Title :
A QR-based least mean squares algorithm for adaptive parameter estimation
Author :
Liu, Zheng-She ; Li, Jian
Author_Institution :
Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA
fDate :
3/1/1998 12:00:00 AM
Abstract :
The optimum nonlinearly modified least-mean-square (ONM-LMS) algorithm has been shown to perform better than both the LMS and the normalized LMS algorithms. This paper proposes a QR-LMS adaptive parameter estimation algorithm that can perform significantly better than ONM-LMS. The performances of QR-LMS, including its numerical stability, error propagation property, and tracking ability, are analyzed. These properties are also verified with numerical examples
Keywords :
adaptive estimation; error analysis; least mean squares methods; matrix decomposition; numerical stability; parameter estimation; QR decomposition; adaptive parameter estimation; error propagation; least mean squares algorithm; numerical stability; tracking; Algorithm design and analysis; Convergence; Equations; Error analysis; Filters; Least squares approximation; Numerical stability; Parameter estimation; Performance analysis; Signal processing algorithms;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
