Abstract: This paper presents the bias-policy iteration, a modified adaptive dynamic programming method, to achieve optimal control design of discrete-time nonlinear systems. Firstly, the formulation ...
Abstract: In this brief, we investigate the approximation theory (AT) of Bayesian recurrent neural network (BRNN) for stochastic time series forecasting (TSF) from a probabilistic standpoint. Due to ...
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