Research ArticleOpen accessIn the keywordsAsymptotic Behavior for Solution of Reaction-Diffusion SystemsM. Yahi, K. SaoudiThe existence, uniqueness, and asymptotic behavior of the solution of a balanced two-component reaction-diffusion system have been investigated. It was shown that a global and unique solution existed and its second component can be estimated using the Lyapunov Functional. It was, also, demonstrated that each component of the solution converged, at infinity, to a constant which can be found in … …Journal of Mathematics and Statistics, Vol. 3, Issue 3 · 30 Sep 2007 · 6,845 accessesView PDFCite
Research ArticleOpen accessIn the abstractNew sufficient condition of Discrete-time systems of neural networksManlika Tanusit, Kreangkri RatchagitProblem statement: In this study, we derive a new sufficient condition for asymptotic stability of the zero solution of delay-differential system of neural networks in terms of certain matrix inequalities by using a discrete analog of the new Lyapunov second method. Conclusion/Recommendations: The problem is solved by applying a novel Lyapunov functional and an improved delay-dependent stability criterion is obtained … …American Journal of Applied Sciences, Vol. 8, Issue 2 · 28 Feb 2011 · 7,005 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Delay-Dependent for Discrete-Time SystemsKreangkri RatchagitProblem statement: This study is concerned with the problem of delay-dependent stability analysis for discrete-time systems with interval-like time-varying delays. Conclusion/Recommendations: The problem is solved by applying a novel Lyapunov functional and an improved delay-dependent stability criterion is obtained in terms of a linear matrix inequality. …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 7,076 accessesView PDFCite
Research ArticleOpen accessIn the abstractAsymptotic Behavior of an Artificial Neural Network Defined on Multipartite Directed GraphN. C. Majee, A. B. RoyProblem statement: Artificial Neural Network (ANN) are simple models to mimic some essential features of the complex central nervous system. ANN models are realistic due to their inherent stochastic nature of neural computation and strong synchronicity. Different ANN models are associated with directed and signed graphs. The present study proceeded by relaxing certain simplifying assumptions in the ANN model. Approach: … …OnLine Journal of Biological Sciences, Vol. 10, Issue 1 · 30 Jun 2010 · 7,476 accessesView PDFCite
Research ArticleOpen accessIn the abstractStability of Non-Neutral and Neutral Dynamic Switched Systems Subject to Internal DelaysM. De la Sen, J. L. Malaina, A. Gallego, J. C. SotoThis study deals with the quadratic stability and linear state-feedback and output-feedback stabilization of switched delayed linear dynamic systems with, in general, a finite number of non commensurate constant internal point delays. The results are obtained based on Lyapunov’s stability analysis via appropriate Krasovsky-Lyapunov’s functionals and the related stability study is performed to obtain both delay independent and delay dependent … …American Journal of Applied Sciences, Vol. 2, Issue 10 · 31 Oct 2005 · 6,720 accessesView PDFCite