Abstract

An all-optical generalized linear machine applied to a high-bandwidth temporal signal-classification problem is demonstrated. The classifier consists of a dimensional increasing acousto-optic triple-product processor feature extractor cascaded through an optically addressed spatial light modulator into a volume holographic implementation of a linear classifier. Multiple-exposure implementations of learning are used to train the classifier interconnection weights in a photorefractive crystal for a training set of wide-bandwidth temporal signals input to the acousto-optic triple-product processor. Experimental implementation of high-speed, time-shift and Doppler invariant, wide-bandwidth signal identification is demonstrated.

© 1996 Optical Society of America

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