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

Upsampling01:22

Upsampling

204
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...
204
Bandpass Sampling01:17

Bandpass Sampling

162
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
162
Aliasing01:18

Aliasing

119
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
119
Downsampling01:20

Downsampling

130
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...
130
Sampling Plans01:23

Sampling Plans

167
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
167
Sampling Theorem01:15

Sampling Theorem

302
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
302

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

Tunlametinib (HL-085) plus vemurafenib in patients with advanced BRAF V600-mutant solid tumors: an open-label, single-arm, multicenter, phase I study.

Experimental hematology & oncology·2024
Same author

Evolutionary Diversity of Coxsackievirus A6 Causing Severe Hand, Foot, and Mouth Disease - China, 2012-2023.

China CDC weekly·2024
Same author

NmTHC: a hybrid error correction method based on a generative neural machine translation model with transfer learning.

BMC genomics·2024
Same author

Clinical, radiological, and laboratory features of HIV-negative pulmonary cryptococcosis with regard to serum lateral flow assay.

Frontiers in medicine·2024
Same author

A Novel Fault Diagnosis Method of High-Speed Train Based on Few-Shot Learning.

Entropy (Basel, Switzerland)·2024
Same author

The impact of childhood trauma on Adolescent Depressive Symptoms: the Chain Mediating role of borderline personality traits and self-control.

BMC psychiatry·2024

相关实验视频

Updated: Jun 6, 2025

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.2K

根据无线传感器网络的区域划分进行适应性压缩采样.

Wei Wang1, Xiaoping Jin2, Daying Quan2

  • 1College of Information Engineering The Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, China Jiliang University, Hangzhou, 310018, China. 2229401508@qq.com.

Scientific reports
|November 29, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了无线传感器网络 (WSN) 的适应性采样率方案,使用块压缩采样 (BCS). 该方法有效地根据图像区域的复杂性分配采样率,减少总体采样需求并提高重建质量.

更多相关视频

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

487
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

369

相关实验视频

Last Updated: Jun 6, 2025

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.2K
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

487
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

369

科学领域:

  • 无线传感器网络 (WSN) 是一种无线传感器网络.
  • 图像处理 图像处理
  • 信号压缩 压缩信号

背景情况:

  • 在资源有限的无线传感器网络 (WSN) 中,图像采集和传输面临着由于高数据速率和能源限制的挑战.
  • 区块压缩采样 (BCS) 通过降低采样速率提供了一个解决方案,但如果没有完整的信号信息,则难以分配适应速率.
  • 区块信号的稀疏性和平滑性是BCS的关键参数,影响采样率设置.

研究的目的:

  • 为无线传感器网络 (WSN) 提出一种新的自适应采样率分配方案,以应对图像采集和传输方面的挑战.
  • 为了在资源不足的多媒体传感应用中实现高效的压缩采样.
  • 提高信号重建质量,同时降低总体采样率.

主要方法:

  • 使用区域划分策略来区分复杂和光滑的图像区域.
  • 对于光滑区域,块被划分为剩余和平均块,剩余块的稀疏性估计.
  • 复杂的地区获得更高的基线采样率,根据区块特征适应分配额外率.

主要成果:

  • 拟议的方案有效地将适当的抽样率分配给单个图像块.
  • 实现了总抽样率的显著降低.
  • 同时观察到信号重建质量的大幅改善.

结论:

  • 开发的自适应采样率分配方案提高了WSN图像传感中的效率和性能.
  • 该方法成功地平衡了采样率的降低与高质量的信号重建.
  • 这种方法为资源有限的多媒体传感应用提供了可行的解决方案.