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
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

2.6K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.6K
Standard Entropy Change for a Reaction03:00

Standard Entropy Change for a Reaction

20.6K
Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
20.6K
Reversible and Irreversible Processes01:14

Reversible and Irreversible Processes

4.3K
The thermodynamic processes can be classified into reversible and irreversible processes. The processes that can be restored to their initial state are called reversible processes. It is only possible if the process is in quasi-static equilibrium, i.e., it takes place in infinitesimally small steps, and the system remains at equilibrium However, these are ideal processes and do not occur naturally. An ideal system undergoing a reversible process is always in thermodynamic equilibrium within...
4.3K
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
Applications of Normal Distribution01:22

Applications of Normal Distribution

5.2K
The normal distribution is a useful statistical tool. One of its practical applications is determining the door height after considering the normal distribution of heights of persons, such that many can pass through it easily without striking their heads. The normal distribution can also determine the probability of a person having a height less than a specific height.
The heights of 15 to 18-year-old males from Chile from 1984 to 1985 followed a normal distribution. The mean height is 172.36...
5.2K

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

Bounds on the Excess Minimum Risk via Generalized Information Divergence Measures.

Entropy (Basel, Switzerland)·2025
Same author

A Unifying Generator Loss Function for Generative Adversarial Networks.

Entropy (Basel, Switzerland)·2024
Same author

Lossless Transformations and Excess Risk Bounds in Statistical Inference.

Entropy (Basel, Switzerland)·2023
Same author

On Decoder Ties for the Binary Symmetric Channel with Arbitrarily Distributed Input.

Entropy (Basel, Switzerland)·2023
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jul 24, 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

8.1K

雷尼对常见分布和具有记忆力的过程的交叉度测量.

Ferenc Cole Thierrin1, Fady Alajaji1, Tamás Linder1

  • 1Department of Mathematics and Statistics, Queen's University, Kingston, ON K7L 3N6, Canada.

Entropy (Basel, Switzerland)
|July 8, 2023
PubMed
概括
此摘要是机器生成的。

这项研究为指数式家族分布推导了封闭形式的Rényi和自然Rényi微分交叉. 这些措施对于改善深度学习生成对抗网络和分析信息速率至关重要.

关键词:
斯过程是高斯过程.马尔科夫的来源 马尔科夫的来源进行多项信息化措施.交叉的交叉.差异化措施的差异化措施.指数级家庭分布的指数级家庭分布.

更多相关视频

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

33.8K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.4K

相关实验视频

Last Updated: Jul 24, 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

8.1K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

33.8K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.4K

科学领域:

  • 信息理论 信息理论
  • 机器学习 机器学习
  • 统计推理 统计推理

背景情况:

  • 香农交叉是信息理论的一个基本概念.
  • 雷尼类型的交叉为深度学习中的应用提供了概括.
  • 生成对抗网络 (GANs) 从改进的损失函数中受益.

研究的目的:

  • 为雷尼和自然雷尼微分交叉导出封闭形式的表达式.
  • 为了分析这些指标,在指数家族中分析常见的连续分布.
  • 为了总结高斯过程和马尔科夫源的交叉率.

主要方法:

  • 对差异交叉度测量的分析表达式的导数.
  • 对指数式家族分布的结果的表化.
  • 对于特定的随机过程的交叉率的总结.

主要成果:

  • 对于雷尼和自然雷尼差异交叉的封闭形式解决方案被介绍.
  • 为广泛的指数家族分布类提供了结果.
  • 对于静止高斯过程和有限字母马尔科夫源的交叉率进行了总结.

结论:

  • 由此产生的指标为深度学习应用提供了有价值的工具,特别是GANs.
  • 表格化结果有助于实际应用和不同分布的比较.
  • 该研究增强了对复杂系统中的信息理论速率的理解.