Journal ArticleDOI
Multiple description quantization by deterministic annealing
P. Koulgi,S.L. Regunathan,Kenneth Rose +2 more
- Vol. 49, Iss: 8, pp 2067-2075
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TLDR
This work proposes to pursue a deterministic annealing approach which is independent of initialization, does not assume any prior knowledge of the source density, and avoids many poor local minima of the cost surface.Abstract:
The design of vector quantizers for diversity-based communication over two or more channels of possibly differing capacities and failure probabilities, is considered. The crucial dependence of current design techniques on initialization, especially of index assignment, is well recognized. Instead, we propose to pursue a deterministic annealing approach which is independent of initialization, does not assume any prior knowledge of the source density, and avoids many poor local minima of the cost surface. The approach consists of iterative optimization of a random encoder at gradually decreasing levels of randomness as measured by the Shannon entropy. At the limit of zero entropy, a hard multiple description (MD) quantizer is obtained. This process is directly analogous to annealing processes in statistical physics. Via an alternative derivation, we show that it may also be interpreted as approximating the minimum rate sums among points on the convex hull of the MD achievable rate-distortion region of El Gamal and Cover, subject to constraints on the sizes of the reproduction alphabets. To illustrate the potential of our approach, we present simulation results that show substantial performance gains over existing design techniques.read more
Citations
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Proceedings ArticleDOI
Multiple description lattice vector quantization
TL;DR: The design of such a quantizer can be reduced to the problem of assigning pair labels to points of a vector quantizer codebook, and a general labeling procedure is presented, along with detailed results for the hexagonal lattice: algorithms, asymptotic performance, and numerical simulations.
Journal ArticleDOI
Multiple Description Quantization Via Gram–Schmidt Orthogonalization
TL;DR: A systematic treatment of the El Gamal-Cover (EGC) achievable MD rate-distortion region is provided, and it can be decomposed into a simplified-EGC (SEGC) region and a superimposed refinement operation.
Posted Content
Multiple-Description Lattice Vector Quantization
TL;DR: This thesis constructs and analyze multiple-description codes based on lattice vector quantization and analyzes their implications for knowledge of latticevector quantization.
Proceedings ArticleDOI
On efficient quantizer design for robust distributed source coding
TL;DR: This paper proposes a deterministic annealing approach for the design of all components of a generic distributed source coding system, which avoids many poor local optima, is independent of initialization, and does not assume any prior information on the underlying source distribution.
Proceedings ArticleDOI
On index assignment and the design of multiple description quantizers
TL;DR: The practical design of multiple description quantizers for diversity-based communication is investigated and a simulated annealing based method is proposed for obtaining the optimal index assignment for a multiple-description vector quantizer.
References
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Journal ArticleDOI
Information Theory and Statistical Mechanics. II
TL;DR: In this article, the authors consider statistical mechanics as a form of statistical inference rather than as a physical theory, and show that the usual computational rules, starting with the determination of the partition function, are an immediate consequence of the maximum-entropy principle.
Journal ArticleDOI
Least squares quantization in PCM
TL;DR: In this article, the authors derived necessary conditions for any finite number of quanta and associated quantization intervals of an optimum finite quantization scheme to achieve minimum average quantization noise power.
Least Squares Quantization in PCM
TL;DR: The corresponding result for any finite number of quanta is derived; that is, necessary conditions are found that the quanta and associated quantization intervals of an optimum finite quantization scheme must satisfy.
Journal ArticleDOI
An Algorithm for Vector Quantizer Design
Y. Linde,A. Buzo,Robert M. Gray +2 more
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.
Book
Vector Quantization and Signal Compression
Allen Gersho,Robert M. Gray +1 more
TL;DR: The author explains the design and implementation of the Levinson-Durbin Algorithm, which automates the very labor-intensive and therefore time-heavy and expensive process of designing and implementing a Quantizer.