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

Navier–Stokes Equations01:28

Navier–Stokes Equations

370
For incompressible Newtonian fluids, where density remains constant, stresses show a linear relationship with the deformation rate, defined by normal and shear stresses. Normal stresses depend on the pressure exerted on the fluid and the rate of deformation in specific directions, which determines how fluid flows under varying pressures. Shear stresses, on the other hand, act tangentially across fluid layers. They explain how adjacent fluid layers slide relative to one another, connecting...
370
Region of Convergence of Laplace Tarnsform01:20

Region of Convergence of Laplace Tarnsform

464
The Region of Convergence (ROC) is a fundamental concept in signal processing and system analysis, particularly associated with the Laplace transform. The ROC represents an area in the complex plane where the Laplace transform of a given signal converges, determining the transform's applicability and utility.
Consider a decaying exponential signal that begins at a specific time. When deriving its Laplace transform, the time-domain variable is replaced with a complex variable. This...
464
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

81
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
81
Bernoulli's Equation: Problem Solving01:16

Bernoulli's Equation: Problem Solving

698
A Venturi meter is essential for measuring fluid flow rates in pipelines. It utilizes the relationship between fluid velocity and pressure described by Bernoulli's equation. When installed in a sewage system, the Venturi meter accurately determines the wastewater flow rate by measuring pressure differences.
The first step is to compute the cross-sectional areas of the pipe and the Venturi throat to analyze the pressure difference indicated by the pressure gauge. Next, the continuity...
698
Newtonian Fluid: Problem Solving01:18

Newtonian Fluid: Problem Solving

170
Newtonian fluids exhibit a constant viscosity, meaning their shear stress and shear strain rate are directly proportional. This property ensures a predictable and stable response to applied forces, maintaining a linear relationship between force and flow. Examples include water, air, and light oils, consistently demonstrating this proportional behavior regardless of external conditions.
A velocity gradient forms within the fluid when a Newtonian fluid is placed between two parallel plates, with...
170
Neural Circuits01:25

Neural Circuits

974
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
974

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

Catalytic and Gating Nanoreactors: Cu(I)/Cu(II)-MOF@HMS for Size-Selective DNA-Templated Click Ligation Chain Reaction and Detection of Nucleic Acids.

Analytical chemistry·2026
Same author

MARCH2 prevents doxorubicin-induced cardiomyopathy by stabilizing NR1H2 and promoting clearance of apoptotic cardiomyocytes.

Nature communications·2026
Same author

Fine-tuning AlphaFold with limited cryo-EM observations.

Communications chemistry·2026
Same author

Deep Learning With Data Privacy via Residual Perturbation.

IEEE transactions on pattern analysis and machine intelligence·2025
Same author

Nanosized hollow Cu(I)/Cu(II)-metal-organic frameworks for highly efficient catalysis in azide-alkyne cycloaddition and nucleic acid-templated ligation.

Journal of colloid and interface science·2025
Same author

Three detection modes with one electrode: A multifunctional electrochemical sensing platform for thrombin, p53 gene, and cholesterol detection.

Bioelectrochemistry (Amsterdam, Netherlands)·2025

相关实验视频

Updated: May 24, 2025

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.6K

传递-扩散方程:神经网络的理论认证框架

Tangjun Wang, Chenglong Bao, Zuoqiang Shi

    IEEE transactions on pattern analysis and machine intelligence
    |March 3, 2025
    PubMed
    概括

    本研究介绍了神经网络的部分微分方程 (PDE) 模型,揭示了一个对流-扩散方程,它统一了现有的网络结构,并激发了基于扩散的新型架构.

    科学领域:

    • 计算数学是指计算数学.
    • 机器学习理论机器学习理论
    • 人工智能的人工智能是人工智能.

    背景情况:

    • 神经网络表现出与网络结构固有的联系,将离散层与连续方程连接起来.
    • 现有的研究主要探讨普通微分方程 (ODE) 和输入信号的特征转换.

    研究的目的:

    • 为了研究神经网络的部分微分方程 (PDE) 模型.
    • 建立一个连接神经网络与PDE的理论框架,特别是对流-扩散方程.
    • 以PDE原则为灵感,开发一种新的神经网络架构.

    主要方法:

    • 将神经网络视为从分类器的最后一层基础模型上运行的函数.
    • 应用尺度空间理论来推导神经网络映射的对流-扩散方程.
    • 设计一个新的网络架构,采用基于衍生PDE模型的扩散机制.

    主要成果:

    • 理论证明神经网络映射可以通过特定假设的对流-扩散方程来制定.
    • 证明该框架包括各种现有的网络结构和培训技术.
    • 通过广泛的实验验证一种基于扩散的新型神经网络架构.

    结论:

    更多相关视频

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
    11:18

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

    Published on: March 2, 2015

    10.2K
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    8.9K

    相关实验视频

    Last Updated: May 24, 2025

    Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
    10:50

    Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

    Published on: June 21, 2022

    1.6K
    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
    11:18

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

    Published on: March 2, 2015

    10.2K
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    8.9K
    • 这项研究为理解神经网络提供了一个数学基础的PDE框架.
    • 卷积-扩散方程为网络行为和结构提供了新的见解.
    • 拟议的基于扩散的网络架构在基准和现实世界数据集上显示出有效性.