On the Asymptotic Behavior of Hopfield Neural Network With Periodic Inputs

XIANG Lan; ZHOU Jin; LIU Zeng-rong; SUN Shu

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Article Navigation > Applied Mathematics and Mechanics > 2002 > 23(12): 1220-1226

XIANG Lan, ZHOU Jin, LIU Zeng-rong, SUN Shu. On the Asymptotic Behavior of Hopfield Neural Network With Periodic Inputs[J]. Applied Mathematics and Mechanics, 2002, 23(12): 1220-1226.

Citation:

XIANG Lan, ZHOU Jin, LIU Zeng-rong, SUN Shu. On the Asymptotic Behavior of Hopfield Neural Network With Periodic Inputs[J]. Applied Mathematics and Mechanics, 2002, 23(12): 1220-1226.

Citation:

XIANG Lan, ZHOU Jin, LIU Zeng-rong, SUN Shu. On the Asymptotic Behavior of Hopfield Neural Network With Periodic Inputs[J]. Applied Mathematics and Mechanics, 2002, 23(12): 1220-1226.

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On the Asymptotic Behavior of Hopfield Neural Network With Periodic Inputs

1.
Department of Physics, Hebei University of Technology, Tianjin 300130, P R China;
2.
Department of Mathematics, Shanghai University, Shang-hai 200436, P R China;
3.
Naval Submarine Academy, Qingdao 266071, P R China

Received Date: 2001-07-24
Rev Recd Date: 2002-04-30
Publish Date: 2002-12-15

Abstract

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.
- Hopfield neural network,
- periodic solution,
- global exponential stability,
- coincidence degree,
- Liapunov function

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References(10)

References

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