Modified stochastic gradient estimation algorithms for Box-Jenkins model based on auxiliary model

摘要

An auxiliary model based stochastic gradient estimation algorithm in proposed in this paper. The unknown variables in the information vector can be estimated by using the auxiliary model. Then the unknown parameters can be estimated by the stochastic gradient algorithm. Furthermore, in order to increase the convergence rate, a modified stochastic gradient algorithm is also proposed. The simulation results indicate that the proposed algorithm has good performances.