A hybrid projection based and Radial Basis Function architecture

Shimon Cohen*, Nathan Intrator

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A hybrid architecture that includes Radial Basis Functions (RBF) and projection based hidden units is introduced together with a simple gradient based training algorithm. Classification and regression results are demonstrated on various data sets and compared with several variants of RBF networks. In particular, best classification results are achieved on the vowel classification data [1].

Original languageEnglish
Title of host publicationMultiple Classifier Systems - First International Workshop, MCS 2000, Proceedings
EditorsJosef Kittler, Fabio Roli
PublisherSpringer Verlag
Pages147-156
Number of pages10
ISBN (Print)3540677046, 9783540677048
DOIs
StatePublished - 2000
Event1st International Workshop on Multiple Classifier Systems, MCS 2000 - Cagliari, Italy
Duration: 21 Jun 200023 Jun 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1857 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Workshop on Multiple Classifier Systems, MCS 2000
Country/TerritoryItaly
CityCagliari
Period21/06/0023/06/00

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