Name
Abstract | ||
|---|---|---|
The chaotic neural network constructed with chaotic neurons presents complex dynamics and has potential application in the associative dynamics and information processing. However, the states of the chaotic neural network wander around all the stored patterns and cannot be stabilized to one of the stored patterns or a periodic orbit because of the chaotic characteristic of the network, which hampering the application of the chaotic associative dynamics of chaotic neural network to information processing. In this work, a dynamic depression control method imposed on the internal state of neurons for chaotic neural networks is proposed. In this way, the decay parameters and the scaling parameter for the refractoriness are time varying determined by the internal state of neurons. Ascribing to dynamic depression control, chaos is controlled in a self-adaptive manner and no target needs to be specified in advance. Furthermore, the theoretic analysis of dynamic depression control is presented. The numerical simulation proves that the chaos in the chaotic neural network can be controlled with the dynamic depression control, and the neural network can be stabilized to a stored pattern if the control strength parameter is chosen suitable. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.neucom.2009.10.015 | Neurocomputing |
Keywords | Field | DocType |
chaotic neural networks,neural network,chaotic neural network,internal state,dynamic depression,associative memory,chaotic characteristic,chaotic associative dynamic,dynamic depression control,information processing,control strength parameter,chaotic neuron,controlling chaos,dynamic depression control method,numerical simulation,complex dynamics | Complex dynamics,Content-addressable memory,Information processing,Associative property,Computer simulation,Control theory,Computer science,Chaotic,Artificial neural network,Synchronization of chaos | Journal |
Volume | Issue | ISSN |
73 | 4-6 | Neurocomputing |
Citations | PageRank | References |
14 | 0.76 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min Xia | 1 | 65 | 3.56 |
| Jian'an Fang | 2 | 80 | 6.91 |
| Yang Tang | 3 | 1310 | 64.50 |
| Zhijie Wang | 4 | 89 | 11.14 |