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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ding, S.Q. Xiang, C. |
| Copyright Year | 2004 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore (Ding, S.Q.; Xiang, C.) |
| Abstract | A special additional input, which is the sum of the squares of the other inputs, is added to the standard multilayer perceptron, so that the multilayer perceptron works similarly as the radial basis function network with localized response. Specially, we will show a three-layered multilayer perceptron with exponential activation function and this kind of additional input is naturally a generalized radial basis function network which can by trained with the well developed training strategies of multilayer perceptrons. A comparative study is also conducted between multilayer perceptron, with additional inputs and radial basis function networks trained by various methods. |
| Starting Page | 69 |
| Ending Page | 74 |
| File Size | 1048669 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780386434 |
| DOI | 10.1109/ICCIS.2004.1460389 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-12-01 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Multilayer perceptrons Radial basis function networks Backpropagation Multi-layer neural network Neural networks Neurons Prototypes Feedforward neural networks |
| Content Type | Text |
| Resource Type | Article |
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