State estimator design for BAM neural networks with time-varying delays

This paper addressed the delay-dependent design problem for BAM neural networks with time-varying delays. By employing the integral inequality and constructing Lyapunov-Krasovskii functional, the delay-dependent linear matrix inequality (LMI) conditions are obtained to estimate the neuron states through available output measurements such that the dynamics of the estimation error is globally asymptotically stable. These criteria can be easily verified by utilizing the recently developed algorithms solving LMIs. A numerical example is provided to demonstrate the effectiveness of the proposed method.