Title :
Partial updating RLS algorithm
Author_Institution :
Sch. of Electron. & Inf. Eng., Dalian Univ. of Technol., China
fDate :
31 Aug.-4 Sept. 2004
Abstract :
In this paper, a new computationally efficient algorithm for recursive least-squares (RLS) algorithm called reduced order RLS, it is also called as partial updating RLS (PU-RLS), algorithm is introduced. The basic idea of UP-RLS algorithm is that a high order filter function is decomposed into two low order simple functions, and then update the sub filter coefficients partially which result in less computation. This kind of adaptive algorithm shows much more enhanced computational efficiency compared to the earlier works such as split RLS algorithm but with better performance than split RLS algorithm based on simulation results.
Keywords :
adaptive filters; least squares approximations; recursive estimation; high order filter function; partial updating RLS algorithm; recursive least-squares algorithm; reduced order RLS; Adaptive algorithm; Adaptive filters; Computational efficiency; Interference cancellation; Lattices; Output feedback; Paper technology; Resonance light scattering; Signal generators; Transversal filters;
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
DOI :
10.1109/ICOSP.2004.1452664