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Rough set theory is a new mathematical approach to imperfect knowledge. The notion of rough sets is generalized by using an arbitrary binary relation on attribute values in information systems, instead of the trivial equality relation. The…

General Mathematics · Mathematics 2015-02-24 M. Abo-Elhamayel

An implicit Euler finite-volume scheme for general cross-diffusion systems with volume-filling constraints is proposed and analyzed. The diffusion matrix may be nonsymmetric and not positive semidefinite, but the diffusion system is assumed…

Numerical Analysis · Mathematics 2021-05-13 Ansgar Jüngel , Antoine Zurek

Given $N\ge2$ closed subspaces $M_1,\dotsc, M_N$ of a Hilbert space $X$, let $P_k$ denote the orthogonal projection onto $M_k$, $1\le k\le N$. It is known that the sequence $(x_n)$, defined recursively by $x_0=x$ and $x_{n+1}=P_N\cdots…

Functional Analysis · Mathematics 2019-02-14 Catalin Badea , David Seifert

Problems of particle dynamics involving unsteady Stokes flows in confined geometries are typically harder to solve than their steady counterparts. Approximation techniques are often the only resort. Felderhof (see e.g. 2005, 2009b) has…

Fluid Dynamics · Physics 2018-04-04 Akarsh Simha , Jianyong Mo , Philip J. Morrison

In two dimensions, Gallagher's theorem is a strengthening of the Littlewood conjecture that holds for almost all pairs of real numbers. We prove an inhomogeneous fibre version of Gallagher's theorem, sharpening and making unconditional a…

Number Theory · Mathematics 2018-07-18 Sam Chow

Over the years a number of topologies for the set of laws of stochastic processes have been proposed. Building on the weak topology they all aim to capture more accurately the temporal structure of the processes. In a parallel paper we show…

Probability · Mathematics 2019-05-03 Manu Eder

We consider large linear and nonlinear fixed point problems, and solution with proximal algorithms. We show that there is a close connection between two seemingly different types of methods from distinct fields: 1) Proximal iterations for…

Numerical Analysis · Computer Science 2019-09-05 Dimitri P. Bertsekas

While dynamic policies have historically formed the foundation of most influential papers dedicated to the joint replenishment problem, we are still facing profound gaps in our structural understanding of optimal such policies as well as in…

Data Structures and Algorithms · Computer Science 2025-06-24 Danny Segev

We study the time it takes for all states of a finite quantum system to return simultaneously to their original configuration. In particular, we define the recurrence time for a quantum system to be the time at which all time-evolved states…

Quantum Physics · Physics 2026-04-29 Chaitanya Gupta , Anthony J. Short

By introducing the self-energy density functionals for the dissipative interactions between the reduced system and its environment, we develop a time-dependent density-functional theory formalism based on an equation of motion for the…

Quantum Physics · Physics 2009-11-13 Xiao Zheng , Fan Wang , Chi Yung Yam , Yan Mo , GuanHua Chen

Estimating the mixing density of a mixture distribution remains an interesting problem in statistics literature. Using a stochastic approximation method, Newton and Zhang (1999) introduced a fast recursive algorithm for estimating the…

Statistics Theory · Mathematics 2022-03-29 Nilabja Guha , Anindya Roy

Using the methods from topological dynamics, H. Furstenberg introduced the notions of Central sets and proved the famous Central Sets Theorem which is the simultaneous extension of the van der Waerden and Hindman Theorem. Later N. Hindman…

Dynamical Systems · Mathematics 2024-06-26 Pintu Debnath , Sayan Goswami , Sourav Kanti Patra

This paper introduces a new asymptotic regime for simplifying stochastic models having non-stationary effects, such as those that arise in the presence of time-of-day effects. This regime describes an operating environment within which the…

Probability · Mathematics 2018-07-19 Zeyu Zheng , Harsha Honnappa , Peter W. Glynn

One of the most influential results in neural network theory is the universal approximation theorem [1, 2, 3] which states that continuous functions can be approximated to within arbitrary accuracy by single-hidden-layer feedforward neural…

Machine Learning · Computer Science 2021-12-16 Clemens Hutter , Recep Gül , Helmut Bölcskei

Motivated by Furstenberg's Theorem on sets in the circle invariant under multiplication by a non-lacunary semigroup, we define a general class of dynamical systems possessing similar topological dynamical properties. We call such systems…

Dynamical Systems · Mathematics 2024-05-10 Van Cyr , Bryna Kra , Scott Schmieding

In this paper, we study the metric theory of dyadic approximation in the middle-third Cantor set. This theory complements earlier work of Levesley, Salp, and Velani (2007), who investigated the problem of approximation in the Cantor set by…

Number Theory · Mathematics 2020-05-20 Demi Allen , Sam Chow , Han Yu

We investigate stochastic averaging theory for locally Lipschitz discrete-time nonlinear systems with stochastic perturbation and its applications to convergence analysis of discrete-time stochastic extremum seeking algorithms. Firstly, by…

Optimization and Control · Mathematics 2015-02-18 Shu-Jun Liu , Miroslav Krstic

We quantify the density of rational points in the unit sphere $S^n$, proving analogues of the classical theorems on the embedding of $\q^n$ into $\r^n$. Specifically, we prove a Dirichlet theorem stating that every point $\alpha \in S^n$ is…

Number Theory · Mathematics 2013-05-28 Dmitry Kleinbock , Keith Merrill

In 1995, Hill and Velani introduced the shrinking targets theory. Given a dynamical system $([0,1],T)$, they investigated the Hausdorff dimension of sets of points whose orbits are close to some fixed point. In this paper, we study the sets…

Dynamical Systems · Mathematics 2011-11-07 Lingmin Liao , Stephane Seuret

We consider again the fast-slow motions setups in the continuous time $\frac {dX_N(t)}{dt}=N^{1/2} \sig(X_N(t))(\xi(tN))+b(X_N(t)),\, t\in [0,T]$ and the discrete time $X_N((n+1)/N)=X_N(n/N)+N^{-1/2}\sig(X_N(n/N))\xi(n)+N^{-1}b(X_N(n/N)),\,…

Probability · Mathematics 2025-06-09 Yuri Kifer