Novel Robust Exponential Stability of Markovian Jumping Impulsive Delayed Neural Networks of Neutral-Type with Stochastic Perturbation

作者：Fang, Yang^*; Li, Kelin; Yan, Yunqi

来源：Mathematical Problems in Engineering, 2016, 2016: 1492908.

DOI：10.1155/2016/1492908

• TIME-VARYING DELAYS
• TO-STATE STABILITY
• ADAPTIVE SYNCHRONIZATION
• DYNAMICAL NETWORKS
• DISCRETE
• PARAMETERS
• STABILIZATION
• INTERVAL

The robust exponential stability problem for a class of uncertain impulsive stochastic neural networks of neutral-type with Markovian parameters and mixed time-varying delays is investigated. By constructing a proper exponential-type Lyapunov-Krasovskii functional and employing Jensen integral inequality, free-weight matrix method, some novel delay-dependent stability criteria that ensure the robust exponential stability inmean square of the trivial solution of the considered networks are established in the form of linear matrix inequalities (LMIs). The proposed results do not require the derivatives of discrete and distributed time-varying delays to be 0 or smaller than 1. Moreover, the main contribution of the proposed approach compared with related methods lies in the use of three types of impulses. Finally, two numerical examples are worked out to verify the effectiveness and less conservativeness of our theoretical results over existing literature.

• 出版日期2016
• 单位四川轻化工大学