An iterative algorithm for calculating posterior probability and model representation

T. Matsushima, T. K. Matsushima, S. Hirasawa

Research output: Contribution to journalConference article

1 Citation (Scopus)


In this paper, we introduce a representation method of probability models that can be applied to any code such as turbo, LDPC or tail-biting code. Moreover, we propose an iterative algorithm that calculates marginal posterior probabilities on the introduced probability model class. The decoding error probability for the LDPC codes of the proposed algorithm is less than that of the sum-product algorithm.

Original languageEnglish
Number of pages1
JournalIEEE International Symposium on Information Theory - Proceedings
Publication statusPublished - 2001 Sep 12
Event2001 IEEE International Symposium on Information Theory (ISIT 2001) - Washington, DC, United States
Duration: 2001 Jun 242001 Jun 29


ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics

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