An estimation of second order autoregressive models using finite memory filter

被引：0

作者：

Kim, Pyung Soo ^{[1
,2
]}

Jang, Mun Suck ^{[1
]}

机构：

[1] Department of Electronic Engineering, Korea Polytechnic University, Siheung-si, Gyeonggi-do 429-793, Korea, Republic of

[2] Center for Embedded Computer Systems, University of California, Irvine, Irvine, CA 92697, United States

来源：

ICIC Express Letters | 2012年 / 6卷 / 11期

关键词：

Bandpass filters;

D O I：

暂无

中图分类号：

TN713 [滤波技术、滤波器];

学科分类号：

摘要：

This letter deals with an estimation of second order autoregressive model using a finite memory filter. The finite memory filter is developed under a weighted least square criterion using only the most recent finite observations on the window. The proposed estimation for second order autoregressive model is shown to have several inherent properties such as unbiasedness, deadbeat, robustness. Through the comparison with Kalman filtering based estimation via computer simulations, the proposed finite memory filtering based estimation is shown to be appropriate for fast estimation of second order autoregressive model that varies relatively quickly. © 2012 ISSN 1881-803X.

引用

页码：2769 / 2773