Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4974198 | Journal of the Franklin Institute | 2017 | 26 Pages |
Abstract
This paper discusses the problems of exponential stability and extended dissipativity analysis of generalized neural networks (GNNs) with time delays. A new criterion for the exponential stability and extended dissipativity of GNNs is established based on the suitable Lyapunov-Krasovskii functionals (LKFs) together with the Wirtinger single integral inequality (WSII) and Wirtinger double integral inequality (WDII) technique, and that is mixed with the reciprocally convex combination (RCC) technique. An improved exponential stability and extended dissipativity criterion for GNNs are expressed in terms of linear matrix inequalities (LMIs). The major contributions of this study are an exponential stability and extended dissipativity concept can be developed to analyze simultaneously the solutions of the exponential Hâ, L2âLâ, passivity, and dissipativity performance for GNNs by selecting the weighting matrices. Finally, several interesting numerical examples are developed to verify the usefulness of the proposed results, among them one example was supported by real-life application of the benchmark problem that associates with reasonable issues under extended dissipativity performance.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
R. Manivannan, G. Mahendrakumar, R. Samidurai, Jinde Cao, Ahmed Alsaedi,