Stability Analysis for Stochastic Markovian JumpReaction‐Diffusion Neural Networks with Partially Known TransitionProbabilities and Mixed Time Delays
Weiyuan Zhang, Junmin Li, Shi Naizheng · Discrete Dynamics in Nature and Society · 2012
The stability problem is proposed for a new class of stochastic Markovian jump reaction‐diffusion neural networks with partial information on transition probability and mixed time delays. The new stability conditions are established in terms of linear matrix inequalities (LMIs). To reduce the conservatism of the stability conditions, an improved Lyapunov‐Krasovskii functional and free‐connection weighting matrices are introduced. The obtained results are dependent on delays and the measure of the space AND, therefore, have less conservativeness than delay‐independent and space‐independent ones. An example is given to show the effectiveness of the obtained results.