Title :
A noise constrained VS-LMS algorithm
Author :
Bilcu, Radu Ciprian ; Kuosmanen, Pauli ; Rus, Corneliu
Author_Institution :
Signal Process. Lab., Tampere Univ. of Technol., Finland
Abstract :
In many practical applications from the field of system identification, an accurate estimation of the noise variance is available. Therefore, we introduce a new variable step-size LMS algorithm that exploits this information in order to provide a faster convergence speed. The new algorithm is called NCVS-LMS. The convergence speed and steady-state error performance of the new algorithm are analyzed. The experimental results show that the new algorithm outperforms the LMS and other variable step algorithms
Keywords :
adaptive filters; convergence of numerical methods; filtering theory; identification; least mean squares methods; noise; NCVS-LMS; adaptive filtering; adaptive systems; convergence speed; experimental results; noise constrained VS-LMS algorithm; noise variance estimation; steady-state error performance; system identification; variable step algorithms; variable step-size LMS algorithm; Adaptive filters; Convergence; Digital signal processing; Laboratories; Least squares approximation; Performance analysis; Signal processing; Signal processing algorithms; Steady-state; System identification;
Conference_Titel :
EUROCOMM 2000. Information Systems for Enhanced Public Safety and Security. IEEE/AFCEA
Conference_Location :
Munich
Print_ISBN :
0-7803-6323-X
DOI :
10.1109/EURCOM.2000.874766
