| 反向传播网络与径向基网络函数逼近的仿真比较 |
| |
| 引用本文： | 魏国辉,孔英,李庆玲.反向传播网络与径向基网络函数逼近的仿真比较[J].济宁医学院学报,2011,34(3):203-204,207. |
| |
| 作者姓名： | 魏国辉 孔英 李庆玲 |
| |
| 作者单位： | 济宁医学院信息工程学院,山东,日照,276826 |
| |
| 基金项目： | 济宁医学院2010年科研立项项目 |
| |
| 摘 要： | 目的对反向传播网络与径向基网络的函数逼近进行仿真比较。方法依据反向传播算法与径向基算法,对某一特定函数进行仿真逼近。结果仿真实验表明：两者都有很好的逼近能力,径向基网络的逼近性更好。结论反向传播网络在函数逼近方面差的原因是激励函数的全局性、隐层结点数目的不确定性。
|
| 关 键 词： | 反向传播网络 径向基网络 函数逼近 仿真 |
A comparative study on BPNN and RBFNN in function approximation |
| |
| WEI Guo-Hui,KONG Ying,LI Qing-Ling.A comparative study on BPNN and RBFNN in function approximation[J].Jounal of Jinning Medical College,2011,34(3):203-204,207. |
| |
| Authors: | WEI Guo-Hui KONG Ying LI Qing-Ling |
| |
| Institution: | WEI Guo-Hui,KONG Ying,LI Qing-Ling(College of Information Engineering,Jining Medical University,Rizhao 276826,China) |
| |
| Abstract: | Objective To compare the BPNN with RBFNN in function approximation.Methods According to the BPNN and RBFNN algorithms a specific function was simulated.Results The simulation showed that RBFNN was done better than BPNN in function approximation.Conclusion Because of the inspirit function's globaling and the number of the Hidden Layer'node uncertainty the BPNN was not done well. |
| |
| Keywords: | BPNN RBFNN Function approximation Simultion |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
