An Enhanced Genetic Algorithm Based Decoder for Linear Codes

H. Berbia, Faissal El Bouanani, M. Belkasmi, R. Romadi
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引用次数: 4

Abstract

This paper introduces a new decoder based on genetic algorithms and neural networks for binary linear codes. The search space, in contrast to our previous algorithms which was limited to the codeword space, now covers the whole binary vector space.The neural network is used to favor feasible solution namely codewords. Previous genetic algorithm based decoders [2] require a lot of computing resources when used with large codes. The new decoder eludes a great number of coding operations by using the neural network. This reduces greatly the complexity of the decoder while maintaining comparable performances.
基于改进遗传算法的线性码解码器
介绍了一种基于遗传算法和神经网络的二进制线性码译码器。与我们以前的算法局限于码字空间相比,现在的搜索空间涵盖了整个二进制向量空间。利用神经网络选择可行解即码字。以往基于遗传算法的解码器[2]在处理大码时需要大量的计算资源。该解码器利用神经网络,避免了大量的编码操作。这大大降低了解码器的复杂性,同时保持了相当的性能。
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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