Results 81 to 90 of about 341,424 (240)
Tensor‐Based Reduction of Linear Parameter‐Varying State‐Space Models
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT The linear parameter‐varying (LPV) framework is a powerful tool for controlling nonlinear (NL) and complex systems, but the conversion of NL models into LPV forms often results in high‐dimensional and overly conservative LPV models. To be able to apply control strategies, there is often a need for model reduction in order to reduce ...
Bogoljub Terzin +4 more
wiley +1 more source
On a Norm Inequality for Three 2 × 2 Matrices with One Normal Factor
MathematicsIn this paper, we continue to investigate the norm inequality for three real matrices that was recently conjectured by L. László. We establish the validity of the conjecture for the case where n=2 and one of the matrices is normal.
Na Li, Fen Wang
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The role of identification in data‐driven policy iteration: A system theoretic study
International Journal of Robust and Nonlinear Control, EarlyView.Abstract The goal of this article is to study fundamental mechanisms behind so‐called indirect and direct data‐driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of ...
Bowen Song, Andrea Iannelli
wiley +1 more source
A Frobenius Norm Regularization Method for Convolutional Kernel Tensors in Neural Networks. [PDF]
Comput Intell Neurosci, 2022 Guo PC.
europepmc +1 more source
International Journal of Satellite Communications and Networking, EarlyView.ABSTRACT Low Earth Orbit (LEO) satellite constellations offer unprecedented opportunities for global broadband connectivity but pose significant beamforming challenges due to rapid platform motion and stringent onboard hardware constraints. Fully digital architectures, while optimal in theory, remain impractical for satellite payloads, motivating ...
Mohammad Momani +2 more
wiley +1 more source
Material Heterogeneity and Waste‐Trade Networks in EU‐27 Circular‐Economy Convergence
Sustainable Development, EarlyView.ABSTRACT EU monitoring summarizes circular‐economy progress with aggregate indicators, although material‐specific adjustment and cross‐border secondary‐resource links may follow different paths. This study examines convergence across the EU‐27, heterogeneity among biomass, metal ores, non‐metallic minerals, and fossil‐energy materials, and network ...
Pan Jiang, Shuaiyi Lu, Lianghan Cong
wiley +1 more source
Iterative Solution to a System of Matrix Equations
Abstract and Applied Analysis, 2013 An efficient iterative algorithm is presented to solve a system of linear matrix equations , with real matrices and . By this iterative algorithm, the solvability of the system can be determined automatically.
Yong Lin, Qing-Wen Wang
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Alternating Direction Method of Multipliers for Generalized Low-Rank Tensor Recovery
Algorithms, 2016 Low-Rank Tensor Recovery (LRTR), the higher order generalization of Low-Rank Matrix Recovery (LRMR), is especially suitable for analyzing multi-linear data with gross corruptions, outliers and missing values, and it attracts broad attention in the fields
Jiarong Shi +3 more
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Enhancing generalized spectral clustering with embedding Laplacian graph regularization
CAAI Transactions on Intelligence Technology, EarlyView.Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang +5 more
wiley +1 more source
Group Choice Using Matrix Norms
Известия Иркутского государственного университета: Серия "Математика", 2016 The article describes the approach to the construction of methods of the group choice and ranking of objects in order of preference, based on the minimizing the deviation of the matrix, characterizing objects (of an evaluation matrix) from some peer ...
Y. N. Artamonov
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