An iterative algorithm for calculating posterior probability and model representation

T. Matsushima, T. Matsushima, S. Hirasawa
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引用次数: 1

Abstract

We introduce a representation method of probability models that can be applied to any code such as turbo, low density parity check (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.
一种计算后验概率和模型表示的迭代算法
我们介绍了一种概率模型的表示方法,该方法可以应用于任何代码,如turbo,低密度奇偶校验(LDPC)或咬尾代码。此外,我们提出了一种迭代算法来计算引入的概率模型类的边际后验概率。该算法对LDPC码的译码错误概率小于和积算法的译码错误概率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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