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Neural network model for unequally distributed neuron states

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Abstract

A modified neural network model suitable for patterns with unequally distributed neuron states is proposed. The storage capacity and content addressability are greatly improved by adding a linear modification term to the interconnection weights of the Hopfield model. Computer simulations were performed to demonstrate the robustness of the modified model compared to the original. A grating-modulated holographic hybrid system was employed for an optical demonstration. Experimental results are shown.

© 1992 Optical Society of America

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