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We develop a method to control discrete-time systems with constant but initially unknown parameters from linear temporal logic (LTL) specifications. We introduce the notions of (non-deterministic) parametric and adaptive transition systems…

Systems and Control · Computer Science 2017-03-23 Sadra Sadraddini , Calin Belta

This paper interprets the stabilized finite element method via residual minimization as a variational multiscale method. We approximate the solution to the partial differential equations using two discrete spaces that we build on a…

Computational Engineering, Finance, and Science · Computer Science 2023-05-23 Juan F. Giraldo , Victor M. Calo

We define variational properties for dynamical systems with subexponential complexity, and study these properties in certain specific examples. By computing the value of slow entropy directly, we show that some subshifts are not…

Dynamical Systems · Mathematics 2024-10-22 Minhua Cheng , Carlos Ospina , Kurt Vinhage , Yibo Zhai

A constrained multivariate linear model is a multivariate linear model with the columns of its coefficient matrix constrained to lie in a known subspace. This class of models includes those typically used to study growth curves and…

Methodology · Statistics 2021-01-05 Dennis Cook , Liliana Forzani , Lan Liu

In this paper, we explore adaptive inference based on variational Bayes. Although several studies have been conducted to analyze the contraction properties of variational posteriors, there is still a lack of a general and computationally…

Statistics Theory · Mathematics 2024-03-12 Ilsang Ohn , Lizhen Lin

This article primarily aims to unify the various formalisms of multivariate coefficients of variation, leveraging advanced concepts of generalized means, whether weighted or not, applied to the eigenvalues of covariance matrices. We…

Instrumentation and Detectors · Physics 2024-03-13 Elise Colin , Razvigor Ossikovski

We consider the dynamics of thin two-dimensional viscous droplets on chemically heterogeneous surfaces moving under the combined effects of slip, mass transfer and capillarity. The resulting long-wave evolution equation for the droplet…

Fluid Dynamics · Physics 2021-12-20 Danny Groves , Nikos Savva

In this paper, we introduce a wavelet-based method for estimating the EDR space in Li's semiparametric regression model for achieving dimension reduction. This method is obtained by using linear wavelet estimators of the density and…

Statistics Theory · Mathematics 2020-05-04 Emmanuel de Dieu Nkou , Guy Martial Nkiet

Time series measured from real-world systems are generally noisy, complex and display statistical properties that evolve continuously over time. Here, we present a method that combines wavelet analysis and non-stationary surrogates to…

Data Analysis, Statistics and Probability · Physics 2018-04-12 Mario Chavez , Bernard Cazelles

The Easy Path Wavelet Transform is an adaptive transform for bivariate functions (in particular natural images) which has been proposed in [1]. It provides a sparse representation by finding a path in the domain of the function leveraging…

Information Theory · Computer Science 2017-02-16 Renato Budinich

Microstructured materials, such as architected metamaterials and phononic crystals, exhibit complex wave propagation phenomena due to their internal structure. While full-scale numerical simulations can capture these effects, they are…

Computational Physics · Physics 2025-05-21 Gianluca Rizzi , Angela Madeo

High-dimensional multivariate spatial-temporal data arise frequently in a wide range of applications; however, there are relatively few statistical methods that can simultaneously deal with spatial, temporal and variable-wise dependencies…

Methodology · Statistics 2020-02-05 Elynn Y. Chen , Xin Yun , Rong Chen , Qiwei Yao

The dynamics of systems of many degrees of freedom evolving on multiple scales are often modeled in terms of stochastic differential equations. Usually the structural form of these equations is unknown and the only manifestation of the…

Methodology · Statistics 2023-04-05 Dimitra Maoutsa

We revisit the problem of computing (robust) controlled invariant sets for discrete-time linear systems. Departing from previous approaches, we consider implicit, rather than explicit, representations for controlled invariant sets.…

Optimization and Control · Mathematics 2022-08-10 Tzanis Anevlavis , Zexiang Liu , Necmiye Ozay , Paulo Tabuada

Recent results in control systems and numerical integration literature utilize invariant set theory to lift dynamical systems evolving on nonlinear manifolds to those evolving on vector spaces. We leverage this technique to propose an…

Optimization and Control · Mathematics 2022-08-09 Siddharth H. Nair

We consider a framework for the construction of iterative schemes for operator equations that combine low-rank approximation in tensor formats and adaptive approximation in a basis. Under fairly general assumptions, we obtain a rigorous…

Numerical Analysis · Mathematics 2014-03-17 Markus Bachmayr , Wolfgang Dahmen

An analogue of the geometrical optics for description of the modal structure of a wave field in a range-dependent waveguide is considered. In the scope of this approach the mode amplitude is expressed through solutions of the ray equations.…

Atmospheric and Oceanic Physics · Physics 2009-11-10 A. L. Virovlyansky , A. Yu. Kazarova , L. Ya. Lyubavin

An adaptive finite element method is presented for the elastic scattering of a time-harmonic plane wave by a periodic surface. First, the unbounded physical domain is truncated into a bounded computational domain by introducing the…

Numerical Analysis · Mathematics 2016-05-30 Xue Jiang , Peijun Li , Junliang Lv , Weiying Zheng

We present a method of discrete modeling and analysis of multilevel dynamics of complex large-scale hierarchical dynamic systems subject to external dynamic control mechanism. Architectural model of information system supporting simulation…

Computational Engineering, Finance, and Science · Computer Science 2008-09-23 Armen Bagdasaryan

Learning on evolving(dynamic) graphs has caught the attention of researchers as static methods exhibit limited performance in this setting. The existing methods for dynamic graphs learn spatial features by local neighborhood aggregation,…

Machine Learning · Computer Science 2022-11-23 Anson Bastos , Abhishek Nadgeri , Kuldeep Singh , Toyotaro Suzumura , Manish Singh
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