首页> 外文期刊>IEEE Transactions on Information Theory >On estimation of a class of nonlinear systems by the kernel regression estimate
【24h】

On estimation of a class of nonlinear systems by the kernel regression estimate

机译:基于核回归估计的一类非线性系统的估计

获取原文
获取原文并翻译 | 示例

摘要

The estimation of a multiple-input single-output discrete Hammerstein system is studied. Such a system contains a nonlinear memoryless subsystem followed by a dynamic linear subsystem. The impulse response of the dynamic linear subsystem is obtained by the correlation method. The main results concern the estimation of the nonlinear memoryless subsystem. No conditions are imposed on the functional form of the nonlinear subsystem, and the nonlinearity is recovered using the kernel regression estimate. The distribution-free pointwise and global convergence of the estimate is demonstrated-that is, no conditions are imposed on the input distribution, and convergence is proven for virtually all nonlinearities. The rates of pointwise as well as global convergence are obtained for all input distributions and for Lipschitz type nonlinearities.
机译:研究了多输入单输出离散哈默斯坦系统的估计。这样的系统包含一个非线性无记忆子系统,然后是一个动态线性子系统。动态线性子系统的脉冲响应是通过相关方法获得的。主要结果涉及非线性无记忆子系统的估计。非线性子系统的功能形式没有施加任何条件,并且使用核回归估计来恢复非线性。证明了估计的无分布的逐点和全局收敛性,也就是说,没有条件施加在输入分布上,并且对几乎所有非线性都证明了收敛。对于所有输入分布和Lipschitz型非线性,都获得了逐点和全局收敛的速率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号