davies, H.; McNeill, D. J.

    1986-01-01

    Reviews the potential of a data acquisition system for illustrating the nature and significance of ideas in digital signal processing. Focuses on the fast Fourier transform and the utility of its two-channel format, emphasizing cross-correlation and its two-microphone technique of acoustic intensity measurement. Includes programing format. (ML)

  16. Cancer systems biology: signal processing for cancer research.

    PubMed

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

    2011-04-01

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

  17. An Interactive Graphics Program for Investigating Digital Signal Processing.

    ERIC Educational Resources Information Center

    Miller, Billy K.; And Others

    1983-01-01

    Describes development of an interactive computer graphics program for use in teaching digital signal processing. The program allows students to interactively configure digital systems on a monitor display and observe their system's performance by means of digital plots on the system's outputs. A sample program run is included. (JN)

  18. 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…

  19. 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.

  20. SEMICONDUCTOR TECHNOLOGY A signal processing method for the friction-based endpoint detection system of a CMP process

    NASA Astrophysics Data System (ADS)

    Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang

    2010-12-01

    A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Mass spectral peak distortion due to Fourier transform signal processing.

    PubMed

    Rockwood, Alan L; Erve, John C L

    2014-12-01

    Distortions of peaks can occur when one uses the standard method of signal processing of data from the Orbitrap and other FT-based methods of mass spectrometry. These distortions arise because the standard method of signal processing is not a linear process. If one adds two or more functions, such as time-dependent signals from a Fourier transform mass spectrometer and performs a linear operation on the sum, the result is the same as if the operation was performed on separate functions and the results added. If this relationship is not valid, the operation is non-linear and can produce unexpected and/or distorted results. Although the Fourier transform itself is a linear operator, the standard algorithm for processing spectra in Fourier transform-based methods include non-linear mathematical operators such that spectra processed by the standard algorithm may become distorted. The most serious consequence is that apparent abundances of the peaks in the spectrum may be incorrect. In light of these considerations, we performed theoretical modeling studies to illustrate several distortion effects that can be observed, including abundance distortions. In addition, we discuss experimental systems where these effects may manifest, including suggested systems for study that should demonstrate these peak distortions. Finally, we point to several examples in the literature where peak distortions may be rationalized by the phenomena presented here.

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

    PubMed Central

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

    2015-01-01

    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

  7. 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

  8. Asynchronous spiking photonic neuron for lightwave neuromorphic signal processing.

    PubMed

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

    2012-08-15

    We developed an asynchronous spiking photonic neuron that forms the basic building block for hybrid analog/digital lightwave neuromorphic processing. Our approach enables completely asynchronous spiking in response to input signals while maximizing the throughput relative to synchronous approaches. Asynchronous operation is achieved by generating the spike source for the photonic neuron through four-wave mixing. This hybrid analog/digital photonic neuron has an electro-absorption modulator as the temporal integration unit for analog processing, while the digital processing portion employs optical thresholding in a highly Ge-doped nonlinear loop mirror.

  9. Application of image processing technology to 2-D signal processing (Abstract Only)

    NASA Astrophysics Data System (ADS)

    Meckley, John R.

    1991-04-01

    The analytical and processing developments in the field of Image Understanding over the last 15 years have led to the creation of a set of processing tools for the detection, characterization (feature extraction), and classification of 2 dimensional signals. This set of tools is applicable to 2 dimensional signals other than the traditional "image" type signals. In particular, for passive sonar detection processing several 2 dimensional signal transforms are generated from the 1 dimensional sensor time series data. These transforms are selected in order to concentrate signal energy locally within the 2 dimensional transform. A classic example is the Lofargram which is a grequency versus time transform of the time series data. If the acoutic source is emitting tones (for example from machinery) then the Lofargram will contain line like structures.

  10. 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.

  11. Synthetic aperture radar signal processing on the MPP

    NASA Astrophysics Data System (ADS)

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

    1987-07-01

    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.

  12. 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.

  13. 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

  14. 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.

  15. Signal Processing in Periodically Forced Gradient Frequency Neural Networks.

    PubMed

    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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. Nonlinear signal processing of electroencephalograms for automated sleep monitoring

    NASA Astrophysics Data System (ADS)

    Wilson, D.; Rowlands, D. D.; James, Daniel A.; Cutmore, T.

    2005-02-01

    An automated classification technique is desirable to identify the different stages of sleep. In this paper a technique for differentiating the characteristics of each sleep phase has been developed. This is an ideal pre-processor stage for classifying systems such as neural networks. A wavelet based continuous Morlet transform was developed to analyse the EEG signal in both the time and frequency domain. Test results using two 100 epoch EEG test data sets from pre-recorded EEG data are presented. Key rhythms in the EEG signal were identified and classified using the continuous wavelet transform. The wavelet results indicated each sleep phase contained different rhythms and artefacts (noise from muscle movement in the EEG); providing proof that an EEG can be classified accordingly. The coefficients founded by the wavelet transform have been emphasised by statistical techniques. Hypothesis testing was used to highlight major differences between adjacent sleep stages. Various signal processing methods such as power spectrum density and the discrete wavelet transform have been used to emphasise particular characteristics in an EEG. By implementing signal processing methods on an EEG data set specific rules for each sleep stage have been developed suitable for a neural network classification solution.

  2. 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.

  3. 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

  4. Fetal QRS extraction from abdominal recordings via model-based signal processing and intelligent signal merging.

    PubMed

    Haghpanahi, Masoumeh; Borkholder, David A

    2014-08-01

    Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother's abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice.

  5. 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.

  6. Integrated electronics for peripheral nerve recording and signal processing.

    PubMed

    Limnuson, Kanokwan; Tyler, Dustin J; Mohseni, Pedram

    2009-01-01

    This paper describes the integrated circuit implementation of an electronic system for peripheral nerve recording and signal processing. Specifically, the system aims to record and condition neural activity from the phrenic nerve as a good indicator for breathing, and generate a stimulus trigger signal for a laryngeal pacemaker device to reanimate a paralyzed muscle with electrical stimulation paced with respiration. The 2.2 x 2.2-mm(2) integrated circuit is fabricated using the AMI 1.5 microm 2P/2M n-well CMOS process, and consumes 1 mW from +/-1.5 V. System architecture, circuit design, simulation results, and measurement data in benchtop experiments are presented.

  7. TOF-LIDAR signal processing using the CFAR detector

    NASA Astrophysics Data System (ADS)

    Ogawa, Takashi; Wanielik, Gerd

    2016-09-01

    In recent years, the lidar sensor has been receiving greater attention as being one of the prospective sensors for future intelligent vehicles. In order to enable advanced applications in a variety of road environments, it has become more important to detect various objects at a wider distance. Therefore, in this research we have focused on lidar signal processing to detect low signal-to-noise ratio (SNR) targets and proposed a higher sensitive detector. The detector is based on the constant false alarm rate (CFAR) processing framework in which an additional functionality of adaptive intensity integration is incorporated. Fundamental results through static experiments have shown a significant advantage in the detection performance in comparison to a conventional detector with constant thresholding.

  8. 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.

  9. Signal processing for Internet video streaming: a review

    NASA Astrophysics Data System (ADS)

    Lu, Jian

    2000-04-01

    Despite the commercial success, video streaming remains a black art owing to its roots in proprietary commercial development. As such, many challenging technological issues that need to be addressed are not even well understood. The purpose of this paper is to review several important signal processing issues related to video streaming, and put them in the context of a client-server based media streaming architecture on the Internet. Such a context is critical, as we shall see that a number of solutions proposed by signal processing researchers are simply unrealistic for real-world video streaming on the Internet. We identify a family of viable solutions and evaluate their pros and cons. We further identify areas of research that have received less attention and point to the problems to which a better solution is eagerly sought by the industry.

  10. Biomedical applications of dipeptides and tripeptides.

    PubMed

    Santos, Sara; Torcato, Inês; Castanho, Miguel A R B

    2012-01-01

    Peptides regulate many physiological processes, acting at some sites as endocrine or paracrine signals and at others as neurotransmitters or growth factors, for instance. These molecules represent a major evolution in medical and industrial fields, as it is becoming mandatory to design and exploit molecules that do not necessarily fit the description of classical drug classes. The list of peptides with potential biomedical applications is huge and is growing each year. These biomedical applications range from uses as drugs to flavor-active peptides as ingredients in natural health products, nutraceuticals and functional foods. Among the peptide family, dipeptides and tripeptides are very appealing for drug discovery and development because of their cost-effectiveness, possibility of oral administration, and simplicity to perform molecular structural and quantitative structure-activity studies. Our objective is to review different actual and future uses of dipeptides and tripeptides as well as the major advances and obstacles in this growing area. PMID:23193593

  11. Optoelectronic signal processing using finite impulse response neural networks

    NASA Astrophysics Data System (ADS)

    H. B. Xavier da Silveira, Paulo Eduardo

    2001-08-01

    This thesis investigates the use of finite impulse response neural network as the computational algorithm for efficient optoelectronic signal processing. The study begins with the analysis and development of different suitable algorithms, followed by the optoelectronic design of single-layer and multi-layer architectures, and it is concluded with the presentation of the results of a successful experimental implementation. First, finite impulse response adaptive filters and neural networks-the algorithmic building blocks-are introduced, followed by a description of finite impulse response neural networks. This introduction is followed by a historical background, describing early optoelectronic implementations of these algorithms. Next, different algorithms capable of temporal back-propagation are derived in detail, including a novel modification to the conventional algorithm, called delayed-feedback back- propagation. Based on these algorithms, different optoelectronic processors making use of adaptive volume holograms and three-dimensional optical processing are developed. Two single-layer architectures are presented: the input delay plane architecture and the output delay plane architecture. By combining them it is possible to implement both forward and backward propagation in two complementary multi-layer architectures: the first making use of the conventional temporal back-propagation and the second making use of delayed feedback back-propagation. Next, emphasis is given to a specific application: the processing of signals from adaptive antenna arrays. This research is initiated by computer simulations of different scenarios with multiple broadband signals and jammers, in planar and circular arrays, studying issues such as the effect of modulator non-linearities to the performance of the array, and the relation between the number of jammers and the final nulling depth. Two sets of simulations are presented: the first set applied to RF antenna arrays and the

  12. 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.

  13. Biomedical informatics and translational medicine.

    PubMed

    Sarkar, Indra Neil

    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

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Interactions between visceral afferent signaling and stimulus processing.

    PubMed

    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

  2. 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

  3. Signal processing and tracking of arrivals in ocean acoustic tomography.

    PubMed

    Dzieciuch, Matthew A

    2014-11-01

    The signal processing for ocean acoustic tomography experiments has been improved to account for the scattering of the individual arrivals. The scattering reduces signal coherence over time, bandwidth, and space. In the typical experiment, scattering is caused by the random internal-wave field and results in pulse spreading (over arrival-time and arrival-angle) and wander. The estimator-correlator is an effective procedure that improves the signal-to-noise ratio of travel-time estimates and also provides an estimate of signal coherence. The estimator-correlator smoothes the arrival pulse at the expense of resolution. After an arrival pulse has been measured, it must be associated with a model arrival, typically a ray arrival. For experiments with thousands of transmissions, this is a tedious task that is error-prone when done manually. An error metric that accounts for peak amplitude as well as travel-time and arrival-angle can be defined. The Viterbi algorithm can then be adapted to the task of automated peak tracking. Repeatable, consistent results are produced that are superior to a manual tracking procedure. The tracking can be adjusted by tuning the error metric in logical, quantifiable manner. PMID:25373953

  4. Signal processing and tracking of arrivals in ocean acoustic tomography.

    PubMed

    Dzieciuch, Matthew A

    2014-11-01

    The signal processing for ocean acoustic tomography experiments has been improved to account for the scattering of the individual arrivals. The scattering reduces signal coherence over time, bandwidth, and space. In the typical experiment, scattering is caused by the random internal-wave field and results in pulse spreading (over arrival-time and arrival-angle) and wander. The estimator-correlator is an effective procedure that improves the signal-to-noise ratio of travel-time estimates and also provides an estimate of signal coherence. The estimator-correlator smoothes the arrival pulse at the expense of resolution. After an arrival pulse has been measured, it must be associated with a model arrival, typically a ray arrival. For experiments with thousands of transmissions, this is a tedious task that is error-prone when done manually. An error metric that accounts for peak amplitude as well as travel-time and arrival-angle can be defined. The Viterbi algorithm can then be adapted to the task of automated peak tracking. Repeatable, consistent results are produced that are superior to a manual tracking procedure. The tracking can be adjusted by tuning the error metric in logical, quantifiable manner.

  5. A Signal Processing Analysis of Purkinje Cells in vitro

    PubMed Central

    Abrams, Ze'ev R.; Warrier, Ajithkumar; Trauner, Dirk; Zhang, Xiang

    2010-01-01

    Cerebellar Purkinje cells in vitro fire recurrent sequences of Sodium and Calcium spikes. Here, we analyze the Purkinje cell using harmonic analysis, and our experiments reveal that its output signal is comprised of three distinct frequency bands, which are combined using Amplitude and Frequency Modulation (AM/FM). We find that the three characteristic frequencies – Sodium, Calcium and Switching – occur in various combinations in all waveforms observed using whole-cell current clamp recordings. We found that the Calcium frequency can display a frequency doubling of its frequency mode, and the Switching frequency can act as a possible generator of pauses that are typically seen in Purkinje output recordings. Using a reversibly photo-switchable kainate receptor agonist, we demonstrate the external modulation of the Calcium and Switching frequencies. These experiments and Fourier analysis suggest that the Purkinje cell can be understood as a harmonic signal oscillator, enabling a higher level of interpretation of Purkinje signaling based on modern signal processing techniques. PMID:20508748

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. Multiplexed interferometric fiber-optic sensors with digital signal processing.

    PubMed

    Sadkowski, R; Lee, C E; Taylor, H F

    1995-09-01

    A microcontroller-based digital signal processing system developed for use with fiber-optic sensors for measuring pressure in internal combustion engines is described. A single distributed feedback laser source provides optical power for four interferometric sensors. The laser current is repetitively modulated so that its optical frequency is nearly a linear function of time over most of a cycle. The interferometer phase shift is proportional to the elapsed time from the initiation of a sawtooth until the sensor output signal level crosses a threshold value proportional to the laser output power. This elapsed time, assumed to vary linearly with the combustion chamber pressure, is determined by the use of a digital timer-counter. The system has been used with fiber Fabry-Perot interferometer transducers for in-cylinder pressure measurement on a four-cylinder gasoline-powered engine.

  13. The EVLA Correlator - Signal Processing for Ultra-Sensitive Astronomy

    NASA Astrophysics Data System (ADS)

    Dewdney, P. E.; Carlson, B. R.

    2000-05-01

    Companion papers by the EVLA team illustrate the power of the EVLA, which can be enabled only by the most powerful, flexible correlator conceived to date. Moreover, since the correlator will be expected to process signals containing interference, it must be robust to radio frequency interference. We propose to build a correlator to process signals from up to 40 antennas in eight independently tunable, 2 GHz wide IF-bands (typically four left and four right polarizations). This will provide the basic continuum sensitivity needed to explore the high red-shift objects of the ``Evolving Universe'' or the weak polarized signals of the ``Magnetic Universe''. High spectral resolution confers the ability to observe very narrow spectral lines or to carry out esoteric planetary radar observations. Large numbers of channels permit searches for highly red-shifted spectral lines over large volumes of the universe at once or simultaneous observations of multiple spectral lines in the ``Obscured Universe''. We expect to be able to provide 16384 channels per baseline that can be flexibly distributed over all the IF-bands or concentrated in very narrow sub-bands. Objects in the ``Transient Universe'', from pulsars to solar bursts can be accomodated by 10 ms integration periods, asynchronous triggering of short observation ``bursts'', and up to 1024 pulsar ``phase bins'' per baseline. Strong signals from astronomical masers, the sun, and interference require spectral dynamic range of >105, which combined with high spectral resolution, will permit the expurgation of interference. These are the most important specifications needed to realize the potential of the EVLA. We expect to be able to meet them, using an innovative correlator architecture.

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. An adaptive signal-processing approach to online adaptive tutoring.

    PubMed

    Bergeron, Bryan; Cline, Andrew

    2011-01-01

    Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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

  5. Social signal processing for studying parent-infant interaction.

    PubMed

    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.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. Biomedical electronics: potentialities and problems.

    PubMed

    LEDLEY, R S; LUSTED, L B

    1962-01-19

    The present annual expenditure in the biomedical sciences, now less than 2 percent of the funds appropriated for defense, must be significantly increased if the great gain that can result from the adequate application of electronic technology in biomedical science is to be realized. Such use of electronics in biomedical science holds promise of tremendous advances in the study of the origins of the life processes; it may result in spectacular advances in medical science, which could have a definite effect on individual health and longevity; it might pave the way for the discovery and development of whole new technologies based on intimate knowledge of biological processes. Great strides can be made in surmounting the major obstacles by combating apathy, through making the public and the industrial community aware of the potentialities of modern biomedical research, and by giving scientists adequate cross-disciplinary training and using the abilities of those so trained (1).

  11. 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

  12. 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.

  13. 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.

  14. Septo-hippocampal signal processing: breaking the code.

    PubMed

    Tsanov, Marian

    2015-01-01

    The septo-hippocampal connections appear to be a key element in the neuromodulatory cholinergic control of the hippocampal neurons. The cholinergic neuromodulation is well established in shifting behavioral states of the brain. The pacemaker role of medial septum in the limbic theta rhythm is demonstrated by lesions and pharmacological manipulations of GABAergic neurons, yet the link between the activity of different septal neuronal classes and limbic theta rhythm is not fully understood. We know even less about the information transfer between the medial septum and hippocampus--is there a particular kind of processed information that septo-hippocampal pathways transmit? This review encompasses fundamental findings together with the latest data of septo-hippocampal signal processing to tackle the frontiers of our understanding about the functional significance of medial septum to the hippocampal formation.

  15. Phase resolved digital signal processing in optical coherence tomography

    NASA Astrophysics Data System (ADS)

    de Boer, Johannes F.; Tripathi, Renu; Park, Boris H.; Nassif, Nader

    2002-06-01

    We present phase resolved digital signal processing techniques for Optical Coherence Tomography to correct for the non Gaussian shape of source spectra and for Group Delay Dispersion (GDD). A broadband source centered at 820 nm was synthesized by combining the spectra of two superluminescent diodes to improve axial image resolution in an optical coherence tomography (OCT) system. Spectral shaping was used to reduce the side lobes (ringing) in the axial point spread function due to the non-Gaussian shape of the spectra. Images of onion cells taken with each individual source and the combined sources, respectively, show the improved resolution and quality enhancement in a turbid biological sample. An OCT system operating at 1310 nm was used to demonstrate that the broadening effect of group delay dispersion (GDD) on the coherence function could be eliminated completely by introducing a quadratic phase shift in the Fourier domain of the interferometric signal. The technique is demonstrated by images of human skin grafts with group delay dispersion mismatch between sample and reference arm before and after digital processing.

  16. The use of digital signal processing in satellite communication

    NASA Astrophysics Data System (ADS)

    Bramwell, Jonathan Richard

    1988-06-01

    The recent emphasis on information technology has increased the need for methods of data communications with a greater interest in the areas of satellite communications. Data communications over a satellite can be easily achieved by the use of excessive power and bandwidth but efficient management of the satellite resource requires more elegant means of transmission. The optimum modulator and demodulator can be described by mathematical expressions to represent the physical processes that are required to transmit and receive a signal. Digital signal processing circuits can be used to implement these mathematical functions and once correctly designed are not susceptible to variations in accuracy and hence can maintain an accurate representation of the mathematical model. This thesis documents an investigation into the algorithms and techniques that can be used in the digital implementation of a satellite data modem. The technique used for carrier phase recovery and data decoding is a major variation on a method proposed by Viterbi and Viterbi and relies on phase estimation instead of the more common carrier regeneration techniques. A computer simulation of this algorithm and its performance is described and the overall performance of the simulation is compared to theoretical analysis and experimental performance of a multi-data rate satellite modem covering data rates in the range of 16 Ksymbol/sec to 256 Ksymbol/sec in both the BPSK and QPSK data formats.

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. Internal wave signal processing: A model-based approach

    SciTech Connect

    Candy, J.V.; Chambers, D.H.

    1995-02-22

    A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (depth) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. These models are then generalized to the stochastic case where an approximate Gauss-Markov theory applies. The resulting 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 problem for internal waves. In particular, a processor is designed that allows in situ recursive estimation of the required velocity functions. 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.

  3. 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

  4. 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.

  5. A Systolic Array Architecture For Processing Sonar Narrowband Signals

    NASA Astrophysics Data System (ADS)

    Mintzer, L.

    1988-07-01

    Modern sonars relay more upon visual rather than aural contacts. Lofargrams presenting a time history of hydrophone spectral content are standard means of observing narrowband signals. However, the frequency signal "tracks" are often embedded in noise, sometimes rendering their detection difficult and time consuming. Image enhancement algorithms applied to the 'grams can yield improvements in target data presented to the observer. A systolic array based on the NCR Geometric Arithmetic Parallel Processor (GAPP), a CMOS chip that contains 72 single bit processors controlled in parallel, has been designed for evaluating image enhancement algorithms. With the processing nodes of the GAPP bearing a one-to-one correspondence with the pixels displayed on the 'gram, a very efficient SIMD architecture is realized. The low data rate of sonar displays, i.e., one line of 1000-4000 pixels per second, and the 10-MHz control clock of the GAPP provide the possibility of 107 operations per pixel in real time applications. However, this architecture cannot handle data-dependent operations efficiently. To this end a companion processor capable of efficiently executing branch operations has been designed. A simple spoke filter is simulated and applied to laboratory data with noticeable improvements in the resulting lofargram display.

  6. Modeling and processing of laser Doppler reactive hyperaemia signals

    NASA Astrophysics Data System (ADS)

    Humeau, Anne; Saumet, Jean-Louis; L'Huiller, Jean-Pierre

    2003-07-01

    Laser Doppler flowmetry is a non-invasive method used in the medical domain to monitor the microvascular blood cell perfusion through tissue. Most commercial laser Doppler flowmeters use an algorithm calculating the first moment of the power spectral density to give the perfusion value. Many clinical applications measure the perfusion after a vascular provocation such as a vascular occlusion. The response obtained is then called reactive hyperaemia. Target pathologies include diabetes, hypertension and peripheral arterial occlusive diseases. In order to have a deeper knowledge on reactive hyperaemia acquired by the laser Doppler technique, the present work first proposes two models (one analytical and one numerical) of the observed phenomenon. Then, a study on the multiple scattering between photons and red blood cells occurring during reactive hyperaemia is carried out. Finally, a signal processing that improves the diagnosis of peripheral arterial occlusive diseases is presented.

  7. Super-resolution signal processing aids RCS testing

    NASA Astrophysics Data System (ADS)

    Deats, Bradley W.; Farina, David J.; Bull, Jeffrey F.

    1991-03-01

    Recent advances in super-resolution (SR) signal-processing techniques for radar-cross-section (RCS) measurement are described and demonstrated. The resolution problem for RCS data is explored theoretically, and consideration is given to SR direction-finding algorithms, algorithms based on eigenvector decomposition of the covariance matrix, the MUSIC algorithm, the eigenvalue method, the thermal-noise algorithm, the maximum-likelihood (or least-mean-square) algorithm, and the maximum-entropy method. These methods are applied in test analyses of data measured on a flat conductive plate target at 201 frequencies between 6.0 and 18.2 GHz, and numerical results are presented in graphs. SR methods are shown to permit detection of very closely spaced scatterers of differing magnitude, a significant improvement over conventional FFT analysis schemes.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. A nonlinear optoelectronic filter for electronic signal processing.

    PubMed

    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

  13. 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

  14. Real-time radar signal processing using GPGPU (general-purpose graphic processing unit)

    NASA Astrophysics Data System (ADS)

    Kong, Fanxing; Zhang, Yan Rockee; Cai, Jingxiao; Palmer, Robert D.

    2016-05-01

    This study introduces a practical approach to develop real-time signal processing chain for general phased array radar on NVIDIA GPUs(Graphical Processing Units) using CUDA (Compute Unified Device Architecture) libraries such as cuBlas and cuFFT, which are adopted from open source libraries and optimized for the NVIDIA GPUs. The processed results are rigorously verified against those from the CPUs. Performance benchmarked in computation time with various input data cube sizes are compared across GPUs and CPUs. Through the analysis, it will be demonstrated that GPGPUs (General Purpose GPU) real-time processing of the array radar data is possible with relatively low-cost commercial GPUs.

  15. Moire and grid methods: a signal-processing approach

    NASA Astrophysics Data System (ADS)

    Surrel, Yves

    1994-11-01

    This presentation is a formulation of moire and grid methods with the vocabulary of signal processing. It addresses basically the case of in-plane geometrical moire, but, as is well known, any geometrical moire setup can be related to in-plane moire. We show that the moire phenomenon is not a measurement method by itself, but only a step in a process of information transmission by spatial frequency modulation. The distortion of a grid bonded onto the surface of a loaded specimen or structure will cause locally a modulation (Delta) F of the spatial frequency vector F of the grid. The modulation (Delta) F is linearly related to the strain and rotation tensors. An equivalent point of view is to consider the same phenomenon as a phase modulation, caused by the inverse displacements. In this approach, moire is presented merely as an analog means of frequency substraction. The interpretation of the classical fringe processing techniques -- temporal and spatial phase shifting, Fourier transform method -- is made, and some consequences of the zoom-in effect induced by the moire phenomenon are given.

  16. A joint signal processing and cryptographic approach to multimedia encryption.

    PubMed

    Mao, Yinian; Wu, Min

    2006-07-01

    In recent years, there has been an increasing trend for multimedia applications to use delegate service providers for content distribution, archiving, search, and retrieval. These delegate services have brought new challenges to the protection of multimedia content confidentiality. This paper discusses the importance and feasibility of applying a joint signal processing and cryptographic approach to multimedia encryption, in order to address the access control issues unique to multimedia applications. We propose two atomic encryption operations that can preserve standard compliance and are friendly to delegate processing. Quantitative analysis for these operations is presented to demonstrate that a good tradeoff can be made between security and bitrate overhead. In assisting the design and evaluation of media security systems, we also propose a set of multimedia-oriented security scores to quantify the security against approximation attacks and to complement the existing notion of generic data security. Using video as an example, we present a systematic study on how to strategically integrate different atomic operations to build a video encryption system. The resulting system can provide superior performance over both generic encryption and its simple adaptation to video in terms of a joint consideration of security, bitrate overhead, and friendliness to delegate processing.

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. Pathophysiologic mechanisms of biomedical nanomaterials.

    PubMed

    Wang, Liming; Chen, Chunying

    2016-05-15

    Nanomaterials (NMs) have been widespread used in biomedical fields, daily consuming, and even food industry. It is crucial to understand the safety and biomedical efficacy of NMs. In this review, we summarized the recent progress about the physiological and pathological effects of NMs from several levels: protein-nano interface, NM-subcellular structures, and cell-cell interaction. We focused on the detailed information of nano-bio interaction, especially about protein adsorption, intracellular trafficking, biological barriers, and signaling pathways as well as the associated mechanism mediated by nanomaterials. We also introduced related analytical methods that are meaningful and helpful for biomedical effect studies in the future. We believe that knowledge about pathophysiologic effects of NMs is not only significant for rational design of medical NMs but also helps predict their safety and further improve their applications in the future.

  4. 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.

  5. 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.

  6. Adaptive beamforming for array signal processing in aeroacoustic measurements.

    PubMed

    Huang, Xun; Bai, Long; Vinogradov, Igor; Peers, Edward

    2012-03-01

    Phased microphone arrays have become an important tool in the localization of noise sources for aeroacoustic applications. In most practical aerospace cases the conventional beamforming algorithm of the delay-and-sum type has been adopted. Conventional beamforming cannot take advantage of knowledge of the noise field, and thus has poorer resolution in the presence of noise and interference. Adaptive beamforming has been used for more than three decades to address these issues and has already achieved various degrees of success in areas of communication and sonar. In this work an adaptive beamforming algorithm designed specifically for aeroacoustic applications is discussed and applied to practical experimental data. It shows that the adaptive beamforming method could save significant amounts of post-processing time for a deconvolution method. For example, the adaptive beamforming method is able to reduce the DAMAS computation time by at least 60% for the practical case considered in this work. Therefore, adaptive beamforming can be considered as a promising signal processing method for aeroacoustic measurements.

  7. Signal processing for NQR discrimination of buried land mines

    NASA Astrophysics Data System (ADS)

    Tantum, Stacy L.; Collins, Leslie M.; Carin, Lawrence; Gorodnitsky, Irina; Hibbs, Andrew D.; Walsh, David O.; Barrall, Geoffrey A.; Gregory, David M.; Matthews, Robert; Vierkotter, Stephie A.

    1999-08-01

    Nuclear quadrupole resonance (NQR) is a technique that discriminates mines from clutter by exploiting unique properties of explosives, rather than the attributes of the mine that exist in many forms of anthropic clutter. After exciting the explosive with a properly designed electromagnetic-induction (EMI) system, one attempts to sense late-time spin echoes, which are characterized by radiation at particular frequencies. It is this narrow-band radiation that indicates the presence of explosives, since this effect is not seen in most clutter, both natural and anthropic. However, this problem is complicated by several issues. First, the late-time radiation if often very weak, particularly for TNT, and therefore the signal-to-noise ratio must be high for extracting the NQR response. Further, the frequency at which the explosive radiates is often a strong function of the background environment, and therefore in practice the NQR radiation frequency is not known a priori. Finally, at the frequencies of interest, there is a significant amount of background radiation, which induces radio frequency interference (RFI). In this paper we discuss several signal processing tools we have developed to enhance the utility of NQR explosives detection. In particular, with regard to the RFI, we exposure least-mean-squares algorithms which have proven well suited to extracting background interference. Algorithm performance is assessed through consideration of actual measured data. With regard to the detection of the NQR electromagnetic echo, we consider a Bayesian discrimination algorithm. The performance of the Bayesian algorithm is presented, again using measured NQR data.

  8. 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.

  9. Temporally selective processing of communication signals by auditory midbrain neurons

    PubMed Central

    Christensen-Dalsgaard, Jakob; Kelley, Darcy B.

    2011-01-01

    Perception of the temporal structure of acoustic signals contributes critically to vocal signaling. In the aquatic clawed frog Xenopus laevis, calls differ primarily in the temporal parameter of click rate, which conveys sexual identity and reproductive state. We show here that an ensemble of auditory neurons in the laminar nucleus of the torus semicircularis (TS) of X. laevis specializes in encoding vocalization click rates. We recorded single TS units while pure tones, natural calls, and synthetic clicks were presented directly to the tympanum via a vibration-stimulation probe. Synthesized click rates ranged from 4 to 50 Hz, the rate at which the clicks begin to overlap. Frequency selectivity and temporal processing were characterized using response-intensity curves, temporal-discharge patterns, and autocorrelations of reduplicated responses to click trains. Characteristic frequencies ranged from 140 to 3,250 Hz, with minimum thresholds of −90 dB re 1 mm/s at 500 Hz and −76 dB at 1,100 Hz near the dominant frequency of female clicks. Unlike units in the auditory nerve and dorsal medullary nucleus, most toral units respond selectively to the behaviorally relevant temporal feature of the rate of clicks in calls. The majority of neurons (85%) were selective for click rates, and this selectivity remained unchanged over sound levels 10 to 20 dB above threshold. Selective neurons give phasic, tonic, or adapting responses to tone bursts and click trains. Some algorithms that could compute temporally selective receptive fields are described. PMID:21289132

  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. 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%.

  12. [Scientometrics and bibliometrics of biomedical engineering periodicals and papers].

    PubMed

    Zhao, Ping; Xu, Ping; Li, Bingyan; Wang, Zhengrong

    2003-09-01

    This investigation was made to reveal the current status, research trend and research level of biomedical engineering in Chinese mainland by means of scientometrics and to assess the quality of the four domestic publications by bibliometrics. We identified all articles of four related publications by searching Chinese and foreign databases from 1997 to 2001. All articles collected or cited by these databases were searched and statistically analyzed for finding out the relevant distributions, including databases, years, authors, institutions, subject headings and subheadings. The source of sustentation funds and the related articles were analyzed too. The results showed that two journals were cited by two foreign databases and five Chinese databases simultaneously. The output of Journal of Biomedical Engineering was the highest. Its quantity of original papers cited by EI, CA and the totality of papers sponsored by funds were higher than those of the others, but the quantity and percentage per year of biomedical articles cited by EI were decreased in all. Inland core authors and institutions had come into being in the field of biomedical engineering. Their research topics were mainly concentrated on ten subject headings which included biocompatible materials, computer-assisted signal processing, electrocardiography, computer-assisted image processing, biomechanics, algorithms, electroencephalography, automatic data processing, mechanical stress, hemodynamics, mathematical computing, microcomputers, theoretical models, etc. The main subheadings were concentrated on instrumentation, physiopathology, diagnosis, therapy, ultrasonography, physiology, analysis, surgery, pathology, method, etc.

  13. 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

  14. 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

  15. 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.

  16. Photoelectricity signal processing circuit of interferometric fiber optic pressure sensor

    NASA Astrophysics Data System (ADS)

    Guo, Zhenwu; Li, Wei-xiang; Meng, Qing-bin; Pan, Yong; Liu, Guang-wei; Ge, Fu-wei; Zhang, Rong-xin

    2009-07-01

    We have designed an intensity-demodulated sensing system based on Fabry-Perot interferometric sensor for pressure measurement. The structure of the sensing probe has been presented. The sensing system is interrogated by broadband source. For compensating drift of the source power and fluctuation in fiber attenuation, the light beam is separated into two channels by a fiber Bragg Grating, the transmitted light used as reference signal and the reflected light used as sensing signal. In order to improve the signal-to-noise ratio(SNR) of the detection system, the input light is modulated by pulse signal, and the low noise preamplifier is given. The more important factor to improve the SNR is that a synchronization integrator is employed to construct a narrow band filter to restrain noises and disturbances. It has better performance with a narrow band noise filter rather than the general RC active bandpass filter. The sensing signal and the reference signal are transformed into DC voltage signal from AC voltage signal after they passed the synchronization integrator circuit. Subsequently the division operation of the sensing signal and the reference signal is implemented. At last a linear output model is established. The system has advantages of fast response, strong ability and low cost. The dynamic range of the sensor is from 0 to 400KPa, and the resolution reaches to 200Pa.

  17. A high performance biometric signal and image processing method to reveal blood perfusion towards 3D oxygen saturation mapping

    NASA Astrophysics Data System (ADS)

    Imms, Ryan; Hu, Sijung; Azorin-Peris, Vicente; Trico, Michaël.; Summers, Ron

    2014-03-01

    Non-contact imaging photoplethysmography (PPG) is a recent development in the field of physiological data acquisition, currently undergoing a large amount of research to characterize and define the range of its capabilities. Contact-based PPG techniques have been broadly used in clinical scenarios for a number of years to obtain direct information about the degree of oxygen saturation for patients. With the advent of imaging techniques, there is strong potential to enable access to additional information such as multi-dimensional blood perfusion and saturation mapping. The further development of effective opto-physiological monitoring techniques is dependent upon novel modelling techniques coupled with improved sensor design and effective signal processing methodologies. The biometric signal and imaging processing platform (bSIPP) provides a comprehensive set of features for extraction and analysis of recorded iPPG data, enabling direct comparison with other biomedical diagnostic tools such as ECG and EEG. Additionally, utilizing information about the nature of tissue structure has enabled the generation of an engineering model describing the behaviour of light during its travel through the biological tissue. This enables the estimation of the relative oxygen saturation and blood perfusion in different layers of the tissue to be calculated, which has the potential to be a useful diagnostic tool.

  18. 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

  19. 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.

  20. 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)

  1. Programmable rate modem utilizing digital signal processing techniques

    NASA Astrophysics Data System (ADS)

    Bunya, George K.; Wallace, Robert L.

    1989-07-01

    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.

  2. 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.

  3. Magnetoencephalographic Signals Identify Stages in Real-Life Decision Processes

    PubMed Central

    Braeutigam, Sven; Stins, John F.; Rose, Steven P. R.; Swithenby, Stephen J.; Ambler, Tim

    2001-01-01

    We used magnetoencephalography (MEG) to study the dynamics of neural responses in eight subjects engaged in shopping for day-to-day items from supermarket shelves. This behavior not only has personal and economic importance but also provides an example of an experience that is both personal and shared between individuals. The shopping experience enables the exploration of neural mechanisms underlying choice based on complex memories. Choosing among different brands of closely related products activated a robust sequence of signals within the first second after the presentation of the choice images. This sequence engaged first the visual cortex (80-100 ms), then as the images were analyzed, predominantly the left temporal regions (310-340 ms). At longer latency, characteristic neural activetion was found in motor speech areas (500-520 ms) for images requiring low salience choices with respect to previous (brand) memory, and in right parietal cortex for high salience choices (850-920 ms). We argue that the neural processes associated with the particular brand-choice stimulus can be separated into identifiable stages through observation of MEG responses and knowledge of functional anatomy. PMID:12018772

  4. Ultrafast optical signal processing on silicon-based platforms

    NASA Astrophysics Data System (ADS)

    Tan, Dawn T. H.

    2016-03-01

    The development of silicon - based photonic components and systems has advanced tremendously over the last decade, largely for applications in optical interconnects. The role of silicon - based platforms for both linear and nonlinear optics remains highly pertinent because of their ability to be integrated with CMOS - based electronics. In this paper, we present recent research progress pertaining to ultrafast optical signal processing on silicon - based platforms. Advances in on - chip multiplexing strategies with the potential for meeting 200GHz dense wavelength division multiplexing standards across the C - and L - bands will be discussed. In addition, the development of a silicon - based nonlinear optics platform with high nonlinear figures of merit will be presented. Nonlinear optical devices fabricated from the developed platform possess nonlinear parameters 500 times larger than that in silicon nitride waveguides, while possessing negligible nonlinear losses at 1.55μm. Ultra - broadband, low power nonlinear wavelength generation using these devices, as well as their potential for realizing advanced light sources for optical interconnect - based applications will be presented.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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.

  11. 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

  12. Digital Signal Processing Techniques for the GIFTS SM EDU

    NASA Astrophysics Data System (ADS)

    Tian, J.; Reisse, R.; Gazarik, M.

    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

  13. 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

  14. Perceptions regarding biomedical engineering

    NASA Astrophysics Data System (ADS)

    Pearson, James E.

    1995-10-01

    Perceptions of biomedical engineering are important because they can influence private and public decisions on R&D funding and public policy. A survey was conducted of a group of persons active in biomedical engineering research in an attempt to determine the perceptions of the general public and of the biomedical community regarding biomedical engineering. The public is believed to have 'a little' knowledge of biomedical engineering, and to have a wide range of opinions on what biomedical engineers do. The survey respondents believe they are in general agreement with the public on several questions regarding biomedical engineering. However, the public is believed to be more inclined than workers in the field to think that biomedical engineering increases the cost of health care, and to be less supportive of increased R&D funding for health care technology.

  15. 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.

  16. 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.

  17. The design of digital filters for biomedical signal processing. Part 3: The design of Butterworth and Chebychev filters.

    PubMed

    Challis, R E; Kitney, R I

    1983-04-01

    The first two papers in this series reviewed the basic concepts which apply to digital filter theory and presented design techniques based on the z plane pole-zero plot. In this paper these methods are used to develop digital versions of Butterworth and Chebychev filters. The basic theory of both filter types is reviewed and the bilinear transformation is used to derive the z-transforms of the filters from their s-plane continuous time descriptions. Recurrence relationships which may be used to implement filters of various orders are developed. The impulse and frequency responses of the elements are illustrated and examples are given of their application to ECG data.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. An epidemic process mediated by a decaying diffusing signal

    NASA Astrophysics Data System (ADS)

    Faria, Fernando P.; Dickman, Ronald

    2012-06-01

    We study a stochastic epidemic model consisting of elements (organisms in a community or cells in tissue) with fixed positions, in which damage or disease is transmitted by diffusing agents ('signals') emitted by infected individuals. The signals decay as well as diffuse; since they are assumed to be produced in large numbers, the signal concentration is treated deterministically. The model, which includes four cellular states (susceptible, transformed, depleted, and removed), admits various interpretations: spread of an infection or infectious disease, or of damage in a tissue in which injured cells may themselves provoke further damage, and as a description of the so-called radiation-induced bystander effect, in which the signals are molecules capable of inducing cell damage and/or death in unirradiated cells. The model exhibits a continuous phase transition between spreading and nonspreading phases. We formulate two mean-field theory (MFT) descriptions of the model, one of which ignores correlations between the cellular state and the signal concentration, and another that treats such correlations in an approximate manner. Monte Carlo simulations of the spread of infection on the square lattice yield values for the critical exponents and the fractal dimension consistent with the dynamic percolation universality class.

  5. Sparse Methods for Biomedical Data

    PubMed Central

    Ye, Jieping; Liu, Jun

    2013-01-01

    Following recent technological revolutions, the investigation of massive biomedical data with growing scale, diversity, and complexity has taken a center stage in modern data analysis. Although complex, the underlying representations of many biomedical data are often sparse. For example, for a certain disease such as leukemia, even though humans have tens of thousands of genes, only a few genes are relevant to the disease; a gene network is sparse since a regulatory pathway involves only a small number of genes; many biomedical signals are sparse or compressible in the sense that they have concise representations when expressed in a proper basis. Therefore, finding sparse representations is fundamentally important for scientific discovery. Sparse methods based on the ℓ1 norm have attracted a great amount of research efforts in the past decade due to its sparsity-inducing property, convenient convexity, and strong theoretical guarantees. They have achieved great success in various applications such as biomarker selection, biological network construction, and magnetic resonance imaging. In this paper, we review state-of-the-art sparse methods and their applications to biomedical data. PMID:24076585

  6. 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

  7. 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

    2016-01-27

    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.

  8. The contribution of extrasynaptic signaling to cerebellar information processing

    PubMed Central

    Coddington, Luke T.; Nietz, Angela K.; Wadiche, Jacques I.

    2014-01-01

    The diversity of synapses within the simple modular structure of the cerebellum has been crucial for study of the phasic extrasynaptic signaling by fast neurotransmitters collectively referred to as ‘spillover.’ Additionally, the accessibility of cerebellar components for in vivo recordings and their recruitment by simple behaviors or sensory stimuli has allowed for both direct and indirect demonstrations of the effects of transmitter spillover in the intact brain. The continued study of spillover in the cerebellum not only promotes our understanding of information transfer through cerebellar structures but also how extrasynaptic signaling may be regulated and interpreted throughout the CNS. PMID:24590660

  9. Silicon technology compatible photonic molecules for compact optical signal processing

    SciTech Connect

    Barea, Luis A. M. Vallini, Felipe; Jarschel, Paulo F.; Frateschi, Newton C.

    2013-11-11

    Photonic molecules (PMs) based on multiple inner coupled microring resonators allow to surpass the fundamental constraint between the total quality factor (Q{sub T}), free spectral range (FSR), and resonator size. In this work, we use a PM that presents doublets and triplets resonance splitting, all with high Q{sub T}. We demonstrate the use of the doublet splitting for 34.2 GHz signal extraction by filtering the sidebands of a modulated optical signal. We also demonstrate that very compact optical modulators operating 2.75 times beyond its resonator linewidth limit may be obtained using the PM triplet splitting, with separation of ∼55 GHz.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. Quantum broadcasting problem in classical low-power signal processing

    SciTech Connect

    Janzing, Dominik; Steudel, Bastian

    2007-02-15

    We prove a no-broadcasting theorem for the Holevo information of a noncommuting ensemble stating that no operation can generate a bipartite ensemble such that both copies have the same information as the original. We argue that upper bounds on the average information over both copies imply lower bounds on the quantum capacity required to send the ensemble without information loss. This is because a channel with zero quantum capacity has a unitary extension transferring at least as much information to its environment as it transfers to the output. For an ensemble being the time orbit of a pure state under a Hamiltonian evolution, we derive such a bound on the required quantum capacity in terms of properties of the input and output energy distribution. Moreover, we discuss relations between the broadcasting problem and entropy power inequalities. The broadcasting problem arises when a signal should be transmitted by a time-invariant device such that the outgoing signal has the same timing information as the incoming signal had. Based on previous results we argue that this establishes a link between quantum information theory and the theory of low power computing because the loss of timing information implies loss of free energy.

  17. 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.

  18. Signal processing of MEMS gyroscope arrays to improve accuracy using a 1st order Markov for rate signal modeling.

    PubMed

    Jiang, Chengyu; Xue, Liang; Chang, Honglong; Yuan, Guangmin; Yuan, Weizheng

    2012-01-01

    This paper presents a signal processing technique to improve angular rate accuracy of the gyroscope by combining the outputs of an array of MEMS gyroscope. A mathematical model for the accuracy improvement was described and a Kalman filter (KF) was designed to obtain optimal rate estimates. Especially, the rate signal was modeled by a first-order Markov process instead of a random walk to improve overall performance. The accuracy of the combined rate signal and affecting factors were analyzed using a steady-state covariance. A system comprising a six-gyroscope array was developed to test the presented KF. Experimental tests proved that the presented model was effective at improving the gyroscope accuracy. The experimental results indicated that six identical gyroscopes with an ARW noise of 6.2 °/√h and a bias drift of 54.14 °/h could be combined into a rate signal with an ARW noise of 1.8 °/√h and a bias drift of 16.3 °/h, while the estimated rate signal by the random walk model has an ARW noise of 2.4 °/√h and a bias drift of 20.6 °/h. It revealed that both models could improve the angular rate accuracy and have a similar performance in static condition. In dynamic condition, the test results showed that the first-order Markov process model could reduce the dynamic errors 20% more than the random walk model.

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. 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 %.

  4. Temporal signal processing of dolphin biosonar echoes from salmon prey.

    PubMed

    Au, Whitlow W L; Ou, Hui Helen

    2014-08-01

    Killer whales project short broadband biosonar clicks. The broadband nature of the clicks provides good temporal resolution of echo highlights and allows for the discriminations of salmon prey. The echoes contain many highlights as the signals reflect off different surfaces and parts of the fish body and swim bladder. The temporal characteristics of echoes from salmon are highly aspect dependent and six temporal parameters were used in a support vector machine to discriminate between species. Results suggest that killer whales can classify salmon based on their echoes and provide some insight as to which features might enable the classification. PMID:25096148

  5. 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).

  6. Temporal signal processing of dolphin biosonar echoes from salmon prey.

    PubMed

    Au, Whitlow W L; Ou, Hui Helen

    2014-08-01

    Killer whales project short broadband biosonar clicks. The broadband nature of the clicks provides good temporal resolution of echo highlights and allows for the discriminations of salmon prey. The echoes contain many highlights as the signals reflect off different surfaces and parts of the fish body and swim bladder. The temporal characteristics of echoes from salmon are highly aspect dependent and six temporal parameters were used in a support vector machine to discriminate between species. Results suggest that killer whales can classify salmon based on their echoes and provide some insight as to which features might enable the classification.

  7. Low Bandwidth Vocoding using EM Sensor and Acoustic Signal Processing

    SciTech Connect

    Ng, L C; Holzrichter, J F; Larson, P E

    2001-10-25

    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 [1]. By combining these data with the corresponding acoustic signal, we've demonstrated an almost 10-fold bandwidth reduction in speech compression, compared to a standard 2.4 kbps LPC10 protocol used in the STU-III (Secure Terminal Unit, third generation) telephone. This paper describes a potential EM sensor/acoustic based vocoder implementation.

  8. Weighted LS-SVM for function estimation applied to artifact removal in bio-signal processing.

    PubMed

    Caicedo, Alexander; Van Huffel, Sabine

    2010-01-01

    Weighted LS-SVM is normally used for function estimation from highly corrupted data in order to decrease the impact of outliers. However, this method is limited in size and big time series should be segmented in smaller groups. Therefore, border discontinuities represent a problem in the final estimated function. Several methods such as committee networks or multilayer networks of LS-SVMs are used to address this problem, but these methods require extra training and hence the computational cost is increased. In this paper a technique that includes an extra weight vector in the formulation of the cost function for the LS-SVM problem is proposed as an alternative solution. The method is then applied to the removal of some artifacts in biomedical signals.

  9. Generic vs custom; analogue vs digital: on the implementation of an online EEG signal processing algorithm.

    PubMed

    Casson, Alexander J; Rodriguez-Villegas, Esther

    2008-01-01

    This paper quantifies the performance difference between custom and generic hardware algorithm implementations, illustrating the challenges that are involved in Body Area Network signal processing implementations. The potential use of analogue signal processing to improve the power performance is also demonstrated.

  10. Low Power and Robust Domino Circuit with Process Variations Tolerance for High Speed Digital Signal Processing

    NASA Astrophysics Data System (ADS)

    Wang, Jinhui; Peng, Xiaohong; Li, Xinxin; Hou, Ligang; Wu, Wuchen

    Utilizing the sleep switch transistor technique and dual threshold voltage technique, a source following evaluation gate (SEFG) based domino circuit is presented in this paper for simultaneously suppressing the leakage current and enhancing noise immunity. Simulation results show that the leakage current of the proposed design can be reduced by 43%, 62%, and 67% while improving 19.7%, 3.4 %, and 12.5% noise margin as compared to standard low threshold voltage circuit, standard dual threshold voltage circuit, and SEFG structure, respectively. Also, the inputs and clock signals combination static state dependent leakage current characteristic is analyzed and the minimum leakage states of different domino AND gates are obtained. At last, the leakage power characteristic under process variations is discussed.

  11. DEVELOPMENT OF SIGNAL PROCESSING TOOLS AND HARDWARE FOR PIEZOELECTRIC SENSOR DIAGNOSTIC PROCESSES

    SciTech Connect

    OVERLY, TIMOTHY G.; PARK, GYUHAE; FARRAR, CHARLES R.

    2007-02-09

    This paper presents a piezoelectric sensor diagnostic and validation procedure that performs in -situ monitoring of the operational status of piezoelectric (PZT) sensor/actuator arrays used in structural health monitoring (SHM) applications. The validation of the proper function of a sensor/actuator array during operation, is a critical component to a complete and robust SHM system, especially with the large number of active sensors typically involved. The method of this technique used to obtain the health of the PZT transducers is to track their capacitive value, this value manifests in the imaginary part of measured electrical admittance. Degradation of the mechanical/electric properties of a PZT sensor/actuator as well as bonding defects between a PZT patch and a host structure can be identified with the proposed procedure. However, it was found that temperature variations and changes in sensor boundary conditions manifest themselves in similar ways in the measured electrical admittances. Therefore, they examined the effects of temperature variation and sensor boundary conditions on the sensor diagnostic process. The objective of this study is to quantify and classify several key characteristics of temperature change and to develop efficient signal processing techniques to account for those variations in the sensor diagnostis process. In addition, they developed hardware capable of making the necessary measurements to perform the sensor diagnostics and to make impedance-based SHM measurements. The paper concludes with experimental results to demonstrate the effectiveness of the proposed technique.

  12. 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

  13. 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.

  14. 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

  15. Proceedings of the array signal processing symposium: Treaty Verification Program

    SciTech Connect

    Harris, D.B.

    1988-02-01

    A common theme underlying the research these groups conduct is the use of propagating waves to detect, locate, image or otherwise identify features of the environment significant to their applications. The applications considered in this symposium are verification of nuclear test ban treaties, non-destructive evaluation (NDE) of manufactured components, and sonar and electromagnetic target acquisition and tracking. These proceedings cover just the first two topics. In these applications, arrays of sensors are used to detect propagating waves and to measure the characteristics that permit interpretation. The reason for using sensors arrays, which are inherently more expensive than single sensor systems, is twofold. By combining the signals from multiple sensors, it is usually possible to suppress unwanted noise, which permtis detection and analysis of waker signals. Secondly, in complicated situations in which many waves are present, arrays make it possible to separate the waves and to measure their individual characteristics (direction, velocity, etc.). Other systems (such as three-component sensors in the seismic application) can perform these functions to some extent, but none are so effective and versatile as arrays. The objectives of test ban treaty verification are to detect, locate and identify underground nuclear explosions, and to discriminate them from earthquakes and conventional chemical explosions. Two physical modes of treaty verification are considered: monitoring with arrays of seismic stations (solid earth propagation), and monitoring with arrays of acoustic (infrasound) stations (atmospheric propagation). The majority of the presentations represented in these proceeding address various aspects of the seismic verification problem.

  16. Toward lightweight biometric signal processing for wearable devices.

    PubMed

    Francescon, Roberto; Hooshmand, Mohsen; Gadaleta, Matteo; Grisan, Enrico; Yoon, Seung Keun; Rossi, Michele

    2015-01-01

    Wearable devices are becoming a natural and economic means to gather biometric data from end users. The massive amount of information that they will provide, unimaginable until a few years ago, owns an immense potential for applications such as continuous monitoring for personalized healthcare and use within fitness applications. Wearables are however heavily constrained in terms of amount of memory, transmission capability and energy reserve. This calls for dedicated, lightweight but still effective algorithms for data management. This paper is centered around lossy data compression techniques, whose aim is to minimize the amount of information that is to be stored on their onboard memory and subsequently transmitted over wireless interfaces. Specifically, we analyze selected compression techniques for biometric signals, quantifying their complexity (energy consumption) and compression performance. Hence, we propose a new class of codebook-based (CB) compression algorithms, designed to be energy efficient, online and amenable to any type of signal exhibiting recurrent patterns. Finally, the performance of the selected and the new algorithm is assessed, underlining the advantages offered by CB schemes in terms of memory savings and classification algorithms.

  17. Toward lightweight biometric signal processing for wearable devices.

    PubMed

    Francescon, Roberto; Hooshmand, Mohsen; Gadaleta, Matteo; Grisan, Enrico; Yoon, Seung Keun; Rossi, Michele

    2015-01-01

    Wearable devices are becoming a natural and economic means to gather biometric data from end users. The massive amount of information that they will provide, unimaginable until a few years ago, owns an immense potential for applications such as continuous monitoring for personalized healthcare and use within fitness applications. Wearables are however heavily constrained in terms of amount of memory, transmission capability and energy reserve. This calls for dedicated, lightweight but still effective algorithms for data management. This paper is centered around lossy data compression techniques, whose aim is to minimize the amount of information that is to be stored on their onboard memory and subsequently transmitted over wireless interfaces. Specifically, we analyze selected compression techniques for biometric signals, quantifying their complexity (energy consumption) and compression performance. Hence, we propose a new class of codebook-based (CB) compression algorithms, designed to be energy efficient, online and amenable to any type of signal exhibiting recurrent patterns. Finally, the performance of the selected and the new algorithm is assessed, underlining the advantages offered by CB schemes in terms of memory savings and classification algorithms. PMID:26737218

  18. A kind of integrated method discuss of fOG signal processing circuit

    NASA Astrophysics Data System (ADS)

    Lu, Jun; Pan, Xin; Ying, Jiaju; Liu, Jie

    2014-12-01

    In view of the circuit miniaturization need in project application of fiber optic gyroscope(FOG), a new integrated technical scheme adopting system in package(SIP) for signal processing circuit of FOG was put forward. At first, the principle on signal processing circuit of FOG was analyzed, and the technical scheme adopting SIP based on low-temperature co-fired substrate technology was presented according to circuit characteristic and actual condition. Secondly, under the prerequisite of the concept introduction of SIP and LTCC, the SIP prototype of signal processing circuit of FOG was trialed produced,and it passed through the debug test. This SIP modular is an overall circuit complete integrated the signal processing circuit of FOG, and only a potentiometer and EPROM do not case outside. The testing results indicate that SIP is a kind of feasible scheme that carries out miniaturization for signal processing circuit of FOG.

  19. Acoustic emission signal processing technique to characterize reactor in-pile phenomena

    SciTech Connect

    Agarwal, Vivek; Tawfik, Magdy S.; Smith, James A.

    2015-03-31

    Existing and developing advanced sensor technologies and instrumentation will allow non-intrusive in-pile measurement of temperature, extension, and fission gases when coupled with advanced signal processing algorithms. The transmitted measured sensor signals from inside to the outside of containment structure are corrupted by noise and are attenuated, thereby reducing the signal strength and the signal-to-noise ratio. Identification and extraction of actual signal (representative of an in-pile phenomenon) is a challenging and complicated process. In the paper, empirical mode decomposition technique is utilized to reconstruct actual sensor signal by partially combining intrinsic mode functions. Reconstructed signal will correspond to phenomena and/or failure modes occurring inside the reactor. In addition, it allows accurate non-intrusive monitoring and trending of in-pile phenomena.

  20. Dynamic signal processing by ribozyme-mediated RNA circuits to control gene expression

    PubMed Central

    Shen, Shensi; Rodrigo, Guillermo; Prakash, Satya; Majer, Eszter; Landrain, Thomas E.; Kirov, Boris; Daròs, José-Antonio; Jaramillo, Alfonso

    2015-01-01

    Organisms have different circuitries that allow converting signal molecule levels to changes in gene expression. An important challenge in synthetic biology involves the de novo design of RNA modules enabling dynamic signal processing in live cells. This requires a scalable methodology for sensing, transmission, and actuation, which could be assembled into larger signaling networks. Here, we present a biochemical strategy to design RNA-mediated signal transduction cascades able to sense small molecules and small RNAs. We design switchable functional RNA domains by using strand-displacement techniques. We experimentally characterize the molecular mechanism underlying our synthetic RNA signaling cascades, show the ability to regulate gene expression with transduced RNA signals, and describe the signal processing response of our systems to periodic forcing in single live cells. The engineered systems integrate RNA–RNA interaction with available ribozyme and aptamer elements, providing new ways to engineer arbitrary complex gene circuits. PMID:25916845