Generation of binary vectors that optimize a given weight function with application to soft-decision decoding

A. Valembois, M. Fossorier
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引用次数: 2

Abstract

Many decoding algorithms need to compute some lists of binary vectors that minimize a given weight function. Furthermore, it is often desirable that these vectors are generated by increasing weight. The considered weight function is usually decreasing in the a priori likelihood that the vector yields correct decoding. We present a new technique to generate candidates for error patterns from the most a priori likely to the least, that proves significantly more efficient than any other known method.
生成二进制矢量,优化给定的权重函数,应用于软判决解码
许多解码算法需要计算一些最小化给定权重函数的二进制向量列表。此外,通常希望通过增加权重来生成这些向量。所考虑的权重函数通常在向量产生正确解码的先验可能性中减小。我们提出了一种新的技术来生成候选的错误模式,从最先验的可能性到最小的可能性,证明比任何其他已知的方法更有效。
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