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

Inertia Tensor01:24

Inertia Tensor

502
The concept of the inertia tensor is employed to depict the mass distribution and rotational inertia of a solid or rigid object. This tensor is expressed through a three-by-three matrix. Each component within this matrix corresponds to varying moments of inertia about specific axes.
The diagonal components of the inertia tensor matrix represent the moments of inertia concerning the principal axes of the object. These primary axes are defined as the axes where the object experiences the least...
502
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

527
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...
527
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

13.9K
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...
13.9K
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

2.5K
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...
2.5K
Scalar and Vector Triple Products01:06

Scalar and Vector Triple Products

2.4K
Two vectors can be multiplied using a scalar product or a vector product. The resultant of a scalar product is scalar, while with vector products, the resultant is a vector. These rules of the scalar or vector product between two vectors can be applied to multiple vectors to obtain meaningful combinations. The scalar triple product is the dot product of a vector with the cross product of two vectors.
The scalar triple product is the dot product of a vector with the cross product of two vectors....
2.4K
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

260
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...
260

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

MoRE-Net: An Interpretable and Modality-robust Model for Brain Tumor Grading.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine·2026
Same author

Swelling Property and Metal Adsorption of Dialdehyde Crosslinked Poly Aspartate/Alginate Gel Beads.

Polymers·2026
Same author

Hydrophobic Modification of Alginate Nanofibrous Membrane by Group IV Elements Ion Crosslinking.

Polymers·2026
Same author

Mirror Descent and Exponentiated Gradient Algorithms Using Trace-Form Entropies.

Entropy (Basel, Switzerland)·2025
Same author

RaLo: Rank-aware low-rank adaptation for pre-trained foundation models.

Neural networks : the official journal of the International Neural Network Society·2025
Same author

Electroencephalogram-Based Sustained Attention Assessment Using Sparse Model for Feature Selection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Exploiting audio-visual modalities in videos: Object detection via multi-stage bilateral coupling network.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Reliability-aware modality completion with cross-modal distillation for federated learning with missing modalities.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

IGFD-Net: Illumination-guided frequency decoupling for polarization image fusion.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Multiple-Strategies dung beetle optimizer and its applications in engineering optimization and bankruptcy prediction.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Aggregating global-scale pixel-wise forgery cues within a graph.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Finite-Time intermittent control for secure synchronization of Neutral-Type stochastic delayed neural networks under aperiodic DoS attacks.

Neural networks : the official journal of the International Neural Network Society·2026
查看所有相关文章

相关实验视频

Updated: Jul 11, 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

28.5K

非参数张量环分解与可扩展的折旧推理.

Zerui Tao1, Toshihisa Tanaka1, Qibin Zhao1

  • 1Department of Electronic and Information Engineering, Tokyo University of Agriculture and Technology, 184-8588, Tokyo, Japan; RIKEN Center for Advanced Intelligence Project (AIP), 103-0027, Tokyo, Japan.

Neural networks : the official journal of the International Neural Network Society
|November 6, 2023
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的非参数张量分解 (TD) 方法,使用神经网络和摊销推理. 这种方法增强了复杂,多维数据的分析,克服了大型数据集传统张量分解技术的局限性.

关键词:
数据归算数据的归算方法斯过程是高斯过程.张量器完成完成的过程张量分解的张量分解变化的自动编码器.

更多相关视频

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

1.1K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

相关实验视频

Last Updated: Jul 11, 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

28.5K
Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

1.1K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

科学领域:

  • 机器学习 机器学习
  • 数据科学数据科学数据科学
  • 人工智能的人工智能

背景情况:

  • 多维数据分析在视频处理和时间序列分析等领域至关重要.
  • 传统的张量分解 (TD) 方法受到多线性和可扩展到大数据集的假设的限制.

研究的目的:

  • 开发一种非参数张量分解 (TD) 方法,克服传统方法的局限性.
  • 通过建模复杂的潜伏结构并使其适用于大规模数据集来增强TD的表达力.

主要方法:

  • 建议使用神经网络进行张量环分解的非线性延伸.
  • 在模型交叉样本相关性和物理结构之前,纳入了矩阵高斯过程 (GP).
  • 开发了一种类似于变量自编码器 (VAE) 的摊销推理网络,用于大规模数据集中的高效后置推理.

主要成果:

  • 拟议的方法有效地模拟了超越多线性复杂的潜在结构.
  • 摊销推断使得TD可以应用于具有大量样本的数据集.
  • 通过对Healing MNIST数据集和多变量时间序列数据的数据归算任务来证明优势.

结论:

  • 带有摊销推理的非参数式DT为分析复杂的多维数据提供了一种强大而可扩展的方法.
  • 这种方法通过捕捉隐藏的张量结构来增强TD的表达力,优于传统技术.