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Analog hardware for learning neural networksThis is a recurrent or feedforward analog neural network processor having a multi-level neuron array and a synaptic matrix for storing weighted analog values of synaptic connection strengths which is characterized by temporarily changing one connection strength at a time to determine its effect on system output relative to the desired target. That connection strength is then adjusted based on the effect, whereby the processor is taught the correct response to training examples connection by connection.
Document ID
19910023538
Acquisition Source
Legacy CDMS
Document Type
Other - Patent
Authors
Eberhardt, Silvio P.
(Jet Propulsion Lab. California Inst. of Tech., Pasadena., United States)
Date Acquired
August 14, 2013
Publication Date
October 8, 1991
Subject Category
Computer Systems
Report/Patent Number
Patent Number: NASA-CASE-NPO-17664-1-CU
Patent Application Number: US-PATENT-APPL-SN-463720
Patent Number: US-PATENT-5,056,037
Accession Number
91N32852
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Patent
NASA-CASE-NPO-17664-1-CU|US-PATENT-5,056,037
Patent Application
US-PATENT-APPL-SN-463720
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