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Visual object tracking is a challenging computer vision task with numerous real-world applications. Here we propose a simple but efficient Spectral Filter Tracking (SFT)method. To characterize rotational and translation invariance of…

Computer Vision and Pattern Recognition · Computer Science 2017-07-19 Zhen Cui , You yi Cai , Wen ming Zheng , Jian Yang

We demonstrate an application of the spectral method as a numerical approximation for solving Hyperbolic PDEs. In this method a finite basis is used for approximating the solutions. In particular, we demonstrate a set of such solutions for…

Mathematical Physics · Physics 2008-11-26 P. Pedram , M. Mirzaei , S. S. Gousheh

The spectral/hp element method combines the geometric flexibility of the classical h-type finite element technique with the desirable numerical properties of spectral methods, employing high-degree piecewise polynomial basis functions on…

Pseudospectral schemes are a class of numerical methods capable of solving smooth problems with high accuracy thanks to their exponential convergence to the true solution. When applied to discontinuous problems, such as fluid shocks and…

Numerical Analysis · Mathematics 2019-10-03 Joanna Piotrowska , Jonah M. Miller

We incorporate an arbitrarily high-order method for the Laplacian operator into the Spectral Difference method (SD). The resulting method is capable of capturing shocks thanks to its a-posteriori limiting methodology, and therefore it is…

Instrumentation and Methods for Astrophysics · Physics 2026-04-09 David A. Velasco-Romero , Romain Teyssier

We propose a new reinforcement learning algorithm for partially observable Markov decision processes (POMDP) based on spectral decomposition methods. While spectral methods have been previously employed for consistent learning of (passive)…

Artificial Intelligence · Computer Science 2017-06-20 Kamyar Azizzadenesheli , Alessandro Lazaric , Animashree Anandkumar

We prove that the most common filtering procedure for nodal discontinuous Galerkin (DG) methods is stable. The proof exploits that the DG approximation is constructed from polynomial basis functions and that integrals are approximated with…

Numerical Analysis · Mathematics 2020-07-15 Jan Nordström , Andrew R. Winters

In this work, we explore various relevant aspects of the Smoothed Particle Hydrodynamics regarding Burger's equation. The stability, precision, and efficiency of the algorithm are investigated in terms of different implementations. In…

Computational Physics · Physics 2020-01-08 Chong Ye , Philipe Mota , Jin Li , Kai Lin , Wei-Liang Qian

High order entropy stable discontinuous Galerkin (DG) methods for nonlinear conservation laws satisfy an inherent discrete entropy inequality. The construction of such schemes has relied on the use of carefully chosen nodal points or volume…

Numerical Analysis · Mathematics 2019-08-06 Jesse Chan

The selective frequency damping (SFD) method is an alternative to classical Newton's method to obtain unstable steady-state solutions of dynamical systems. However this method has two main limitations: it does not converge for arbitrary…

Fluid Dynamics · Physics 2015-10-28 Bastien E. Jordi , Colin J. Cotter , Spencer J. Sherwin

The discontinuous Galerkin (DG) method and the spectral volume (SV) method are two widely-used numerical methodologies for solving hyperbolic conservation laws. In this paper, we demonstrate that under specific subdivision assumptions, the…

Numerical Analysis · Mathematics 2024-09-18 Zhuoyun Li , Kailiang Wu

Modal stability analysis provides information about the long-time growth or decay of small-amplitude perturbations around a steady-state solution of a dynamical system. In fluid flows, exponentially growing perturbations can initiate…

Fluid Dynamics · Physics 2019-11-21 Gokul Hariharan , Mihailo R. Jovanović , Satish Kumar

A time discretization method is called strongly stable, if the norm of its numerical solution is nonincreasing. It is known that, even for linear semi-negative problems, many explicit Runge--Kutta (RK) methods fail to preserve this…

Numerical Analysis · Mathematics 2019-12-30 Zheng Sun , Chi-Wang Shu

In this work we explore the fidelity of numerical approximations to the analytic spectra of hyperbolic partial differential equation systems with variable coefficients. We are particularly interested in the ability of discrete methods to…

Numerical Analysis · Mathematics 2025-08-12 Brittany A. Erickson

We perform simulations of the Kelvin-Helmholtz instability using smoothed particle hydrodynamics (SPH). The instability is studied both in the linear and strongly non-linear regimes. The smooth, well-posed initial conditions of Lecoanet et…

Instrumentation and Methods for Astrophysics · Physics 2019-08-07 Terrence S. Tricco

We demonstrate that accurate computation of the spectral proper orthogonal decomposition (SPOD) critically depends on the choice of frequency resolution. Using both artificially generated data and large-eddy simulation data of a turbulent…

Fluid Dynamics · Physics 2024-02-27 Liam Heidt , Tim Colonius

Variable screening is a fast dimension reduction technique for assisting high dimensional feature selection. As a preselection method, it selects a moderate size subset of candidate variables for further refining via feature selection to…

Statistics Theory · Mathematics 2015-06-09 Xiangyu Wang , Chenlei Leng , David B. Dunson

This paper presents a technique for reducing speckle in Polarimetric Synthetic Aperture Radar (PolSAR) imagery using Nonlocal Means and a statistical test based on stochastic divergences. The main objective is to select homogeneous pixels…

Information Theory · Computer Science 2013-04-18 Leonardo Torres , Sidnei J. S. Sant'Anna , Corina C. Freitas , Alejandro C. Frery

Smoothed Dissipative Particle Dynamics (SDPD) is a mesoscopic method which allows to select the level of resolution at which a fluid is simulated. In this work, we study the consistency of the resulting thermodynamic properties as a…

Statistical Mechanics · Physics 2016-10-19 G. Faure , J. Roussel , J. -B. Maillet , G. Stoltz

The spectral bundle method developed by Helmberg and Rendl is well-established for solving large-scale semidefinite programs (SDPs) in the dual form, especially when the SDPs admit $\textit{low-rank primal solutions}$. Under mild regularity…

Optimization and Control · Mathematics 2026-02-05 Feng-Yi Liao , Lijun Ding , Yang Zheng