Title :
Convergence of output signal based combination of two LMS adaptive filters
Author_Institution :
Dept. of Radio & Telecommun. Eng., Tallinn Univ. of Technol., Tallinn, Estonia
Abstract :
In this paper we investigate a combination of two LMS adaptive algorithms, one with large and another one with small step size. Large step size of one of the filters allows fast initial convergence and small step size of the other filter allows a small steady state mean square error. The outputs of the two filters are combined together via a combination parameter λ. We compute this parameter using the output signals of the individual filters. In the paper we derive formulae that predict the entire learning curve of the combination of two LMS adaptive filters. The theoretical findings are confirmed in our simulation study.
Keywords :
adaptive filters; convergence of numerical methods; errors; least mean squares methods; transient analysis; LMS adaptive algorithms; LMS adaptive filters; combination parameter; convergence speed; large step size algorithm; learning curve; least mean square algorithm; output signal based combination; small step size algorithm; steady state mean square error; transient analysis; Adaptation model; Convergence; Least squares approximation; Mean square error methods; Simulation; Steady-state; Transient analysis;
Conference_Titel :
Electrical and Electronics Engineers in Israel (IEEEI), 2010 IEEE 26th Convention of
Conference_Location :
Eliat
Print_ISBN :
978-1-4244-8681-6
DOI :
10.1109/EEEI.2010.5661910
