Robust adaptive control of Cohen-Grossberg neural networks with discontinuous activation functions
In this paper, robust adaptive control of Cohen-Grossberg neural networks with discontinuous activation functions is considered. Based on differential inclusion theory and matrix inequality technique, we originally propose the adaptive controller for neural networks with discontinuous activation functions. Our objective is to design the controller to ensure neural networks be globally asymptotically stable at its equilibrium point. The designed controller is accessible. Finally, a numerical example is given to verify the effectiveness and robustness of the proposed result.