The Parameters Estimation of the Mixed Model of Sianals with the Form Invariance Signs Under Autorgeressive Operator

易东云; 蒋正宇

您当前的位置：

首页 >

文章列表页 >

The Parameters Estimation of the Mixed Model of Sianals with the Form Invariance Signs Under Autorgeressive Operator

更新时间：2025-12-08

- The Parameters Estimation of the Mixed Model of Sianals with the Form Invariance Signs Under Autorgeressive Operator
- Acta Electronica Sinica Issue 7, (1997)
- 作者机构：
  
  1. 国防科技大学
  2. 湖南大学邵阳分校
  3. 国防科技大学湖南大学邵阳分校
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911
- Published：1997
- 稿件说明：
移动端阅览
[1]易东云,蒋正宇.自回归算于作用下不变类信号组合模型的参数估计[J].电子学报,1997(07):12-15.

易东云, 蒋正宇. The Parameters Estimation of the Mixed Model of Sianals with the Form Invariance Signs Under Autorgeressive Operator[J]. Acta Electronica Sinica, 1997, (7).
[1]易东云,蒋正宇.自回归算于作用下不变类信号组合模型的参数估计[J].电子学报,1997(07):12-15. DOI：

易东云, 蒋正宇. The Parameters Estimation of the Mixed Model of Sianals with the Form Invariance Signs Under Autorgeressive Operator[J]. Acta Electronica Sinica, 1997, (7). DOI：

摘要

本文针对带有ＡＲ噪声的且具有在自回归算子作用下保持形式不变的一大类信号，采用分离参数和两步最小二乘的方法直接给出自回归参数的估计，井由此得到真实信号参数的估计．该方法克服了以往方法中ＡＲ噪声未知的难点，算法为线性求解，简便、实用、运算速度快、求解精度高．

Abstract

In this paper

a class of signals with AR noise which are invariable under autoregressive operator are discussed. By use of parameter separating and two-steps least-squares estimate methods

we directly give parameters estimation in AR noise and so in true signs. The method overcomes the difficulty that AR noise is unknown. The algorithm is linear and has fast computing speed and higher accuracy.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

基于粒子群优化算法的Logistic模型参数估计

An Algorithm for Recognition and Parameters Estimation of OFDM in Alpha Stable Distribution Noise

Related Author

JIN Yan

JI Hong-bing

LUO Jun-hui

徐星

李元香

吴昱

金彤

ZHANG Jun-lin

Related Institution

School of Electronic Engineering, Xidian University

武汉大学软件工程国家重点实验室

School of Information Systems Engineering, PLA Information Engineering University

State Key Laboratory of Integrated Service Networks, Xidian University

School of Information Systems Engineering PLA Information Engineering University Zhengzhou Henan China

⁰