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共 172 条记录，以下是91-100 订阅

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Integrated numeric and symbolic signal processing using a heterogeneous design environment 6

Integrated numeric and symbolic signal processing using a he...

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conference on advanced signal processing algorithms, architectures, and implementations VI

作者： Mani, R Nawab, SH Winograd, JM Evans, BL BOSTON UNIV BOSTONMA 02215

ISBN: (纸本)0819422347

We present a solution to a complex multi-tone transient detection problem to illustrate the integrated use of symbolic and numeric processing techniques which are supported by well-established underlying models. Examples of such models include synchronous dataflow for numeric processing and the blackboard paradigm for symbolic heuristic search. Our transient detection solution serves to emphasize the importance of developing system design methods and tools which can support the integrated use of well- established symbolic and numerical models of computation. Recently, we incorporated a blackboard-based model of computation underlying the Integrated processing and Understanding of signals (IPUS) paradigm into a system-level design environment for numeric processing called Ptolemy. Using the IPUS/Ptolemy environment, we are implementing our solution to the multi-tone transient detection problem.

关键词： design environments symbolic signal processing heuristic search blackboard model synchronous dataflow model Ptolemy Integrated processing and Understanding of signals (IPUS) multi-tone transient detection Adaptive Time-Frequency Representation (ATFR)

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A unified Bayesian framework for algorithms to recover blocky signals

A unified Bayesian framework for algorithms to recover block...

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conference on advanced signal processing algorithms, architectures, and implementations XVII

作者： Calvetti, Daniela Somersalo, Erkki Case Western Reserve Univ Dept Math Cleveland OH 44106 USA Case Western Reserve Univ Ctr Modeling Integrated Metab Syst Cleveland OH 44106 USA Aalto Univ Dept Math Helsinki Finland

ISBN: (纸本)9780819468451

We consider the problem of recovering signals from noisy indirect observations under the additional a priori information that the signal is believed to be slowly varying except at all unknown number of points where it may have discontinuities of unknown size. The model problem is a linear deconvolution problem. To take advantage of the qualitative prior information available, we use a non-stationary Markov model with the variance of the innovation process also unknown, and apply Bayesian techniques to estimate both the signal and the prior variance. We propose a fast iterative method for computing a MAP estimates and we show that, with a rather standard choices of the hyperpriors, the algorithm produces the fixed point iterative solutions of the total variation and of the Perona-Malik regularization methods. We also demonstrate that, unlike the non-statistical estimation methods, the Bayesian approach leads to a very natural reliability assessment of edge detection by a Markov Chain Monte Carlo (MCMC) based analysis of the posterior.

关键词： signal processing Data modeling Reliability Stochastic processes Atrial fibrillation Autoregressive models Deconvolution Monte Carlo methods Statistical analysis Mathematics

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Segmented chirp features and hidden Gauss-Markov models for classification of wandering-tone signals

Segmented chirp features and hidden Gauss-Markov models for ...

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conference on advanced signal processing algorithms, architectures and implementations xiI

作者： Ainsleigh, PL USN Undersea Warfare Ctr Newport RI 02840 USA

ISBN: (纸本)0819445584

A new feature set and decision function are proposed for classifying transient wandering-tone signals. signals are partitioned in time and modeled as having piecewise-linear instantaneous frequency and piecewise-constant amplitude. The initial frequency, chirp rate, and amplitude are estimated in each segment. The resulting sequences of estimates are used as features for classification. The decision function employs a linear Gaussian dynamical model, or hidden Gauss-Markov model (HGMM). The parameters that characterize the HGMM for each class are estimated from labeled training sequences, and the trained models are used to evaluate the class-conditional likelihoods of an unlabeled signal. The signal is assigned to the-class whose model gives the maximum conditional likelihood. Simulation experiments demonstrate perfect classification performance in a three-class forced-choice problem.

关键词： Ferroelectric materials Bismuth Picosecond phenomena Information technology Weapons of mass destruction signal processing

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A novel signal detection technique based on generalized scale transforms - art. no. 63130Y

A novel signal detection technique based on generalized scal...

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conference on advanced signal processing algorithms, architectures, and implementations XVI

作者： Nickel, Robert M. Penn State Univ Dept Elect Engn University Pk PA 16802 USA

ISBN: (纸本)0819463922

We are presenting an extension to the classic multiple signal classification method (MUSIC) developed by Schmidt and Bienvenu in 1979.(1) While the classic MUSIC algorithm is limited to the detection of constant frequency sinusoids in white noise, the proposed new method is capable of detecting signals with a continuously varying instantaneous frequency. The method is based on the development of a discrete-time version of the generalized scale transform (GST) which was introduced by Nickel and Williams in 1999.(2) As a byproduct we obtain techniques for discrete-time warp-shift invariant filtering which can be used in addition to the signal detection to separate signals with different instantaneous frequency contours.

关键词： warping functions sampling theory generalized scale transform signal detection multiple signal classification (MUSIC)

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Missile signal processing common computer architecture for rapid technology upgrade

Missile signal processing common computer architecture for r...

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conference on advanced signal processing algorithms, architectures, and implementations xiV

作者： Rabinkin, D Rutledge, E Monticciolo, P MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819454974

Interceptor missiles process IR images captured by a focal plane array for locating and guiding the interceptor toward an intended target. A typical interceptor signal processing chain comprises two parts. Front-end video processing operates on all pixels of the image and performs such operations as non-uniformity correction (NUC), image stabilization, frame integration and detection. Back-end target processing, which tracks and classifies targets detected in the image, performs such algorithms as Kalman tracking, spectral feature extraction and target discrimination. signal processing requirements increased as sensor bandwidth increases and interceptors operate against more sophisticated targets. In the past, video processing was implemented using ASICs or FPGAs because computation requirements exceeded the throughput of general-purpose processors. Target processing was performed using hybrid architectures that included ASICs. DSPs and general-purpose processors. The resulting systems tended to be very function-specific, and required custom software development. These systems were developed using non-integrated toolsets, and test equipment had to be developed along with the processor platform. The lifespan of the interceptor platform on which the signal processors operate often spans decades, while the specialized nature of processsor hardware and software makes it difficult and costly to upgrade. As a result., the signal processing systems often run on outdated components, signal processing algorithms are difficult to update. and system effectiveness is impaired by the inability to rapidly, respond to new threats. A new design approach to interceptor signal processing is made possible by three developments: Moore's Law - driven improvement in computational throughput;a newly introduced vector computing capability in general-purpose processors and a modern set of open interface software standards. Today's multiprocessor commercial-off-the-shelf (COTS) platforms hav

关键词： signal processing Digital signal processing Target detection Detection and tracking algorithms Image processing Standards development MATLAB Commercial off the shelf technology signal to noise ratio Software development

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Application of time-frequency analysis methods to speaker verification

Application of time-frequency analysis methods to speaker ve...

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conference on advanced signal processing algorithms, architectures, and implementations XVI

作者： Williams, W. J. Bossemeyer, R. W. Quantum Signal LLC Ann Arbor MI 48176 USA Univ Michigan EECS Ann Arbor MI 48109 USA Speech Technol Appl Res Inc St Charles IL USA

ISBN: (纸本)0819463922

Time-Frequency Analysis has previously been successfully applied to characterize and quantify a variety of acoustic signals, including marine mammal sounds. In this research, Time-Frequency analysis is applied to human speech signals in an effort to reveal signal structure salient to the biometric speaker verification challenge. Prior approaches to speaker verification have relied upon signal processing analysis such as linear prediction or weighted Cepstrum spectral representations of segments of speech and classification techniques based on stochastic pattern matching. The authors believe that the classification of identity of a speaker based on time-frequency representation of short time events occurring in speech could have substantial advantages. Using these ideas, a speaker verification algorithm was developed(1) and has been refined over the past several years. In this presentation, the authors describe the testing of the algorithm using a large speech database, the results obtained, and recommendations for further improvements.

关键词： time-frequency speaker verification multimodal biometrics homeland security pattern recognition

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Modern microphone array for hearing aid and speech processing 6

Modern microphone array for hearing aid and speech processin...

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conference on advanced signal processing algorithms, architectures, and implementations VI

作者： Wang, A Yao, K Hudson, RE Korompis, D Lorenzelli, F Soli, SD Gao, S UNIV CALIF LOS ANGELES DEPT ELECT ENGNLOS ANGELESCA 90095

ISBN: (纸本)0819422347

For various audio, teleconference, hearing aid, and voice recognition applications, a microphone array is known to be an effective method to enhance the SNR in noisy environments resulting in significant improvement of speech intelligibility or recognition. We propose an novel electronically steerable microphone array based on the Maximum Energy concentration criterion to form a focused beam toward the desired speech source, attenuating background noises and rejecting discrete spatial interferers. The design and implementation of a prototype DSP-based microphone array system are described. Some details on microphone measurement, calibration, and optimization needed to achieve a high performance microphone array are discussed. Computer simulated and measured array performances are presented to show the effectiveness of the array system.

关键词： Sensors Calibration signal to noise ratio Digital signal processing Computer simulations Near field Acoustics Computing systems signal processing Speaker recognition

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A multivariate speech activity detector based on the syllable rate

A multivariate speech activity detector based on the syllabl...

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SPIE conference on advanced signal processing algorithms, architectures, and implementations VIII

作者： Smith, D Townsend, J Nelson, DJ US Dept Def Ft George G Meade MD 20755 USA

ISBN: (纸本)0819429163

Computationally efficient algorithms which perform speech activity detection have significant potential economic and labor saving benefit, by automating an extremely tedious manual process. In many applications, it is desirable to extract intervals of speech which are bounded by segments of other signal types (fax/modem, music, static, dial tones, etc.). In the past, algorithms which successfully discriminate between speech and one specific other signal type have been developed. Frequently, these algorithms fail when the specific non-speech signal is replaced by a different non-speech signal. Little work has been done on combining such discriminators in order to solve the general speech vs. non-speech discrimination problem. Typically, several signal specific discriminators are blindly combined with predictable negative results. Moreover, when a large number of discriminators are involved, dimension reduction is achieved using Principal Components, which optimally compresses signal variance into the fewest number of dimensions. Unfortunately, these new coordinates are not necessarily optimal for discrimination. In this paper we apply graphical tools to determine a set of discriminators which produce excellent speech vs. non-speech clustering, thereby eliminating the guesswork in selecting good feature vectors. This cluster structure provides a basis for a general multivariate speech vs. non-speech discriminator, which compares very favorably with the TALKATIVE speech extraction algorithm.

关键词： signal processing

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Binary openings and closings in one pass using finite-state machines 6

Binary openings and closings in one pass using finite-state ...

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conference on advanced signal processing algorithms, architectures, and implementations VI

作者： Waltz, FM Consultant (United States)

ISBN: (纸本)0819422347

In a series of ten papers published since 1994, a radically new technique for implementing a wide range of standard image processing operations has been presented, under the acronym SKIPSM (Separated-Kernel Image processing using finite State Machines). Key steps are: (1) the operation is separated into a row operation followed by a column operation, (2) these row and column operations are put in recursive form. That is, in a form compatible with either one-step software implementation or pipelined raster-scan hardware implementation, (3) the resulting operations are realized as FSMs (finite-state machines), and (4) these FSMs are implemented in software or in inexpensive off-the-shelf integrated circuits. Note that this technique does not require separability, in the usual sense. In this paper, the SKIPSM technique is applied to computing binary openings and closings in one pass using arbitrary binary structuring elements. Whether the resulting finite state machines are implemented in software or hardware, the result is generally much faster and/or much cheaper than conventional implementations. Furthermore, this same SKIPSM architecture is highly versatile and programmable, allowing it to be software-reconfigured to perform hundreds of other software- based or pipelined image processing operations, such a binary and grey-level morphology, the Grassfire Transform, binary and grey-level template matching, binary skeletonization, etc.

关键词： fast implementations image processing finite-state machines separability pipelining real-time inspection

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How bad are symmetric Pick matrices

How bad are symmetric Pick matrices

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conference on advanced signal processing algorithms, architectures, and implementations X

作者： Fasino, D Olshevsky, V Univ Udine Dipartimento Matemat & Informat I-33100 Udine Italy

ISBN: (纸本)0819437611

Let P be a symmetric positive definite Pick matrix of order n. The following facts will be proven here: 1. P is the Gram matrix of a set of rational functions, with respect to a inner product defined in terms of a "generating function" associated to P;2. Its condition number is lower-bounded by a function growing exponentially in n. 3. P can be effectively preconditioned by the Pick matrix generated by the same nodes and a constant function.

关键词： Matrices Condition numbers algorithms Computing systems Control systems Image information entropy Linear algebra Mathematics Platinum signal processing

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