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Research articles

ScienceAsia (): 179-186 |doi: 10.2306/scienceasia1513-1874...179


Synchronization stability for recurrent neural networks with time-varying delays


Ahmadjan Muhammadhaji*, Azhar Halik

 
ABSTRACT:     This paper studies the general decay synchronization (GDS) of a class of recurrent neural networks (RNNs) with general activation functions and time-varying delays. By constructing suitable Lyapunov-Krasovskii functionals and employing useful inequality techniques, some sufficient conditions on the GDS of considered RNNs are established via a type of nonlinear control. In addition, an example with numerical simulations is presented to illustrate the obtained theoretical results.

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a College of Mathematics and Systems Science, Xinjiang University, Urumqi 830046 China

* Corresponding author, E-mail: ahmatjanam@aliyun.com

Received 8 Jul 2018, Accepted 9 Apr 2019