A new analytical method for AM neural networks and its application to pattern recognition

The problems of asymptotical stability and associative memory (AM) for Hopfield-type neural networks are analyzed. A new kind of energy function is introduced which is different from Hopfield´s definition. The networks´ asymptotical stability is analyzed by means of the new energy function. Two theorems are obtained. By comparing these two theorems with the existing conclusions it can be found that, in some cases, they are consistent and, in other cases, they are not equivalent but rather complement each other. By using these theorems, one associative memory neural network is designed, and their applications to pattern recognition are demonstrated