Method and Circuits for Neuron Perturbation in Artificial Neural Network Memory Modification.
Patent, Filed 1 Oct 90, patented 22 Sep 92,
DEPARTMENT OF THE NAVY WASHINGTON DC
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An artificial neural network has a plurality of output circuits individually perturbable for memory modification or learning by the network. The network has a plurality of synapses individually connecting each of a plurality of inputs to each output circuit. Each synapse has a weight determining the effect on the associated output circuit of a signal provided on the associated input, and the synapse is addressable for selective variation of the weight. A perturbation signal is provided to one input, while data signals are provided to others of the inputs, so that perturbation of each output circuit may be controlled by varying the weights of a set of the synapses connecting the perturbation signal to the output circuits. An output circuit may be selected for perturbation by loading an appropriate weight in the synapse connecting the perturbation signal to the output circuit while zeroing the weights of the synapses connecting the perturbation signal to other output circuits.
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