Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

13.8K
It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
13.8K
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

2.3K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
2.3K
Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

50
The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
50
Weighted Mean00:57

Weighted Mean

5.0K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
5.0K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

448
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
448
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

209
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
209

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Optimizing Exclusion Criteria for Clinical Trials of Persistent Lyme Disease Using Real-World Data.

Healthcare (Basel, Switzerland)·2025
Same author

Matrix Completion With Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling.

IEEE transactions on pattern analysis and machine intelligence·2023
Same journal

Human-AI Interaction in Interventional Radiology: A Narrative Review of Current Applications, Challenges, and Future Directions.

Journal of imaging·2026
Same journal

Coronary Artery Anomalies and Anatomical Variants: Cross-Sectional Diagnostic Imaging and Clinical Background.

Journal of imaging·2026
Same journal

YoLeTooth: A Unified Framework for Joint Tooth Segmentation and Periapical Lesion Detection in Panoramic Radiographs.

Journal of imaging·2026
Same journal

Radiomics-Guided Multi-Sequence Learning for Pathological Complete Response Prediction from Breast MRI with Missing Auxiliary Sequences.

Journal of imaging·2026
Same journal

Cutaneous Thermography in Arthropathies: Quantitative Imaging, Machine Learning, and Clinical Translation.

Journal of imaging·2026
Same journal

Two-Stage Dynamic Synergistic Segmentation Method for Myocardial Pathology.

Journal of imaging·2026
查看所有相关文章

相关实验视频

Updated: Jun 18, 2025

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.4K

基于HOSVD的加权张量完成算法

Zehan Chao1, Longxiu Huang1, Deanna Needell1

  • 1Department of Mathematics, University of California, Los Angeles, CA 90095, USA.

Journal of imaging
|July 31, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种高效的加权高阶单数值分解 (HOSVD) 算法,用于张量完成,有效地从不完整的数据中恢复低级张量. 该方法在模拟中证明了准确性和效率,推进了数据归算技术.

关键词:
在HOSVD的分解过程中,张量器的完成完成.权重张量器加权张量器

更多相关视频

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

7.6K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.4K

相关实验视频

Last Updated: Jun 18, 2025

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.4K
A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

7.6K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.4K

科学领域:

  • 数据科学数据科学数据科学
  • 应用数学 应用数学 应用数学
  • 数字分析 数字分析

背景情况:

  • 矩阵完成解决了低维结构矩阵中缺失的数据.
  • 张量完成将这些原理扩展到更高阶的张量,旨在根据低级假设计算缺失的条目.

研究的目的:

  • 开发一个高效的算法,用确定性和潜在的不统一的采样模式来完成张量.
  • 为拟议的张量完成方法推导出误差极限.

主要方法:

  • 提出了一种高效的加权高序单数值分解 (HOSVD) 算法.
  • 使用加权度量来计算噪音张量观测的衍生误差边界.

主要成果:

  • 权重的HOSVD算法证明了底层低级张量器的高效和准确的恢复.
  • 在特定条件下,为拟议的方法建立了错误极限.

结论:

  • 开发的加权HOSVD算法对于张量完成是有效的,即使是复杂的采样模式.
  • 数字模拟证实了算法在合成和真实数据集上的效率和准确性.