| 基于小波和RBF神经网络的手写体数字识别 |
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| 引用本文： | 胡永东,叶青.基于小波和RBF神经网络的手写体数字识别[J].微处理机,2005,26(4):24-25,28. |
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| 作者姓名： | 胡永东 叶青 |
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| 作者单位： | 长沙理工大学计算机与通信工程学院,长沙,410076 |
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| 摘 要： | 针对传统的手写体数字识别技术的局限性，本文提出了基于小波和RBF神经网络的手写体数字识别方法，即利用小波较强的去噪功能以及RBF神经网络学习快速、容错性较好等优点来解决手写体数字识别的问题。实验表明，该方法的识别正确率较高。
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| 关 键 词： | 军写体数字 识别 小波 RBF神经网络 |
| 文章编号： | 1002-2279（2005）04-0024-02 |
| 收稿时间： | 2004-03-30 |
| 修稿时间： | 2004-03-30 |
Handwritten Number Recognition Based on Wavelet & RBF Neural Network |
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| Hu Yong-dong,YE Qing.Handwritten Number Recognition Based on Wavelet & RBF Neural Network[J].Microprocessors,2005,26(4):24-25,28. |
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| Authors: | Hu Yong-dong YE Qing |
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| Abstract: | To avoid the limitation of traditional handwritten number recognition methods,a new recognition method of handwritten numbers by using wavelet and RBF neural network is presented in this paper.This paper integrates wavelet's better de-nosing ability and RBF neural network's faster learning attribute to solve this problem. Experiment results show that this new method has better accuracy rate. |
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| Keywords: | Handwritten number Recognition Wavelet RBF neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
