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HOSAKA TADAAKI
Department Undergraduate School , School of Science and Technology Position Associate Professor |
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| Language | English |
| Publication Date | 2006/06 |
| Type | Academic Journal |
| Peer Review | Peer reviewed |
| Title | Statistical mechanical approach to lossy data compression: Theory and practice |
| Contribution Type | Co-authored (first author) |
| Journal | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS |
| Journal Type | Another Country |
| Publisher | ELSEVIER SCIENCE BV |
| Volume, Issue, Page | 365(1),pp.113-119 |
| Author and coauthor | T Hosaka,Y Kabashima |
| Details | 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. (c) 2006 Elsevier B.V. All rights reserved. |
| DOI | 10.1016/j.physa.2006.01.013 |
| ISSN | 0378-4371 |