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

作　　者：Jing CHEN Rui-feng DING 

机构地区：[1]School of Science,Jiangnan University [2]School of Internet of Things Engineering,Jiangnan University

出　　处：《Journal of Zhejiang University-Science C(Computers and Electronics)》2014年第2期147-152,共6页浙江大学学报C辑（计算机与电子（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(No.60973043);the Natural Science Foundation of Jiangsu Province,China(No.BK20131109)

摘　　要：Based on the work in Ding and Ding(2008),we develop a modifed 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 fnite 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 efective.Based on the work in Ding and Ding （2008）, we develop a modifi ed 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 fi nite 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.

关 键 词：Parameter estimation Auxiliary model Dual-rate system Stochastic gradient Box-Jenkins model FIR model 

分 类 号：O211.6[理学—概率论与数理统计]