Maximum entropy deconvolver circuit based on neural net principles

摘要

Disclosed are two modifications of the Tank-Hopfield circuit, each of which enables the deconvolution of a signal in the presence of noise. In each embodiment, the Tank-Hopfield circuit is modified so that the equation for total circuit energy reduces to one term representing convolution and another information theoretic (or Shannon) entropy. Thus, in finding its global minimum energy state, each modified circuit inherently identifies an optimal estimate of a deconvoluted input signal without noise.