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Fitted finite element methods are constructed for a singularly perturbed convection-diffusion problem in two space dimensions. Exponential splines as basis functions are combined with Shishkin meshes to obtain a stable parameter-uniform…

Numerical Analysis · Mathematics 2023-10-03 Alan F. Hegarty , Eugene O'Riordan

A system of singularly perturbed ordinary differential equations of first order with given initial conditions is considered. The leading term of each equation is multiplied by a small positive parameter. These parameters are assumed to be…

Numerical Analysis · Mathematics 2009-03-11 S Valarmathi , John J H Miller

In this paper, a new parametrization of the relative motion between two satellites orbiting a central body is presented. The parametrization is based on the nodal elements: a set of angles describing the orbit geometry with respect to the…

Systems and Control · Electrical Eng. & Systems 2021-01-22 Mirko Leomanni , Andrea Garulli , Antonio Giannitrapani , Renato Quartullo

The true- and eccentric-anomaly parametrizations of the Kepler motion are generalized to quasiperiodic orbits by considering perturbations of the radial part of kinetic energy as a series in the negative powers of the orbital radius. A…

General Relativity and Quantum Cosmology · Physics 2007-05-23 László Á. Gergely , Zoltán I. Perjés , Mátyás Vasúth

We propose a general framework for studying optimal impulse control problem in the presence of uncertainty on the parameters. Given a prior on the distribution of the unknown parameters, we explain how it should evolve according to the…

Probability · Mathematics 2017-12-06 N. Baradel , B. Bouchard , Ngoc Minh Dang

A singularly perturbed linear system of second order partial differential equations of parabolic reaction-diffusion type with given initial and boundary conditions is considered. The leading term of each equation is multiplied by a small…

Numerical Analysis · Mathematics 2010-08-17 V. Franklin , M. Paramasivam , S. Valarmathi , J. J. H. Miller

This work aims to provide a deep-learning solution for the motion interpolation task. Previous studies solve it with geometric weight functions. Some other works propose neural networks for different problem settings with consecutive pose…

Computer Vision and Pattern Recognition · Computer Science 2023-06-13 Shuo Huang , Jia Jia , Zongxin Yang , Wei Wang , Haozhe Wu , Yi Yang , Junliang Xing

In this paper we consider a linearized variable-time-step two-step backward differentiation formula (BDF2) scheme for solving nonlinear parabolic equations. The scheme is constructed by using the variable time-step BDF2 for the linear term…

Numerical Analysis · Mathematics 2025-08-29 Chengchao Zhao , Nan Liu , Yuheng Ma , Jiwei Zhang

Models of relativistic particle with Lagrangian ${\cal L}(k_1)$, depending on the curvature of the worldline $k_1$, are considered. By making use of the Frenet basis, the equations of motion are reformulated in terms of the principal…

High Energy Physics - Theory · Physics 2009-10-28 V. V. Nesterenko , A. Feoli , G. Scarpetta

Dynamics of ideal fluid with free surface can be effectively solved by perturbing the Hamiltonian in weak nonlinearity limit. However it is shown that perturbation theory, which includes third and fourth order terms in the Hamiltonian,…

Pattern Formation and Solitons · Physics 2009-11-10 Pavel M. Lushnikov , Vladimir E. Zakharov

We present a novel simple yet effective algorithm for motion-based video frame interpolation. Existing motion-based interpolation methods typically rely on a pre-trained optical flow model or a U-Net based pyramid network for motion…

Computer Vision and Pattern Recognition · Computer Science 2022-11-08 Xin Jin , Longhai Wu , Guotao Shen , Youxin Chen , Jie Chen , Jayoon Koo , Cheul-hee Hahm

Reasoning about 3D scenes from their 2D image projections is one of the core problems in computer vision. Solutions to this inverse and ill-posed problem typically involve a search for models that best explain observed image data. Notably,…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Quentin Le Lidec , Ivan Laptev , Cordelia Schmid , Justin Carpentier

We proposed a novel approach to coherent imaging of dynamic samples. The inter-frame similarity of the sample's local structures is found to be a powerful constraint in phasing a sequence of diffraction patterns. We devised a new image…

Optics · Physics 2024-07-11 Pengju Sheng , Fucai Zhang

Frames have established themselves as a means to derive redundant, yet stable decompositions of a signal for analysis or transmission, while also promoting sparse expansions. However, when the signal dimension is large, the computation of…

Numerical Analysis · Mathematics 2011-06-30 Peter G. Casazza , Andreas Heinecke , Felix Krahmer , Gitta Kutyniok

The problems of optimally estimating a phase, a direction, and the orientation of a Cartesian frame (or trihedron) with general pure states are addressed. Special emphasis is put on estimation schemes that allow for inconclusive answers or…

Quantum Physics · Physics 2013-08-09 B. Gendra , E. Ronco-Bonvehi , J. Calsamiglia , R. Muñoz-Tapia , E. Bagan

Optimization is an important module of modern machine learning applications. Tremendous efforts have been made to accelerate optimization algorithms. A common formulation is achieving a lower loss at a given time. This enables a…

Machine Learning · Computer Science 2025-05-29 Zhonglin Xie , Yiman Fong , Haoran Yuan , Zaiwen Wen

In this work we propose a new kind of parameterized outer estimate of the united solution set to an interval parametric linear system. The new method has several advantages compared to the methods obtaining parameterized solutions…

Numerical Analysis · Mathematics 2020-04-02 Evgenija D. Popova

The generalization of (super)integrable Euclidean classical Hamiltonian systems to the two-dimensional sphere and the hyperbolic space by preserving their (super)integrability properties is reviewed. The constant Gaussian curvature of the…

Mathematical Physics · Physics 2019-07-16 Angel Ballesteros , Alfonso Blasco , Francisco J. Herranz

Bayesian optimization works effectively optimizing parameters in black-box problems. However, this method did not work for high-dimensional parameters in limited trials. Parameters can be efficiently explored by nonlinearly embedding them…

Machine Learning · Computer Science 2022-06-14 Shoki Miyagawa , Atsuyoshi Yano , Naoko Sawada , Isamu Ogawa

The complexity of mathematical models describing respiratory mechanics has grown in recent years to integrate with cardiovascular models and incorporate nonlinear dynamics. However, additional model complexity has rarely been studied in the…

Tissues and Organs · Quantitative Biology 2020-01-17 Laura Ellwein Fix