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相关概念视频

Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

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Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
101
Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

181
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
181
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

85
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,...
85
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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Phase Contrast and Differential Interference Contrast Microscopy01:26

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Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
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Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

104
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...
104

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相关实验视频

Updated: Jul 13, 2025

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
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PSNet:一个基于深度学习模型的单击数字相位转移算法.

Zhaoshuai Qi1,2, Xiaojun Liu1,2, Jingqi Pang1,2

  • 1College of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China.

Sensors (Basel, Switzerland)
|October 14, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了PSNet,这是一种用于数字相位转换 (PS) 的深度学习算法. 通过考虑边缘模式之间的时间依赖,PSNet提高了相位检索准确度,超过了现有的方法.

关键词:
3D重建重建的3D重建深度学习是一种深度学习.边缘投影 边缘投影 边缘投影阶段转移转移的阶段转移相对阶段检索相对阶段检索

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相关实验视频

Last Updated: Jul 13, 2025

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08:39

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科学领域:

  • 光学计量学 在光学计量学
  • 计算成像技术的成像
  • 人工智能的人工智能

背景情况:

  • 传统的相位转移 (PS) 算法需要多个边缘模式,从而限制了效率.
  • 数字PS算法从一个生成多个模式,提高效率.
  • 深度学习模型对复杂的表面具有先进的阶段检索,但往往忽视时间依赖.

研究的目的:

  • 提出PSNet,一种基于深度学习的新数字相位转移算法.
  • 通过整合全球时间信息来提高相位检索的准确性.
  • 解决现有的深度学习PS方法中忽视框架间依赖性的局限性.

主要方法:

  • 开发了一个深度学习模型,PSNet,用于数字化阶段转换.
  • 构建了一个损失函数,将局部和全球时间信息从边缘模式集成在一起.
  • 专注于学习相邻生成模式之间的框架间依赖性.

主要成果:

  • 在生成相位转移模式方面,PSNet表现出更高的准确性.
  • 在相关的相位检索过程中观察到更高的准确性.
  • 模拟和现实世界的实验都验证了算法的性能.

结论:

  • 拟议的PSNet算法有效地利用时间信息进行准确的相位检索.
  • 在数字化阶段转换中,PSNet比最先进的方法提供了显著的改进.
  • 局部和全球时间损失的整合提高了复杂表面相位检索的稳定性.