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Stability and synchronization of discrete-time neural networks with switching parameters and time-varying delays

Journal Article


Abstract


  • This paper is concerned with the problems of exponential stability analysis and synchronization of discrete-time switched delayed neural networks. Using the average dwell time approach together with the piecewise Lyapunov function technique, sufficient conditions are proposed to guarantee the exponential stability for the switched neural networks with time-delays. Benefitting from the delay partitioning method and the free-weighting matrix technique, the conservatism of the obtained results is reduced. In addition, the decay estimates are explicitly given and the synchronization problem is solved. 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. © 2012 IEEE.

Publication Date


  • 2013

Citation


  • Wu, L., Feng, Z., & Lam, J. (2013). Stability and synchronization of discrete-time neural networks with switching parameters and time-varying delays. IEEE Transactions on Neural Networks and Learning Systems, 24(12), 1957-1972. doi:10.1109/TNNLS.2013.2271046

Scopus Eid


  • 2-s2.0-84887995866

Web Of Science Accession Number


Start Page


  • 1957

End Page


  • 1972

Volume


  • 24

Issue


  • 12

Abstract


  • This paper is concerned with the problems of exponential stability analysis and synchronization of discrete-time switched delayed neural networks. Using the average dwell time approach together with the piecewise Lyapunov function technique, sufficient conditions are proposed to guarantee the exponential stability for the switched neural networks with time-delays. Benefitting from the delay partitioning method and the free-weighting matrix technique, the conservatism of the obtained results is reduced. In addition, the decay estimates are explicitly given and the synchronization problem is solved. 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. © 2012 IEEE.

Publication Date


  • 2013

Citation


  • Wu, L., Feng, Z., & Lam, J. (2013). Stability and synchronization of discrete-time neural networks with switching parameters and time-varying delays. IEEE Transactions on Neural Networks and Learning Systems, 24(12), 1957-1972. doi:10.1109/TNNLS.2013.2271046

Scopus Eid


  • 2-s2.0-84887995866

Web Of Science Accession Number


Start Page


  • 1957

End Page


  • 1972

Volume


  • 24

Issue


  • 12