Title: Global asymptotic stability of neural networks with uncertain parameters and time-varying delay

Authors: Yang Li; Jianhua Zhang; Xueli Wu

Addresses: Hebei University of Science and Technology, Shijiazhuang 050018, China ' Hebei University of Science and Technology, Shijiazhuang 050018, China ' Hebei University of Science and Technology, Shijiazhuang 050018, China

Abstract: This paper is concerned with global asymptotically stability problem for a class of neural networks with uncertain parameters and time-varying delay. Using a new proposed inequality called free-matrix-based integral inequality, the new robust criterion is proposed, which is expressed by linear matrix inequalities, by means of linear matrix inequality technique to deal with the unknown parameters in the neutral systems. An example is simulated to demonstrate the effectiveness and efficiency of the obtained criterion.

Keywords: neural networks stability; time-varying delay; uncertain parameters; Lyapunov-Krasovskii functional.

DOI: 10.1504/IJCAT.2018.092975

International Journal of Computer Applications in Technology, 2018 Vol.57 No.3, pp.228 - 236

Received: 06 Jan 2017
Accepted: 02 Mar 2017
Published online: 04 Jul 2018 *

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