Statistical mechanical approach to lossy data compression: Theory and practice

Tadaaki Hosaka and Yoshiyuki Kabashima

Physica A: Statistical Mechanics and its Applications, 2006, vol. 365, issue 1, 113-119

Abstract: The encoder and decoder for lossy data compression of binary memoryless sources are developed on the basis of a specific-type nonmonotonic perceptron. Statistical mechanical analysis indicates that the potential ability of the perceptron-based code saturates the theoretically achievable limit in most cases although exactly performing the compression is computationally difficult. To resolve this difficulty, we provide a computationally tractable approximation algorithm using belief propagation (BP), which is a current standard algorithm of probabilistic inference. Introducing several approximations and heuristics, the BP-based algorithm exhibits performance that is close to the achievable limit in a practical time scale in optimal cases.

Keywords: Lossy data compression; Rate-distortion function; Error exponent; Replica method; Belief propagation (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:365:y:2006:i:1:p:113-119

DOI: 10.1016/j.physa.2006.01.013

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