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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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
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