Improved Synthesis and Analysis Results on Synchronization of T-S Fuzzy Neural Network Systems

This paper studies the synchronization problem for nonlinear neural network systems (NNSs) via T-S fuzzy models. Under a convex optimization framework, an improved asymptotic stability condition is obtained to ensure the synchronization of the fuzzy drive NNS with the response NNS. By introducing several auxiliary matrix multipliers, increased freedom are involved and the conservativeness can be further reduced. Simulation studies are given to show the effectiveness of the proposed method.