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arXiv cs/0609088cs.ITmath.IT
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从合作优化导出规范化最小和算法

Deriving the Normalized Min-Sum Algorithm from Cooperative Optimization

Xiaofei Huang

摘要:

归一化最小和算法在译码LDPC码时可以达到接近最优的性能。然而,理解算法背后的数学原理是一个关键问题。传统上,人们认为归一化最小和算法是LDPC码和Turbo码译码的和积算法的一个很好的近似。本文提供了另一种方法来理解归一化最小和算法。该算法是直接从合作优化,一个新发现的全局/组合优化的一般方法。这种方法为算法提供了另一个理论基础,并对其功能和局限性提供了新的见解。它也为我们设计新的解码算法提供了一个通用的框架。

英文摘要:

The normalized min-sum algorithm can achieve near-optimal performance at decoding LDPC codes. However, it is a critical question to understand the mathematical principle underlying the algorithm. Traditionally, people thought that the normalized min-sum algorithm is a good approximation to the sum-product algorithm, the best known algorithm for decoding LDPC codes and Turbo codes. This paper offers an alternative approach to understand the normalized min-sum algorithm. The algorithm is derived directly from cooperative optimization, a newly discovered general method for global/combinatorial optimization. This approach provides us another theoretical basis for the algorithm and offers new insights on its power and limitation. It also gives us a general framework for designing new decoding algorithms.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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