Results 1 to 10 of about 328,340 (188)
Ensemble Linear Subspace Analysis of High-Dimensional Data [PDF]
Entropy, 2021 Regression models provide prediction frameworks for multivariate mutual information analysis that uses information concepts when choosing covariates (also called features) that are important for analysis and prediction.
S. Ejaz Ahmed, Saeid Amiri, Kjell Doksum
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Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control. [PDF]
PLoS ONE, 2016 In this wIn this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions.
Steven L Brunton +3 more
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Tensor local linear embedding with global subspace projection optimisation
IET Computer Vision, 2022 In this paper, a novel tensor dimensionality reduction (TDR) approach is proposed, which maintains the local geometric structure of tensor data by tensor local linear embedding and explores the global feature by optimising global subspace projection ...
Guo Niu, Zhengming Ma
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Gait recognition based on sparse linear subspace
IET Image Processing, 2021 Gait recognition has broad application prospects in intelligent security monitoring. However, due to the variability of human walking states and the complexity of external conditions during sample collection, gait recognition is still facing many ...
Junqin Wen, Xiuhui Wang
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A Comparative Analysis of Kernel Subspace Target Detectors for Hyperspectral Imagery
EURASIP Journal on Advances in Signal Processing, 2007 Several linear and nonlinear detection algorithms that are based on spectral matched (subspace) filters are compared. Nonlinear (kernel) versions of these spectral matched detectors are also given and their performance is compared with linear versions ...
Kwon Heesung, Nasrabadi Nasser M
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Towards deterministic subspace identification for autonomous nonlinear systems [PDF]
, 2015 The problem of identifying deterministic autonomous linear and nonlinear systems is studied. A specific version of the theory of deterministic subspace identification for discrete-time autonomous linear systems is developed in continuous time.
Astolfi, A, Padoan, A
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Intra-class Low-Rank Subspace Learning for Face Recognition [PDF]
Jisuanji kexue yu tansuo, 2022 As a simple and effective tool, linear regression has been widely used in pattern recognition. However, the direct projection from high-dimensional data to binary labels may not be flexible enough and suitable data rep-resentation for classification ...
CAI Yuhong, WU Xiaojun
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Sobolev subspaces of nowhere bounded functions [PDF]
, 2016 We prove that in any Sobolev space which is subcritical with respect to the Sobolev Embedding Theorem there exists a closed infinite dimensional linear subspace whose non zero elements are nowhere bounded functions.
Lamberti, PIER DOMENICO +1 more
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Ellipsoidal Subspace Support Vector Data Description
IEEE Access, 2020 In this paper, we propose a novel method for transforming data into a low-dimensional space optimized for one-class classification. The proposed method iteratively transforms data into a new subspace optimized for ellipsoidal encapsulation of target ...
Fahad Sohrab +3 more
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Rank-metric codes as ideals for subspace codes and their weight properties
AKCE International Journal of Graphs and Combinatorics, 2019 Let , a prime, a positive integer, and the Galois field with cardinality and characteristic . In this paper, we study some weight properties of rank-metric codes and subspace codes.
Bryan S. Hernandez, Virgilio P. Sison
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