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Open AccessJournal ArticleDOI

A study of vector quantization for noisy channels

TLDR
It is concluded that the channel-optimized vector quantizer design algorithm, if used carefully, can result in a fairly robust system with no additional delay.
Abstract
Several issues related to vector quantization for noisy channels are discussed. An algorithm based on simulated annealing is developed for assigning binary codewords to the vector quantizer code-vectors. It is shown that this algorithm could result in dramatic performance improvements as compared to randomly selected codewords. A modification of the simulated annealing algorithm for binary codeword assignment is developed for the case where the bits in the codeword are subjected to unequal error probabilities (resulting from unequal levels of error protection). An algorithm for the design of an optimal vector quantizer for a noisy channel is briefly discussed, and its robustness under channel mismatch conditions is studied. Numerical results for a stationary first-order Gauss-Markov source and a binary symmetric channel are provided. It is concluded that the channel-optimized vector quantizer design algorithm, if used carefully, can result in a fairly robust system with no additional delay. The case in which the communication channel is nonstationary (as in mobile radio channels) is studied, and some preliminary ideas for quantizer design are presented. >

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Citations
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Journal ArticleDOI

Quantization

TL;DR: The key to a successful quantization is the selection of an error criterion – such as entropy and signal-to-noise ratio – and the development of optimal quantizers for this criterion.
Journal ArticleDOI

Deterministic annealing for clustering, compression, classification, regression, and related optimization problems

TL;DR: The deterministic annealing approach to clustering and its extensions has demonstrated substantial performance improvement over standard supervised and unsupervised learning methods in a variety of important applications including compression, estimation, pattern recognition and classification, and statistical regression.
Journal ArticleDOI

Efficient vector quantization of LPC parameters at 24 bits/frame

TL;DR: It is shown that the split vector quantizer can quantize LPC information in 24 bits/frame with an average spectral distortion of 1 dB and less than 2% of the frames having spectral distortion greater than 2 dB.
Journal ArticleDOI

Unequal loss protection: graceful degradation of image quality over packet erasure channels through forward error correction

TL;DR: It is found that when optimizing for an exponential packet loss model with a mean loss rate of 20% and using a total rate of 0.2 bits per pixel on the Lenna image, good image quality can be obtained even when 40% of transmitted packets are lost.
Book

Digital Speech: Coding for Low Bit Rate Communication Systems

A. Kindoz, +1 more
TL;DR: A detailed account of the most recently developed digital speech coders designed specifically for use in the evolving communications systems, including an in-depth examination of the important topic of code excited linear prediction (CELP).
References
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Journal ArticleDOI

Optimization by Simulated Annealing

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Journal ArticleDOI

Equation of state calculations by fast computing machines

TL;DR: In this article, a modified Monte Carlo integration over configuration space is used to investigate the properties of a two-dimensional rigid-sphere system with a set of interacting individual molecules, and the results are compared to free volume equations of state and a four-term virial coefficient expansion.
Journal ArticleDOI

An Algorithm for Vector Quantizer Design

TL;DR: An efficient and intuitive algorithm is presented for the design of vector quantizers based either on a known probabilistic model or on a long training sequence of data.
Journal Article

Vector quantization

TL;DR: During the past few years several design algorithms have been developed for a variety of vector quantizers and the performance of these codes has been studied for speech waveforms, speech linear predictive parameter vectors, images, and several simulated random processes.
Journal ArticleDOI

Fast Probabilistic Algorithms for Verification of Polynomial Identities

TL;DR: Vanous fast probabdlsttc algonthms, with probability of correctness guaranteed a prion, are presented for testing polynomial ldentmes and propemes of systems of polynomials and ancdlary fast algorithms for calculating resultants and Sturm sequences are given.
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