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相关概念视频

Bandpass Sampling01:17

Bandpass Sampling

160
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....
160
Sampling Theorem01:15

Sampling Theorem

291
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.
291
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

199
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
199
Sampling Distribution01:12

Sampling Distribution

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Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
12.3K
Sampling Plans01:23

Sampling Plans

165
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...
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Random Sampling Method01:09

Random Sampling Method

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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...
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Sampling for Estimating Frankliniella Species Flower Thrips and Orius Species Predators in Field Experiments
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普森抽样对于非静止的盗问题

Han Qi1, Fei Guo1, Li Zhu1

  • 1School of Software Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

Entropy (Basel, Switzerland)
|January 24, 2025
PubMed
概括

我们介绍了两种新算法,即折扣的普森采样 (TS) 和滑窗TS,用于分析具有突然变化的非静止多武装强盗问题. 我们的方法提供了一个令人遗憾的结果,与这个具有挑战性的场景的现有下限相匹配.

科学领域:

  • 机器学习 机器学习
  • 人工智能的人工智能
  • 优化优化 优化优化

背景情况:

  • 非静止的多武器强盗 (MAB) 问题,其特点是改变奖励分布,越来越重要.
  • 环境突然变化,分布在未知的时间步骤中发生变化,这带来了独特的挑战.
  • 现有的普森采样 (TS) 方法缺乏对这些非静止环境中的无信息先验的遗憾分析.

研究的目的:

  • 开发和分析MAB问题与突然变化的奖励分布的算法.
  • 在这样的动态环境中,为基于TS的方法提供理论上的遗憾界限.
  • 与现有方法对比,评估拟议的算法的经验性能.

主要方法:

  • 提出了两种新的算法:折扣的普森采样 (TS) 和滑窗TS.
  • 专门为子高斯奖励分布设计的算法.
  • 通过分析非最佳手臂运动的频率,确定了预期后悔的上限.

主要成果:

  • 对于折扣的TS和滑窗TS,推导出O~(TBT) 的预期后悔上限,其中T是时间地平线,BT是断点的数量.
  • 证明了这个上限与 MAB 问题突然变化的下限密切匹配.
  • 经验评估显示,与其他非静止盗算法相比,其性能具有竞争力.
关键词:
普森采样采样 普森采样多重武装的强盗.非静止的非静止的

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相关实验视频

Last Updated: May 31, 2025

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结论:

  • 折扣式TS和滑窗TS为突然变化的MAB问题提供了有效的解决方案.
  • 理论上的遗憾界限为这些算法的性能提供了有价值的见解.
  • 提出的方法代表了处理动态强盗环境的重大进步.