.png){kind=icon}
返回
An automatic frequency domain modal parameter estimation algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/S0022-460X(02)01461-X.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this article, a frequency-domain modal parameter estimation method is proposed. The algorithm automatically separates physical poles from mathematical ones. An important issue in the automatization of the algorithm is the inclusion of noise information to estimate the standard deviations of the poles. These standard deviations are used (together with other features) as the inputs of a fuzzy clustering algorithm. The clustering algorithm then classifies the poles into the mathematical and physical ones. The method requires no user interaction, and a parameter is available quantifying the success of the classification. (C) 2002 Elsevier Science Ltd. All rights reserved.
Keyword:
IDENTIFICATION
SYSTEMS
ORDER
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:
4.9
论文数:
1.7W
被引数:
4.8W
机构
暂无机构信息
引用论文
LPS-aggravated Ferroptosis via Disrupting Circadian Rhythm by Bmal1/AKT/p53 in Sepsis-Induced Myocardial Injury.png)
Inflammation
InflammationIF0
PREAI
分享收藏Airy Kernel Determinant Solutions to the KdV Equation and Integro-Differential Painlevé Equations
PREAI
分享收藏The Novel KLF4/BIG1 Regulates LPS-mediated Neuro-inflammation and Migration in BV2 Cells via PI3K/Akt/NF-kB Signaling PathwayNeuroscience
NeuroscienceIF0
PREAI
分享收藏Order estimation for linear time-invariant systems using frequency domain identification methods使用频域识别方法的线性时不变系统的阶数估计
PREAI
分享收藏分享收藏
查看更多内容