Maximum likelihood sequence estimation of minimum shift keying modulated signals using a Hopfield neural network

For the detection of minimum shift keying modulated signals in the presence of intersymbol interference and additive white Gaussian noise, the feasibility of using Hopfield artificial neural networks is investigated. The principle of maximum likelihood sequence estimation is mapped onto the neural network, and an appropriate receiver structure to detect the transmitted signals is described. Simulation results give insight into the equalizer performance which is approximately as good as that of a Viterbi equalizer.<
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