Neural network model for unequally distributed neuron states
Yuhe Zhang, Xuming Wang, Guoguang Mu · Applied Optics · 1992
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 gratingmodulated holographic hybrid system was employed for an optical demonstration. Experimental results are shown.