Title :
Comparison of Two Modern Pattern Recognition Methods
Author_Institution :
Dept. of Machine Eng., Dalian Jiaotong Univ., Dalian
Abstract :
Two methods of pattern recognition are introduced in this paper: Unsupervised learning algorithm - fuzzy clustering method and supervised learning algorithm - neural network. The pattern recognition becomes failure pattern recognition if it is used in the fault diagnosis of the machine. Both merits and shortages of these two methods are discussed through a specific example in the mechanical faults diagnosis.
Keywords :
fuzzy set theory; neural nets; pattern recognition; unsupervised learning; fuzzy clustering method; mechanical faults diagnosis; neural network; pattern recognition; supervised learning algorithm; unsupervised learning algorithm; Clustering algorithms; Clustering methods; Fault diagnosis; Fuzzy neural networks; Intelligent networks; Learning systems; Neural networks; Pattern recognition; Signal processing algorithms; Unsupervised learning;
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing, 2008. IIHMSP '08 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-0-7695-3278-3
DOI :
10.1109/IIH-MSP.2008.29
