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Non-fragile state observer design for neural networks with Markovian jumping parameters and time-delays. (English) Zbl 1300.34175

Summary: This paper investigates the non-fragile observer based design for neural networks with mixed time-varying delays and Markovian jumping parameters. By developing a reciprocal convex approach and based on the Lyapunov-Krasovskii functional, and stochastic stability theory, a delay-dependent stability criterion is obtained in terms of linear matrix inequalities (LMIs). The observer gains are given from the LMI feasible solutions. Finally, three numerical examples are given to illustrate the effectiveness of the derived theoretical results. Among them the third example deals the practical system of quadruple tank process.

MSC:

34K35 Control problems for functional-differential equations
34K50 Stochastic functional-differential equations
92B20 Neural networks for/in biological studies, artificial life and related topics
93B30 System identification
93B51 Design techniques (robust design, computer-aided design, etc.)
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