{"title":"Exponential State Estimation for Neural Networks with Leakage, Discrete and Distributed Delays","authors":"Liyuan Wang, Shouming Zhong","volume":89,"journal":"International Journal of Mathematical and Computational Sciences","pagesStart":862,"pagesEnd":873,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/9999220","abstract":"
In this paper, the design problem of state estimator for
\r\nneural networks with the mixed time-varying delays are investigated
\r\nby constructing appropriate Lyapunov-Krasovskii functionals and
\r\nusing some effective mathematical techniques. In order to derive
\r\nseveral conditions to guarantee the estimation error systems to be
\r\nglobally exponential stable, we transform the considered systems
\r\ninto the neural-type time-delay systems. Then with a set of linear
\r\ninequalities(LMIs), we can obtain the stable criteria. Finally, three
\r\nnumerical examples are given to show the effectiveness and less
\r\nconservatism of the proposed criterion.<\/p>\r\n","references":"[1] Y. Liu, Z. Wang, X. Liu, \"Global exponential stsbility of generalized\r\nrecurrent neural networks with discrete and distributed delays,\u201d Neural\r\nNetworks 19(2006)667-675.\r\n[2] Y. Wang , Z. Wang , J. Liang ,\"On robust stability of stochastic genetic\r\nregulatory networks with time-delays : a delay fractioning papproach,\u201d\r\nIEEE Trans.Syst.Man Cybern.PartB 40(2010)729-740.\r\n[3] X.Liu,\"Delay-dependent H \u221d control for uncertain fuzzy systems with\r\ntime-varying delays,\u201d Nonlinear Analysis:Theory,Methods Applications\r\n68(2008)1352-1361.\r\n[4] S. Y. 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