Journal
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
Volume 56, Issue 8, Pages 659-663Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSII.2009.2024244
Keywords
Globally asymptotic stability; linear matrix inequality (LMI); neural networks; time-varying delay
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Funding
- Central Queensland University for Research Development and Incentives Program-Seed
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This brief is concerned with the stability analysis for cellular neural networks with time-varying delays. First, an appropriate Lyapunov-Krasovskii functional is introduced to form some new delay-dependent stability conditions in terms of linear matrix inequalities (LMIs). Quite differently, these stability criteria are derived by using the convex combination property, which equivalently converts the original LMI containing a convex combination on the time-varying delay into two boundary LMIs. Second, this newly proposed approach is then extended to a class of uncertain neural networks with time-varying delays, from which new delay-dependent robust stability criteria are formulated. Finally, two numerical examples are given to show that the proposed criteria are of much less conservatism than the existing ones in the literature.
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