DocumentCode
1245725
Title
Efficient computational schemes for the orthogonal least squares algorithm
Author
Chng, E.S. ; Chen, S. ; Mulgrew, B.
Author_Institution
Dept. of Electr. Eng., Edinburgh Univ., UK
Volume
43
Issue
1
fYear
1995
fDate
1/1/1995 12:00:00 AM
Firstpage
373
Lastpage
376
Abstract
The orthogonal least squares (OLS) algorithm is an efficient implementation of the forward selection method for subset model selection. The ability to find good subset parameters with only a linearly increasing computational requirement makes this method attractive for practical implementations. We examine the computational complexity of the algorithm and present a preprocessing method for reducing the computational requirement
Keywords
computational complexity; least squares approximations; parameter estimation; prediction theory; signal processing; computational complexity; computational requirement reduction; forward selection method; nonlinear predictors; orthogonal least squares algorithm; preprocessing method; subset model selection; subset parameters; Computational complexity; Degradation; Integrated circuit modeling; Least squares methods; Linear regression; Predictive models; Signal processing algorithms; Vectors;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.365331
Filename
365331
Link To Document