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Optical bipolar kth-order neural network based on inner-product representation

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Abstract

A new polarization-encoding scheme for a bipolar kth-order neural network based on inner-product representation is proposed. Bipolar data multiplication is achieved as the rotation of linearly polarized light. A compact architecture of the bipolar kth-order neural network is suggested. In the architecture, no subtractions are needed, and the threshold levels for the neurons are fixed. Also, we show that a liquid-crystal device such as a liquid-crystal television is acceptable as a polarization modulator in the proposed architecture by computer simulation.

© 1994 Optical Society of America

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