Results 61 to 70 of about 328,340 (188)
Eigenvector Weighting Function in Face Recognition
Discrete Dynamics in Nature and Society, 2011 Graph-based subspace learning is a class of dimensionality reduction technique in face recognition. The technique reveals the local manifold structure of face data that hidden in the image space via a linear projection.
Pang Ying Han +2 more
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Multiple model predictive control of robot manipulator
Gong-kuang zidonghua, 2014 A multiple model predictive control method based on membership function was proposed according to nonlinear characteristics of robot manipulator. An appropriate scheduling variable was selected according to the characteristics of the robot manipulator ...
DU Jingjing +2 more
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Semi-Supervised Cross-Modal Retrieval Based on Discriminative Comapping
Complexity, 2020 Most cross-modal retrieval methods based on subspace learning just focus on learning the projection matrices that map different modalities to a common subspace and pay less attention to the retrieval task specificity and class information. To address the
Li Liu, Xiao Dong, Tianshi Wang
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Structure-Based Subspace Method for Multi-Channel Blind System Identification
, 2017 In this work, a novel subspace-based method for blind identification of multichannel finite impulse response (FIR) systems is presented. Here, we exploit directly the impeded Toeplitz channel structure in the signal linear model to build a quadratic form
Abed-Meraim, Karim +2 more
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Posterior Shrinkage Towards Linear Subspaces
Bayesian AnalysisIt is common to hold prior beliefs that are not characterized by points in the parameter space but instead are relational in nature and can be described by a linear subspace. While some previous work has been done to account for such prior beliefs, the focus has primarily been on point estimators within a regression framework.
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Linear decision trees, subspace arrangements and Möbius functions [PDF]
Journal of the American Mathematical Society, 1994 Topological methods are described for estimating the size and depth of decision trees where a linear test is performed at each node. The methods are applied, among others, to the questions of deciding by a linear decision tree whether givennnreal numbers (1) somekkof them are equal, or (2) somekkof them are unequal.
Björner, Anders, Lovász, László
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Sparse signal subspace decomposition based on adaptive over-complete dictionary
EURASIP Journal on Image and Video Processing, 2017 This paper proposes a subspace decomposition method based on an over-complete dictionary in sparse representation, called “sparse signal subspace decomposition” (or 3SD) method. This method makes use of a novel criterion based on the occurrence frequency
Hong Sun +2 more
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A Preconditioned Fast Collocation Method for a Linear Nonlocal Diffusion Model in Convex Domains
IEEE Access, 2020 Recently, there are many papers dedicated to develop fast numerical methods for nonlocal diffusion and peridynamic models. However, these methods require the physical domain where we solve the governing equations is rectangular. To relax this restriction,
Xuhao Zhang, Aijie Cheng, Hong Wang
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Engineering Stable Discrete-Time Quantum Dynamics via a Canonical QR Decomposition
, 2009 We analyze the asymptotic behavior of discrete-time, Markovian quantum systems with respect to a subspace of interest. Global asymptotic stability of subspaces is relevant to quantum information processing, in particular for initializing the system in ...
Bolognani, Saverio, Ticozzi, Francesco
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Simultaneous Principal-Component Extraction with Application to Adaptive Blind Multiuser Detection
EURASIP Journal on Advances in Signal Processing, 2002 SIPEX-G is a fast-converging, robust, gradient-based PCA algorithm that has been recently proposed by the authors. Its superior performance in synthetic and real data compared with its benchmark counterparts makes it a viable alternative in applications
Erdogmus Deniz +3 more
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