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

Maximum Power Transfer01:16

Maximum Power Transfer

239
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
239
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

97
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
97
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

85
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
85
Network Function of a Circuit01:25

Network Function of a Circuit

271
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
271
Frequency-Domain Interpretation of PD Control01:24

Frequency-Domain Interpretation of PD Control

98
Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
The proportional control gain, combined with the...
98
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

180
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the...
180

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

Elevating Tetracycline Removal in Microbial Electrochemical Systems: Insights from Extracellular Electron Transfer and Rational Aggregation of Microbial Consortia.

ACS applied materials & interfaces·2026
Same author

Biological applications and future perspectives of bioactive compounds as pig feed additives.

Animal nutrition (Zhongguo xu mu shou yi xue hui)·2026
Same author

Aging of mesenchymal stem cells in bone aging: Mechanisms, impact, and therapeutic perspectives.

Ageing research reviews·2026
Same author

Wear Status Monitoring Method of Milling Cutter Under Variable Working Conditions Based on Transfer Learning and Lightweight SqueezeNet Model.

Sensors (Basel, Switzerland)·2026
Same author

Plasma miRNA signature for the diagnosis of pulmonary tuberculosis in symptomatic patients.

Thorax·2026
Same author

Large language models for acute coronary syndrome triage at first medical contact in emergency departments.

NPJ digital medicine·2026

相关实验视频

Updated: Jun 14, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

503

通过LWDDPG算法在EH-CIoT网络中的反干扰资源分配方法.

Fushuai Li1, Jiawang Bao1, Jun Wang1

  • 1College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China.

Sensors (Basel, Switzerland)
|August 29, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种对能源采集认知物联网网络的反干扰方法,以最大限度地提高长期吞吐量. 拟议的线性加权深度决定性政策梯度算法有效地分配资源,并在干扰攻击下收集能量.

关键词:
在EH-CIoT网络网络上.防止堵塞的方法.线性加权的深度决定性政策梯度.资源分配的资源分配.

更多相关视频

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.8K
Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.0K

相关实验视频

Last Updated: Jun 14, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

503
Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.8K
Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.0K

科学领域:

  • 无线通信网络 无线通信网络
  • 网络安全 网络安全
  • 资源管理 资源管理

背景情况:

  • 收集能源的认知物联网 (EH-CIoT) 网络由于干扰攻击而面临吞吐量退化.
  • 现有的方法缺乏适应未知的干扰器策略和主要用户活动的适应性.

研究的目的:

  • 为EH-CIoT网络开发一种防止干扰的资源分配方法.
  • 为了最大限度地提高长期吞吐量 (LTT),尽管阻塞和能源限制.

主要方法:

  • 在没有事先知识的情况下,将问题建模为马尔科夫决策过程 (MDP).
  • 设计一个包含吞吐量和能量奖励的二维奖励函数.
  • 建议使用线性加权深度决定性政策梯度 (LWDDPG) 算法来分配资源.

主要成果:

  • LWDDPG算法有效地将通道,功率和工作模式分配给二级用户 (SU).
  • 该方法使SUS能够在未干扰的频道上发射,并收集射频能量.
  • 模拟结果验证了拟议的方法对传统方法的优越性,可以抵御多重干扰攻击.

结论:

  • 开发的反干扰策略增强了EH-CIoT网络中的LTT.
  • LWDDPG算法为动态和对抗性环境中的资源分配提供了有效的解决方案.
  • 该方法平衡了吞吐量最大化与能源采集,以实现可持续的网络运行.