A CONSTRUCTION METHOD OF PATTERN RECOGNITION RBF ANNS BASED ON A FUZZY AUTOMATIC CLUSTERING ALGORITHM

Purpose RBF ANNs are being applied more and more frequently, especially in pattern recognition. But it is quite difficult to determine the number of hidden-layer nodes and every hidden-layer node’s function. Based on a fuzzy automatic clustering algorithm, a construction method of pattern recognitio...

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Veröffentlicht in:Proceedings Of The 11Th Joint International Computer Conference S. 576 - 579
Hauptverfasser: ZHAO, Tieshan, LI, Zengzhi, ZHANG, Zhifen
Format: Buchkapitel
Sprache:Englisch
Veröffentlicht: WORLD SCIENTIFIC 01.10.2005
Schlagworte:
Knowledge Engineering
equation sets
number of hidden-layer nodes
fuzzy automatic clustering algorithm
pattern recognition RBF ANNs
construction method
hidden-layer nodes’ radial basis functions
example
ISBN:9812565329, 9789812565327, 9789814479134, 9812701532, 9814479136, 9789812701534
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Zusammenfassung:Purpose RBF ANNs are being applied more and more frequently, especially in pattern recognition. But it is quite difficult to determine the number of hidden-layer nodes and every hidden-layer node’s function. Based on a fuzzy automatic clustering algorithm, a construction method of pattern recognition RBF ANNs is presented in this paper. Technology and Methods First, the given swatches are clustered with the fuzzy automatic clustering algorithm. How many clusters there are, how many hidden-layer nodes are needed. Every cluster’ center is its correspondent radial basis function’s center. Every radial basis function’s width isn’t less than its correspondent cluster’ radius. Second, because only 1 swatch is recognized every time, there is only 1 input-layer node. Third, how many patterns the given swatches may have, how many output-layer nodes are needed. If all given swatches can only be normal or abnormal, 2 output-layer nodes are enough. Results and Conclusions The construction method is introduced in detail with an example, and a RBF ANN is constructed. Good pattern recognition RBF ANNs can be constructed step by step with the construction method presented in this paper.
ISBN:9812565329
9789812565327
9789814479134
9812701532
9814479136
9789812701534
DOI:10.1142/9789812701534_0130