Decomposition based iterative estimation algorithm forautoregressive moving average models

摘要：

This paper discusses an iterative least squares algorithm for identifying the parameters of autoregressive moving average models using the matrix decomposition technique. The basic idea is to use the block matrix inversion lemma to avoid repeatedly computing the inverse of the involved data matrix at each iteration. The simulation results show that the proposed algorithm works well.

关键词： Parameter estimation Least squares Iterative method ARMA model

作者: Huiyi Hu Ruifeng Ding

作者单位: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan Univ School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 1932-1937

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）