Analysis and design concerning state estimator for BAM neural networks with time-varying delays of neutral type
Jia Liu, Yunxi Zhang, Kuansheng Zou, Ji-Gong Li · 2016
This paper deals with the analysis and design of the state estimator concerning BAM neural networks with time-varying delays of neutral type. Based on Lyapunov-Krasovskii theory and integral equality approach, the delay-dependent sufficient condition is obtained to ensure the closed-loop error system is globally asymptotically stable. Furthermore, the gain matrices of the estimator can be determined and the state estimator is designed completely. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.