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A Novel Two-Stage Classical Gram-Schmidt Algorithm for Wavelet Network Construction
Journal article   Open access   Peer reviewed

A Novel Two-Stage Classical Gram-Schmidt Algorithm for Wavelet Network Construction

Long Zhang, Kang Li, Er-Wei Bai and Shu-Juan Wang
IFAC Proceedings Volumes, Vol.45(16), pp.644-649
07/2012
DOI: 10.3182/20120711-3-BE-2027.00357
url
https://doi.org/10.3182/20120711-3-BE-2027.00357View
Published (Version of record) Open Access

Abstract

This paper proposes a two-stage orthogonal least squares (OLS) algorithm based on the classical Gram-Schimdt (CGS) method for the construction of wavelet networks. The main objective is to improve the compactness of the wavelet networks model built by the orthogonal forward stepwise methods. The proposed two stage stepwise method selects model terms one by one from a candidate term pool to construct an initial model in the first stage, and then replaces some insignificant terms by reviewing their contributions to the cost function in the second stage, leading to a significantly improved compact model. The efficacy and effectiveness of the proposed technique is illustrated by a numerical example.
backward model refinement Classical Gram-Schmidt forward stepwise subset selection orthogonal least squares

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