Abstract
The present paper investigates the fixed-time synchronization for fuzzy cellular neural networks with time-varying delays and discontinuous activations. In the framework of differential inclusions, new and useful fixed-time synchronization criteria for the networks considered are established by utilizing the discontinuous state feedback control and constructing Lyapunov functionals, which significantly generalize and improve recent works in the literature. Numerical simulations are given to show the effectiveness of the fixed-time synchronization schemes.
Highlights
Since cellular neural networks (CNNs) were first proposed by Chua and Yang in 1988 [1], [2], they have been extensively investigated because of their wide applications in many fields such as classification of patterns, associative memories, image processing, associative memories, quadratic optimization, classification of patterns
We study the fixed-time synchronization of delayed fuzzy cellular neural networks (FCNNs) with discontinuous activations by designing a suitable fixed-time controller
The simulation results show that the fixed-time synchronization of the drive-response FCNNs with time-varying delays and discontinuous activations can be achieved by using our method
Summary
Since cellular neural networks (CNNs) were first proposed by Chua and Yang in 1988 [1], [2], they have been extensively investigated because of their wide applications in many fields such as classification of patterns, associative memories, image processing, associative memories, quadratic optimization, classification of patterns. Tang and Yang [20] investigated the finite-time cluster synchronizing issue for the coupled FCNNs with discontinuous activations, unbounded time-dependent delays, Markovian switching topology, and proportional leakage. Sun: Fixed-Time Synchronization of FCNNs With Time-Varying Delays and Discontinuous Activations synchronization mentioned above is either asymptotic or finite-time, which greatly limited its practical applications. The neural network model discussed in this paper includes discontinuous activations, fuzzy logic and time-varying delays simultaneously.
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