Results 251 to 260 of about 32,682,305 (325)

Boosting random subspace method

Neural Networks, 2008
In this paper we propose a boosting approach to random subspace method (RSM) to achieve an improved performance and avoid some of the major drawbacks of RSM. RSM is a successful method for classification. However, the random selection of inputs, its source of success, can also be a major problem.
García-Pedrajas, Nicolás, Ortiz-Boyer, Domingo   +1 more
openaire   +3 more sources

Fast Parameter-Free Multi-View Subspace Clustering With Consensus Anchor Guidance

IEEE Transactions on Image Processing, 2021
Multi-view subspace clustering has attracted intensive attention to effectively fuse multi-view information by exploring appropriate graph structures. Although existing works have made impressive progress in clustering performance, most of them suffer ...
Siwei Wang, Xinwang Liu, Xinzhong Zhu, Pei Zhang, Yi Zhang, Feng Gao, En Zhu   +6 more
semanticscholar   +1 more source

From Pseudo to Real: Generalized Subspace Method for Power Spectrum Reconstruction

IEEE transactions on industrial electronics (1982. Print)
Subspace methods are widely used in statistical signal processing owing to their super-resolution. Conventional subspace methods, such as multiple signal classification (MUSIC) identify parameters containing frequency and direction of arrival by ...
Jiahui Cao, Zhibo Yang, Xuefeng Chen, Ruqiang Yan   +3 more
semanticscholar   +1 more source

Generalized Latent Multi-View Subspace Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Subspace clustering is an effective method that has been successfully applied to many applications. Here, we propose a novel subspace clustering model for multi-view data using a latent representation termed Latent Multi-View Subspace Clustering (LMSC ...
Changqing Zhang, H. Fu, Q. Hu, Xiaochun Cao, Yuan Xie, D. Tao, Dong Xu   +6 more
semanticscholar   +1 more source

SubspaceNet: Deep Learning-Aided Subspace Methods for DoA Estimation

IEEE Transactions on Vehicular Technology, 2023
Direction of arrival (DoA) estimation is a fundamental task in array processing. A popular family of direction of arrival (DoA) estimation algorithms are subspace methods, which operate by dividing the measurements into distinct signal and noise ...
Dor H. Shmuel, J. Merkofer, Guy Revach, R. J. Sloun, Nir Shlezinger   +4 more
semanticscholar   +1 more source

Difference Subspace and Its Generalization for Subspace-Based Methods

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
Subspace-based methods are known to provide a practical solution for image set-based object recognition. Based on the insight that local shape differences between objects offer a sensitive cue for recognition, this paper addresses the problem of extracting a subspace representing the difference components between class subspaces generated from each set
Kazuhiro Fukui, Atsuto Maki
openaire   +2 more sources

Performance-Indicator-Oriented Concurrent Subspace Process Monitoring Method

IEEE transactions on industrial electronics (1982. Print), 2019
Process monitoring is an effective means to ensure process safety and improve product quality. On the one hand, it is possible that the fault will not affect process safety or product quality.
Bing Song, Xinggui Zhou, Hong-bo Shi, Yang Tao   +3 more
semanticscholar   +1 more source

A refined invariant subspace method and applications to evolution equations

, 2012
The invariant subspace method is refined to present more unity and more diversity of exact solutions to evolution equations. The key idea is to take subspaces of solutions to linear ordinary differential equations as invariant subspaces that evolution ...
W. Ma
semanticscholar   +2 more sources

Subspace linear inverse method

Inverse Problems, 1994
The paper describes a numerical algorithm for the iterative solution of large scale linear inverse problems. From optimization point of view weighted least squares subject to parameters which are compatible with the data are used to find approximate solutions of linear inverse problems.
Oldenburg, Douglas W., Li, Yaoguo
openaire   +1 more source

From the Subspace Methods to the Mutual Subspace Method

2010
The Subspace Method [25, 21] is a classic method of pattern recognition, and has been applied to various tasks. The Mutual Subspace Method [19] is an extension of the Subspace Methods, in which canonical angles (principal angles) between two subspaces are used to define similarity between two patterns (or two sets of patterns). The method is applied to
openaire   +1 more source