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相关概念视频

Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

129
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
129
Types Of Transformers01:16

Types Of Transformers

943
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
943
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

85
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....
85
Energy Losses in Transformers01:21

Energy Losses in Transformers

819
In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
819
Transformers in Distribution System01:27

Transformers in Distribution System

98
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
98
Discrete Fourier Transform01:15

Discrete Fourier Transform

206
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
206

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相关实验视频

Updated: May 25, 2025

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
07:21

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

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HFFTrack:通过混合频特征进行变压器跟踪.

Sugang Ma1, Zhen Wan2, Licheng Zhang3

  • 1School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an 710121, China; School of Information Engineering, Chang'an University, Xi'an 710064, China.

Neural networks : the official journal of the International Neural Network Society
|February 25, 2025
PubMed
概括

这项研究引入了一种新的混合频率特征追踪器,通过融合多频率目标信息来改善对象追踪. 这种新方法通过结合CNN和变压器网络来提高追踪精度,以实现强大的特征提取.

关键词:
双分支编码器的编码器混合频率的特征是混合频率的特征.变压器变压器变压器视觉对象跟踪 视觉对象跟踪波段变换的波段变换是什么

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Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
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Magnetic Tweezers for the Measurement of Twist and Torque

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科学领域:

  • 计算机视觉 计算机视觉
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 基于变压器的追踪器利用全球建模,但与精确目标定位至关重要的高频特征作斗争.
  • 现有的方法往往缺乏有效提取和利用高频和低频目标信息的能力.

研究的目的:

  • 开发一个先进的对象跟踪算法,有效地融合多频特征以提高性能.
  • 为了解决变压器模型在捕获准确跟踪所必需的高频细节方面的局限性.

主要方法:

  • 一个结合卷积神经网络 (CNN) 和变压器的新型特征提取网络,以逐步学习多频目标特征.
  • 一个双分支编码器,旨在捕捉全球上下文和本地目标特征.
  • 一个多频特征融合网络,利用波波变换和卷积来整合高频和低频信息.

主要成果:

  • 拟议的追踪器在六个具有挑战性的基准数据集中表现出卓越的性能:LaSOT,TrackingNet,GOT-10k,TNL2K,UAV123和OTB100.
  • 实验结果验证了融合混合频率特征的有效性,以提高对象跟踪精度.

结论:

  • 混合频率特征融合方法显著提高了基于变压器的追踪器的性能.
  • 设计的网络有效地平衡高频和低频信息,从而实现强大而准确的对象跟踪.