Stability Analysis of Continuous-Time Switched Neural Networks With Time-Varying Delay Based on Admissible Edge-Dependent Average Dwell Time

• Published in: IEEE transaction on neural networks and learning systems Vol. 32; no. 11; pp. 5108 - 5117
• Main Authors: Wang, Hui-Ting, He, Yong, Zhang, Chuan-Ke
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.11.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Admissible edge-dependent average dwell time (AED-ADT); Delays; Dwell time; Neural networks; relaxed integral inequalities; Stability analysis; Stability criteria; Subsystems; switched neural networks (SNNs); Switched systems; time-varying delay; Time-varying systems
• ISSN: 2162-237X; 2162-2388; 2162-2388
• DOI: 10.1109/TNNLS.2020.3026912

This article investigates the stability of the switched neural networks (SNNs) with a time-varying delay. To effectively guarantee the stability of the considered system with unstable subsystems and reduce conservatism of the stability criteria, admissible edge-dependent average dwell time (AED-ADT) is first utilized to restrict switching signals for the continuous-time SNNs, and multiple Lyapunov-Kravosikii functionals (LKFs) combining relaxed integral inequalities are employed to develop two novel less-conservative stability conditions. Finally, the numeral examples clearly indicate that the proposed criteria can reduce conservatism and ensure the stability of continuous-time SNNs.