DocumentCode
2286895
Title
Theoretical considerations on the dynamics of hysteresis binary Hopfield networks for combinatorial optimization
Author
Matsuda, Satoshi
Author_Institution
901-25, Eda-cho, Aoba-ku, Yokohama, Japan
Volume
6
fYear
2000
fDate
2000
Firstpage
480
Abstract
It has been reported that hysteresis binary Hopfield networks achieve good performance for many combinatorial optimization problems. The theoretical analysis of the network dynamics or this good performance, however, is not given yet. In this paper, conditions for the convergence to an energy minimum state, and for the stability of the feasible and infeasible solutions to combinatorial optimization problems are shown in terms of the hysteresis size. Then, a theoretical explanation of the good performance of hysteresis binary Hopfield networks is also given. Simulations illustrate these theoretical conclusions
Keywords
Hopfield neural nets; combinatorial mathematics; hysteresis; optimisation; combinatorial optimization; hysteresis binary Hopfield networks; network dynamics; stability; Convergence; Hysteresis; Neurons; Performance analysis; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location
Como
ISSN
1098-7576
Print_ISBN
0-7695-0619-4
Type
conf
DOI
10.1109/IJCNN.2000.859441
Filename
859441
Link To Document