Dynamical behaviors of Cohen-Grossberg neural networks with discontinuous activation functions

In this paper, we discuss dynamics of Cohen-Grossberg neural networks with discontinuous activations functions. We provide a relax set of sufficient conditions based on the concept of Lyapunov diagonally stability (LDS) for Cohen-Grossberg networks to be absolutely stable. Moreover, under certain conditions we prove that the system is exponentially stable globally or convergent globally in finite time. Convergence rate for global exponential convergence and convergence time for global convergence in finite time are also provided.

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