Neural networks for error correction of Hamming codes

Proceedings of 1994 Workshop on Information Theory and Statistics Pub Date : 1994-10-27 DOI:10.1109/WITS.1994.513921

O. Mayora-Ibarra, A. González-Gutiérrez, J. Ruiz-Suárez

引用次数: 1

Abstract

A comparative analysis of three neural network models: backpropagation (BPP), bidirectional associative memory (BAM) and holographic associative memory (HAM); and a classical method for error-correction is presented. Each method is briefly described, results are reported and finally some advantages are concluded.

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汉明码纠错的神经网络

反向传播(BPP)、双向联想记忆(BAM)和全息联想记忆(HAM)三种神经网络模型的比较分析并提出了一种经典的误差校正方法。对各种方法进行了简要描述，并对结果进行了报道，最后总结出了一些优点。

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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来源期刊

Proceedings of 1994 Workshop on Information Theory and Statistics

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