Stochastic gradient algorithm for a dual-rate Box-Jenkins model based on auxiliary model and FIR model

摘要

Based on the work in Ding and Ding (2008), we develop a modified stochastic gradient (SG) parameter estimation algorithm for a dual-rate box-Jenkins model by using an auxiliary model. We simplify the complex dual-rate box-Jenkins model to two finite impulse response (FIR) models, present an auxiliary model to estimate the missing outputs and the unknown noise variables, and compute all the unknown parameters of the system with colored noises. Simulation results indicate that the proposed method is effective.