Total least mean squares algorithm

Author

Feng, Da-Zheng ; Bao, Zheng ; Jiao, Li-Cheng

Author_Institution

Res. Inst. of Electron. Eng., Xidian Univ., Xi´´an, China

Volume

46

Issue

8

fYear

1998

fDate

8/1/1998 12:00:00 AM

Firstpage

2122

Lastpage

2130

Abstract

Widrow (1971) proposed the least mean squares (LMS) algorithm, which has been extensively applied in adaptive signal processing and adaptive control. The LMS algorithm is based on the minimum mean squares error. On the basis of the total least mean squares error or the minimum Raleigh quotient, we propose the total least mean squares (TLMS) algorithm. The paper gives the statistical analysis for this algorithm, studies the global asymptotic convergence of this algorithm by an equivalent energy function, and evaluates the performances of this algorithm via computer simulations

Keywords

adaptive control; adaptive signal processing; error analysis; least mean squares methods; numerical stability; statistical analysis; LMS algorithm; TLMS algorithm; adaptive control; adaptive signal processing; computer simulations; equivalent energy function; global asymptotic convergence; minimum Raleigh quotient; minimum mean squares error; performance evaluation; stability; statistical analysis; total least mean squares algorithm; total least mean squares error; Adaptive control; Adaptive signal processing; Computer simulation; Convergence; Least mean square algorithms; Least squares approximation; Mean square error methods; Performance evaluation; Signal processing algorithms; Statistical analysis;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.705421

Filename

705421