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| APPROXIMATION MULTIDIMENSION FUCTION WITH FUNCTIONAL NETWORK | |
| 作者姓名： | Li Weibin Liu Fang Jiao Licheng Zhang Shuling Li Zongling |
| 作者单位： | [1]Institute of Graphics and Image Processing, Xianyang Normal University, Xianyang 712000, China [2]National Key Laboratory for Radar Signal Processing, Xidian University, Xi＇an 710071, China [3]Insititute of Intelligent Information Processing, Xidian University, Xi＇an 710071, China |
| 基金项目： | Partly supported by the National Natura Science Foundation of China（No.60133010）, the Natura Science Foundation of Education Department of Shaanxi Province （No.05JK312）, and the Natura Science Foundation of Xianyang Normal University（No.04XSYK101 ） |
| 摘 要： | The functional network was introduced by E.Catillo, which extended the neural network. Not only can it solve the problems solved, but also it can formulate the ones that cannot be solved by traditional network. This paper applies functional network to approximate the multidimension function under the ridgelet theory. The method performs more stable and faster than the traditional neural network. The numerical examples demonstrate the performance. |
| 关 键 词： | 泛函网络 神经网络 神经元 逼近值 时频系统 |
| 收稿时间： | 2003-02-25 |
| 修稿时间： | 2004-03-08 |
Approximation multidimension fuction with functional network |
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| Li Weibin Liu Fang Jiao Licheng Zhang Shuling Li Zongling.APPROXIMATION MULTIDIMENSION FUCTION WITH FUNCTIONAL NETWORK[J].Journal of Electronics,2006,23(1):81-84. | |
| Authors: | Weibin Li PhD Fang Liu Licheng Jiao Shuling Zhang Zongling Li |
| Affiliation: | 1. Institute of Graphics and Image Processing,Xianyang Normal University,Xianyang 712000,China;National Key Laboratory for Radar Signal Processing,Xidian University,Xi' an 710071,China;Insititute of Intelligent Information Processing,Xidian University,Xi' an 710071,China 2. National Key Laboratory for Radar Signal Processing,Xidian University,Xi' an 710071,China;Insititute of Intelligent Information Processing,Xidian University,Xi' an 710071,China 3. Institute of Graphics and Image Processing,Xianyang Normal University,Xianyang 712000,China |
| Abstract: | The functional network was introduced by E.Catillo, which extended the neural network. Not only can it solve the problems solved, but also it can formulate the ones that cannot be solved by traditional network This paper applies functional network to approximate the multidimension function under the ridgelet theory. The method performs more stable and faster than the traditional neural network. The numerical examples demonstrate the performance. |
| Keywords: | Functional network Ridgelet Approximation |
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