Impulsive Control of Complex-Valued Neural Networks with Mixed Time Delays and Uncertainties

Yujuan Tian, Yuhan Yin, Fei Wang and Kening Wang
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Yujuan Tian: School of Mathematics and Statistics, Shandong Normal University, Jinan 250014, China
Yuhan Yin: School of Mathematics and Statistics, Shandong Normal University, Jinan 250014, China
Fei Wang: School of Mathematics and Statistics, Shandong Normal University, Jinan 250014, China
Kening Wang: Department of Mathematics and Statistics, University of North Florida, Jacksonville, FL 32224, USA

Mathematics, 2022, vol. 10, issue 3, 1-14

Abstract: This paper investigates the global exponential stability of uncertain delayed complex-valued neural networks (CVNNs) under an impulsive controller. Both discrete and distributed time-varying delays are considered, which makes our model more general than previous works. Unlike most existing research methods of decomposing CVNNs into real and imaginary parts, some stability criteria in terms of complex-valued linear matrix inequalities (LMIs) are obtained by employing the complex Lyapunov function method, which is valid regardless of whether the activation functions can be decomposed. Moreover, a new impulsive differential inequality is applied to resolve the difficulties caused by the mixed time delays and delayed impulse effects. Finally, an illustrative example is provided to back up our theoretical results.

Keywords: complex-valued neural networks; impulsive control; time-varying delays; globally exponentially stable (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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