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

Limits with Oscillating Discontinuities01:19

Limits with Oscillating Discontinuities

480
An oscillating discontinuity is a type of discontinuity in which a function’s values fluctuate infinitely often as the input approaches a particular point. Unlike jump discontinuities, where the function suddenly shifts between two values, or infinite discontinuities, where the function diverges without bound, an oscillating discontinuity arises from rapid back-and-forth variation. Because the function never stabilizes toward a single value, no finite limit exists at that point.One of the...
480
Limits on Trigonometric Functions01:25

Limits on Trigonometric Functions

77
Limits on Trigonometric FunctionsThe limits of trigonometric functions play a fundamental role in calculus, particularly in defining derivatives. One of the most important results is:which is important for differentiating trigonometric functions and is widely applied in mathematical analysis and physics.Geometric IntuitionA common approach to proving this result involves analyzing a sector of a unit circle with an angle subtended at the center. Since the arc length is numerically equal to the...
77
Limiting Reactant02:27

Limiting Reactant

70.3K
The relative amounts of reactants and products represented in a balanced chemical equation are often referred to as stoichiometric amounts. However, in reality, the reactants are not always present in the stoichiometric amounts indicated by the balanced equation.
70.3K
Moment of Inertia about an Arbitrary Axis01:20

Moment of Inertia about an Arbitrary Axis

650
The moment of inertia is typically associated with principal axes, but it can also be computed for any random axis. When an arbitrary axis is under consideration, the moment of inertia is determined by integrating the mass distribution of the object along that specific axis. It is crucial in applications like the design of machinery, where components rotate about various axes, and balance and stability are essential.
In this scenario, the perpendicular distance between the chosen arbitrary axis...
650
Angular Momentum about an Arbitrary Axis01:11

Angular Momentum about an Arbitrary Axis

471
Imagine a rigid body with a mass denoted as 'm', which has its center of mass at point G and is rotating around an inertial reference frame. The angular momentum at an arbitrary point P can be calculated by taking the cross product of the position vector and linear momentum vector for each individual mass element.
The velocity of a mass element comprises its translational velocity and the relative velocity instigated by the body's rotation. Substituting the velocity equation into...
471
The Phosphorus Cycle01:21

The Phosphorus Cycle

44.1K
Unlike carbon, water, and nitrogen, phosphorus is not present in the atmosphere as a gas. Instead, most phosphorus in the ecosystem exists as compounds, such as phosphate ions (PO43-), found in soil, water, sediment and rocks. Phosphorus is often a limiting nutrient (i.e., in short supply). Consequently, phosphorus is added to most agricultural fertilizers, which can cause environmental problems related to runoff in aquatic ecosystems.
44.1K

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

Dynamic mode decomposition for detecting oscillatory transient activity via sparsity and smoothness regularization.

Chaos (Woodbury, N.Y.)·2026
Same author

On the efficiency of pairwise Hamiltonian control to desynchronize the higher-order Kuramoto model.

Chaos (Woodbury, N.Y.)·2026
Same author

Optimal control for phase locking of synchronized oscillator populations via dynamical reduction techniques.

Chaos (Woodbury, N.Y.)·2025
Same author

Phase autoencoder for limit-cycle oscillators.

Chaos (Woodbury, N.Y.)·2024
Same author

Dynamic mode decomposition for Koopman spectral analysis of elementary cellular automata.

Chaos (Woodbury, N.Y.)·2024
Same author

Higher-order interactions induce anomalous transitions to synchrony.

Chaos (Woodbury, N.Y.)·2024

相关实验视频

Updated: Feb 10, 2026

Reconstitution of Cell-cycle Oscillations in Microemulsions of Cell-free Xenopus Egg Extracts
06:31

Reconstitution of Cell-cycle Oscillations in Microemulsions of Cell-free Xenopus Egg Extracts

Published on: September 27, 2018

8.6K

实现高阶库拉莫托动态的最佳交互函数与任意极限周期振荡器.

Norihisa Namura1, Riccardo Muolo1,2, Hiroya Nakao1,3

  • 1Department of Systems and Control Engineering, Institute of Science Tokyo, Tokyo, Japan.

Chaos (Woodbury, N.Y.)
|February 9, 2026
PubMed
概括

研究人员设计了最佳交互函数,以精确地从极限周期振荡器中推导出高阶库拉莫托模型. 这允许精确建模集体同步动态和控制在像FitzHugh-Nagumo振荡器这样的系统.

更多相关视频

A Microfluidics Approach for the Functional Investigation of Signaling Oscillations Governing Somitogenesis
08:06

A Microfluidics Approach for the Functional Investigation of Signaling Oscillations Governing Somitogenesis

Published on: March 19, 2021

3.2K
Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands
07:26

Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands

Published on: January 31, 2025

895

相关实验视频

Last Updated: Feb 10, 2026

Reconstitution of Cell-cycle Oscillations in Microemulsions of Cell-free Xenopus Egg Extracts
06:31

Reconstitution of Cell-cycle Oscillations in Microemulsions of Cell-free Xenopus Egg Extracts

Published on: September 27, 2018

8.6K
A Microfluidics Approach for the Functional Investigation of Signaling Oscillations Governing Somitogenesis
08:06

A Microfluidics Approach for the Functional Investigation of Signaling Oscillations Governing Somitogenesis

Published on: March 19, 2021

3.2K
Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands
07:26

Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands

Published on: January 31, 2025

895

科学领域:

  • 动态系统理论 动态系统理论
  • 非线性动力学是一种非线性动力学.
  • 计算神经科学是一种计算神经科学.

背景情况:

  • 库拉莫托模型是研究合振荡器同步的一个基本工具.
  • 标准的相减法方法并不总是为一般振荡器产生库拉莫托模型.
  • 现有的方法在准确捕捉复杂的同步行为方面存在局限性.

研究的目的:

  • 开发一种方法,准确地从任意极限周期振荡器中推导出高阶库拉莫托模型.
  • 为了实现集体同步现象的精确数学建模.
  • 为了证明复杂的振荡系统中集体动态的控制.

主要方法:

  • 最佳配对和更高阶交互函数的人工设计.
  • 阶段减小技术应用于工程振荡器相互作用.
  • 数字模拟使用FitzHugh-Nagumo振荡器进行验证.
  • 奥特-安东森减小用于控制分析.

主要成果:

  • 成功推导出任意光滑极限周期振荡器的高阶库拉莫托模型.
  • 通过对FitzHugh-Nagumo振荡器的模拟,验证了衍生模型的准确性.
  • 证明了集体相位同步的有效控制.

结论:

  • 开发的方法为各种振荡器的高阶库拉莫托建模提供了准确的框架.
  • 这种方法提高了复杂的同步动态的理解和控制.
  • 这些发现对模拟神经振荡和其他合系统有意义.