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Delay-Dependent H∞ and Generalized H2 Filtering for Delayed Neural Networks.
- Source :
- IEEE Transactions on Circuits & Systems. Part I: Regular Papers; Apr2009, Vol. 56 Issue 4, p846-857, 12p, 2 Black and White Photographs, 1 Chart, 9 Graphs
- Publication Year :
- 2009
-
Abstract
- This paper focuses on studying the H∞ and generalized H<subscript>2</subscript> filtering problems for a class of delayed neural networks. The time-varying delay is only required to be continuous and bounded. Delay-dependent criteria are proposed such that the resulting filtering error system is globally exponentially stable with a guaranteed H∞ or generalized H<subscript>2</subscript> performance. It is also shown that the designs of the desired filters are achieved by solving a set of linear matrix inequalities, which can be facilitated efficiently by resorting to standard numerical algorithms. It should be noted that, based on a novel bounding technique, several slack variables are introduced to reduce the conservatism of the derived conditions. Three examples with simulation results are provided to illustrate the effectiveness and performance of the developed approaches. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15498328
- Volume :
- 56
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Circuits & Systems. Part I: Regular Papers
- Publication Type :
- Periodical
- Accession number :
- 38716437
- Full Text :
- https://doi.org/10.1109/TCSI.2008.2003372