A Stable Least Square Algorithm Based on Predictors and Its Application to Fast Newton Transversal Filters

Youhua WANG  Kenji NAKAYAMA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E78-A   No.8   pp.999-1003
Publication Date: 1995/08/25
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section LETTER (Special Section on Digital Signal Processing)
adaptive filters,  RLS algorithm,  fast RLS algorithm,  fast Newton transversal filters,  stability,  

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In this letter, we introduce a predictor based least square (PLS) algorithm. By involving both order- and time-update recursions, the PLS algorithm is found to have a more stable performance compared with the stable version (Version II) of the RLS algorithm shown in Ref.[1]. Nevertheless, the computational requirement is about 50% of that of the RLS algorithm. As an application, the PLS algorithm can be applied to the fast Newton transversal filters (FNTF). The FNTF algorithms suffer from the numerical instability problem if the quantities used for extending the gain vector are computed by using the fast RLS algorithms. By combing the PLS and the FNTF algorithms, we obtain a much more stable performance and a simple algorithm formulation.