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共 176 条记录，以下是51-60 订阅

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Multi-scale blind deconvolution of sensor array signals via scale transform

Multi-scale blind deconvolution of sensor array signals via ...

引用

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

作者： Izzetoglu, M Akgül, T Drexel Univ Dept Elect & Comp Engn Philadelphia PA 19104 USA

ISBN: (纸本)0819432938

In this paper we introduce a. multi-scale deconvolution technique performed in the scale-domain. In sensor array applications such as in radar, sonar and seismic processing, the sensor outputs are modeled as the convolution of the unknown source signal with various unknown system impulse responses that are scaled versions of each other with unknown scale parameters. In many applications these signals or the scaling parameters are needed to be estimated only from the sensor outputs. In our earlier work, we estimated the unknown scale parameters by using properties of the scale transform and then employed existing deconvolution algorithms. Here, we derive the multiscale blind deconvolution algorithm in the scale transform domain. The performance of the method is illustrated using simulation examples.

关键词： Sensors Deconvolution Reflectors Convolution signal processing Algorithm development Computer simulations Electronic filtering Image processing Radar

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Proceedings of SPIE: advanced signal processing algorithms, architectures, and implementations XI

Proceedings of SPIE: Advanced signal processing algorithms, ...

引用

advanced signal processing: algorithms, architectures and implementations XI

The proceedings contains 56 papers from the conference on SPIE: advanced signal processing algorithms, architectures, and implementations XI. The topics discussed include: modulation frequency and efficient audio coding;application of wavelet- and wavelet-packet-transform to human skin data;Wigner distribution and pulse propagation;time-frequency analysis using sidelobe apodization;spectral phase algorithm for detecting and estimating pitch;and minimum entropy approach to denoising time-frequency distributions.

关键词： signal processing

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Wigner equations of motion for classical systems

Wigner equations of motion for classical systems

引用

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

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

ISBN: (纸本)0819437611

We present a general procedure for obtaining equations of motion for the Wigner distribution of functions that are governed by ordinary and partial differential equations. For the case of fields we show that in general one must consider Wigner distributions of the four variables, position, momentum, time and frequency. We also show that in general one cannot write an equation of motion for position and momentum however it can be done in some cases, the Schrodinger equation being one such case. Our method leads to an equation of motion for the Schrodinger equation with time dependent potentials in contrast to the result obtained by Wigner and Moyal which was for time independent potentials.

关键词： Ordinary differential equations Partial differential equations Fourier transforms Oscillators Differential equations Acoustics Electromagnetism signal processing Switches

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Local signal to noise ratio

Local signal to noise ratio

引用

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

作者： Galleani, Lorenzo Cohen, Leon Nelson, Douglas CUNY 695 Pk Ave New York NY 10021 USA US Dept Def Ft George G Meade MD 20755 USA Politecn Torino Dipartimento Elettron I-10129 Turin Italy

ISBN: (纸本)0819463922

We argue that the standard definition of signal to noise ratio may be misleading when the signal or noise are nonstationary. We introduce a new measure that we call local signal to noise ratio (LSNR) which is well suited to take into account nonstationary situations. The advantage of our measure is that it is a local property unlike the standard SNR which is a single number representing the total duration of the signal. We simulated a number of cases to show that our measure is more indicative of the noise and signal level for nonstationary situations.

关键词： signal to Noise Ratio time-frequency white noise

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Dynamically parameterized algorithms and architectures to exploit signal variations for improved performance and reduced power

Dynamically parameterized algorithms and architectures to ex...

引用

IEEE International conference on Acoustics, Speech, and signal processing

作者： Burleson, W Tessier, R Goeckel, D Swaminathan, S Jain, P Euh, J Venkatraman, S Thyagarajan, V Univ Massachusetts Dept Elect & Comp Engn Amherst MA 01003 USA

ISBN: (纸本)0780370414

signal processing algorithms and architectures can use dynamic reconfiguration to exploit variations in signal statistics with the objectives of improved performance and reduced power consumption. Parameters provide a simple and formal way to characterize incremental changes to a computation and its computing mechanism. This paper examines five parameterized computations which are typically implemented in hardware for a wireless multimedia terminal: 1) motion estimation, 2) discrete cosine transform, 3) Lempel-Ziv lossless compression, 4) 3D graphics light rendering and 5) viterbi decoding, Each computation is examined for the capability of dynamically adapting the algorithm and architecture parameters to variations in their respective input signals. Dynamically reconfigurable low-power implementations of each computation are currently underway.

关键词： Digital signal processing

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Evolutionary spectrum estimation by deconvolving bilinear time-frequency distributions

Evolutionary spectrum estimation by deconvolving bilinear ti...

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

作者： Emresoy, MK El-Jaroudi, A Univ Pittsburgh Real Time Signal Proc Lab Pittsburgh PA 15261 USA

ISBN: (纸本)0819429163

A deconvolution technique to estimate the Evolutionary Spectrum (ES) of nonstationary signals by deconvolving the blurring effects of the kernel function fi om bilinear time frequency distributions (TFD) is presented. The resulting ES has desirable properties such as positivity, higher resolution, higher concentration in time-frequency. The proposed algorithm is computationally more efficient compared to the recently proposed entropy based deconvolution method. Unlike the entropy method the new algorithm can be adapted to deconvolve TFDs other than the spectrogram.

关键词： evolutionary spectrum bilinear time-frequency distributions deconvolution

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Time-frequency approximations, with application to filtering, modulation and propagation - art. no. 63130S

Time-frequency approximations, with application to filtering...

引用

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

作者： Loughlin, Patrick J. Univ Pittsburgh Pittsburgh PA 15261 USA

ISBN: (纸本)0819463922

signals with time-varying spectral content arise in a number of situations, such as in shallow water sound propagation, biomedical signals, machine and structural vibrations, and seismic signals, among others. The Wigner distribution and its generalization have become standard methods for analyzing such time-varying signals. We derive approximations of the Wigner distribution that can be applied to gain insights into the effects of filtering, amplitude modulation, frequency modulation, and dispersive propagation on the time-varying spectral content of signals.

关键词： signal filtering and prediction

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Information theoretic signal detection on the time-frequency plane

Information theoretic signal detection on the time-frequency...

引用

conference on advanced signal processing algorithms architectures and implementations XIII

作者： Aviyente, S Michigan State Univ E Lansing MI 48824 USA

ISBN: (纸本)0819450782

A comprehensive theory for time-frequency based signal detection has been developed during the past decade. The time-frequency detectors proposed in literature are linear structures operating on the time-frequency representation of the signals and are equivalent to quadratic receivers that are defined in the,time domain. In this paper, an information theoretic approach for signal detection on the time-frequency plane is introduced. In recent years, Renyi entropy has been proposed as an effective measure for quantifying signal complexity on the time-frequency plane and some important properties of this measure have been proven. In this paper, a new approach that uses the entropy functional as the test statistic for signal detection is developed. The minimum error detection algorithm is derived and the performance of this new signal detection method is demonstrated through examples.

关键词： signal detection Time-frequency analysis Detection and tracking algorithms Interference (communication) Sensors Radar Algorithm development Backscatter signal to noise ratio Receivers

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Adaptive radar CFAR using signal based suppression

Adaptive radar CFAR using signal based suppression

引用

conference on advanced signal processing - algorithms, architectures, and implementations viI

作者： Brovko, TTN Whang, YE Hughes Aircraft Co. (United States)

ISBN: (纸本)0819425842

The primary basis for adaptive radar algorithm design is that (1) a Binary Hypothesis formulation with unknown parameters is an adequate test and (2) that radar interference is composed of combinations of thermal noise, self induced clutter, and extraneous noise. This is the typical generalized likelihood formulation that yield the CFAR characteristic for the assumed conditions. implementations have shown that such formulations yield inadequate performance in complex clutter environments. As compensation measure, a secondary CFAR process then addresses the potential violation of this assumption by large ''target-like'' interference such as large Clutter discretes or a large number of targets interfering with each other. In order to detect small targets, an approach based on the Likelihood Statistic provides a technique for optimally suppressing the neighboring large signals. Performance is characterized as a function of a generalized distance and relative signal power ratios in the Joint Space-Time domain.

关键词： Target detection signal detection Doppler effect Distortion Radar Modulation Electronic filtering signal processing Interference (communication) signal to noise ratio

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Multilinear algebra for independent component analysis

Multilinear algebra for independent component analysis

引用

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

作者： McWhirter, JG Clarke, IJ Spence, G Def Evaluat & Res Agcy Malvern WR14 3PS Worcs England

ISBN: (纸本)0819432938

It is shown how some simple multilinear transformations may be used to generate an alternative, and potentially faster, version of the BLISS algorithm for blind signal separation. The BLISS algorithm performs an independent component analysis of the type proposed by Comon but uses a different method for estimating the pairwise rotation angles. It has been applied to a wide range of communication signals and proved extremely successful in practice. The reformulated version of BLISS requires less arithmetic operations provided the number of signals to be separated is fairly small (similar to 3 to 5) as found in a range of important communication scenarios.

关键词： multilinear algebra independent component analysis higher order statistics blind signal separation

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