Results 11 to 20 of about 229,971 (268)
Constrained Minimization Algorithms [PDF]
EAS Publications Series, 2013 In this paper, we consider the inverse problem of restoring an unknown signal or image, knowing the transformation suffered by the unknowns. More specifically we deal with transformations described by a linear model linking the unknown signal to an unnoisy version of the data. The measured data are generally corrupted by noise.
H. Lantéri, C. Theys, C. Richard
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Mathematical Camera Array Optimization for Face 3D Modeling Application
Sensors, 2023 Camera network design is a challenging task for many applications in photogrammetry, biomedical engineering, robotics, and industrial metrology, among other fields.
Bashar Alsadik +3 more
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Positive radial solutions for a class of quasilinear Schrödinger equations in $\mathbb{R}^3$
Electronic Journal of Qualitative Theory of Differential Equations, 2022 This paper is concerned with the following quasilinear Schrödinger equations of the form: \begin{equation*} -\Delta u-u\Delta (u^2)+u=|u|^{p-2}u, \qquad x\in \mathbb{R}^3, \end{equation*} where $p\in\left(2,12\right)$.
Zhongxiang Wang, Gao Jia, Weifeng Hu
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Minimal constrained supergravity
Physics Letters B, 2017 We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called "de Sitter" supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.
CRIBIORI, NICCOLÒ +3 more
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Constrained Least-Squares Parameter Estimation for a Double Layer Capacitor
Energies, 2023 This paper presents an estimation of the parameters for a Double Layer Super Capacitor (DLC) that is modelled with a two-branch circuit. The estimation is achieved using a constrained minimization technique, which is developed off-line and uses a single ...
Nayzel I. Jannif +4 more
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Journal of Function Spaces and Applications, 2012 It is well known that the gradient-projection algorithm (GPA) for solving constrained convex minimization problems has been proven to have only weak convergence unless the underlying Hilbert space is finite dimensional.
Lu-Chuan Ceng, Ching-Feng Wen
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OPTIMASS: A Package for the Minimization of Kinematic Mass Functions with Constraints [PDF]
, 2015 Reconstructed mass variables, such as $M_2$, $M_{2C}$, $M_T^\star$, and $M_{T2}^W$, play an essential role in searches for new physics at hadron colliders.
Cho, Won Sang +7 more
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A Hybrid Gradient-Projection Algorithm for Averaged Mappings in Hilbert Spaces
Journal of Applied Mathematics, 2012 It is well known that the gradient-projection algorithm (GPA) is very useful in solving constrained convex minimization problems. In this paper, we combine a general iterative method with the gradient-projection algorithm to propose a hybrid gradient ...
Ming Tian, Min-Min Li
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Non-Convex Split Feasibility Problems: Models, Algorithms and Theory
Open Journal of Mathematical Optimization, 2020 In this paper, we propose a catalog of iterative methods for solving the Split Feasibility Problem in the non-convex setting. We study four different optimization formulations of the problem, where each model has advantages in different settings of the ...
Gibali, Aviv +2 more
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Sharp RIP Bound for Sparse Signal and Low-Rank Matrix Recovery [PDF]
, 2013 This paper establishes a sharp condition on the restricted isometry property (RIP) for both the sparse signal recovery and low-rank matrix recovery.
Cai, T. Tony, Zhang, Anru
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