返回
Numerically robust transfer function modeling from noisy frequency domain data
DOI:10.1109/TAC.2005.858651.png)
摘要
En 中文
Using vector orthogonal polynomials as basis functions for the representation of the rational form of a linear time invariant system, in frequency domain identification problems, it is shown that the notorious numerical ill conditioning of these maximum likelihood problems can be overcome completely. For the identification of high-order (100/100) systems operating over a wide frequency band, or even in the situation of over- or undermodeling, condition numbers less than ten are reported for real measurements.
Keyword:
discrete rational approximation
frequency domain identification
maximum likelihood
vector orthogonal polynomials
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7
论文数:
1.3W
被引数:
6.7W
机构
暂无机构信息
引用论文
Frequency-domain system identification using non-parametric noise models estimated from a small number of data sets
AUTOMATICA
IF5.9
Randomized Double-Blind, Multicenter Study of Prostaglandin E1 in Patients with the Adult Respiratory Distress Syndrome
Chest
IF0
Clinical application and outcomes of sentinel node navigation surgery in patients with early gastric cancer
Oncotarget
IF0
Generating robust starting values for frequency-domain transfer function estimation生成用于频域传递函数估计的鲁棒初始值
AUTOMATICA
IF5.9
Comparison of PCSK9 Inhibitor Evolocumab vs Ezetimibe in Statin‐Intolerant Patients: Design of the Goal Achievement After Utilizing an Anti‐PCSK9 Antibody in Statin‐Intolerant Subjects 3 (GAUSS‐3) TrialPCSK9 抑制剂Evolocumab与依泽替米贝在他汀不耐受患者中的比较: 在他汀不耐受受试者3 ( 高斯 -3) 试验中使用抗 PCSK9 抗体后的目标实现设计

