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- W2579293556 abstract "This paper is concerned with the problem of $H_{infty}$ state estimation problem for a class of delayed static neural networks. The purpose of the problem is to design a delay-dependent state estimator such that the dynamics of the error system is globally exponentially stable with a prescribed $H_{infty}$ performance. Some improved delay-dependent conditions are established by using delay partitioning method and the free-matrix-based integral inequality. The gain matrix and the optimal performance index are obtained via solving a convex optimization problem subject to LMIs (linear matrix inequality). Numerical examples are provided to illustrate the effectiveness of the proposed method comparing with some existing results." @default.
- W2579293556 created "2017-01-26" @default.
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- W2579293556 date "2017-01-16" @default.
- W2579293556 modified "2023-09-23" @default.
- W2579293556 title "New results on H ∞ $H_{infty}$ state estimation of static neural networks with time-varying delay" @default.
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- W2579293556 doi "https://doi.org/10.1186/s13662-016-1056-3" @default.
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