The application of fuzzy set and neural network in system identification and classification

K. B. Goh, W. L. Chiang

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

Abstract

Outlines a new learning algorithm to deal with interval information for a feedforward neural network. From the concept of fuzzy sets and using the vertex method, a new backpropagation neural network, called virtual vertex backpropagation, VVBP, is presented. A dynamic tracing machine is introduced to overcome weight correction in the learning process. Two applications in simple system identification and pattern classification are presented to discuss the effectiveness of VVBP.

Original languageEnglish
Title of host publicationProceedings - 2nd International Symposium on Uncertainty Modeling and Analysis, ISUMA 1993
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages145-152
Number of pages8
ISBN (Electronic)0818638508, 9780818638503
DOIs
StatePublished - 1993
Event2nd International Symposium on Uncertainty Modeling and Analysis, ISUMA 1993 - College Park, United States
Duration: 25 Apr 199328 Apr 1993

Publication series

NameProceedings - 2nd International Symposium on Uncertainty Modeling and Analysis, ISUMA 1993

Conference

Conference2nd International Symposium on Uncertainty Modeling and Analysis, ISUMA 1993
Country/TerritoryUnited States
CityCollege Park
Period25/04/9328/04/93

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