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

Author

Zhenjiang, Mia0 ; Baozong, Yuan

Author_Institution

Inst. of Inf. Sci., Northern Jiatong Univ., Beijing, China

fYear

1993

fDate

1993

Firstpage

1570

Abstract

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

Keywords

Hopfield neural nets; content-addressable storage; image recognition; Hopfield-type neural networks; associative memory neural nets; asymptotical stability; energy function; pattern recognition; Artificial neural networks; Associative memory; Asymptotic stability; Hopfield neural networks; Information analysis; Jacobian matrices; Neural networks; Pattern analysis; Pattern recognition; Stability analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1993., IEEE International Conference on

Conference_Location

San Francisco, CA

Print_ISBN

0-7803-0999-5

Type

conf

DOI

10.1109/ICNN.1993.298790

Filename

298790