基于IRBFNN和IRAN的非线性动态系统在线自适应建模

来源 :华东理工大学学报（自然科学版） | 被引量 : 0次 | 上传用户：xumingxingHUANG

【摘要】

：

将资源分配网络算法(RAN)与相似隐单元合并操作、冗余隐单元删除操作和基于滑动数据窗连接权值学习相结合,形成了改进的资源分配网络(IRAN)算法.IRAN算法用于非线性动态系统

【出处】

：

华东理工大学学报（自然科学版）

【发表日期】

：

2006年7期

【关键词】

：

非对称高斯函数 IRAN算法非线性动态系统在线自适应建模

【基金项目】

：

浙江省自然科学基金;浙江省留学回国人员科研启动基金;杭州电子科技大学科研启动基金

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将资源分配网络算法(RAN)与相似隐单元合并操作、冗余隐单元删除操作和基于滑动数据窗连接权值学习相结合,形成了改进的资源分配网络(IRAN)算法.IRAN算法用于非线性动态系统的在线建模,能有效地改善模型精度和泛化能力.将改进径向基函数(RBF)神经网络(IRBFNN)和IRAN结合可以用于不确定非线性动态系统自适应建模.仿真研究表明:所提出的建模方法在模型精简、泛化和自适应等方面均具有优良的性能.

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基于IRBFNN和IRAN的非线性动态系统在线自适应建模

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