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共 458 条记录，以下是231-240 订阅

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An efficient high-resolution time-frequency representation

An efficient high-resolution time-frequency representation

引用

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

作者： Nelson, D. J. Smith, D. C. US Dept Def R61 Ft George G Meade MD 20755 USA

ISBN: (纸本)0819463922

We address the problem of efficient resolution, detection and estimation of weak tones in a potentially massive amount of data. Our goal is to produce a relatively small reduced data set characterizing the signals in the environment in time and frequency. The requirements for this problem are that the process must be computationally efficient, high gain and able to resolve signals and efficiently compress the signal information into a form that may be easily displayed and further processed. We base our process on the cross spectral representation we have previously applied to other problems. In selecting this method, we have considered other representations and estimation methods such as the Wigner distribution and Welch's method. We compare our method to these methods. The spectral estimation method we propose is a variation of Welch's method and the cross-power spectral (CPS) estimator which was first applied to signal estimation and detection in the mid 1980's. The CPS algorithm and the method we present here are based on the principles first described by Kodera et at. now frequently called the reassignment principle.

关键词： signal detection signal estimation transient signals time-frequency representations

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Operational data processing to improve SPOT image resolution

Operational data processing to improve SPOT image resolution

引用

Conference on advanced signal processing algorithms, architectures, and implementations XI

作者： Breton, E Latry, C Lévy, F Rougé, B IGN F-31055 Toulouse France

ISBN: (纸本)0819441880

Mainly digital images are under sampled. It is the same for SPOT digital image satellite. The very meaning is that the instrument is too much powerful for this sampling. The worth side effect is that artifacts (aliasing) are introduced in the image, the good side is that images can be improved if the sampling density is increased. In this paper we use images from the two HRVIR instruments onboard SPOT1-4 satellite to multiply by a factor two the density and the resolution of the image.

关键词： super resolution operational data processing interlaced sampling interpolation correlation SPOT

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Optimum microphone placement for array sound capture

Optimum microphone placement for array sound capture

引用

Conference on advanced signal processing - algorithms, architectures, and implementations VII

作者： Rabinkin, DV Renomeron, RJ French, JC Flanagan, JL Rutgers Univ. (United States)

ISBN: (纸本)0819425842

Microphone arrays can be used for high-quality sound pick up in reverberant and noisy environments. The beamforming capabilities of microphone array systems allow highly directional sound capture, providing superior signal-to-noise ratio (SNR) when compared to single microphone performance. There are two aspects in microphone array system performance: The ability of the system to locate and track sound sources, and its ability to selectively capture sound from those sources. Both aspects of system performance are strongly affected by the spatial placement of microphone sensors. A method is needed to optimize sensor placement based on geometry of the environment and assumed sound source behavior. The objective of the optimization is to obtain the greatest average system SNR using a specified number of sensors. A method is derived to evaluate array performance for a given array configuration defined by the above mentioned metrics. An overall performance function is described based on these metrics. A framework for optimum placement of sensors under the practical considerations of possible sensor placement and potential location of sound sources is also characterized.

关键词： signal to noise ratio Sensors Error analysis Interference (communication) Acoustics Monte Carlo methods signal attenuation Statistical analysis Environmental sensing signal processing

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Time-frequency domain reflectometry for smart wiring systems

Time-frequency domain reflectometry for smart wiring systems

引用

Conference on advanced signal processing algorithms, architectures and implementations XII

作者： Shin, YJ Song, ES Kim, JW Park, JB Yok, JG Powers, EJ Univ Texas Dept Elect & Comp Engn Austin TX 78712 USA

ISBN: (纸本)0819445584

In this paper, a new high resolution reflectometry scheme, time-frequency domain reflectometry, is proposed to detect and locate a fault in wiring. Traditional reflectometry methods have been achieved in either the time domain or frequency domain only. However, time-frequency domain reflectometry utilizes time and frequency information of a transient signal to detect and locate the fault. The time-frequency domain reflectometry approach described in this paper is characterized by time-frequency reference signal design and post-processing of the reference and reflected signals to detect and locate the fault. Using a computational electromagnetic model of a coaxial cable with a fault, time-frequency domain reflectometry has been demonstrated. Knowledge of time and frequency localized information for the reference and reflected signal gained via time-frequency analysis, allows one to detect the fault and estimate the location accurately.

关键词： time-frequency domain reflectometry chirp signal fault detection fault location smart wiring

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Blind source separation using joint signal representations for arbitrary variables.

Blind source separation using joint signal representations f...

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Conference on advanced signal processing - algorithms, architectures, and implementations VII

作者： Belouchrani, A Amin, MG Villanova Univ. (United States)

ISBN: (纸本)0819425842

Blind source separation is an emerging field of fundamental research with a broad range of applications. It is motivated by practical problems that involve several source signals and several sensors. Each sensor receives an instantaneous linear mixture of the source signals. The problem of the blind source separation consists then of recovering the original waveforms of the sources without any knowledge of the mixture structure. So far, the problem of the blind source separation has been solved using statistical information available on the source signals. A blind source separation approach for non-stationary signals based on time-frequency representations (TFR) have been recently introduced by the authors (SPIE 1996). Herein, we generalize the TFR based blind source separation approach to arbitrary variables, including time and frequency. 'Spatial joint arbitrary variable distributions' are introduced and used for blind source separation via joint diagonalization techniques.

关键词： blind source separation time-frequency representation joint signal representation spatial joint arbitrary variable distributions joint diagonalization

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Local regularization and Bayesian hypermodels

Local regularization and Bayesian hypermodels

引用

advanced signal processing algorithms, architectures, and implementations XV

作者： Calvetti, Daniela Somersalo, Erkki Department of Mathematics Center for Modeling Integrated Metabolic Systems Case Western Reserve University Cleveland OH United States Department of Mathematics Helsinki University of Technology Helsinki Finland

In this paper, we restore a one-dimensional signal that a priori is known to be a smooth function with a few jump discontinuities from a blurred, noisy specimen signal using a local regularization scheme derived in a Bayesian statistical inversion framework. The proposed method is computationally effective and reproduces well the jump discontinuities, thus is an alternative to using a total variation (TV) penalty as a regularizing functional. Our approach avoids the non-differentiability problems encountered in TV methods and is completely data driven in the sense that the parameter selection is done automatically and requires no user intervention. A computed example illustrating the performance of the method when applied to the solution of a deconvolution problem is also presented.

关键词： signal processing

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RECURSIVE LEAST-SQUARES LEARNING algorithms FOR NEURAL NETWORKS

RECURSIVE LEAST-SQUARES LEARNING ALGORITHMS FOR NEURAL NETWO...

引用

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

作者： LEWIS, PS HWANG, JN Los Alamos National Lab. (United States) Univ. of Washington (United States)

ISBN: (纸本)0819404098

This paper presents the development of a pair of recursive least squares (ItLS) algorithms for online training of multilayer perceptrons which are a class of feedforward artificial neural networks. These algorithms incorporate second order information about the training error surface in order to achieve faster learning rates than are possible using first order gradient descent algorithms such as the generalized delta rule. A least squares formulation is derived from a linearization of the training error function. Individual training pattern errors are linearized about the network parameters that were in effect when the pattern was presented. This permits the recursive solution of the least squares approximation either via conventional RLS recursions or by recursive QR decomposition-based techniques. The computational complexity of the update is 0(N2) where N is the number of network parameters. This is due to the estimation of the N x N inverse Hessian matrix. Less computationally intensive approximations of the ilLS algorithms can be easily derived by using only block diagonal elements of this matrix thereby partitioning the learning into independent sets. A simulation example is presented in which a neural network is trained to approximate a two dimensional Gaussian bump. In this example RLS training required an order of magnitude fewer iterations on average (527) than did training with the generalized delta rule (6 1 BACKGROUND Artificial neural networks (ANNs) offer an interesting and potentially useful paradigm for signal processing and pattern recognition. The majority of ANN applications employ the feed-forward multilayer perceptron (MLP) network architecture in which network parameters are " trained" by a supervised learning algorithm employing the generalized delta rule (GDIt) [1 2]. The GDR algorithm approximates a fixed step steepest descent algorithm using derivatives computed by error backpropagatiori. The GDII algorithm is sometimes referred to as the

关键词： Algorithm development Detection and tracking algorithms Evolutionary algorithms Neural networks Network architectures Artificial neural networks Pattern recognition Chemical elements Machine learning signal processing

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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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An efficient array processor for accurate downdating of ULV decomposition

An efficient array processor for accurate downdating of ULV ...

引用

Conference on advanced signal processing algorithms, architectures, and implementations XI

作者： Yoon, PA Sibul, LH Trinity Coll Dept Comp Sci Hartford CT 06106 USA

ISBN: (纸本)0819441880

We present an efficient array processor for downdating the ULVD. The array processor exploits the block structure of the decomposition to determine the effective rank at every step of modification and maintains the rank-revealing nature of the decomposition throughout the steps by tracking exact quantities of Frobenius norms of all three blocks of the lower triangular factor in the decomposition. Thus. a deflation step that is necessary to compute its numerical rank can be often avoided. This feature of the algorithm is particularly attractive to its array processor implementation because the deflation steps usually require some condition estimation. and most of good condition estimators are not well pipelined.

关键词： signal processing null space rank detection array processors

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Convergence results on adaptive approximate filtering 6

Convergence results on adaptive approximate filtering

引用

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

作者： Ludwig, JT Nawab, SH Chandrakasan, AP MIT ELECT RES LABCAMBRIDGEMA 02139

ISBN: (纸本)0819422347

We present an IIR filtering technique based upon a recently proposed approach for reducing power consumption in implementation of frequency-selective filters. The basic idea in such techniques is to utilize the most recent input and output signal samples to estimate the current SNR (defined as the ratio of the in-band signal power to the out-of-band signal power) at the filter's input. This estimated input SNR is then used to update the filter order to the minimum value which would guarantee a minimum tolerable SNR at the filter's output. A key issue addressed in this paper is how well the estimated filter order converges to the theoretical minimum for situations satisfying the assumptions behind the derivation of the technique. Experimental results are used to verify that convergence to the correct filter order depends (1) upon the number of input and output samples used for estimating the input SNR, (2) upon the filter order applied in generating the output samples that are used in estimating the input SNR and (3) upon the proximity of the actual input SNR to boundaries in the input-SNR space corresponding to changes in the optimal choice for filter order.

关键词： low power approximate processing incremental refinement structure frequency-selective filtering Butterworth filters adaptive filtering

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