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Exponential Stability, Passivity, and Dissipativity Analysis of Generalized Neural Networks With Mixed Time-Varying Delays
- Issue Date
- Feb-2019
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Exponential passivity; generalized neural networks (GNNs); (D, G, R)-gamma-dissipativity; time-varying delay; weighted integral inequality (WII)
- Citation
- IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, v.49, no.2, pp.395 - 405
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
- Volume
- 49
- Number
- 2
- Start Page
- 395
- End Page
- 405
- ISSN
- 2168-2216
- Abstract
- In this paper, we analyze the exponential stability, passivity, and (D, G, R)-gamma-dissipativity of generalized neural networks (GNNs) including mixed time-varying delays in state vectors. Novel exponential stability, passivity, and (D, G, R)-gamma-dissipativity criteria are developed in the form of linear matrix inequalities for continuous-time GNNs by constructing an appropriate Lyapunov-Krasovskii functional (LKF) and applying a new weighted integral inequality for handling integral terms in the time derivative of the established LKF for both single and double integrals. Some special cases are also discussed. The superiority of employing the method presented in this paper over some existing methods is verified by numerical examples.
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Related Researcher
- Ahn, Choon ki
- College of Engineering (School of Electrical Engineering)