Study on pattern recognition model based on principal component analysis and radius basis function neural network

Author

Hu, Enyong ; Wang, Hui ; Wang, Jianhua ; Lu, Song ; Tian, Lei

Author_Institution

Dept. of Sizhan, Coll. of Xuzhou Air Force, Xuzhou, China

Volume

2

fYear

2011

fDate

10-12 June 2011

Firstpage

388

Lastpage

390

Abstract

A pattern recognition model was proposed. Firstly, the theories of principal component analysis and radius basis function neural network were introduced. By the method of principal component analysis, the principal components influencing the pattern recognition were extracted. Based on the analysed results, the model of pattern recognition based on principal component analysis and radius basis function neural network was established. Then it was applied to classify 20 wear particles. And the accuracy of recognition reached 91.3%. The result indicates that this model could get faster speed and higher accuracy, and is worthy of further study and wide use.

Keywords

pattern recognition; principal component analysis; radial basis function networks; pattern recognition model; principal component analysis; radius basis function neural network; wear particle classification; Accuracy; Artificial neural networks; Atmospheric modeling; Character recognition; Indexes; Principal component analysis; neural network; pattern recognition; principal component analysis; radius basis function;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-8727-1

Type

conf

DOI

10.1109/CSAE.2011.5952493

Filename

5952493