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

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

98
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
98
Classification of Systems-I01:26

Classification of Systems-I

169
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
169
Classification of Systems-II01:31

Classification of Systems-II

134
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
134
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

102
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
102
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

42
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
42
Associative Learning01:27

Associative Learning

298
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
298

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

OATP1A2 mRNA downregulation in canine hepatocellular carcinoma.

Veterinary record open·2026
Same author

Clinical Utility of Postoperative Day 1 Technetium-99m Mercaptoacetyltriglycine Scintigraphy for Early Assessment of Graft Function in Living Donor Kidney Transplant Recipients.

Journal of transplantation·2026
Same author

Structural insights into the interaction between the BH3-like domain of hepatitis B virus X protein and LC3B.

Biochimica et biophysica acta. Proteins and proteomics·2026
Same author

Computed Tomography Findings of Pulmonary Lymphoma in a Dog and Two Cats.

Veterinary medicine and science·2026
Same author

Conservative management of cranial cruciate ligament injury in an Asian small-clawed otter (Aonyx cinereus).

The Journal of veterinary medical science·2026
Same author

Post-bronchoscopy sputum culture improves detection of nontuberculous mycobacterial pulmonary disease: A retrospective Study.

Respiratory investigation·2026

相关实验视频

Updated: Jun 7, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

471

基于特征的学习系统的复杂性,适用于储库计算.

Hiroki Yasumoto1, Toshiyuki Tanaka1

  • 1Graduate School of Informatics, Kyoto University, 36-1, Yoshida Honmachi, Sakyo-ku, Kyoto, 606-8501, Japan.

Neural networks : the official journal of the International Neural Network Society
|November 16, 2024
PubMed
概括

本研究探讨了基于特征的学习系统的复杂度指标,包括储库系统. 它分析了诸如不调节性和线性等系统属性如何影响复杂性,提供了改进的理论见解.

科学领域:

  • 机器学习 机器学习
  • 计算复杂性理论 计算复杂性理论

背景情况:

  • 储计算系统是机器学习中使用的复杂模型.
  • 了解这些系统的复杂性对于它们的有效应用至关重要.
  • 现有的复杂度指标可能无法完全捕捉水库系统的细微差别.

研究的目的:

  • 介绍和分析一个基于特征的通用学习系统模型.
  • 在这个框架内,研究各种复杂度指标,包括增长函数,VC维度,伪维度和Rademacher复杂度.
  • 检查水库系统特征对这些复杂度指标的影响.

主要方法:

  • 开发一种基于特征的通用学习系统模型.
  • 应用和分析已确定的复杂度指标 (增长函数,VC维度,伪维度,Rademacher复杂度).
  • 关于水库系统中不调节性和线性对复杂性的理论分析.

主要成果:

  • 该研究为分析学习系统复杂性的研究提供了通用框架.
  • 阐明了水库不可调节性和读出线性对复杂度指标的具体影响.
  • 介绍了新的理论结果,将现有的现场发现概括和改进.

结论:

关键词:
增长功能 增长功能伪维度是一种伪维度.雷达制造商的复杂性储水库计算器 储水库计算这是一个VC维度.

更多相关视频

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.0K
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

42.5K

相关实验视频

Last Updated: Jun 7, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

471
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.0K
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

42.5K
  • 一般化模型提供了一种更全面的方法来理解学习系统的复杂性.
  • 这些发现为设计和优化水库计算系统提供了宝贵的见解.
  • 这项工作有助于机器学习和计算复杂性的理论基础.