不连续激活函数的时滞神经网络的多稳定性

陈晓丰; 宋乾坤

doi:10.3879/j.issn.1000-0887.2013.04.007

不连续激活函数的时滞神经网络的多稳定性

doi: 10.3879/j.issn.1000-0887.2013.04.007

重庆交通大学理学院,重庆 400074

基金项目: 国家自然科学基金资助项目（61273021）

详细信息

作者简介:
陈晓丰(1980—),男,江苏江阴人,讲师, 硕士(E-mail:xxffch@126.com);宋乾坤(1963—),男,教授,博士(通讯作者. E-mail:qiankunsong@163.com).

中图分类号: O175.13
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- 被引次数: 0
出版历程
- 收稿日期: 2013-03-18
- 修回日期: 2013-04-03
- 刊出日期: 2013-04-15

Multistability of Delayed Neural Networks With Discontinuous Activations

Department of Mathematics, Chongqing Jiaotong University,Chongqing 400074, P.R.China

摘要

摘要: 研究了不连续激活函数的时滞神经网络的多稳定性问题，在所研究的神经网络中，激活函数并不需要是连续的和单调的．给出了判断该神经网络多个平衡点存在及局部指数稳定的充分条件．最后，给出了两个数值仿真例子来验证本文获得结果的有效性和较小的保守性．
- 神经网络 /
- 不连续激活函数 /
- 多重稳定 /
- 指数稳定
Abstract: The problem on the multistability was investigated for delayed neural networks with discontinuous activations. For the neural networks under studied,the traditional assumptions on the continuity and the monotonicity of the activation functions were not required. Several sufficient conditions for checking the coexistence and local exponential stability of equilibria for the considered neural networks were given. Finally, two numerical examples were given to show the effectiveness and less conservatism of the proposed criteria.
- neural network /
- discontinuous neuron activation /
- multistability /
- exponential stability

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