Title :
A class of modified variable step-size NLMS algorithms for system identification
Author :
Zhao, Shengkui ; Man, Zhihong ; Khoo, Suiyang
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
Abstract :
This paper proposes a class of modified variable step-size normalized least mean square (VS NLMS) algorithms. The class of schemes are obtained from estimating the optimum step-size of NLMS that minimizes the mean square deviation (MSD). During the estimation, we consider the properties of the additive noise and the input excitation together. The developed class of VS NLMS algorithms have simple forms and give improved tradeoff of fast convergence rate and low misadjustment in system identification.
Keywords :
adaptive filters; least mean squares methods; noise; adaptive filtering; additive noise; input excitation; mean square deviation; modified variable step-size normalized least mean square algorithms; optimum step-size estimation; system identification; Adaptive filters; Additive noise; Australia; Computer industry; Convergence; Filtering algorithms; Least squares approximation; Paper technology; Stability; System identification; Least mean square; system identification; variable step-size;
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
DOI :
10.1109/ICIEA.2009.5138756
