The residual based interactive stochastic gradient algorithms for controlled moving average models

摘要

This paper derives a residual based interactive stochastic gradient (ISG) parameter estimation algorithm for controlled moving average (CMA) models and studied the performance of the residual based ISG algorithm under weaker conditions on statistical properties of the noise. Compared with the residual based extended stochastic gradient algorithm for identifying CMA models, the proposed ISG algorithm can give highly accurate parameter estimates by the simulation example.