By employing Friedrichs’ inequality and constructing new Lyapunov-Krasovskii functional, we have investigated the stabilization of delayed reaction-diffusion control systems with Markovian jump parameters and Robin boundary conditions. Different from existing traditional results, our easy-to-test control design on global exponential stabilization in the mean square is based also on diffusion coefficients and boundary conditions, which discloses the crucial role of the diffusion effect and boundary information in the stabilization of neural control systems. The model here includes many models as special cases and the global exponential stabilization has a wider adaptive range. An example and its simulations are demonstrated to verify the effectiveness of theoretical results.
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