• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IFAC PapersOnLine >A sequential least squares algorithm for ARMAX dynamic network identification ?
【24h】

A sequential least squares algorithm for ARMAX dynamic network identification ?

机译：用于ARMAX动态网络识别的顺序最小二乘算法 ？

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Identification of dynamic networks in prediction error setting often requires the solution of a non-convex optimization problem, which can be difficult to solve especially for large-scale systems. Focusing on ARMAX models of dynamic networks, we instead employ a method based on a sequence of least-squares steps. For single-input single-output models, we show that the method is equivalent to the recently developed Weighted Null Space Fitting, and, drawing from the analysis of that method, we conjecture that the proposed method is both consistent as well as asymptotically efficient under suitable assumptions. Simulations indicate that the sequential least squares estimates can be of high quality even for short data sets.
机译：在预测误差设置中识别动态网络通常需要解决非凸优化问题，这对于大型系统尤其难以解决。着眼于动态网络的ARMAX模型，我们改为采用基于最小二乘法步骤序列的方法。对于单输入单输出模型，我们表明该方法等效于最近开发的加权零空间拟合，并且从对该方法的分析得出，我们推测该方法既一致又渐近有效。适当的假设。仿真表明，即使对于较短的数据集，顺序最小二乘估计也可以是高质量的。

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