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NEURAL-NETWORK processing TO MINIMIZE QUANTIZATION LOSSES 4

NEURAL-NETWORK PROCESSING TO MINIMIZE QUANTIZATION LOSSES

引用

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

作者： WU, YJ CHAU, PM Univ. of California/San Diego (United States)

ISBN: (纸本)0819412767

A general neural network co-processor has been investigated and designed to adaptively adjust the quantization thresholds of a data quantizer, and thus a data quantizer with minimum quantization loss can be obtained. For a given probability density function and number of quantization levels, the neural network is designed to learn the near optimal quantization uniform step-size which minimizes the loss caused by the quantizer. With this neural network co-processor approach, consistent and substantial performance improvements have been verified on either an AWGN or a Rayleigh fading communication channel with convolutional encoder and maximum likelihood decoder. This general neural network co-processor approach can be applied to any digital signal processing system which has quantization loss, such as digital communication, image data compression, or adaptive signal processing.

关键词： Neural networks Quantization Digital signal processing Data communications signal processing signal to noise ratio Analog electronics Modulation signal attenuation Telecommunications

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A NEW ALGORITHM FOR RATIONAL SUBSPACE ESTIMATION BASED ON CASCADABLE ADAPTIVE LOSSLESS FILTERS 4

A NEW ALGORITHM FOR RATIONAL SUBSPACE ESTIMATION BASED ON CA...

引用

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

作者： FIJALKOW, I LOUBATON, P REGALIA, PA Telecom Paris Dept. Signal 46 rue Barrault Paris Cedex 13 75634 France Institut National des Telecommunications 9 rue Charles Fourier Evry Cedex 91011 France

ISBN: (纸本)0819412767

In a previous work, a time domain algorithm was proposed to adaptively estimate a rational and orthonormal spanning of a rational subspace. However, its convergence was not proved and it seems that asymptotic misbehaviour may occur. A new algorithm is proposed, for which satisfactory convergence properties hold. It provides robustness with regard to the signal model and shows an especially good asymptotical performance for small SNR. © 1993 SPIE. All rights reserved.

关键词： Time domain analysis

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algorithms FOR INSTANTANEOUS FREQUENCY ESTIMATION - A COMPARATIVE-STUDY

ALGORITHMS FOR INSTANTANEOUS FREQUENCY ESTIMATION - A COMPAR...

引用

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

作者： BOASHASH, B OSHEA, P ARNOLD, MJ Univ. of Queensland (Australia)

ISBN: (纸本)0819404098

This paper examines the problem of instantaneous frequency (IF) estimation for Frequency Modulated (FM) signals imbedded in white Gaussian noise. It reviews currently available techniques and in addition proposes some new ones based on a modelling of the signal phase as a polynomial. Both linear least-squares techniques and Maximum Likelihood (ML) techniques are investigated for estimating the polynomial coefficients. It is seen that the linear least squares approach is efficient (i. e. unbiased and meets the Cramer-Rao bounds) for high SNR while the ML scheme is efficient for a much larger range of SNR. Theoretical lower variance bounds are given for estimating the polynomial coefficients and are compared with the results of simulations. Guidelines are given as to which estimation method should be used for a given signal class and signal to Noise Ratio (SNR) level.

关键词： signal to noise ratio Fermium Frequency modulation Interference (communication) Modeling Modulation

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Time-frequency decomposition based on information

Time-frequency decomposition based on information

引用

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

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

ISBN: (纸本)0819463922

In array processing applications, it is desirable to extract the sources that generate the observed signals. There are various source separation and component extraction algorithms in literature including principal component analysis (PCA) and independent component analysis (ICA). However, most of these methods are not designed to deal with time-varying signals and thus are formulated in the time domain. In this paper, we introduce a new time-frequency based decomposition method using an information measure as the decomposition criteria. It is shown that under the assumption of disjoint source signals on the time-frequency plane, this method can extract the sources up to a scalar factor. Based on the QR decomposition of the mixing matrix, the source extraction algorithm is reduced to finding the optimal N-dimensional rotation of the observed time-frequency distributions. The proposed algorithm is implemented using the steepest descent approach to find the optimal rotation angle. The performance of the method is illustrated for example signals and compared to some well-known decomposition techniques.

关键词： Time-frequency analysis Independent component analysis Transform theory Principal component analysis Associative arrays Image information entropy Matrices signal processing Sensors Array processing

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INSTANTANEOUS AMPLITUDE AND FREQUENCY ESTIMATION - PERFORMANCE BOUNDS AND APPLICATIONS TO SOURCE LOCALIZATION

INSTANTANEOUS AMPLITUDE AND FREQUENCY ESTIMATION - PERFORMAN...

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CONF ON advanced signal processing algorithms, architectures, AND implementations 2

作者： ARUN, KS LIANG, RM Univ. of Illinois/Urbana-Champaign (United States)

ISBN: (纸本)0819406945

Estimation and tracking of the instantaneous amplitudes and frequencies of superimposed, slowly varying narrowband signals is a difficult signal processing problem that shows up in many applications. Our approach to this problem is to achieve global noise averaging via SVD-based rank reduction of a matrix constructed from the entire data record. Compared to methods that use local noise averaging using many smaller matrices, the strength of the new approach is in affecting better noise reduction at a lower computational cost. Moreover, no model is needed for the variation of the amplitudes and frequencies with time. In this paper, Cramer-Rao bounds for the variance of the error in tracking the instantaneous amplitudes and frequencies (without assuming a parametric model for their variation with time) will be presented. In addition, we will also show how the algorithm can be used on sensor array data to estimate range and direction of multiple narrow-band sources.

关键词： Sensors signal processing Detection and tracking algorithms signal to noise ratio Source localization Data modeling Denoising Matrices Array processing Data analysis

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Optical infrared flame detection system with neural networks

Optical infrared flame detection system with neural networks

引用

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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BLOCK CIRCULANT PRECONDITIONERS FOR 2-D DECONVOLUTION

BLOCK CIRCULANT PRECONDITIONERS FOR 2-D DECONVOLUTION

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CONF ON advanced signal processing algorithms, architectures, AND implementations 3

作者： CHAN, RH NAGY, JG PLEMMONS, RJ Univ. of Hong Kong (Hong Kong China) Univ. of Minnesota (United States) Wake Forest Univ. (United States)

ISBN: (纸本)081940943X

Discretized 2-D deconvolution problems arising, e.g., in image restoration and seismic tomography, can be formulated as 1eas squares compuaions, mm lib— Tx112 where T is often a large-scale rectangular Toeplitz-block matrix. We consider solving such block least squares problems by the preconditioned conjugate gradient algorithm using square nonsingular circulant-block and related preconditioners, constructed from the blocks of the rectangular matrix T. Preconditioning with such matrices allows efficient implementation using the 1-D or 2-D Fast Fourier Transform (FFT). It is well known that the resolution of ill-posed deconvolution problems can be substantially improved by regularization to compensate for their ill-posed nature. We show that regularization can easily be incorporated into our preconditioners, and we report on numerical experiments on a Cray Y-MP. The experiments illustrate good convergence properties of these FET—based preconditioned iterations.

关键词： Image restoration Matrices Deconvolution Fourier transforms Point spread functions Radon Image processing Information operations Iterative methods Mathematics

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Analytical approximations of translational subpixel shifts in signal and image registrations

Analytical approximations of translational subpixel shifts i...

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Conference on advanced signal processing algorithms, architectures, and Implementantions XViii

作者： Zhang, Qiang Wake Forest Univ Hlth Sci Biostat Sci Dept Winston Salem NC 27157 USA

ISBN: (纸本)9780819472946

Analytical approximations of translational subpixel shifts in both signal and image registrations are derived by setting the derivatives of a normalized cross correlation function to zero and solving them. Without the need of iterative searching, this methods achieves a complexity of only O(mn), given an image size of m x n. Without the need to upsample, computation memory is also saved. Tests using simulated signals and images show good results.

关键词： Subpixel image registration image superresolution

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Architecture for real time wood inspection

Architecture for real time wood inspection

引用

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

作者： Malasne, N Paindavoine, M Lab Elect & Informat Image F-21078 Dijon France

This study has been realized to improve industrial machines that allow to analyze planks by detecting their width and too important defects thanks to a computer vision system. These machines are currently piloted by s... 详细信息

ISBN: (纸本)0819437611

关键词： real time processing defects detection FPGA

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The marginals and time-frequency distributions

The marginals and time-frequency distributions

引用

Conference on advanced signal processing algorithms architectures and implementations Xiii

作者： Cohen, L Loughlin, P CUNY New York NY 10021 USA

ISBN: (纸本)0819450782

We address the question of the importance of satisfying the marginal conditions in a time-frequency distribution and discuss in detail the fundamental and practical issues involved. We also examine the marginals of the spectrogram. The spectrogram often gives reasonable results even though both marginals can never be satisfied exactly, but sometimes it can give very unreasonable results. We show by examples that the spectrogram gives the clearest characterization of the time-frequency properties of a signal when the combined error in both of its marginals is as small as possible. In contrast, when the error in either one of the marginals of the spectrogram is large, the time-frequency characterization degrades. Some different error measures are described. We discuss the issues involved both theoretically and by way of numerical simulations. We also address the issue of marginals for the random case.

关键词： Time-frequency analysis Surface plasmons Fourier transforms signal processing Fermium Frequency modulation Numerical simulations Differential equations Physics Visualization

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