| 基于径向基神经网络的目标识别研究 |
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| 引用本文： | 王晓东,秦超英.基于径向基神经网络的目标识别研究[J].西南民族学院学报(自然科学版),2006,32(1):195-198. |
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| 作者姓名： | 王晓东 秦超英 |
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| 作者单位： | 西北工业大学应用数学系，西北工业大学应用数学系 西安710072，西安工程科技学院理学院，西安710048，西安710072 |
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| 摘 要： | 本文讨论了传统的径向基(RBF)神经网络聚类算法的基本原理,针对其选取初始中心矢量的不足,提出了一种新的选择初始中心矢量的方法,给出了新的学习算法,并将其应用于目标识别.仿真结果表明,新算法比传统的RBF算法具有更强的聚类能力,使目标识别更加准确.
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| 关 键 词： | 径向基神经网络 目标识别 样本密度 |
| 文章编号： | 1003-2843（2006）01-0195-04 |
| 收稿时间： | 2005-06-15 |
| 修稿时间： | 2005-06-15 |
Research on target recognition based on RBF neural network |
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| WANG Xiao-dong,QIN Chao-ying.Research on target recognition based on RBF neural network[J].Journal of Southwest Nationalities College(Natural Science Edition),2006,32(1):195-198. |
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| Authors: | WANG Xiao-dong QIN Chao-ying |
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| Abstract: | In this paper,the basic principle of clustering algorithm based on Radial Basis Function(RBF) neural network is discussed.Considering its deficiency of selecting initial center vectors,a new method is brought forward,and a new algorithm is given and applied to target recognition.Simulation results prove the new algorithm's cluster capacity is stronger than the traditional and makes the target recognition more accurate. |
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| Keywords: | radial basis function network target recognition sample density |
| 本文献已被 CNKI 维普 等数据库收录！ |
