| 引用本文: | 汪小帆 ，王执铨， 宋文忠.径向基函数神经网络的新型混合递推学习算法[J].控制理论与应用,1998,15(2):272~276.[点击复制] |
| WANG Xiaofan and WANG Zhiquan，SONG Wenzhong.A New Hybrid Recursive Learning Algorithm for Radial Basis Function Neural Networks[J].Control Theory and Technology,1998,15(2):272~276.[点击复制] |
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| 径向基函数神经网络的新型混合递推学习算法 |
| A New Hybrid Recursive Learning Algorithm for Radial Basis Function Neural Networks |
| 摘要点击 1234 全文点击 503 投稿时间：1996-01-09 修订日期：1997-04-22 |
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| DOI编号 |
| 1998,15(2):272-276 |
| 中文关键词 径向基函数 神经网络 学习算法 系统辨识 |
| 英文关键词 radial basis function neual network learning algorithm system identification |
| 基金项目 |
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| 中文摘要 |
| 从径向基函数网络的硬件实现和实时应用的角度出发，给出了RBF网络的一种新型混合递推学习算法。该算法既具有良好的数值性质又易于并行实现，把RBF网络用于非线性系统在线辨识，仿真结果显示了本文方法的有效性。 |
| 英文摘要 |
| A new hybrid recursive learning algorithm for the radial basis function (RBF) neural network is proposed from the viewpoint of hardware implementations and on-line applications. The new algorithm has superior numerical properties and can be implemented in paralledl easily. Finally, recursive identification of nonlinear systems using RBF network is investigated. The simulations show that the algorithm is very effective. |