Title :
A fast approximate RLS algorithm
Author :
Chansarkar, M.M. ; Desai, U.B.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol., Bombay, India
Abstract :
Motivated by the real time applications of adaptive signal processing algorithms a new Approximate RLS algorithm is developed. It is shown that the computational complexity of this algorithm is comparable to that of the LMS algorithm. Convergence analysis for this algorithm is presented showing the unconditional convergence of the algorithm in the mean and the mean square sense for stationary data. It is shown that the rate of convergence of this algorithm is n/sup -1/. The convergence characteristics of this algorithm shows that the algorithm is much faster than the LMS algorithm but somewhat slower than the RLS algorithm. Modifications to this algorithm are suggested for use in nonstationary data environment. Simulation results for this algorithm are compared with those for the LMS and the RLS algorithms.<>
Keywords :
computational complexity; convergence of numerical methods; least squares approximations; recursive functions; signal processing; LMS algorithm; RLS algorithm; adaptive signal processing algorithms; approximate RLS algorithm; computational complexity; convergence analysis; convergence rate; nonstationary data environment; real time applications; simulation results; stationary data; Adaptive signal processing; Algorithm design and analysis; Approximation algorithms; Computational complexity; Convergence; Least squares approximation; Resonance light scattering; Scheduling algorithm; Signal processing algorithms; Transversal filters;
Conference_Titel :
TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on
Conference_Location :
Beijing, China
Print_ISBN :
0-7803-1233-3
DOI :
10.1109/TENCON.1993.328038
