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相关概念视频

Feedback control systems01:26

Feedback control systems

319
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
319
Design Example01:23

Design Example

332
The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
332
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

101
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
101
Mason's Rule01:20

Mason's Rule

354
Mason's rule is a powerful tool in control systems and signal processing. It simplifies the calculation of transfer functions from signal-flow graphs. This method leverages various elements, including loop gains, forward-path gains, and non-touching loops, to determine the transfer function efficiently.
Loop gain is determined by identifying and tracing a path from a node back to itself. This involves computing the product of branch gains along the loop. Each loop's gain is crucial for...
354
Control Systems01:10

Control Systems

1.2K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
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Active Filters01:25

Active Filters

837
Active filters are electronic circuits that use operational amplifiers (op-amps), resistors, and capacitors to filter out unwanted frequency components from a signal. A first-order low-pass active filter is designed to pass signals with a frequency lower than a certain cutoff frequency and attenuate frequencies higher than that cutoff frequency. The transfer function for a first-order low-pass active filter is:
837

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相关实验视频

Updated: Jul 12, 2025

High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition
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High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition

Published on: June 27, 2025

23

使用基于模糊规则的逻辑控制的数字过技术.

Xiao-Xia Yin1, Sillas Hadjiloucas2

  • 1Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou 510006, China.

Journal of imaging
|October 27, 2023
PubMed
概括
此摘要是机器生成的。

模糊逻辑控制有效地消除了数字图像中的冲动噪声,保留了细节和边缘. 这种方法提供了快速的计算和优异的噪声抑制,即使在复杂的图像中,混杂的噪声类型.

关键词:
彩色图像的序列图像的序列.模糊的过器 模糊的过器图像处理是图像处理的过程.多通道过的多通道过神经模糊网络的神经模糊网络

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科学领域:

  • 图像处理 图像处理
  • 人工智能的人工智能
  • 控制系统 控制系统

背景情况:

  • 冲动噪声会显著降低数字图像质量.
  • 传统的消除噪声方法经常与边缘保护和复杂的噪声模式作斗争.

研究的目的:

  • 探索模糊逻辑控制概念,以有效消除数字图像中的冲动噪声.
  • 在图像过过程中增强边缘和细节保存.
  • 介绍和比较各种基于模糊规则的过技术.

主要方法:

  • 基于模糊规则的逻辑控制用于噪声过.
  • 在RGB图像中使用矢量定向过器进行模糊推断.
  • 模糊的蜂自动机与摩尔社区建筑.
  • 模糊的深度学习组合分类器 (CNN,RNN,LSTM,GRU) 与模糊的Min-Max (FMM).
  • 模糊的非局部平均波器方法.

主要成果:

  • 模糊逻辑过器展示了高质量的边缘保护.
  • 有效的空间噪声抑制,特别是在复杂的图像中.
  • 强大的消除混合添加剂和冲动噪声的噪声.
  • 讨论的算法的快速计算实现.

结论:

  • 模糊逻辑控制为先进的数字图像消除噪音提供了一个强大的框架.
  • 本文所介绍的基于模糊规则的方法在图像质量和噪音抑制方面明显优于传统技术.
  • 深度学习组合与模糊逻辑相结合,在复杂的噪音场景中显示出有希望的结果.