Exponential convergence and stability of delayed fuzzy cellular neural networks with time-varying coefficients
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Hardware and Architecture,Control and Systems Engineering
Link
http://link.springer.com/content/pdf/10.1007/s11768-011-8146-2.pdf
Reference17 articles.
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2. J. Cao, J. Wang. Global exponential stability and periodicity of recurrent neural networks with time delays. IEEE Transactions on Circuits and Systems I — Regular Papers, 2005, 52(5): 920–931.
3. M. Tan, Y. Zhang. New sufficient conditions for global asymptotic stability of Cohen-Grossberg neural networks with time-varying delays. Nonlinear Analysis: Real World Applications, 2009, 10(4): 2139–2145.
4. B. Liu. Exponential convergence for a class of delayed cellular neural networks with time-varying coefficients. Physics Letters A, 2008, 372(4): 424–428.
5. Y. Hou, T. Liao, J. Yan. Stability analysis of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays. IEEE Transactions on Systems, Man, and Cybernetics — Part B: Cybernetics, 2007, 37(3): 720–726.
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