Title :
Efficient NLMS and RLS Algorithms for Perfect and Imperfect Periodic Sequences
Author_Institution :
Dept. of Math., Phys. & Inf., Univ. of Urbino Carlo Bo, Urbino, Italy
fDate :
4/1/2010 12:00:00 AM
Abstract :
The paper discusses computationally efficient NLMS and RLS algorithms for perfect and imperfect periodic excitation sequences. The most interesting aspect of these algorithms is that they are exact LMS and RLS algorithms suitable for identification and tracking of every linear system and they require a real-time computational effort of just a multiplication, an addition and a subtraction per sample time. Moreover, the algorithms have convergence and tracking properties that can be better than or comparable with the NLMS algorithm for white noise input. The transient and steady state behavior of the algorithms and their tracking properties are also studied in the paper.
Keywords :
adaptive filters; target tracking; white noise; NLMS algorithms; RLS algorithms; adaptive filters; imperfect periodic excitation sequences; perfect periodic excitation sequences; steady state analysis; white noise input; Adaptive filters; identification; steady-state analysis; tracking; transient analysis;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2009.2039821