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Interval-valued computing is a relatively new computing paradigm. It uses finitely many interval segments over the unit interval in a computation as data structure. The satisfiability of Quantified Boolean formulae and other hard problems,…

Data Structures and Algorithms · Computer Science 2014-04-02 Benedek Nagy , Sándor Vályi

In this paper, we propose a method for computing eigenvalues of elliptic problems using Deep Learning techniques. A key feature of our approach is that it is independent of the space dimension and can compute arbitrary eigenvalues without…

Numerical Analysis · Mathematics 2026-03-04 Julian Fernandez Bonder , Ariel M. Salort

We study stochastic delay differential equations (SDDE) where the coefficients depend on the moving averages of the state process. As a first contribution, we provide sufficient conditions under which a linear path functional of the…

Probability · Mathematics 2013-10-17 Salvatore Federico , Peter Tankov

In this paper the author introduces a new domain decomposition method for the solution of discretised integral equation eigenvalue problems. The new domain decomposition method is motivated by the so-called automated multi-level…

Numerical Analysis · Mathematics 2017-12-29 Peter Gerds

The iterative diagonalization of a sequence of large ill-conditioned generalized eigenvalue problems is a computational bottleneck in quantum mechanical methods employing a nonorthogonal basis for {\em ab initio} electronic structure…

Materials Science · Physics 2013-08-13 Yunfeng Cai , Zhaojun Bai , John E. Pask , N. Sukumar

Partial differential equation (PDE) models are widely used in engineering and natural sciences to describe spatio-temporal processes. The parameters of the considered processes are often unknown and have to be estimated from experimental…

Numerical Analysis · Mathematics 2016-12-21 Romana Boiger , Jan Hasenauer , Sabrina Hross , Barbara Kaltenbacher

This paper is a tutorial for eigenvalue and generalized eigenvalue problems. We first introduce eigenvalue problem, eigen-decomposition (spectral decomposition), and generalized eigenvalue problem. Then, we mention the optimization problems…

Machine Learning · Statistics 2023-05-23 Benyamin Ghojogh , Fakhri Karray , Mark Crowley

In this paper, we discuss the solution of certain matrix-valued partial differential equations. Such PDEs arise, for example, when constructing a Riemannian contraction metric for a dynamical system given by an autonomous ODE. We develop…

Numerical Analysis · Mathematics 2017-06-29 Peter Giesl , Holger Wendland

Partial Integral Equations (PIEs) have been used to represent both systems with delay and systems of Partial Differential Equations (PDEs) in one or two spatial dimensions. In this paper, we show that these results can be combined to obtain…

Optimization and Control · Mathematics 2024-06-18 Declan S. Jagt , Matthew M. Peet

Delay-Differential Equations (DDEs) are the most common representation for systems with delay. However, the DDE representation is limited. In network models with delay, the delayed channels are low-dimensional and accounting for this…

Optimization and Control · Mathematics 2020-12-21 Matthew M. Peet

Understanding how time delays impact the stability of a delay differential equation is important for modeling many natural and technological systems that experience time delays. Here we introduce a new stability criterion for…

Dynamical Systems · Mathematics 2025-08-25 Quinlan Leishman , Benjamin Webb

We consider the identification of a scalar coefficient in a PDE-based parameter estimation problem with contact constraints. The considered problem can be used as an idealized model of a membrane under forces, constrained by a barrier or…

Numerical Analysis · Mathematics 2026-05-12 Simon Hubmer , Stefan Kindermann , Ekaterina Sherina

The conjoining of dynamical systems and deep learning has become a topic of great interest. In particular, neural differential equations (NDEs) demonstrate that neural networks and differential equation are two sides of the same coin.…

Machine Learning · Computer Science 2022-02-08 Patrick Kidger

This article revisits the approximation problem of systems of nonlinear delay differential equations (DDEs) by a set of ordinary differential equations (ODEs). We work in Hilbert spaces endowed with a natural inner product including a point…

Chaotic Dynamics · Physics 2015-09-11 Mickaël D. Chekroun , Michael Ghil , Honghu Liu , Shouhong Wang

The intersection of machine learning and dynamical systems has generated considerable interest recently. Neural Ordinary Differential Equations (NODEs) represent a rich overlap between these fields. In this paper, we develop a continuous…

Optimization and Control · Mathematics 2023-06-16 Maria Oprea , Mark Walth , Robert Stephany , Gabriella Torres Nothaft , Arnaldo Rodriguez-Gonzalez , William Clark

Partial Differential Equations (PDEs) are central to science and engineering. Since solving them is computationally expensive, a lot of effort has been put into approximating their solution operator via both traditional and recently…

Machine Learning · Computer Science 2025-02-14 Alessandro Longhi , Danny Lathouwers , Zoltán Perkó

The solvability and stability analysis of linear time invariant systems of delay differential-algebraic equations (DDAEs) is analyzed. The behavior approach is applied to DDAEs in order to establish characterizations of their solvability in…

Dynamical Systems · Mathematics 2020-05-13 Phi Ha

We present a computational method for studying transverse homoclinic orbits for periodic solutions of delay differential equations, a phenomenon that we refer to as the \emph{Poincar\'{e} scenario}. The strategy is geometric in nature, and…

Dynamical Systems · Mathematics 2023-10-17 Olivier Hénot , Jean-Philippe Lessard , Jason D. Mireles James

The pseudospectra of a linear time-invariant system are the sets in the complex plane consisting of all the roots of the characteristic equation when the system matrices are subjected to all possible perturbations with a given upper bound.…

Systems and Control · Electrical Eng. & Systems 2020-03-11 Suat Gumussoy , Wim Michiels

Time delays are ubiquitous in industrial processes, and they must be accounted for when designing control algorithms because they have a significant effect on the process dynamics. Therefore, in this work, we propose a simultaneous approach…

Optimization and Control · Mathematics 2024-10-22 Tobias K. S. Ritschel
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