We consider the convergence characteristics of a perceptron learning algorithm,
taking into account the decay of photorefractive holograms during the process of
interconnection weight changes. As a result of the hologram erasure, the
convergence of the learning process is dependent on the exposure time during the
weight changes. A mathematical proof of the conditional convergence, as well as
computer simulations of the photorefractive perceptrons, is presented and
© 1993 Optical Society of America
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