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

Sampling Methods: Overview01:06

Sampling Methods: Overview

302
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
302
Random Sampling Method01:09

Random Sampling Method

11.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
11.0K
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

211
Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
211
Stratified Sampling Method01:16

Stratified Sampling Method

11.9K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
11.9K
Sampling Plans01:23

Sampling Plans

180
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...
180
Systematic Sampling Method01:17

Systematic Sampling Method

10.2K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
10.2K

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

[Association between genetic polymorphism of tumor necrosis factor and chronic severe hepatitis B in patients].

Zhonghua yi xue za zhi·2007
Same author

In vivo translational inaccuracy in Escherichia coli: missense reporting using extremely low activity mutants of Vibrio harveyi luciferase.

Biochemistry·2007
Same author

[Construction of recombinant adenovirus vector expressing extracellular domain of TbetaR-II-RANTES fusion gene and its anti-tumor effects].

Zhonghua zhong liu za zhi [Chinese journal of oncology]·2007
Same author

[Characteristics, evolution and variation of M genes of human avian H5N1 strains in Guangdong].

Bing du xue bao = Chinese journal of virology·2007
Same author

Dynamic changes in microbial activity and community structure during biodegradation of petroleum compounds: a laboratory experiment.

Journal of environmental sciences (China)·2007
Same author

Differences in optical transport properties between human meridian and non-meridian.

The American journal of Chinese medicine·2007

相关实验视频

Updated: Jun 22, 2025

Author Spotlight: Innovative Device Development for Advancing Dendroecology and Wood Anatomy Research
07:05

Author Spotlight: Innovative Device Development for Advancing Dendroecology and Wood Anatomy Research

Published on: September 27, 2024

2.6K

一种新的快速代STAP方法,采用coprime采样结构.

Mingfu Li1,2, Hui Li1

  • 1School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China.

Sensors (Basel, Switzerland)
|June 27, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种快速代算法,用于使用截断的内核规范最小化进行 coprime 时空自适应处理 (STAP). 它通过创建虚拟杂乱共变矩阵,通过有限的训练数据来改善杂乱抑制.

关键词:
杂乱的协变矩阵的杂乱.副类型采样结构.时间空间适应性处理截断的核的规范是截断的.

更多相关视频

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.5K
An Unbiased Approach of Sampling TEM Sections in Neuroscience
10:56

An Unbiased Approach of Sampling TEM Sections in Neuroscience

Published on: April 13, 2019

7.2K

相关实验视频

Last Updated: Jun 22, 2025

Author Spotlight: Innovative Device Development for Advancing Dendroecology and Wood Anatomy Research
07:05

Author Spotlight: Innovative Device Development for Advancing Dendroecology and Wood Anatomy Research

Published on: September 27, 2024

2.6K
Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.5K
An Unbiased Approach of Sampling TEM Sections in Neuroscience
10:56

An Unbiased Approach of Sampling TEM Sections in Neuroscience

Published on: April 13, 2019

7.2K

科学领域:

  • 信号处理 信号处理
  • 雷达系统 雷达系统
  • 适应性过是一种自适应性过.

背景情况:

  • 与统一的线性数组相比,在时空自适应处理 (STAP) 中的coprime采样提供了增强的杂乱抑制和更低的硬件成本.
  • 在实际的STAP应用中,算法性能经常受到足够的训练样本的可用性限制.

研究的目的:

  • 为了解决培训样本短缺的局限性,在STAP.
  • 提出一种新的快速代算法,以提高STAP系统的性能.

主要方法:

  • 提出了一个快速代的coprime STAP算法,利用截断的内核规范最小化 (TKNM).
  • 建立了一个虚拟杂乱共变矩阵 (CCM),结合TKNM规范化以确保低等级.
  • 不凸的优化问题被转换为凸的问题,使用交替方向方法解决.

主要成果:

  • 拟议的基于TKNM的算法有效地处理有限的训练样本在STAP中.
  • 模拟实验证实了算法能够实现准确的杂乱抑制的能力.
  • 该方法在样本有限的条件下,与现有方法相比,显示出更高的性能.

结论:

  • 基于TKNM的快速代的coprime STAP算法提供了一种有效的解决方案,用于在有限的训练数据下抑制杂乱.
  • 已建立的虚拟CCM和凸优化方法提高了STAP系统的稳定性和准确性.
  • 这种方法为采用副首要采样结构的雷达系统提供了实际的进步.