Passivity Analysis of Dynamic Neural Networks with Different Time-scales

被引：0
作者：
Wen Yu
Xiaoou Li
机构：
[1] CINVESTAV-IPN,Departamento de Control Automatico
[2] CINVESTAV-IPN,Departamento de Computación
来源：
Neural Processing Letters | 2007年 / 25卷
关键词：
different time scales; neural networks; passivity; stability;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Dynamic neural networks with different time-scales include the aspects of fast and slow phenomenons. Some applications require that the equilibrium points of the designed networks are stable. In this paper, the passivity-based approach is used to derive stability conditions for dynamic neural networks with different time-scales. Several stability properties, such as passivity, asymptotic stability, input-to-state stability and bounded input bounded output stability, are guaranteed in certain senses. A numerical example is also given to demonstrate the effectiveness of the theoretical results.
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页码：143 / 155
页数：12
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  • [1] Amari S.(1982)Competitive and cooperative aspects in dynamics of neural excitation and self-organization Competition Cooperation Neural Networks 20 1-28
  • [2] Byrnes C.I.(1991)Passivity, feedback equivalence, and the global stabilization of minimum phase nonlinear systems IEEE Transaction Automatic Control 36 1228-1240
  • [3] Isidori A.(1996)CMAC neural networks for control of nonlinear dynamical systems: structure, stability and passivity Automatica 33 635-641
  • [4] Willems J.C.(1994)Necessary and sufficient condition for absolute stability of neural networks IEEE Transactions on Circuit and Systems-I 41 491-494
  • [5] Commuri S.(1976)Adaptive pattern classification and universal recording Biological Cybernetics 23 121-134
  • [6] Lewis F.L.(1984)Neurons with grade response have collective computational properties like those of a two-state neurons Proceedings of the National Academy of Science USA 81 3088-3092
  • [7] Forti M.(1996)Identification of nonlinear dynamical systems using multilayered neural networks Automatica 32 1707-1712
  • [8] Manetti S.(1999)Stable dynamic backpropagation learning in recurrent neural networks IEEE Transactions on Neural Networks 10 1321-1334
  • [9] Marini M.(1994)On a class of globally stable neural circuits IEEE Transactions on Circuit and Systems-I 41 171-174
  • [10] Grossberg S.(1995)High-order neural network structures for identification of dynamical systems IEEE Transactions on Neural Networks 6 442-431
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