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Exponential Stability and Stabilization of Delayed Memristive Neural Networks Based on Quadratic Convex Combination Method.
- Source :
-
IEEE Transactions on Neural Networks & Learning Systems . Nov2016, Vol. 27 Issue 11, p2337-2350. 14p. - Publication Year :
- 2016
-
Abstract
- This paper is concerned with the exponential stability and stabilization of memristive neural networks (MNNs) with delays. First, we present some generalized double-integral inequalities, which include some existing inequalities as their special cases. Second, combining with quadratic convex combination method, these double-integral inequalities are employed to formulate a delay-dependent stability condition for MNNs with delays. Third, a state-dependent switching control law is obtained for MNNs with delays based on the proposed stability conditions. The desired feedback gain matrices are accomplished by solving a set of linear matrix inequalities. Finally, the feasibility and effectiveness of the proposed results are tested by two numerical examples. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 2162237X
- Volume :
- 27
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Neural Networks & Learning Systems
- Publication Type :
- Periodical
- Accession number :
- 119032853
- Full Text :
- https://doi.org/10.1109/TNNLS.2015.2485259