On the asymptotic behavior of hopfield neural network with periodic inputs
Received: 24 July 2001 Revised: 30 April 2002 DOI:
10.1007/BF02438376 Cite this article as: Lan, X., Jin, Z., Zeng-rong, L. et al. Appl Math Mech (2002) 23: 1367. doi:10.1007/BF02438376 Abstract
Without assuming the boundedness and differentiability of the nonlinear activation functions, the new sufficient conditions of the existence and the global exponential stability of periodic solutions for Hopfield neural network with periodic inputs are given by using Mawhin's coincidence degree theory and Liapunov's function method.
Key words Hopfield neural network periodic solution global exponential stability concidence degree Liapunov's function CLC numbers O175 TN911
Contributed by Liu Zeng-rong
Biography: Xiang Lan (1964-) References
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