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Local Training for Radial Basis Function Networks: Towards Solving the Hidden Unit Problem

Holcomb, Tyler and Morari, Manfred (1991) Local Training for Radial Basis Function Networks: Towards Solving the Hidden Unit Problem. In: 1991 American Control Conference. IEEE , Piscataway, NJ, pp. 2331-2336. ISBN 0-87942-565-2. https://resolver.caltech.edu/CaltechAUTHORS:20170626-153041273

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Abstract

This work examines training methods for radial basis function networks (RBFNs). First, the theoretical and practical motivation for RBFNs is reviewed, as are two currently popular training methods. Next a new training method is developed using well known results from functional analysis. This method trains each kidden unit individually, and is thus called the local training method. The structure of the method allows analysis of individual hidden units; moreover a covariance-related quantity is defined that gives insight into how many hidden units to employ. Two examples illustrate the usefulness of the method. Lastly, an ad hoc method to further improve RBFN performance is demonstrated.


Item Type:Book Section
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http://ieeexplore.ieee.org/document/4791821/PublisherArticle
Additional Information:© 1991 IEEE. Tyler Holcomb is a recipient of a National Science Foundation Graduate Fellowship. This research was supported by the Caltech Consortium in Chemistry and Chemical Engineering. Founding members of the Consortium are E. I. du Pont de Nemours and Company, inc., Eastman Kodak Company, Minnesota Mining and Manufacturing Company, and Shell Oil Company Foundation.
Funders:
Funding AgencyGrant Number
NSF Graduate Research FellowshipUNSPECIFIED
Caltech Consortium in Chemistry and Chemical EngineeringUNSPECIFIED
Record Number:CaltechAUTHORS:20170626-153041273
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170626-153041273
Official Citation:T. Holcomb and M. Morari, "Local Training for Radial Basis Function Networks: Towards Solving the Hidden Unit Problem," 1991 American Control Conference, Boston, MA, USA, 1991, pp. 2331-2336.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:78579
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:27 Jun 2017 23:33
Last Modified:03 Oct 2019 18:09

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