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

作者： Nair, D Wenzel, L Natl Instruments Austin TX 78727 USA

ISBN: (纸本)0819432938

It is well known that high-dimensional integrals can be solved with Monte Carlo algorithms. Recently, it was discovered that there is a relationship between low discrepancy sets and the efficient evaluation of higher-dimensional integrals. Theory suggests that for midsize dimensional problems, algorithms based on low discrepancy sets should out perform all other existing methods by an order of magnitude in terms of the number of sample points used to evaluate the integrals. We show that the field of image processing can potentially take advantage of specific properties of low discrepancy sets. To illustrate this, we applied the theory of low discrepancy sequences to some relatively simple image processing and computer vision related operations such as the estimation of gray level image statistics, fast location of objects in a binary image and the reconstruction of images from a sparse set of points. Our experiments show that compared to standard methods, the proposed new algorithms are faster and statistically more robust. Classical low discrepancy sets based on the Halton and Sobol' sequences were investigated thoroughly and showed promising results. The use of low discrepancy sequences in image processing for image characterization, understanding and object recognition is a novel and promising area for further investigation.

关键词： sampling random sampling low-discrepancy sequences image statistics image reconstruction

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Time sequenced adaptive filtering using a modified P-vector algorithm 6

Time sequenced adaptive filtering using a modified P-vector ...

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

作者： Williams, R USAF WRIGHT LABAUTOMAT TARGET RECOGNIT DEV BRANCHWRIGHT PATTERSON AFBOH 45433

ISBN: (纸本)0819422347

An adaptive algorithm and two stage filter structure were developed for adaptive filtering of certain classes of signals that exhibit cyclostationary characteristics. The new modified P-vector algorithm (mPa) eliminates the need for a separate desired signal which is typically required by conventional adaptive algorithms. It is then implemented in a time-sequenced manner to counteract the nonstationary characteristics typically found in certain radar and bioelectromagnetic signals. Initial algorithm testing is performed on evoked responses generated by the visual cortex of the human brain with the objective, ultimately, to transition the results to radar signals. Each sample of the evoked response is modeled as the sum of three uncorrelated signal components, a time-varying mean (M), a noise component (N), and a random jitter component (Q). A two stage single channel time-sequenced adaptive filter structure was developed which improves convergence characteristics by de coupling the time-varying mean component from the `Q' and noise components in the first stage. The EEG statistics must be known a priori and are adaptively estimated from the pre stimulus data. The performance of the two stage mPa time-sequenced adaptive filter approaches the performance for the ideal case of an adaptive filter having a noiseless desired response.

关键词： time sequenced adaptive filter EEG biomedical signal processing radar signal processing

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A spectral phase algorithm for detecting and estimating pitch

A spectral phase algorithm for detecting and estimating pitc...

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

作者： Tempkin, JA Nelson, DJ USA Dept Def Ft George G Meade MD 20755 USA

ISBN: (纸本)0819441880

We describe a fast and efficient algorithm for automatic detection and estimation of the fundamental frequency F0 of a harmonic time-domain signal. The method is based on differentiation of the short time Fourier transform (STFT) phase, which is implemented as a cross-spectral product. In estimating and isolating the fundamental frequency, several enhancement processes are developed and applied to the TF surface to improve the signal quality. We describe the algorithm in detail and demonstrate the processing gain achieved at each step. In addition, we apply the algorithm to human speech to recover the pitch fundamental F0 and report the evaluation of the algorithm's performance on the Western Michigan vowel corpus [3].

关键词： signal processing

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Computationally efficient systolic architecture for computing the discrete Fourier transform

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IEEE TRANSACTIONS ON signal processing 2005年第12期53卷 4640-4651页

作者： Nash, JG Centar Los Angeles CA 90077 USA

A new high-performance systolic architecture for calculating the discrete Fourier transform (DFT) is described which is based on two levels of transform factorization. One level uses an index remapping that converts the direct transform into structured sets of arithmetically simple four-point transforms. Another level adds a row/column decomposition of the DFT. The architecture supports transform lengths that are not powers of two or based on products of coprime numbers. Compared to previous systolic implementations, the architecture is computationally more efficient and uses less hardware. It provides low latency as well as high throughput, and can do both one- and two-dimensional DFTs. An automated computer-aided design tool was used to find latency and throughput optimal designs that matched the target field programmable gate array structure and functionality.

关键词： computation fast algorithms parallel processing architectures systolic and wavefront architectures transforms

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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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OPTIMAL KERNELS FOR TIME-FREQUENCY ANALYSIS

OPTIMAL KERNELS FOR TIME-FREQUENCY ANALYSIS

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CONF ON advanced signal-processing algorithms, architectures, AND implementations

作者： BARANIUK, RG JONES, DL Univ. of Illinois/Urbana-Champaign (United States)

ISBN: (纸本)0819404098

Current bilinear time-frequency representations apply a fixed kernel to smooth the Wigner distribution. However the choice of a fixed kernel limits the class ofsignals that can be analyzed effectively. This paper presents optimality criteria for the design of signal-dependeni kernels that suppress cross-components while passing as much auto-component energy as possible irrespective of the form of the signal. A fast algorithm for the optimal kernel solution makes the procedure competitive computationaily with fixed kernel methods. Examples demonstrate the superior performance of the optimal kernel for a frequency modulated signal.

关键词： Time-frequency analysis Fourier transforms Smoothing signal analyzers signal to noise ratio Analytical research Interference (communication) Modulation Convolution Wavelets

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COHERENT signal-SUBSPACE processing FOR NEAR-FIELD BROAD-BAND SOURCE LOCALIZATION 4

COHERENT SIGNAL-SUBSPACE PROCESSING FOR NEAR-FIELD BROAD-BAN...

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4TH CONF ON advanced signal processing algorithms, architectures, AND implementations

作者： LIN, S HUNG, HS Iowa State Univ. (United States)

ISBN: (纸本)0819412767

In this paper, the coherent signal-subspace method (CSM) is extended for estimation of bearing, elevation and range of multiple, near-field, broad-band sources. Analytical results are also derived to justify the effectiveness of the near-field CSM. It is shown that the coherently averaged sample covariance matrix in the near-field CSM has complex Wishart distribution with number of degrees-of-freedom equaling the time-bandwidth product, provided that (1) the frequency components of the array output are statistically independent and Gaussian distributed, and (2) the errors between all the actual source locations and the preliminary estimate of the source cluster center are upperly bounded by a small constant. Some simulation results are provided to show the effectiveness of the near-field CSM.

关键词： Near field signal processing Error analysis Sensors Statistical analysis Data modeling Interference (communication) signal to noise ratio Source localization Spherical lenses

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NUMERICAL-INTEGRATION OF PDES BY DISCRETE PASSIVE MODELING OF PHYSICAL SYSTEMS 4

NUMERICAL-INTEGRATION OF PDES BY DISCRETE PASSIVE MODELING O...

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4TH CONF ON advanced signal processing algorithms, architectures, AND implementations

作者： FETTWEIS, A Ruhr-Univ. Bochum (Germany)

ISBN: (纸本)0819412767

A new method for numerically integrating partial differential equations (PDEs) has been under study for the last few years. This method is based on principles of multidimensional (MD) Kirchhoff circuits and multidimensional wave digital filters (MD WDFs), which explains why it has probably not been discovered earlier. It makes wide use of methods and results that have been developed by extensive research in the areas of circuit theory and digital signal processing, but that are rather unknown outside of the small circle of experts on MD WDFs. Instead of talking about MD WDFs we prefer using, within the context of numerical integration, the designation `discrete multidimensionally passive (MD-passive) dynamical systems.'

关键词： Palladium Wigner distribution functions Systems modeling Neodymium Numerical integration Digital electronics Digital signal processing signal processing Digital filtering Partial differential equations

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STABLE CHASING algorithms FOR MODIFYING COMPLETE AND PARTIAL SINGULAR-VALUE DECOMPOSITIONS 4

STABLE CHASING ALGORITHMS FOR MODIFYING COMPLETE AND PARTIAL...

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4TH CONF ON advanced signal processing algorithms, architectures, AND implementations

作者： BARLOW, JL ZHA, HY YOON, PA The Pennsylvania State Univ. (United States)

ISBN: (纸本)0819412767

Methods for updating and downdating singular value decompositions (SVDs) and partially reduced bidiagonal forms (partial SVDs) are introduced. The methods are based upon chasing procedures for updating the SVD and downdating procedures for orthogonal decompositions. The main feature of these methods is the ability to separate the singular values into `large' and `small' sets and then obtain an updated bidiagonal form with corresponding `large' and `small' columns. This makes for a more accurate update or dosndate.

关键词： Matrices Computer science Feature extraction Tolerancing Applied research Error analysis Lithium signal processing

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signal-ADAPTIVE DECOMPOSITION OF MULTICOMPONENT signalS 4

SIGNAL-ADAPTIVE DECOMPOSITION OF MULTICOMPONENT SIGNALS

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4TH CONF ON advanced signal processing algorithms, architectures, AND implementations

作者： ASSALEH, KT MAMMONE, RJ Rutgers Univ. (United States)

ISBN: (纸本)0819412767

In this paper we present a new method for adaptively decomposing a multicomponent signal into its components. This method is based on fitting an autoregressive (AR) model to the short-time spectra of the signal. The AR parameters represent the coefficients of the linear predictive (LP) polynomial. The roots of this polynomial constitute a set of center frequencies and bandwidths that characterize the modes of the signal. The decomposition process is achieved by applying a time-varying filter bank to the original multicomponent signal. The characteristics of this filter bank are derived from a subset of the roots of the LP polynomial. We have developed a constraining algorithm to determine that subset based on the boundedness of the bandwidths, and the temporal continuity of the center frequencies of the components. We have applied the proposed decomposition method for the separation of the formants of speech signals.

关键词： Autoregressive models signal to noise ratio Electronic filtering Composites Digital filtering Algorithm development signal processing Image segmentation Resonators Time-frequency analysis

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