In this paper, the finite-time stability problem is considered for a class of stochastic Cohen-Grossberg neural networks (CGNNs) with Markovian jumping parameters and distributed time-varying delays. Based on Lyapunov-Krasovskii functional and stability analysis theory, a linear matrix inequality approach is developed to derive sufficient conditions for guaranteeing the stability of the concerned system. It is shown that the addressed stochastic CGNNs with Markovian jumping and distributed time varying delays are finite-time stable. An illustrative example is provided to show the effectiveness of the developed results.
机构:
Seoul Natl Univ Sci & Technol, Dept Automot Engn, Seoul 139743, South KoreaSeoul Natl Univ Sci & Technol, Dept Automot Engn, Seoul 139743, South Korea
机构:
Huaiyin Inst Technol, Fac Math & Phys, Huaian 223003, Jiangsu, Peoples R ChinaHuaiyin Inst Technol, Fac Math & Phys, Huaian 223003, Jiangsu, Peoples R China
机构:
Seoul Natl Univ Sci & Technol, Dept Automot Engn, Seoul 139743, South KoreaSeoul Natl Univ Sci & Technol, Dept Automot Engn, Seoul 139743, South Korea
机构:
Huaiyin Inst Technol, Fac Math & Phys, Huaian 223003, Jiangsu, Peoples R ChinaHuaiyin Inst Technol, Fac Math & Phys, Huaian 223003, Jiangsu, Peoples R China