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An LMI approach for dynamics of switched cellular neural networks with mixed delays. (English) Zbl 1283.34069

Delayed cellular neural networks (DCNNs) are modeled by systems of differential equations of the form \[ \dot{ x}_i(t) = -d_ix_i(t) + \sum_{j=1}^n a_{ij}f_j \big (x_j(t)\big ) +\sum_{j=1}^n b_{ij}f_j \big ( x_j(t-\tau_j)\big ) + J_i, \quad i= 1,2,\dots,n. \] After discussing the history of the problem and briefly reviewing the literature, the objective of the paper is to establish a set of sufficient criteria on the existence of an attractor and the ultimate boundedness of the solutions of the switched system. The dynamics of switched cellular neural networks with mixed delays (interval time-varying delays and distributed-time varying delays) are studied by using Lyapunov-Krasovkii functionals.

MSC:

34K25 Asymptotic theory of functional-differential equations
34K20 Stability theory of functional-differential equations
92B20 Neural networks for/in biological studies, artificial life and related topics

Software:

Matlab
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