Title :
Solution to the Weight Extraction Problem in Fast QR-Decomposition RLS Algorithms
Author :
Shoaib, Mobien ; Werner, Stefan ; Apolinário, José A., Jr. ; Laakso, Timo I.
Author_Institution :
Signal Process. Lab., Helsinki Univ. of Technol., Espoo
Abstract :
Fast QR decomposition RLS (FQRD-RLS) algorithms are well known for their good numerical properties and low computational complexity. However the FQRD-RLS algorithms do not provide access to the filter weights, and so far their use has been limited to problems seeking an estimate of the output error signal. In this paper we present a novel technique to obtain the filter weights of the FQRD-RLS algorithm at any time instant. As a consequence, we extend the range of applications to include problems where explicit knowledge of the filter weights is required. The proposed weight extraction technique is tested in a system identification setup. The results verify our claim that the extracted coefficients of the FQRD-RLS algorithm are identical to those obtained by any RLS algorithm such as the inverse QRD-RLS algorithm
Keywords :
adaptive filters; computational complexity; feature extraction; filtering theory; least squares approximations; recursive estimation; computational complexity; fast QR-decomposition RLS algorithms; filter weights; recursive least squares; system identification setup; weight extraction problem; Adaptive filters; Computational complexity; Equations; Error correction; Filtering algorithms; Laboratories; Resonance light scattering; Robustness; Signal processing algorithms; System identification;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
Print_ISBN :
1-4244-0469-X
DOI :
10.1109/ICASSP.2006.1660718
