Chee C. Wong

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Experimental results from adaptive learning using an optically controlled neural network are presented. The authors have used example problems in nonlinear system identification and signal prediction, two areas of potential neural network application, to study the capabilities of analog neural hardware. These experiments investigated the effects of a(More)
Networks of interconnected nonlinear analog processors, or neurons, are finding increasing use in adaptive problems. Adaptive signal prediction has been widely used for many years but has been primarily restricted to linear systems and signals, for which the mathematical treatment of the problems is tractable. We present results using an optically(More)
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