A novel hysteretic chaotic neural network and its applications

Xiangdong Liu; Chunbo Xiu

doi:10.1016/j.neucom.2007.02.002

A novel hysteretic chaotic neural network and its applications

Xiangdong Liu
, Chunbo Xiu^*

^*此作品的通讯作者

Electronic Information and Communication Evaluation Center
Tiangong University

科研成果: 期刊稿件 › 文章 › 同行评审

30 引用（Scopus）

摘要

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.

源语言	英语
页（从-至）	2561-2565
页数	5
期刊	Neurocomputing
卷	70
期	13-15
DOI	https://doi.org/10.1016/j.neucom.2007.02.002
出版状态	已出版 - 8月 2007
已对外发布	是

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title = "A novel hysteretic chaotic neural network and its applications",

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.",

keywords = "Chaos, Hysteresis, Neural network, Neurons, TSP",

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AB - 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.

KW - Chaos

KW - Hysteresis

KW - Neural network

KW - Neurons

KW - TSP

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A novel hysteretic chaotic neural network and its applications

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