Analog hardware for delta-backpropagation neural networks

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364807, 307201, G06G 712

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active

051013614

ABSTRACT:
This is a fully parallel analog backpropagation learning processor which comprises a plurality of programmable resistive memory elements serving as synapse connections whose values can be weighted during learning with buffer amplifiers, summing circuits, and sample-and-hold circuits arranged in a plurality of neuron layers in accordance with delta-backpropagation algorithms modified so as to control weight changes due to circuit drift.

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Lippmann, Richard P., "An Introduction to Computing with Neural Nets", IEEE ASSP Magazine, Apr. 1987, pp. 4-21.
Rumelhart et al., "Learning Internal Representations by Error Propagation", Parallel Distributed Processing, Explorations in the Microstructure of Cognition, vol. 1: Foundations, MIT Press, 1986, pp. 318-362.

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