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Proceedings of SPIE - advanced signal processing algorithms, architectures, and implementations xvii

Proceedings of SPIE - Advanced Signal Processing Algorithms,...

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advanced signal processing algorithms, architectures, and implementations xvii

ISBN: (纸本)9780819468451

The proceedings contain 28 papers. The topics discussed include: on matrix-vector product based sub-quadratic arithmetic complexity schemes for field multiplication;a unified Bayesian framework for algorithms to recover blocky signals;face recognition algorithm in hyperspectral imagery by employing the K-means method and the mahalanobis distance;time-varying spectral analysis in exercise and sport science;construction of time-frequency representations from moments;a comparative evaluation of image background subtraction techniques;surface compression using over-determined laplacian approximation;theoretical and experimental study of DOA estimation using AML algorithm for an isotropic and non-isotropic 3D array;optimal location of feedback handler under receiver contention schemes for routing in wireless networks;and optical infrared flame detection with neural networks.

关键词： signal processing

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Linear invariant systems

Linear invariant systems

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

作者： Cohen, Leon CUNY New York NY 10021 USA

ISBN: (纸本)9780819468451

We formulate in a simple fashion the concept of invariance for a linear system. We show that one must define what we call an "associated Hermitian operator"' which commutes with the system function. We show that it is this Hermitian operator that defines the invariance and also determines the appropriate transform and other connections between input and output relations.

关键词： signal processing

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Optical infrared flame detection system with neural networks

Optical infrared flame detection system with neural networks

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

作者： Huseynov, Javid J. Baliga, Shankar B. Univ Calif Irvine Sch Informat & Comp Sci Irvine CA 92697 USA Gen Monitors Inc Lake Forest CA 92630 USA

ISBN: (纸本)9780819468451

A model for an infrared (M) flame detection system using artificial neural networks (ANN) is presented. The joint time-frequency analysis (JTFA) in the form of a Short-Time Fourier Transform (STFT) is used for extracting relevant input features for a set of ANNs. Each ANN is trained using the backpropagation conjugate-gradient (CG) method to distinguish all hydrocarbon flames from a particular type of environmental nuisance and background noise. signal saturation caused by the increased intensity of IR sources at closer distances is resolved by an adjustable gain control. A classification scheme with trained ANN connection weights was implemented on a digital signal processor for use in an industrial hydrocarbon flame detector.

关键词： artificial neural networks signal processing infrared detectors fire detection

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Construction of time-frequency representations from moments

Construction of time-frequency representations from moments

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

作者： Cohen, Leon Loughlin, Patrick Davidson, Keith CUNY 695 Pk Ave New York NY 10021 USA Univ Pittsburgh Pittsburgh PA 15261 USA Off Naval Res Arlington VA 22217 USA

ISBN: (纸本)9780819468451

Given the moments of a time-frequency distribution, one can, in principle, construct the characteristic function from which one then obtains the distribution by Fourier transformation. However, often one can not find a closed form for the characteristic function and hence one can not obtain the distribution in a direct manner. We formulate the problem of constructing time-frequency representations from moments without first constructing the characteristic function. Our method is based on expanding the distribution in terms of a complete set of functions where the expansion coefficients are dependent directly on the moments. We apply the method to a case where the even moments are manifestly positive which is a necessary condition for obtaining a proper time-frequency representation.

关键词： Time-frequency analysis Fermium Frequency modulation Acoustics Applied physics Fourier transforms Scattering Scientific research signal processing

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Rapid transient superresolution frequency tracking via generalized ESPRIT

Rapid transient superresolution frequency tracking via gener...

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

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

ISBN: (纸本)9780819468451

We are presenting a new method for super resolution tracking of frequency modulated sinusoids in white noise. The method is specifically designed to handle the rapid transient problem, i.e. the problem of tracking a continuous, rapidly changing instantaneous frequency contour. The proposed method employs to components: 1) an adaptive generalized scale transform 1, 2 which applies a localized change of time-frequency coordinates within the given signal, and 2) an estimation of signal parameters by rotational invariance techniques 3 (ESPRIT). With experiments we have shown that the proposed method provides a significantly higher estimation accuracy than conventional methods. 3 With an optimal choice of transform parameters the estimation error can be reduced dramatically. Error reductions of over 40% have been observed.

关键词： instantaneous frequency tracking non-uniform sampling estimation of signal parameters by rotational invariance techniques (ESPRIT) generalized scale transform

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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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Seismic-array signal processing for moving source localization

Seismic-array signal processing for moving source localizati...

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

作者： Stafsudd, Jing Z. Hudson, Ralph E. Taciroglu, Ertugrul Yao, Kung UCLA Dept Elect Engn Los Angeles CA 90095 USA UCLA Dept Civil & Environm Engn Los Angeles CA 90095 USA

ISBN: (纸本)9780819468451

In this paper, we consider the use of a seismic sensor array for the localization and tracking of a wideband moving source. The proposed solution consists of two steps: source Direction-Of-Arrival (DOA) estimation and localization via DOA estimates. Three DOA estimation methods are considered. The Covariance Matrix Analysis and the Surface Wave Analysis are previously published DOA estimation algorithms shown to be effective in the localization of a stationary wideband source. This paper investigates their performance on moving wideband sources. A novel DOA estimation algorithm, the Modified Kirlin's Method was also developed for the localization of a moving Source. The DOAs estimated by these algorithms are combined rising a least-squares optimization for source localization. The application of these algorithms to real-life data show the effectiveness of both the Surface Wave Analysis and the Modified Kirlin's Method in locating and tracking a wideband moving source.

关键词： direction-of-arrival (DOA) source localization mover localization seismic signal processing surface waves

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Time-varying spectral analysis in exercise and sport science

Time-varying spectral analysis in exercise and sport science

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

作者： Frishberg, Barry A. Galleani, Lorenzo Cohen, Leon S Carolina State Univ 300 Coll St Orangeburg SC 29117 USA Politecn Torino I-10129 Turin Italy CUNY New York NY 10021 USA

ISBN: (纸本)9780819468451

We discuss the application of time-frequency analysis to biomechanical-type signals, and in particular to signals that would be encountered in the study of rotation rates of bicycle pedaling. We simulate a number of such signals and study how well they are represented by various time-frequency methods. We show that time-frequency representations track very well the instantaneous frequency even when there are very fast changes. In addition. we do a correlation analysis between time-series whose instantaneous frequency is changing and show that the traditional correlation coefficient is insufficient to characterize the correlations. We instead show that the correlation coefficient should be evaluated directly from the instantaneous frequencies of the time series, which can be easily estimated from their time-frequency distributions.

关键词： Time-frequency analysis Heart signal generators Biological research Computer simulations signal analyzers Fourier transforms Information operations signal detection Physical phenomena

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VHDL token-based performance modeling for 2D and 3D infrared search and track processing

VHDL token-based performance modeling for 2D and 3D infrared...

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

作者： Pauer, EK Pettigrew, MN Myers, CS Madisetti, VK Signal Proc Ctr Nashua NH 03061 USA

ISBN: (纸本)0819429163

This study develops and evaluates a new VHDL-based performance modeling capability for multiprocessor systems.* The framework for this methodology involved modeling the following system aspects: processor characterization, task modeling, network characterization, and data set size. Initially, all aspects are specified at an abstract) level, and eventually become specified at a detailed level through the process of verification and refinement of design assumptions. Processor characterization involves modeling the processor's speed, instruction set, and memory hierarchy. Task modeling is concerned with the execution time and instruction mix of software tasks within the system. Network characterization models bus protocols, topology, and bandwidths. Data set size refers to how much data is represented by the tokens used in the models. In this study, we applied and evaluated this methodology using both two-dimensional (2D) and three-dimensional (3D) infrared search and track (IRST) algorithms. Two different candidate processors were investigated: IBM PowerPC 604 and Texas Instruments TMS320C80. For the 2D IRST algorithm, the abstract and detailed performance modeling results were obtained far both processors using partitioned data and pipelined algorithmic approaches. For the 3D IRST algorithm, abstract performance models for pipelined and parallelized implementations on the PowerPC were developed. These models examined the feasibility of the implementations, the potential risk areas, and laid the groundwork for detailed performance modeling.

关键词： performance modeling VHDL IRST architectures simulation

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Time-varying noise

Time-varying noise

引用

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

作者： Galleani, L Cohen, L CUNY New York NY 10021 USA

We obtain the exact Wigner spectrum for non-white Gaussian noise. As a special case the Wigner spectrum for the Wiener process is obtained.

ISBN: (纸本)0819454974

We obtain the exact Wigner spectrum for non-white Gaussian noise. As a special case the Wigner spectrum for the Wiener process is obtained.

关键词： signal processing

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