Radial basis function neural network learning with modified backpropagation algorithm
Radial Basis Function Neural Network (RBFNN) is a class of Artificial Neural Network (ANN) widely used in science and engineering for classification problems with Backpropagation (BP) algorithm. However, major disadvantages of BP are due to the relatively slow convergence rate and always being trapp...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/48593/1/UsmanMuhammadTukurMFC2014.pdf http://eprints.utm.my/id/eprint/48593/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:85206?queryType=vitalDismax&query=Radial+basis+function+neural+network+learning+with+modified+backpropagation+algorithm&public=true |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |
Internet
http://eprints.utm.my/id/eprint/48593/1/UsmanMuhammadTukurMFC2014.pdfhttp://eprints.utm.my/id/eprint/48593/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:85206?queryType=vitalDismax&query=Radial+basis+function+neural+network+learning+with+modified+backpropagation+algorithm&public=true