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广义回归神经网络在非线性系统建模中的应用
Application of GRNN and Uniform Design to Nonlinear System Modeling
【摘要】 广义回归神经网络具有设计简单、收敛快等优势,因此在复杂非线性系统建模中得到了广泛应用;在简要介绍了广义回归神经网络的结构和算法的基础上,基于广义回归神经网络和均匀设计理论,提出了一种新的非线性系统稳健建模方法,并给出了仿真算例;仿真结果表明,用文中提出的方法建立非线性系统预测模型,具有预测结果稳定、模型稳健性好等优点。
【Abstract】 GRNN has such advantages as simple design and perfect convergence etc,so it has been widely used for complex nonlinear sys- tem modeling.After briefly introducing the structure and algorithm of GRNN,a new nonlinear system robust modeling method based on GRNN and uniform design is proposed.A numerical simulation example is given,and simulation results show that the proposed method can be applied to nonlinear system modeling successfully and has such advantages as stable prediction results and better robustness etc.
【关键词】 广义回归神经网络;
均匀设计;
非线性系统;
建模;
稳健性;
【Key words】 GRNN; uniform design; nonlinear system; modeling; robustness;
【Key words】 GRNN; uniform design; nonlinear system; modeling; robustness;
【基金】 国防行业重点预研基金(426010502-3);NSAF联合基金(10276005)。
- 【文献出处】 计算机测量与控制 ,Computer Measurement & Control , 编辑部邮箱 ,2007年09期
- 【分类号】TP183
- 【被引频次】51
- 【下载频次】813