標題: Adaptive AR modeling in white Gaussian noise
作者: Wu, WR
Chen, PC
交大名義發表
電信工程研究所
National Chiao Tung University
Institute of Communications Engineering
公開日期: 1-五月-1997
摘要: Autoregresssive (AR) modeling is widely used in signal processing, The coefficients of an AR model can be easily obtained with a least mean square (LMS) prediction error filter, However, it is known that this filter gives a biased solution when the input signal is corrupted by white Gaussian noise, Treichler suggested the gamma-LMS algorithm to remedy this problem and proved that the mean weight vector can converge to the Wiener solution. In this paper, we develop a new algorithm that extends works of Vijayan et al, for adaptive AR modeling in the presence of white Gaussian noise, By theoretical analysis, we show that the performance of the new algorithm is superior to the gamma-LMS filter, Simulations are also provided to support our theoretical results.
URI: http://dx.doi.org/10.1109/78.575693
http://hdl.handle.net/11536/549
ISSN: 1053-587X
DOI: 10.1109/78.575693
期刊: IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume: 45
Issue: 5
起始頁: 1184
結束頁: 1192
顯示於類別:期刊論文


文件中的檔案:

  1. A1997WW84200008.pdf