Efficient adaptive minimum variance control for discrete stochastic linear plant under unknown noise density: a NN-approach

摘要

We propose the recursive procedure for neural network approximation of the optimal transformation function using indirect adaptive control algorithm. The convergence and asymptotic normality theorems formulated above represent a theoretical basis for implementation of the adaptive version of the asymptotically efficient algorithm for the problem considered.