Jove
Visualize
联系我们

相关概念视频

Linear time-invariant Systems01:23

Linear time-invariant Systems

262
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...
262
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
106
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

251
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...
251
Classification of Systems-II01:31

Classification of Systems-II

146
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
146
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
State Space Representation01:27

State Space Representation

209
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
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

AutoKFL: Linux Kernel Fault Localization via ReAct-Based Multi-Agent Framework with Dynamic Crash Reproduction.

Sensors (Basel, Switzerland)·2026
Same author

FP-ZOO: Fast Patch-Based Zeroth Order Optimization for Black-Box Adversarial Attacks on Vision Models.

Sensors (Basel, Switzerland)·2025
Same author

Artificial Intelligence-Based Anomaly Detection Technology over Encrypted Traffic: A Systematic Literature Review.

Sensors (Basel, Switzerland)·2024
Same author

Generating ICS Anomaly Data Reflecting Cyber-Attack Based on Systematic Sampling and Linear Regression.

Sensors (Basel, Switzerland)·2023
Same author

Leveraging Computational Intelligence Techniques for Defensive Deception: A Review, Recent Advances, Open Problems and Future Directions.

Sensors (Basel, Switzerland)·2022
Same author

An Efficient Dynamic Solution for the Detection and Prevention of Black Hole Attack in VANETs.

Sensors (Basel, Switzerland)·2022
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

相关实验视频

Updated: Jul 5, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.8K

在工业控制系统中,合成时间序列生成采用了带有注意力机制的变频循环自编码器.

Seungho Jeon1, Jung Taek Seo2

  • 1Department of Computer Engineering (Smart Security), Gachon University, Seongnam-si 1342, Republic of Korea.

Sensors (Basel, Switzerland)
|January 11, 2024
PubMed
概括

合成数据生成解决了工业控制系统 (ICS) 中的数据稀缺问题. 一个基于注意力的可变循环自编码器 (AVRAE) 有效地生成时间序列ICS数据,捕获时间依赖性,用于改进的AI模型.

关键词:
注意力机制注意力机制工业控制系统 工业控制系统合成数据的生成.时间序列数据数据时间序列数据变异性循环自编码器的自编码器.

更多相关视频

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K
SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.2K

相关实验视频

Last Updated: Jul 5, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.8K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K
SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.2K

科学领域:

  • 数据科学数据科学数据科学
  • 人工智能的人工智能
  • 网络物理系统 网络物理系统

背景情况:

  • 数据稀缺是开发强大的人工智能和数据科学模型的主要挑战.
  • 由于安全和隐私问题,工业控制系统 (ICS) 的数据通常无法获得,这限制了模型开发.
  • ICS数据集具有复杂的时间序列特征,具有短期和长期的时间依赖.

研究的目的:

  • 为工业控制系统 (ICS) 提出一种用于生成合成时间序列数据的新方法.
  • 通过利用合成数据生成,应对ICS环境中数据稀缺的挑战.
  • 为了有效地捕捉和建模ICS数据中固有的时间依赖关系.

主要方法:

  • 开发了一种基于注意力的变异性循环自编码器 (AVRAE) 模型.
  • 将变化推理的证据下限扩展到时间序列数据.
  • 在基于循环神经网络的自编码器中集成了一个注意力机制,以学习时间依赖.

主要成果:

  • 拟议的AVRAE模型成功生成了视觉和统计学上可信的合成ICS时间序列数据.
  • 对HAI ICS数据集的全面评估表明了AVRAE的有效性.
  • 注意力机制使短期和长期时间依赖的有效学习成为可能.

结论:

  • AVRAE提供了一种可行的解决方案,用于生成高质量的合成ICS数据,减轻稀缺问题.
  • 该方法增强了为ICS开发更准确的AI和数据科学模型的潜力.
  • 这项工作为关键基础设施领域的时间序列数据生成提供了一种新的方法.