Article ID Journal Published Year Pages File Type
406462 Neurocomputing 2014 7 Pages PDF
Abstract

This paper is concerned with finite-time synchronization for a class of delayed neural networks with Cohen–Grossberg type. Different from the existing related results, the time-delayed feedback strategy is utilized to investigate finite-time synchronization of delayed Cohen–Grossberg neural networks. By constructing Lyapunov functions and using differential inequalities, several new and effective criteria are derived to realize local and global synchronization in finite time of the addressed neural networks based on two different time-delayed feedback controllers. Besides, the upper bounds of the settling time of synchronization are estimated. Furthermore, as corollaries, some sufficient conditions are given to achieve finite-time synchronization of delayed cellular neural networks. Finally, some numerical examples are provided to verify the theoretical results established in this paper.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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