Title: Global stability of a class of Cohen-Grossberg neural networks with delays

Authors: Zhanshan Wang, Jian Feng, Gang Chen

Addresses: School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China. ' School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China. ' Institute of Science, Shenyang Ligong University, Shenyang, Liaoning 110168, People's Republic of China

Abstract: This paper is concerned with the Global Asymptotic Stability (GAS) of a general class of Cohen-Grossberg neural networks with both multiple time varying delays and distributed delays. Criteria are established to ensure the GAS of the concerned neural networks, which can be expressed in the form of Linear Matrix Inequality and independent of amplification functions. Furthermore, a sufficient condition guaranteeing the global robust stability is established for the general class of Cohen-Grossberg neural networks with both multiple time varying delays and distributed delays in the case of parameter uncertainties.

Keywords: Cohen-Grossberg neural networks; distributed delays; GAS; global asymptotic stability; LMI; linear matrix inequality; multiple time varying delays; robust stability.

DOI: 10.1504/IJISTA.2009.022686

International Journal of Intelligent Systems Technologies and Applications, 2009 Vol.6 No.1/2, pp.22 - 49

Available online: 25 Jan 2009 *

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