Presentation 2003/7/22
Statistical mechanics approach to error exponents for lossy data compression
Tadaaki HOSAKA, Yoshiyuki KABASHIMA,
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Abstract(in English) Data compression is classified to two categories : lossless and lossy compression. Our preceding research provided a scheme for lossy data compression for uniformly biased Boolean messages based on perceptron. Statistical mechanics analysis showed that when the code length is infinite, the performance of this scheme can achieve the rate-distortion function, which is the theoretical limit of the performance for lossy data compression. However, in the view point of real world, it is important to evaluate the performance in finite code length. In this research, we derive the expression of error exponents which is one of guides for the performance in finite code length, employing the replica method. We also describe a construction scheme of the optimal code, which is examined by numerical experiments.
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Keyword(in English) lossy data compression / error exponent / perceptron / statistical mechanics
Paper # NC2003-39
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Committee NC
Conference Date 2003/7/22(1days)
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Registration To Neurocomputing (NC)
Language JPN
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Title (in English) Statistical mechanics approach to error exponents for lossy data compression
Sub Title (in English)
Keyword(1) lossy data compression
Keyword(2) error exponent
Keyword(3) perceptron
Keyword(4) statistical mechanics
1st Author's Name Tadaaki HOSAKA
1st Author's Affiliation Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology()
2nd Author's Name Yoshiyuki KABASHIMA
2nd Author's Affiliation Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology
Date 2003/7/22
Paper # NC2003-39
Volume (vol) vol.103
Number (no) 228
Page pp.pp.-
#Pages 6
Date of Issue