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

Probability Distributions01:32

Probability Distributions

7.3K
 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
7.3K
Probability Histograms01:17

Probability Histograms

11.8K
A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
11.8K
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

2.6K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
2.6K
Poisson Probability Distribution01:09

Poisson Probability Distribution

8.3K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
8.3K
Binomial Probability Distribution01:15

Binomial Probability Distribution

11.2K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
11.2K
Probability Laws01:49

Probability Laws

41.1K
Overview
41.1K

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

On nonlinear amplification: improved quantum limits for photon counting.

Optics express·2019
Same author

Permutationally invariant part of a density matrix and nonseparability of N-qubit states.

Physical review letters·2014
Same author

Measuring Trρn on single copies of ρ using random measurements.

Physical review letters·2012
Same author

Detecting the drift of quantum sources: not the de Finetti theorem.

Physical review letters·2011
Same author

Entanglement verification with finite data.

Physical review letters·2011
Same author

Entanglement of spin waves among four quantum memories.

Nature·2010
Same journal

Erratum: Low-dimensional model for adaptive networks of spiking neurons [Phys. Rev. E 111, 014422 (2025)].

Physical review. E·2026
Same journal

Disentangling the effects of many-body forces on depletion interactions.

Physical review. E·2026
Same journal

Charge transport and mode transition in dual-energy electron beam diodes.

Physical review. E·2026
Same journal

Optimization of multisite reactions in complex compartmentalized media.

Physical review. E·2026
Same journal

Origin of geometric cohesion in nonconvex granular materials: Interplay between interdigitation and rotational constraints enhancing frictional stability.

Physical review. E·2026
Same journal

Interaction of walkers with a standing Faraday wave.

Physical review. E·2026
查看所有相关文章

相关实验视频

Updated: Jul 26, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.2K

汇集概率分布和部分信息分解.

S J van Enk1

  • 1Department of Physics, University of Oregon, Eugene, Oregon 97403, USA.

Physical review. E
|June 17, 2023
PubMed
概括
此摘要是机器生成的。

本研究通过定义协同,冗余和独特的信息来探索部分信息分解 (PID). 它提出了一种新的聚合方法,以解决对多个变量定义这些信息指标的模糊性.

更多相关视频

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.6K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.3K

相关实验视频

Last Updated: Jul 26, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.2K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.6K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.3K

科学领域:

  • 信息理论 信息理论
  • 多变量统计学 多变量统计学
  • 计算神经科学是一种神经科学.

背景情况:

  • 部分信息分解 (PID) 旨在在多个变量之间量化协同作用,冗余和独特的信息.
  • 现有的PID框架缺乏对这些信息措施的准确定义的共识,导致模两可.

研究的目的:

  • 为了说明PID中定义协同,冗余和独特信息的模两可的来源.
  • 提出基于概率分布聚合的PID新框架.

主要方法:

  • 将信息定义为概率分布之间的平均不确定性降低.
  • 将协同效应信息解释为整体与其部分之和之间的差异,使用聚合的概率分布.
  • 开发一个基于最佳概率分布聚合的格子结构.

主要成果:

  • 拟议的聚合方法为PID引入了新的格子结构,与基于冗余的格子不同.
  • 这个框架将概率分布与格子节点联系在一起,而不仅仅是平均.
  • 概率分布之间的重叠成为描述协同和独特信息的关键量.

结论:

  • 该研究提供了一种方法,通过利用概率分布聚合来解决部分信息分解中的模两可.
  • 拟议的聚合方法提供了一种原则的方式来定义协同和独特的信息,提高对多变量信息的理解.
  • 这项工作为分析多变量系统中复杂信息关系提供了灵活的框架.