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

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

81
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
81
Continuous -time Fourier Transform01:11

Continuous -time Fourier Transform

317
The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
317
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

91
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
91
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

243
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
243
Linear time-invariant Systems01:23

Linear time-invariant Systems

258
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
258
Basic Continuous Time Signals01:22

Basic Continuous Time Signals

211
Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...
211

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

Second Order Dynamics Featuring Tikhonov Regularization and Time Scaling.

Journal of optimization theory and applications·2024
Same author

A fast continuous time approach with time scaling for nonsmooth convex optimization.

Advances in continuous and discrete models·2022
查看所有相关文章

相关实验视频

Updated: Jul 3, 2025

Control of Cell Adhesion using Hydrogel Patterning Techniques for Applications in Traction Force Microscopy
12:26

Control of Cell Adhesion using Hydrogel Patterning Techniques for Applications in Traction Force Microscopy

Published on: January 29, 2022

5.7K

使用提霍诺夫规范化技术进行非光滑凸优化的快速连续时间方法.

Mikhail A Karapetyants1

  • 1Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria.

Computational optimization and applications
|February 15, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了一种使用二次动态和提霍诺夫规范化的新型优化方法. 这种方法确保了对凸函数的最小规范解决方案的快速趋同.

关键词:
减弱的惯性动力学减弱的惯性动力学黑森驱动的减压器莫罗的信封 莫罗的信封没有平滑的凸凸优化.靠近操作员的操作员强大的趋同趋同.提霍诺夫规范化的规范化

更多相关视频

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

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.2K
Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.6K

相关实验视频

Last Updated: Jul 3, 2025

Control of Cell Adhesion using Hydrogel Patterning Techniques for Applications in Traction Force Microscopy
12:26

Control of Cell Adhesion using Hydrogel Patterning Techniques for Applications in Traction Force Microscopy

Published on: January 29, 2022

5.7K
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.2K
Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.6K

科学领域:

  • 优化理论 优化理论
  • 凸的分析 凸的分析
  • 数字分析 数字分析

背景情况:

  • 经典的优化问题涉及最小化凸的,较低的半连续函数.
  • 现有的方法可能缺乏保证的收率或轨迹的强烈收.
  • 莫罗信封和蒂霍诺夫规范化是优化中的强大工具.

研究的目的:

  • 为最小化凸函数开发一个二次时间动态方法.
  • 将粘性和赫西安驱动的减压与提霍诺夫规范化相结合.
  • 为了实现函数值的快速收和强烈的收到最小规范解决方案.

主要方法:

  • 利用莫罗封面及其属性来实现不光滑的功能.
  • 将提霍诺夫的规范化扩展到一个不平滑的环境中.
  • 在时间动力学中分析二阶动力学,并结合缓机制.

主要成果:

  • 确保功能和莫罗值的快速融合.
  • 证明了系统轨迹的强烈趋同到最小标准解决方案.
  • 为特定的参数选择推导出精确的收率.

结论:

  • 拟议的动态系统有效地解决了凸的优化问题.
  • 该方法既提供了效率 (快速收),也提供了准确性 (最小规范解决方案).
  • 数字示例验证了理论发现和实际应用.