Function learning using wavelet neural networks
DSpace at IIT Bombay
View Archive InfoField | Value | |
Title |
Function learning using wavelet neural networks
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Creator |
SHASHIDHARA, HL
LOHANI, SUMIT GADRE, VM |
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Subject |
function approximation
learning (artificial intelligence) neural nets signal processing wavelet transforms |
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Description |
A new architecture based on wavelets and neural networks is proposed and implemented for learning a class of functions. The performance of such networks is analyzed for function learning. These functions belong to a common class but possess minor variations. The scheme developed makes use of wavelet neural network. It is useful to have a small dimensional network that can approximate a wide class of functions. The network has two levels of freedom. By this the network not only selects the parameters of the basis wavelets but also provides a variation in the choice.
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Publisher |
IEEE
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Date |
2008-12-28T07:01:30Z
2011-11-28T05:16:04Z 2011-12-15T09:56:39Z 2008-12-28T07:01:30Z 2011-11-28T05:16:04Z 2011-12-15T09:56:39Z 2000 |
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Type |
Article
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Identifier |
Proceedings of IEEE International Conference on Industrial Technology (V 1) Goa, India, 19-22 January 2000, 335-340
0-7803-5812-0 http://hdl.handle.net/10054/507 http://dspace.library.iitb.ac.in/xmlui/handle/10054/507 |
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Language |
en
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