本文提出了一种源于汉明类多层前向神经网络分组码译码器。
This paper presents a neural network decoder of linear block codes which originates from Hamming network.
本文旨在研究神经网络在最小加权距离译码中的应用。
Our main goal is to explore the application of neural networks to minimum weighted distance decoding.
计算机模拟表明，在加性高斯噪声下，使用该神经网络可以达到最大似然译码。
The computer simulation shows that the decoder can achieve maximum likelihood decoding in the environmemts of additive white Gaussian noise.
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