Accessibility navigation

A robust nonlinear identification algorithm using PRESS statistic and forward regression

Lists
Tools

Hong, X. ORCID: https://orcid.org/0000-0002-6832-2298, Sharkey, P. M. and Warwick, K. (2003) A robust nonlinear identification algorithm using PRESS statistic and forward regression. IEEE Transactions on Neural Networks, 14 (2). pp. 454-458. ISSN 1045-9227

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1109/tnn.2003.809422

Abstract/Summary

This letter introduces a new robust nonlinear identification algorithm using the Predicted REsidual Sums of Squares (PRESS) statistic and for-ward regression. The major contribution is to compute the PRESS statistic within a framework of a forward orthogonalization process and hence construct a model with a good generalization property. Based on the properties of the PRESS statistic the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:15287
Uncontrolled Keywords:cross validation, forward regreession, orthogonalization, radial basis, function (RBF) network, structure identification, ORTHOGONAL LEAST-SQUARES, CONSTRUCTION, DESIGN
Altmetric
Deposit Details

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation

See also