Maximum entropy deconvolver circuit based on neural net principl

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364807, G06G 719, G06G 900

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048499250

ABSTRACT:
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.

REFERENCES:
patent: 4660166 (1987-04-01), Hopfield
patent: 4730259 (1988-03-01), Gallant
patent: 4731747 (1988-03-01), Denker
patent: 4737929 (1988-04-01), Denker
patent: 4752906 (1988-06-01), Kleinfield
patent: 4782460 (1980-11-01), Spencer
D. W. Tank and J. J. Hopfield, "Simple `Neural` Optimization Networks: an Converter, Signal Decision Circuit, and a Linear Programming Circuit", vol. CAS-33, No. 5, May, 1986.
J. J. Hopfield, "Neurons With Graded Response Have Collective Computational Properties Like Those of Two-State Neurons", Proceeding of the National Academy of Sciences (U.S.A.), vol. 81, pp. 3088-3092, May, 1984.

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