摘要
We are interested in the asymptotic behaviors of a discrete-time neural network. This network admits transiently chaotic behaviors which provide global searching ability in solving combinatorial optimization problems. As the system evolves, the variables corresponding to temperature in the annealing process decrease, and the chaotic behaviors vanish. We shall find sufficient conditions under which evolutions for the system converge to a fixed point of the system. Attracting sets and uniqueness of fixed point for the system are also addressed. Moreover, we extend the theory to the neural networks with cycle-symmetric coupling weights and other output functions. An application of this annealing process in solving travelling salesman problems is illustrated.
原文 | 英語 |
---|---|
頁(從 - 到) | 805-826 |
頁數 | 22 |
期刊 | Discrete and Continuous Dynamical Systems |
卷 | 10 |
發行號 | 3 |
DOIs | |
出版狀態 | 已發佈 - 2004 4月 |
對外發佈 | 是 |
ASJC Scopus subject areas
- 分析
- 離散數學和組合
- 應用數學