Abstract

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 controlled adaptive neural network for nonlinear signal prediction.

© 1991 Optical Society of America

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