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Exponential stability analysis for delayed neural networks with switching parameters: Average dwell time approach

Journal Article


Abstract


  • This paper is concerned with the problem of exponential stability analysis of continuous-time switched delayed neural networks. By using the average dwell time approach together with the piecewise Lyapunov function technique and by combining a novel Lyapunov-Krasovskii functional, which benefits from the delay partitioning method, with the free-weighting matrix technique, sufficient conditions are proposed to guarantee the exponential stability for the switched neural networks with constant and time-varying delays, respectively. Moreover, the decay estimates are explicitly given. The results reported in this paper not only depend upon the delay but also depend upon the partitioning, which aims at reducing the conservatism. Numerical examples are presented to demonstrate the usefulness of the derived theoretical results. © 2006 IEEE.

Publication Date


  • 2010

Citation


  • Wu, L., Feng, Z., & Zheng, W. X. (2010). Exponential stability analysis for delayed neural networks with switching parameters: Average dwell time approach. IEEE Transactions on Neural Networks, 21(9), 1396-1407. doi:10.1109/TNN.2010.2056383

Scopus Eid


  • 2-s2.0-77956343250

Web Of Science Accession Number


Start Page


  • 1396

End Page


  • 1407

Volume


  • 21

Issue


  • 9

Abstract


  • This paper is concerned with the problem of exponential stability analysis of continuous-time switched delayed neural networks. By using the average dwell time approach together with the piecewise Lyapunov function technique and by combining a novel Lyapunov-Krasovskii functional, which benefits from the delay partitioning method, with the free-weighting matrix technique, sufficient conditions are proposed to guarantee the exponential stability for the switched neural networks with constant and time-varying delays, respectively. Moreover, the decay estimates are explicitly given. The results reported in this paper not only depend upon the delay but also depend upon the partitioning, which aims at reducing the conservatism. Numerical examples are presented to demonstrate the usefulness of the derived theoretical results. © 2006 IEEE.

Publication Date


  • 2010

Citation


  • Wu, L., Feng, Z., & Zheng, W. X. (2010). Exponential stability analysis for delayed neural networks with switching parameters: Average dwell time approach. IEEE Transactions on Neural Networks, 21(9), 1396-1407. doi:10.1109/TNN.2010.2056383

Scopus Eid


  • 2-s2.0-77956343250

Web Of Science Accession Number


Start Page


  • 1396

End Page


  • 1407

Volume


  • 21

Issue


  • 9