Robust predictive vector quantizer design

The design of predictive quantizers generally suffers from difficulties due to the prediction loop, which have an impact on the convergence and the stability of the design procedure. We previously proposed an asymptotically closed-loop approach to quantizer design for predictive coding applications,...

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Bibliographic Details
Published inProceedings DCC 2001. Data Compression Conference pp. 33 - 42
Main Authors Khalil, H., Rose, K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2001
Subjects
Asymptotic stability
Convergence
Design methodology
Design optimization
Frequency
Gaussian processes
Predictive coding
Robustness
Speech
Testing
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ISBN0769510310
9780769510316
ISSN1068-0314
DOI10.1109/DCC.2001.917134

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Summary:The design of predictive quantizers generally suffers from difficulties due to the prediction loop, which have an impact on the convergence and the stability of the design procedure. We previously proposed an asymptotically closed-loop approach to quantizer design for predictive coding applications, which benefits from the stability of open-loop design while asymptotically optimizing the actual closed-loop system. In this paper, we present an enhancement to the approach where joint optimization of both predictor and quantizer is performed within the asymptotically closed-loop framework. The proposed design method is tested on synthetic sources (first-order Gauss and Laplacian-Markov sequences), and on natural sources, in particular, line spectral frequency parameters of speech signals.
ISBN:0769510310
9780769510316
ISSN:1068-0314
DOI:10.1109/DCC.2001.917134