 Stability analysis of reaction-diffusion uncertain memristive neural networks with time-varying delays and leakage termRuoxia Li and Jinde Cao Applied Mathematics and Computation, 2016, vol. 278, issue C, 54-69 Abstract: In this paper, the stability problem is investigated for a class of reaction-diffusion uncertain memristive neural networks with time-varying delays and leakage term. To investigate the dynamic behavior of the memristive system, we turn to the qualitative analysis of a relevant differential inclusion under the framework of Filippov’s solution, which is easier to handle. By using Lyapunov stability theory, Jensen integral inequality, Schur complement Lemma, free-weighting matrix approach together with the linear matrix inequality (LMI) approach, the sufficient conditions are derived to ensure the stability of the considered systems. The easy-to-test stability criteria established in this paper depend on the leakage delay as well as the reaction-diffusion terms, which is more reasonable. Moreover, the existing stability criteria can be treated as a special case of this paper. Finally, two numerical examples are exploited to show the effectiveness of the derived LMI-based stability conditions. Keywords: Memristor; Asymptotic stability; Reaction-diffusion terms; Leakage delay (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:278:y:2016:i:c:p:54-69 DOI: 10.1016/j.amc.2016.01.016 Access Statistics for this article Applied Mathematics and Computation is currently edited by Theodore Simos More articles in Applied Mathematics and Computation from Elsevier |
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