TY - GEN

T1 - Evaluation of the minimum overflow threshold of bayes codes for a Markov source

AU - Saito, Shota

AU - Miya, Nozomi

AU - Matsushima, Toshiyasu

N1 - Publisher Copyright:
© 2014 IEICE.

PY - 2014/12/8

Y1 - 2014/12/8

N2 - The objective of this research is to evaluate the ε-minimum overflow threshold of the Bayes codes for a Markov source. In the lossless variable-length source coding problem, typical criteria are the mean codeword length and the overflow probability. The overflow probability is the probability with which a codeword length per source symbol exceeds a threshold and the ε-minimum overflow threshold is defined. In the non-universal setting, the Shannon code is optimal under the mean codeword length and the ε-minimum overflow threshold for the Shannon code is derived for an i.i.d. source. On the other hand, in the universal setting, the Bayes code is one of universal codes which minimize the mean codeword length under the Bayes criterion. However, few studies have been done on the overflow probability for the Bayes codes. In this paper, we assume a stationary ergodic finite order Markov source and derive the upper and lower bounds of the ε-minimum overflow threshold of the Bayes codes.

AB - The objective of this research is to evaluate the ε-minimum overflow threshold of the Bayes codes for a Markov source. In the lossless variable-length source coding problem, typical criteria are the mean codeword length and the overflow probability. The overflow probability is the probability with which a codeword length per source symbol exceeds a threshold and the ε-minimum overflow threshold is defined. In the non-universal setting, the Shannon code is optimal under the mean codeword length and the ε-minimum overflow threshold for the Shannon code is derived for an i.i.d. source. On the other hand, in the universal setting, the Bayes code is one of universal codes which minimize the mean codeword length under the Bayes criterion. However, few studies have been done on the overflow probability for the Bayes codes. In this paper, we assume a stationary ergodic finite order Markov source and derive the upper and lower bounds of the ε-minimum overflow threshold of the Bayes codes.

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M3 - Conference contribution

AN - SCOPUS:84920516110

T3 - Proceedings of 2014 International Symposium on Information Theory and Its Applications, ISITA 2014

SP - 211

EP - 215

BT - Proceedings of 2014 International Symposium on Information Theory and Its Applications, ISITA 2014

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 International Symposium on Information Theory and Its Applications, ISITA 2014

Y2 - 26 October 2014 through 29 October 2014

ER -