Patent
1994-06-17
1997-04-29
Hafiz, Tariq R.
395 21, 395 23, G06E 100, G06E 300, G06F 1518
Patent
active
056257520
ABSTRACT:
An artificial neural system has input operational amplifiers providing differential voltage input signals to a neuron including a voltage divider network having a plurality of substantially equal resistances selectably connectable to the components of the input signals so as to define the bits of binary weights for each of the input signals and to generate unweighted network output voltage signals corresponding to each bit position of the weights and representing the sums of the products of each input signal and the bit at each bit position. The unweighted bit position signals are provided to a bit position weighting device which is common to all of the weights of a neuron and which weights the unweighted signals by the binary positional values of the bit positions. The unweighted bit position signals are differential signals having one component generated by reference resistances of the network, and the sign of each weight may be selected by connection of the reference resistances to one or the other of the input signal components. A preferred embodiment has only one reference resistance for each weight. This reference resistance corresponds to a sign bit position, and the reference resistances for all of the weights are connected to provide a common reference voltage component for all of the unweighted bit position signals. Differential voltage output signals from a system utilized as one artificial neural layer may be directly connected as differential voltage input signals for the voltage divider network of a system utilized as a second layer.
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Publication:Mark Hollar, Simon Tam, Hernan Castro, and Ronald Benson; "An Electrically Trainable Artificial Neural Network (ETANN) with 10240 `Floating Gate` Synapses"; International Joint Conference on Neural Networks; Washington, D.C.; Jun. 18-20; vol. II, pp. 191-196.
Paper: Chi Yung Fu, Benjamin Law, George Chapline, and Dick Swenson; "Customizable VLSI Artificial Neural Network Chips Based in a Novel Technology"; 1992.
Church Stephen J.
Hafiz Tariq R.
Sliwka Melvin J.
The United States of America as represented by the Secretary of
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