Results 71 to 80 of about 3,247,690 (230)
Substation Equipment 3D Identification Based on KNN Classification of Subspace Feature Vector
Journal of Intelligent Systems, 2017 Aiming to realize rapid and efficient three-dimensional (3D) identification of substation equipment, this article proposes a new method in which the 3D identification of substation equipment is based on K-nearest neighbor (KNN) classification of subspace
Guo Weiying, Ji Yong, Luo Yong, Zhou Yan
doaj +1 more source
Robust Reduced-Rank Adaptive Processing Based on Parallel Subgradient Projection and Krylov Subspace Techniques [PDF]
, 2013 In this paper, we propose a novel reduced-rank adaptive filtering algorithm by blending the idea of the Krylov subspace methods with the set-theoretic adaptive filtering framework.
Isao Yamada +3 more
core
A Multiple Hypothesis Testing Approach to Low-Complexity Subspace Unmixing [PDF]
, 2016 Subspace-based signal processing traditionally focuses on problems involving a few subspaces. Recently, a number of problems in different application areas have emerged that involve a significantly larger number of subspaces relative to the ambient ...
Bajwa, Waheed U., Mixon, Dustin G.
core
Robust multichannel subspace identification
Electronics Letters, 1999 The non-robustness to channel order overestimation and lack of disparity of the Moulines subspace (SS) and the Tong least-squares (LS) approaches are considered to be major limitations to their use in practical situations. A remedial technique is proposed that can be applied to both approaches, offering them the robustness they lack.
openaire +1 more source
IEEE Access, 2018 With the increasing demand for unsupervised learning for fault diagnosis, the subspace clustering has been considered as a promising technique enabling unsupervised fault diagnosis. Although various subspace clustering methods have been developed to deal
Jie Gao +4 more
doaj +1 more source
K4SID: Large-Scale Subspace Identification With Kronecker Modeling
IEEE Transactions on Automatic Control, 2019 In this paper, we consider the identification of matrix state-space models (MSSM) of the following form: \begin{align*} \mathbf {X}(k+1) &= \mathbf {A}_2 \mathbf {X}(k) \mathbf {A}_1^T + \mathbf {B}_2 \mathbf {U}(k) \mathbf {B}_1^T \\ \mathbf {Y}(k) &= \
B. Sinquin, M. Verhaegen
semanticscholar +1 more source
World Electric Vehicle JournalThis paper proposes a model identification method based on the auxiliary variable closed-loop subspace identification algorithm to address the problem of modeling difficulties caused by various complex factors affecting permanent magnet brushless DC ...
Jing Zhang +3 more
doaj +1 more source
Mapping prior information onto LMI eigenvalue-regions for discrete-time subspace identification
, 2019 In subspace identification, prior information can be used to constrain the eigenvalues of the estimated state-space model by defining corresponding LMI regions.
Ricco, Rodrigo A., Teixeira, Bruno O. S.
core +1 more source
Robust and Efficient Recovery of Rigid Motion from Subspace Constraints Solved using Recursive Identification of Nonlinear Implicit Systems [PDF]
, 1994 The problem of estimating rigid motion from projections may be characterized using a nonlinear dynamical system, composed of the rigid motion transformation and the perspective map. The time derivative of the output of such a system, which is also called
Perona, Pietro, Soatto, Stefano
core
A Stochastic Majorize-Minimize Subspace Algorithm for Online Penalized Least Squares Estimation
, 2016 Stochastic approximation techniques play an important role in solving many problems encountered in machine learning or adaptive signal processing. In these contexts, the statistics of the data are often unknown a priori or their direct computation is too
Emilie, Chouzenoux +1 more
core +3 more sources