Title :
Design of Hopfield-type associative memory with maximal basin of attraction
Author :
Chang, Jen-Yuan ; Wu, Chi-Chang
Author_Institution :
Dept. of Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Abstract :
A method is described for enlarging as much as possible the basin of attraction of a Hopfield-type associative memory. The proposed learning rule, a minimum-overlap learning algorithm that includes a threshold parameter, enables a Hopfield-type associative memory to be designed so that the memory will have a maximal basin of attraction. A technique that diminishes the effect of the threshold on the minimum-overlap learning algorithm is devised. Simulation results show that the basin of attraction constructed by the proposed method is indeed larger than that constructed by several well known methods.
Keywords :
Hopfield neural nets; content-addressable storage; learning (artificial intelligence); Hopfield-type associative memory; learning rule; maximal basin of attraction; minimum-overlap learning algorithm; threshold parameter;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19931423