Abstract
In this paper, an adaptive linear feedback controller is presented to study the synchronization problem of different Cohen–Grossberg neural networks with unknown parameters and time-varying delays. Lyapunov stability theory and Barbalat’s lemma are used to guarantee the response system can be synchronized with the drive system. The synchronization criteria of this paper which do not solve any linear matrix inequality are easily verified. These results remove some restrictions on amplification functions and activation functions. Finally, numerical simulations are carried out to illustrate the effectiveness of the obtained results.
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Shi, Y., Zhu, P. Adaptive synchronization of different Cohen–Grossberg chaotic neural networks with unknown parameters and time-varying delays. Nonlinear Dyn 73, 1721–1728 (2013). https://doi.org/10.1007/s11071-013-0898-4
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DOI: https://doi.org/10.1007/s11071-013-0898-4