Regular Papers

International Journal of Control, Automation and Systems 2017; 15(4): 1888-1900

Published online July 10, 2017

https://doi.org/10.1007/s12555-016-9483-1

© The International Journal of Control, Automation, and Systems

Novel results on stability analysis of neutral-type neural networks with additive time-varying delay components and leakage delay

R. Samidurai, S. Rajavel, R. Sriraman, Jinde Cao*, Ahmed Alsaedi and Fuad E. Alsaadi

Southeast University

Abstract

The objective of this paper is to analyze the stability analysis of neutral-type neural networks with additive time-varying delay and leakage delay. By constructing a suitable augmented Lyapunov-Krasovskii functional with triple and four integral terms, some new stability criteria are established in terms of linear matrix inequalities, which is easily solved by various convex optimization techniques. More information of the lower and upper delay bounds of time-varying delays are used to derive the stability criteria, which can lead less conservative results. The obtained conditions are expressed with linear matrix inequalities (LMIs) whose feasible can be checked easily by MATLAB LMI control toolbox. Finally, two numerical examples are given to demonstrate the effectiveness of the proposed method."

Keywords Additive time-varying delays, linear matrix inequality, Lyapunov-Krasovskii functional, neural networks, neutral-type.

Article

Regular Papers

International Journal of Control, Automation and Systems 2017; 15(4): 1888-1900

Published online August 1, 2017 https://doi.org/10.1007/s12555-016-9483-1

Copyright © The International Journal of Control, Automation, and Systems.

Novel results on stability analysis of neutral-type neural networks with additive time-varying delay components and leakage delay

R. Samidurai, S. Rajavel, R. Sriraman, Jinde Cao*, Ahmed Alsaedi and Fuad E. Alsaadi

Southeast University

Abstract

The objective of this paper is to analyze the stability analysis of neutral-type neural networks with additive time-varying delay and leakage delay. By constructing a suitable augmented Lyapunov-Krasovskii functional with triple and four integral terms, some new stability criteria are established in terms of linear matrix inequalities, which is easily solved by various convex optimization techniques. More information of the lower and upper delay bounds of time-varying delays are used to derive the stability criteria, which can lead less conservative results. The obtained conditions are expressed with linear matrix inequalities (LMIs) whose feasible can be checked easily by MATLAB LMI control toolbox. Finally, two numerical examples are given to demonstrate the effectiveness of the proposed method."

Keywords: Additive time-varying delays, linear matrix inequality, Lyapunov-Krasovskii functional, neural networks, neutral-type.

IJCAS
September 2024

Vol. 22, No. 9, pp. 2673~2953

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