Analog decoding using neural networks

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Abstract
This paper develops a particular error correction code which can be effectively decoded by a relatively simple neural network. In high noise situations, this code is comparable to that used at present in deep space communications. The neural decoder has N! stable states with only N 2 neurons, and can quickly extract information from analog noise. This example illustrates the effectiveness of neural networks in solving real problems when the problem can be cast in such a fashion that it fits gracefully on the network.

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