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

Reducing Line Loss01:18

Reducing Line Loss

159
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
159
Lossy Lines and Overvoltages01:22

Lossy Lines and Overvoltages

95
Transmission-line series resistance and shunt conductance cause three primary effects: attenuation, distortion, and power losses.
Attenuation
When constant series resistance and shunt conductance are present, voltage and current equations are modified. The propagation constant indicates that voltage and current waves consist of both forward and backward traveling components. These waves attenuate as they propagate, with the attenuation factor related to the resistance and conductance. In a...
95
Downsampling01:20

Downsampling

169
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
169
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

7.4K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.4K
Upsampling01:22

Upsampling

246
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
246
Lossless Lines01:23

Lossless Lines

133
In electrical engineering, a lossless transmission line is characterized by a purely imaginary propagation constant and a resistive characteristic impedance. The ABCD parameters, which describe the relationship between the input and output voltages and currents, indicate an equivalent π circuit with an imaginary series impedance and a shunt admittance. This results in a transmission line that, when the product of the phase constant (beta) and the length of the line is less than pi,...
133

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

QARV++: An Improved Hierarchical VAE for Learned Image Compression.

IEEE transactions on circuits and systems for video technology : a publication of the Circuits and Systems Society·2026
Same author

Physically Informed 3D Food Reconstruction: Methods and Results.

IEEE journal of biomedical and health informatics·2026
Same author

LncRNA HOTAIR promotes LPS-induced inflammatory responses by activating the NF-κB pathway.

Experimental biology and medicine (Maywood, N.J.)·2026
Same author

User Preferences for an Image-Assisted Dietary Recall: Qualitative Study Comparing 3 Dietary Assessment Methods.

JMIR human factors·2025
Same author

Long-Tailed Continual Learning For Visual Food Recognition.

IEEE transactions on multimedia·2025
Same author

Temporal Eating Patterns and Ultra-Processed Food Consumption Assessed from Mobile Food Records of Australian Adults.

Nutrients·2025
Same journal

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

TraGraph-GS: Trajectory Graph-based Gaussian Splatting for Arbitrary Large-Scale Scene Rendering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

SWIFT: A Small-World Interaction Framework for Flow-Aware Trajectory Prediction in Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

IEEE transactions on pattern analysis and machine intelligence·2026
查看所有相关文章

相关实验视频

Updated: Jul 14, 2025

Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline
09:27

Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline

Published on: January 30, 2019

7.1K

QARV:量子化意识的ResNet VAE用于损失的图像压缩.

Zhihao Duan, Ming Lu, Jack Ma

    IEEE transactions on pattern analysis and machine intelligence
    |October 9, 2023
    PubMed
    概括
    此摘要是机器生成的。

    这项研究引入了一种新的损耗图像压缩方法,即量化感知ResNet VAE (QARV),利用变量自动编码器. QARV提供高效的压缩,快速解码和优越的速率扭曲性能.

    更多相关视频

    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    9.2K
    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    439

    相关实验视频

    Last Updated: Jul 14, 2025

    Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline
    09:27

    Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline

    Published on: January 30, 2019

    7.1K
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    9.2K
    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    439

    科学领域:

    • 计算机视觉 计算机视觉
    • 信息理论 信息理论
    • 机器学习 机器学习

    背景情况:

    • 丢失的图像压缩对于许多应用程序至关重要.
    • 变量自编码器 (VAE) 为生成建模提供了强大的框架,并与压缩有联系.

    研究的目的:

    • 开发一个先进的损耗图像压缩方案.
    • 为了提高压缩效率,解码速度和速率扭曲性能.

    主要方法:

    • 开发了一个新的量化意识的ResNet VAE (QARV) 模型.
    • 整合了层次化的 VAE 架构,测试时间量化和量化意识培训.
    • 设计了一个神经网络,用于快速解码和适应性正常化,用于变速压缩.

    主要成果:

    • QARV展示了有效的可变速率压缩能力.
    • 实现了高速解码性能.
    • 在速率扭曲指标方面表现优于现有的基线方法.

    结论:

    • QARV在损耗图像压缩方面取得了重大进展.
    • 该方法提供了压缩效率,速度和质量的令人信服的平衡.