Results 21 to 30 of about 2,237,660 (304)
Energies, 2021 The integration of renewable energy sources into modern power systems requires simulations with smaller step sizes, larger network models and the incorporation of complex nonlinear component models.
Jan Dinkelbach +4 more
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Jordan Matrix Decomposition [PDF]
Formalized Mathematics, 2008 We follow the rules: i, j, m, n, k denote natural numbers, K denotes a field, and a, λ denote elements of K. Let us consider K, λ, n. The Jordan block of λ and n yields a matrix over K and is defined by the conditions (Def. 1). (Def. 1)(i) len (the Jordan block of λ and n) = n, (ii) width (the Jordan block of λ and n) = n, and (iii) for all i, j such ...
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Low-Rank Based Image Analyses for Pathological MR Image Segmentation and Recovery
Frontiers in Neuroscience, 2019 The presence of pathologies in magnetic resonance (MR) brain images causes challenges in various image analysis areas, such as registration, atlas construction and atlas-based segmentation.
Chuanlu Lin +3 more
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The General Linear Model and the Generalized Singular Value Decomposition; Some Examples [PDF]
, 2009 The general linear model with correlated error variables can be transformed by means of the generalized singular value decomposition to a very simple model (canonical form) where the least squares solution is obvious.
Knüsel, Leo
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Fast Superpixel Based Subspace Low Rank Learning Method for Hyperspectral Denoising
IEEE Access, 2018 Sequential data, such as video frames and event data, have been widely applied in the realworld. As a special kind of sequential data, hyperspectral images (HSIs) can be regarded as a sequence of 2-D images in the spectral dimension, which can be ...
Le Sun +5 more
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Weighted Sparseness-Based Anomaly Detection for Hyperspectral Imagery
Sensors, 2023 Anomaly detection of hyperspectral remote sensing data has recently become more attractive in hyperspectral image processing. The low-rank and sparse matrix decomposition-based anomaly detection algorithm (LRaSMD) exhibits poor detection performance in ...
Xing Lian +6 more
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IEEE Access, 2019 Opportunistic network enables users to form an instant network for data sharing, which is a type of Ad-hoc network in nature, thus depends on cooperation between nodes to complete message transmission.
Peng Zheng +3 more
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Multi-model deep learning approach for collaborative filtering recommendation system
CAAI Transactions on Intelligence Technology, 2020 As a result of a huge volume of implicit feedback such as browsing and clicks, many researchers are involving in designing recommender systems (RSs) based on implicit feedback.
Mohammed Fadhel Aljunid +1 more
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CS Decomposition Based Bayesian Subspace Estimation [PDF]
, 2012 In numerous applications, it is required to estimate the principal subspace of the data, possibly from a very limited number of samples. Additionally, it often occurs that some rough knowledge about this subspace is available and could be used to improve
Besson, Olivier +2 more
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The Roles of Majorization and Generalized Triangular Decomposition in Communication and Signal Processing [PDF]
, 2011 Signal processing is an art that deals with the representation, transformation, and manipulation of the signals and the information they contain based on their specific features.
Weng, Ching-Chih
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