An LMI approach for dynamics of switched cellular neural networks with mixed delays (Q370284)

Delayed cellular neural networks (DCNNs) are modeled by systems of differential equations of the form NEWLINE\[NEWLINE\dot{ x}_i(t) = -d_ix_i(t) + \sum_{j=1}^n a_{ij}f_j \big (x_j(t)\big ) +\sum_{j=1}^n b_{ij}f_j \big ( x_j(t-\tau_j)\big ) + J_i, \quad i= 1,2,\dots,n.NEWLINE\]NEWLINE 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.