Attractors and the attraction basins of discrete-time cellular neural networks

被引：0

作者：

Ma Runnian Xi Youmin School of Management Xian Jiaotong University Xian P R China Key Lab of Information Sciences and Engineering Dalian University Dalian P R China ^{[1
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机构：

来源：

Journal of Systems Engineering and Electronics | 2005年 / 01期

关键词：

discrete-time cellular neural networks; convergent point; k-attractor; attraction basin;

D O I：

暂无

中图分类号：

TP183 [人工神经网络与计算];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The dynamic behavior of discrete-time cellular neural networks(DTCNN), which is strict with zero threshold value, is mainly studied in asynchronous mode and in synchronous mode. In general, a k-attractor of DTCNN is not a convergent point. But in this paper, it is proved that a k-attractor is a convergent point if the strict DTCNN satisfies some conditions. The attraction basin of the strict DTCNN is studied, one example is given to illustrate the previous conclusions to be wrong, and several results are presented. The obtained results on k-attractor and attraction basin not only correct the previous results, but also provide a theoretical foundation of performance analysis and new applications of the DTCNN.

引用

页码：204 / 208

页数：5

共 4 条

[1]

Harrer H,Nossek J A.Discrete-time cellular neural networks. International Journal of Circuit Theory and Applications . 1992

[2]

Perfetti R.Some properties of the attractors of discretetime cellular neural networks. International Journal of Circuit And Applications . 1995

[3]

Zhang Qiang,Ma Runnian,Xu Jin.On the global stability of delayed neural networks. IEEE Transactions on Automatic Control . 2003

[4]

Ma Runnian,Zhang Qiang,Xu Jin.Convergence of discrete-time cellular neural networks. The Chinese Journal . 2002

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