An upper bound on the performance of a novel feedforward perceptron equalizer

The emulation of a nonadaptive, binary, decision-feedback equalizer, operating on a noiseless, finite impulse response channel, by a feedforward multilayer processor is considered. This feedforward perceptron equalizer comprises a triangular array of bandlimiting processing elements. The functional similarity between the two systems is exploited to obtain a tight upper bound on the probability of error as a function of the number of layers, using the theory of finite-state Markov processes.<
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