Title :
Convergence analysis of LMS and NLMS adaptive algorithms
Author_Institution :
University of California, Davis, California
Abstract :
The main contribution of this paper is the unified treatment of convergence analysis for both LMS and NLMS adaptive algorithms. The following new results are obtained: (i) necessary and sufficient conditions of convergence, (ii) optimal adjustment gains and optimal convergence rates, (iii) interrelationship between LMS and NLMS gains, and (iv) non-stationary algorithm design.
Keywords :
Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Convergence; Covariance matrix; Equations; Least squares approximation; Random processes; Recursive estimation; Signal processing;
Conference_Titel :
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '83.
DOI :
10.1109/ICASSP.1983.1172047
