Global Asymptotical Stability Analysis for Fractional Neural Networks with Time-Varying Delays

Zhixin Zhang, Yufeng Zhang, Jia-Bao Liu and Jiang Wei
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Zhixin Zhang: School of Mathematics Sciences, Anhui University, Hefei 230601, China
Yufeng Zhang: School of Mathematics Sciences, Anhui University, Hefei 230601, China
Jia-Bao Liu: School of Mathematics and Physics, Anhui Jianzhu University, Hefei 230601, China
Jiang Wei: School of Mathematics Sciences, Anhui University, Hefei 230601, China

Mathematics, 2019, vol. 7, issue 2, 1-8

Abstract: In this paper, the global asymptotical stability of Riemann-Liouville fractional-order neural networks with time-varying delays is studied. By combining the Lyapunov functional function and LMI approach, some sufficient criteria that guarantee the global asymptotical stability of such fractional-order neural networks with both discrete time-varying delay and distributed time-varying delay are derived. The stability criteria is suitable for application and easy to be verified by software. Lastly, some numerical examples are presented to check the validity of the obtained results.

Keywords: time-varying delay; global asymptotical stability; fractional-order; neural networks; linear matrix inequality (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
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