| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 409364 | Neurocomputing | 2007 | 5 Pages |
Abstract
A model of single neuron with chaotic and hysteretic characteristics is proposed. Neural network coupled by such neurons exhibits complex dynamic behaviors. The network is also studied from the viewpoint of optimization. Chaos and hysteresis phenomena make the network have the characteristic of escaping from a local minimum of the energy function, so it can find a global minimum more easily as compared with others. The experimental results show that it has a higher average success rate of obtaining a global optimization solution.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Xiangdong Liu, Chunbo Xiu,