Abstract: This paper addresses the intricate challenges in stabilizing nonlinear systems amidst event-triggering and switching dynamics, operating under a less stringent input-to-state stability (ISS) ...
Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...
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