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Critical questions in dynamical neuroscience and machine learning are related to the study of continuous-time neural networks and their stability, robustness, and computational efficiency. These properties can be simultaneously established…

Optimization and Control · Mathematics 2025-07-24 Alexander Davydov , Anton V. Proskurnikov , Francesco Bullo

We study the existence and approximation of fixed points of metrically nonspreading mappings and firmly metrically nonspreading mappings in Hadamard spaces. The resolvents of monotone operators satisfying range conditions are typical…

Functional Analysis · Mathematics 2019-10-01 Fumiaki Kohsaka

The proximal point algorithm is a widely used tool for solving a variety of convex optimization problems such as finding zeros of maximally monotone operators, fixed points of nonexpansive mappings, as well as minimizing convex functions.…

Optimization and Control · Mathematics 2018-04-19 Laurentiu Leustean , Adriana Nicolae , Andrei Sipos

In the framework of real Hilbert spaces, we investigate first-order dynamical systems governed by monotone and continuous operators. We demonstrate that when the monotone operator flow is augmented with a Tikhonov regularization term, the…

Optimization and Control · Mathematics 2025-04-29 Radu Ioan Bot , Dang-Khoa Nguyen

We study a specific family of symmetric norms on the algebra $\mathcal B(\mathcal H)$ of operators on a separable infinite-dimensional Hilbert space. With respect to each symmetric norm in this family the identity operator fails to attain…

Functional Analysis · Mathematics 2020-09-24 Satish K. Pandey

This paper studies the regularity problem for block uniformly elliptic operators in divergence form with complex bounded measurable coefficients. We consider the case where the boundary data belongs to Lebesgue spaces with weights in the…

Classical Analysis and ODEs · Mathematics 2020-10-14 Li Chen , José María Martell , Cruz Prisuelos-Arribas

We study several classes of non-Hermitian Hamiltonian systems, which can be expressed in terms of bilinear combinations of Euclidean Lie algebraic generators. The classes are distinguished by different versions of antilinear (PT)-symmetries…

Quantum Physics · Physics 2014-04-29 Sanjib Dey , Andreas Fring , Thilagarajah Mathanaranjan

Continuum limits of Laplace operators on general lattices are considered, and it is shown that these operators converge to elliptic operators on the Euclidean space in the sense of the generalized norm resolvent convergence. We then study…

Mathematical Physics · Physics 2024-10-02 Keita Mikami , Shu Nakamura , Yukihide Tadano

The principle underlying this paper is the basic observation that the problem of simultaneously solving a large class of composite monotone inclusions and their duals can be reduced to that of finding a zero of the sum of a maximally…

Optimization and Control · Mathematics 2010-11-29 L. Briceno-Arias , P. L. Combettes

We propose a forward-backward splitting dynamical system for solving inclusion problems of the form $0\in A(x)+B(x)$ in Hilbert spaces, where $A$ is a maximal operator and $B$ is a single-valued operator. Involved operators are assumed to…

Optimization and Control · Mathematics 2024-07-12 Nam V Tran , Hai T. T. Le , An V. Truong , Vuong T. Phan

Variational inequalities offer a versatile and straightforward approach to analyzing a broad range of equilibrium problems in both theoretical and practical fields. In this paper, we consider a composite generally non-monotone variational…

Optimization and Control · Mathematics 2025-02-06 Roman Emelyanov , Andrey Tikhomirov , Aleksandr Beznosikov , Alexander Gasnikov

We generalize Loewner's method for proving that matrix monotone functions are operator monotone. The relation x \leq y on bounded operators is our model for a definition for C*-relations of being residually finite dimensional. Our main…

Operator Algebras · Mathematics 2019-08-15 Terry A. Loring

We introduce a novel data-driven order reduction method for nonlinear control systems, drawing on recent progress in machine learning and statistical dimensionality reduction. The method rests on the assumption that the nonlinear system…

Optimization and Control · Mathematics 2011-06-15 Jake Bouvrie , Boumediene Hamzi

This paper addresses inverse problems (in a broad sense) for two classes of multivariate neural network (NN) operators, with particular emphasis on saturation results, and both analytical and semi-analytical inverse theorems. One of the key…

Functional Analysis · Mathematics 2025-05-13 Danilo Costarelli

We study Birkhoff-James orthogonality of compact (bounded) linear operators between Hilbert spaces and Banach spaces. Applying the notion of semi-inner-products in normed linear spaces and some related geometric ideas, we generalize and…

Functional Analysis · Mathematics 2018-10-12 Debmalya Sain , Kallol Paul , Arpita Mal

A simple proof is provided to show that any bounded normal operator on a real Hilbert space is orthogonally equivalent to its transpose(adjoint). A structure theorem for invertible skew-symmetric operators, which is analogous to the finite…

Spectral Theory · Mathematics 2020-04-21 B V Rajarama Bhat , Tiju Cherian John

We prove comparison principles for nonlinear potential theories in euclidian spaces in a very straightforward manner from duality and monotonicity. We shall also show how to deduce comparison principles for nonlinear differential operators,…

Analysis of PDEs · Mathematics 2020-09-04 Marco Cirant , F. Reese Harvey , H. Blaine Lawson, , Kevin R. Payne

We consider the monotone inclusion problems in real Hilbert spaces. Proximal splitting algorithms are very popular technique to solve it and generally achieve weak convergence under mild assumptions. Researchers assume the strong conditions…

Optimization and Control · Mathematics 2022-05-05 Avinash Dixit , D. R. Sahu , Pankaj Gautam , T. Som

In the framework of inverse linear problems on infinite-dimensional Hilbert space, we prove the convergence of the conjugate gradient iterates to an exact solution to the inverse problem in the most general case where the self-adjoint,…

Numerical Analysis · Mathematics 2021-11-18 Noe Caruso , Alessandro Michelangeli

We present the first numerical implementation of a non-perturbative renormalization method for lattice operators, based on the study of correlation functions in coordinate space at short Euclidean distance. The method is applied to compute…

High Energy Physics - Lattice · Physics 2009-11-10 V. Gimenez , L. Giusti , S. Guerriero , V. Lubicz , G. Martinelli , S. Petrarca , J. Reyes , B. Taglienti , E. Trevigne
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