Feed forward neural network for unary associative memory

Details Feed forward neural network for unary associative memory Feed forward neural network for unary associative memory

1987-12-08

1991-06-11

Fears, Terrell W.

Static information storage and retrieval

Associative memories

Ferroelectric cell

364900, 371 36, G11C 1500

Patent

active

050238337

ABSTRACT:
Feed forward neural network models for associative content addressable memory utilize a first level matrix of resistor connections to store words and compare addressing cues with the stored words represented by connections of unit resistive value, and a winner-take-all circuit for producing a unary output signal corresponding to the word most closely matched in the first matrix. The unary output signal is converted to a binary output code, such as by a suitable matrix. Cues are coded for the address input as binary 1=+V, binary 0=-V, and unknown =0V. Two input amplifiers are employed with two input conductors for each input bit position, one noninverting and the other inverting, so that the winner-take-all circuit at the output of the first matrix may be organized to select the highest number of matches with stored words as the unary output signal. By inverting the cues at the input to the first matrix, and inverting the output of the first level matrix, the effect of resistor value imprecision in the first matrix is virtually obviated. By space coding, the first and second matrices may be expanded into multiple sets of matrices, each with its own winner-take-all circuit for producing unary output signals applied from the first set to the second set of matrices. The output conductors of the second set of matrices are grouped to provide a sparse output code that is then converted to a binary code corresponding to the word recalled.

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