基于矩阵代数的BCJR算法的神经网络实现

Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005. Pub Date : 2005-12-21 DOI:10.1109/ISSPIT.2005.1577207

M. H. Sazli, C. Isik

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引用次数: 3

摘要

在本文中，我们证明了BCJR算法(或Bahl算法)可以作为一个前馈神经网络结构来实现，该结构基于矩阵代数对算法的重新表述。我们通过计算机模拟验证了这种新颖的神经网络实现与BCJR算法产生相同的结果

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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Neural network implementation of the BCJR algorithm based on reformulation using matrix algebra

In this paper, we show that the BCJR algorithm (or Bahl algorithm) can be implemented as a feedforward neural network structure based on a reformulation of the algorithm using matrix algebra. We verified through computer simulations that this novel neural network implementation yields identical results with the BCJR algorithm

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Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.

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