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

106
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...
106

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

Relaxed conditions and PSO-based optimization for the problem of Mittag-Leffler synchronization and its application in image restoration for fractional-order octonion-valued two-layer neural networks.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Multi-μ-stability and fixed-time multistability of switched fuzzy neural networks with discontinuous activation functions.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Multiscale Attention Unet: An Innovative Approach for Segmentation of Optic Disc and Optic Cup in Early Detection of Retinopathy.

Ophthalmology science·2026
Same author

Self-supervised semantic graph propagation for multi-view clustering.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Distributed Inertial k-Winners-Take-All Neural Network Based on Quadratic Optimization Problems.

IEEE transactions on neural networks and learning systems·2026
Same author

A heterogeneous encoding disentangled representation network for financial time series forecasting.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Exploiting audio-visual modalities in videos: Object detection via multi-stage bilateral coupling network.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Reliability-aware modality completion with cross-modal distillation for federated learning with missing modalities.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

IGFD-Net: Illumination-guided frequency decoupling for polarization image fusion.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Multiple-Strategies dung beetle optimizer and its applications in engineering optimization and bankruptcy prediction.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Aggregating global-scale pixel-wise forgery cues within a graph.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Finite-Time intermittent control for secure synchronization of Neutral-Type stochastic delayed neural networks under aperiodic DoS attacks.

Neural networks : the official journal of the International Neural Network Society·2026
查看所有相关文章

相关实验视频

Updated: Jun 28, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K

自主节奏规范自适应多视图无监督的功能选择.

Xuanhao Yang1, Hangjun Che2, Man-Fai Leung3

  • 1College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China.

Neural networks : the official journal of the International Neural Network Society
|April 13, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了自律调节自适应多视图无监督特征选择 (SPAMUFS),通过自适应权重样本和视图来改善复杂,异质数据的特征选择. 通过更好地利用样本多样性和保存数据结构,SPAMUFS增强了维度缩小.

关键词:
超图形 (Hypergraph) 是一个超图形.多视图无监督特征选择多视图无监督特征选择自己节奏的学习学习.稀少的学习学习.l(2,p) -规范的规范.

更多相关视频

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

706
Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
11:38

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Published on: August 23, 2017

9.8K

相关实验视频

Last Updated: Jun 28, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

706
Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
11:38

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Published on: August 23, 2017

9.8K

科学领域:

  • 机器学习 机器学习
  • 数据科学数据科学数据科学
  • 计算机视觉 计算机视觉

背景情况:

  • 多视图无监督特征选择 (MUFS) 对于减少异质数据中的维度至关重要.
  • 现有的MUFS方法经常忽视样本多样性,并与非凸的优化问题作斗争.
  • 这导致了低于最佳的特征选择和低效的数据表示.

研究的目的:

  • 提出一种新的MUFS方法,即自动节奏调节自适应多视图无监督特征选择 (SPAMUFS),它解决了现有方法的局限性.
  • 增强样本多样性的利用,改善MUFS中非凸度的处理.
  • 为多视图异质数据开发一个强大的特征选择技术.

主要方法:

  • SPAMUFS采用自动学习策略,逐步训练模型使用越来越复杂的样本.
  • 它使用l2,p-norm来测量学习错误和强制执行稀疏性,以适应各种数据集要求.
  • 超图拉普拉斯矩阵是为每个视图构建的,以捕捉局部多元结构和高阶关系,具有自适应视图权重.

主要成果:

  • 拟议的代优化算法有效地解决了SPAMUFS问题,分析了度和计算复杂性.
  • 与9个公共多视图数据集中的8个最先进的算法相比,SPAMUFS表现出更好的性能.
  • 该方法有效地利用样本多样性和视图间的相关性,以改善特征选择.

结论:

  • 通过有效处理样本多样性和复杂的数据结构,SPAMUFS在多视图无监督特征选择方面取得了重大进展.
  • 自动学习和自适应权重机制有助于实现更强大,更有效的尺寸缩小.
  • 拟议的方法为各种涉及多视图异构数据分析的应用提供了有前途的解决方案.