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

Band Theory02:35

Band Theory

15.1K
When two or more atoms come together to form a molecule, their atomic orbitals combine and molecular orbitals of distinct energies result. In a solid, there are a large number of atoms, and therefore a large number of atomic orbitals that may be combined into molecular orbitals. These groups of molecular orbitals are so closely placed together to form continuous regions of energies, known as the bands.
The energy difference between these bands is known as the band gap.
Conductor, Semiconductor,...
15.1K
Principle of Equivalence01:18

Principle of Equivalence

2.2K
According to Albert Einstein (1897-1955), free-falling and feeling weightless are intrinsically linked. If a person were in free-fall under gravity, for example, diving towards the Earth from an airplane, they would feel completely weightless. Similarly, a person descending in a lift may feel partially weightless. Broadly speaking, it is assumed that an object in a uniform gravitational field and an object undergoing constant acceleration in the absence of gravity are under the same...
2.2K
Even and Odd Signals01:17

Even and Odd Signals

823
An even signal, whether in continuous-time or discrete-time, is defined by its symmetry with its time-reversed version. Mathematically, this is represented as
823
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

392
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
392
Pole and System Stability01:24

Pole and System Stability

291
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
291
Bandpass Sampling01:17

Bandpass Sampling

176
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....
176

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

Probabilistic analysis of COVID-19 patients' individual length of stay in Swiss intensive care units.

PloS one·2021
Same author

Stable reliability diagrams for probabilistic classifiers.

Proceedings of the National Academy of Sciences of the United States of America·2021
Same journal

Comparing Two Categorical Gini Correlations with Applications to Classification Problems.

Statistical papers (Berlin, Germany)·2026
Same journal

Handling skewness and directional tails in model-based clustering.

Statistical papers (Berlin, Germany)·2025
Same journal

Maximum likelihood estimation under the Emax model: existence, geometry and efficiency.

Statistical papers (Berlin, Germany)·2025
Same journal

Local linear smoothing for regression surfaces on the simplex using Dirichlet kernels.

Statistical papers (Berlin, Germany)·2025
Same journal

Statistical Inferences for Missing Response Problems Based on Modified Empirical Likelihood.

Statistical papers (Berlin, Germany)·2024
Same journal

On some problems of Bayesian region construction with guaranteed coverages.

Statistical papers (Berlin, Germany)·2024
查看所有相关文章

相关实验视频

Updated: May 4, 2026

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores
09:46

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

Published on: August 19, 2013

13.8K

奥斯班德的识别功能原理

Timo Dimitriadis1,2, Tobias Fissler3,4, Johanna Ziegel5

  • 1Alfred Weber Institute of Economics, Heidelberg University, Bergheimer Str. 58, 69115 Heidelberg, Germany.

Statistical papers (Berlin, Germany)
|March 25, 2024
PubMed
概括
此摘要是机器生成的。

这项研究描述了识别功能,这些功能对于统计估计和预测验证至关重要. 我们为各种统计函数定义了这些函数,这些函数在真实值时的预期为零.

关键词:
校准 校准 校准 校准 校准 校准 校准标志性描述 标志性描述识别功能 识别功能时间点预测是指点预测.Z-估计值是指一个Z估计值.

更多相关视频

Quantification of Orofacial Phenotypes in Xenopus
09:26

Quantification of Orofacial Phenotypes in Xenopus

Published on: November 6, 2014

9.2K
Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

4.7K

相关实验视频

Last Updated: May 4, 2026

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores
09:46

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

Published on: August 19, 2013

13.8K
Quantification of Orofacial Phenotypes in Xenopus
09:26

Quantification of Orofacial Phenotypes in Xenopus

Published on: November 6, 2014

9.2K
Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

4.7K

科学领域:

  • 统计 统计 统计 统计
  • 计量经济学 计量经济学
  • 机器学习 机器学习

背景情况:

  • 在统计推断中,识别功能是基本的.
  • 它们对于验证预测和动态模型至关重要.
  • 现有的文献缺乏向量值函数的完整表征.

研究的目的:

  • 为了充分描述严格识别函数的类别.
  • 将识别函数的理解扩展到向量值的函数.
  • 为它们在统计建模中的应用提供一个严格的框架.

主要方法:

  • 数学推导和理论分析.
  • 在温和的规律条件下对属性的探索.
  • 识别函数空间的表征.

主要成果:

  • 提供了严格识别功能的完整描述.
  • 该理论被扩展到处理向量值的统计函数.
  • 函数的衍生类满足了关键的理论性质.

结论:

  • 该研究提供了对识别函数的全面理解.
  • 这项工作促进了统计估计和预测验证方面的进步.
  • 这些发现适用于复杂的,向量值的函数估计问题.