Stability Analysis for Delayed Neural Networks Considering Both Conservativeness and Complexity

Zhang, Chuan-Ke, He, Yong, Jiang, Lin ORCID: 0000-0001-6531-2791 and Wu, Min (2016) Stability Analysis for Delayed Neural Networks Considering Both Conservativeness and Complexity. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 27 (7). pp. 1486-1501.

Text PDF_TNNLS-2015-P-4532.pdf - Author Accepted Manuscript Download (889kB)

Abstract

This paper investigates delay-dependent stability for continuous neural networks with a time-varying delay. This paper aims at deriving a new stability criterion, considering tradeoff between conservativeness and calculation complexity. A new Lyapunov-Krasovskii functional with simple augmented terms and delay-dependent terms is constructed, and its derivative is estimated by several techniques, including free-weighting matrix and inequality estimation methods. Then, the influence of the techniques used on the conservativeness and the complexity is analyzed one by one. Moreover, useful guidelines for improving criterion and future work are briefly discussed. Finally, the advantages of the proposed criterion compared with the existing ones are verified based on three numerical examples.

Item Type:	Article
Uncontrolled Keywords:	Calculation complexity, conservativeness, delay-dependent stability, delayed neural networks (DNNs), Lyapunov-Krasovskii functional (LKF)
Depositing User:	Symplectic Admin
Date Deposited:	22 Sep 2016 10:26
Last Modified:	19 Jan 2023 07:33
DOI:	10.1109/TNNLS.2015.2449898
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3002340