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In this paper, we study an adaptive finite element method for multiple eigenvalue problems of a class of second order elliptic equations. By using some eigenspace approximation technology and its crucial property which is also presented in…

Numerical Analysis · Mathematics 2013-09-18 Xiaoying Dai , Lianhua He , Aihui Zhou

This paper proposes the capped least squares regression with an adaptive resistance parameter, hence the name, adaptive capped least squares regression. The key observation is, by taking the resistant parameter to be data dependent, the…

Methodology · Statistics 2021-07-02 Qiang Sun , Rui Mao , Wen-Xin Zhou

The extraction of transition frequencies from a spectrum has conventionally relied on empirical methods, and particularly in complex systems, it is a time-consuming and cumbersome process. To address this challenge, we establish a…

Quantum Physics · Physics 2025-07-30 A. Tomonaga , H. Mukai , K. Mizuno , J. S. Tsai

In industrial defect segmentation tasks, while pixel accuracy and Intersection over Union (IoU) are commonly employed metrics to assess segmentation performance, the output consistency (also referred to equivalence) of the model is often…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Zhen Qu , Xian Tao , Fei Shen , Zhengtao Zhang , Tao Li

Since the first optimality proofs for adaptive mesh refinement algorithms in the early 2000s, the theory of optimal mesh refinement for PDEs was inherently limited to stationary problems. The reason for this is that time-dependent problems…

Numerical Analysis · Mathematics 2025-12-08 Michael Feischl , Fernando Henríquez , David Niederkofler

A new method which allows one to study multiple coherent reflection/transmissions by partially transparent interfaces, (e.g., in multi-layer mesoscopic structures or grain boundaries in high-Tc's), in the framework of the quasiclassical…

Superconductivity · Physics 2009-10-31 A. Shelankov , M. Ozana

The design of the proposal distributions, and most notably the kernel parameters, are crucial for the performance of Markov chain Monte Carlo (MCMC) rendering. A poor selection of parameters can increase the correlation of the Markov chain…

Two moment-matching methods for model reduction of linear switched systems (LSSs) are presented. The methods are similar to the Krylov subspace methods used for moment matching for linear systems. The more general one of the two methods, is…

Systems and Control · Computer Science 2016-11-15 Mert Bastug , Mihaly Petreczky , Rafael Wisniewski , John Leth

Millimeter-wave (mm-Wave) cellular systems are a promising option for a very high data rate communication because of the large bandwidth available at mm-Wave frequencies. Due to the large path-loss exponent in the mm-Wave range of the…

Information Theory · Computer Science 2015-11-06 Saeid Haghighatshoar , Giuseppe Caire

The committor function is a central object for quantifying the transitions between metastable states of dynamical systems. Recently, a number of computational methods based on deep neural networks have been developed for computing the…

Computational Physics · Physics 2024-04-10 Bo Lin , Weiqing Ren

A novel approach is suggested for improving the accuracy of fault detection in distribution networks. This technique combines adaptive probability learning and waveform decomposition to optimize the similarity of features. Its objective is…

Signal Processing · Electrical Eng. & Systems 2023-10-03 Xinliang Ma , Weihua Liu , Bingying Jin

Phase type (PH) distributions are widely used in modeling and simulation due to their generality and analytical properties. In such settings, it is often necessary to construct a PH distribution that aligns with real-world data by matching…

Optimization and Control · Mathematics 2025-05-28 Eliran Sherzer , Yehezkel Resheff , Miklos Telek

The present paper deals with the numerical solution of time-fractional advection-diffusion equations involving the Caputo derivative with source term by means of an unconditionally stable implicit finite difference method on quasi-uniform…

Numerical Analysis · Mathematics 2018-02-14 Riccardo Fazio , Alessandra Jannelli

For the planar Navier--Lam\'e equation in mixed form with symmetric stress tensors, we prove the uniform quasi-optimal convergence of an adaptive method based on the hybridized mixed finite element proposed in [Gong, Wu, and Xu:…

Numerical Analysis · Mathematics 2021-03-30 Yuwen Li

Understanding the quasi-static fracture formation and evolution is essential for assessing the mechanical properties and structural load-bearing capacity of materials. Peridynamics (PD) provides an effective computational method to depict…

Numerical Analysis · Mathematics 2024-10-17 Shiwei Hu , Tianbai Xiao , Mingshuo Han , Zuoxu Li , Erkan Oterkus , Selda Oterkus , Yonghao Zhang

An adaptive mesh refinement and error estimation method for numerically solving optimal control problems is developed using Legendre-Gauss-Radau direct collocation. In regions of the solution where the desired accuracy tolerance has not…

Optimization and Control · Mathematics 2024-10-11 George V. Haman , Anil V. Rao

Mesh adaptivity is a useful tool for efficient solution to partial differential equations in very complex geometries. In the present paper we discuss the use of polygonal mesh refinement in order to tackle two common issues: first,…

Numerical Analysis · Mathematics 2021-12-21 Stefano Berrone , Alessandro D'Auria

We present an efficient mixed finite element method to solve the fourth-order thin film flow equations using moving mesh refinement. The moving mesh strategy is based on harmonic mappings developed by Li et al. [J. Comput. Phys., 170…

Numerical Analysis · Mathematics 2018-01-17 Hong Zhang , Paul A Zegeling

This paper is concerned with the estimation of time-varying networks for high-dimensional nonstationary time series. Two types of dynamic behaviors are considered: structural breaks (i.e., abrupt change points) and smooth changes. To…

Statistics Theory · Mathematics 2020-02-19 Mengyu Xu , Xiaohui Chen , Wei Biao Wu

Computational Fluid Dynamics (CFD) is a major sub-field of engineering. Corresponding flow simulations are typically characterized by heavy computational resource requirements. Often, very fine and complex meshes are required to resolve…

Machine Learning · Computer Science 2021-02-26 Keefe Huang , Moritz Krügener , Alistair Brown , Friedrich Menhorn , Hans-Joachim Bungartz , Dirk Hartmann
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