.png){kind=icon}
返回
Constrained quadratic errors-in-variables fitting
.png){kind=icon}
PRE
AI
DOI：10.1007/s00371-013-0885-2.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We propose an estimation method to fit conics and quadrics to data in the context of errors-in-variables where the fit is subject to constraints. The proposed algorithm is based on algebraic distance minimization and consists of solving a few generalized eigenvalue (or singular value) problems and is not iterative. Nonetheless, the algorithm produces accurate estimates, close to those obtained with maximum likelihood, while the constraints are also guaranteed to be satisfied. Important special cases, fitting ellipses, hyperbolas, parabolas, and ellipsoids to noisy data are discussed.
Keyword:
Parameter estimation
Direct methods
Fitting with constraints
Eigenvalue problem
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:
2.9
论文数:
4.7K
被引数:
6.5K
机构
引用论文
MicroRNA-100 promotes the autophagy of hepatocellular carcinoma cells by inhibiting the expression of mTOR and IGF-1R.png)
Oncotarget
OAAI
OncotargetIF0
OAAI分享收藏
分享收藏
查看更多内容