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In this paper, we study the asymptotic behavior of the solutions of nonlocal bistable reaction-diffusion equations starting from compactly supported initial conditions. Depending on the relationship between the nonlinearity, the interaction…

Analysis of PDEs · Mathematics 2022-01-19 Christophe Besse , Alexandre Capel , Grégory Faye , Guilhem Fouilhé

This paper concerns the problem of adaptive output regulation for multivariable nonlinear systems in normal form. We present a regulator employing an adaptive internal model of the exogenous signals based on the theory of nonlinear…

Systems and Control · Electrical Eng. & Systems 2020-09-16 Michelangelo Bin , Pauline Bernard , Lorenzo Marconi

In this work, we investigate the inverse problem of determining the kernel functions that best describe the mechanical behavior of a complex medium modeled by a general nonlocal viscoelastic wave equation. To this end, we minimize a…

Estimation of solution norms and stability for time-dependent nonlinear systems is ubiquitous in numerous applied and control problems. Yet, practically valuable results are rare in this area. This paper develops a novel approach, which…

Dynamical Systems · Mathematics 2018-08-29 Mark A. Pinsky , Steve Koblik

Robustness guarantees are important properties to be looked for during control design. They ensure stability of closed-loop systems in face of uncertainties, unmodeled effects and bounded disturbances. While the theory on robust stability…

Systems and Control · Electrical Eng. & Systems 2022-10-10 Samuele Zoboli , Daniele Astolfi , Vincent Andrieu

We study the higher H\"older regularity of local weak solutions to a class of nonlinear nonlocal elliptic equations with kernels that satisfy a mild continuity assumption. An interesting feature of our main result is that the obtained…

Analysis of PDEs · Mathematics 2021-01-19 Simon Nowak

Nonlocal operators with integral kernels have become a popular tool for designing solution maps between function spaces, due to their efficiency in representing long-range dependence and the attractive feature of being resolution-invariant.…

Machine Learning · Statistics 2022-05-24 Fei Lu , Qingci An , Yue Yu

Coherent structures are solutions to reaction-diffusion systems that are time-periodic in an appropriate moving frame and spatially asymptotic at $x=\pm\infty$ to spatially periodic travelling waves. This paper is concerned with sources…

Analysis of PDEs · Mathematics 2015-05-27 Margaret Beck , Toan Nguyen , Bjorn Sandstede , Kevin Zumbrun

This paper considers a large class of nonlinear integro-differential scalar equations which involve an anomalous diffusion (e.g. driven by a fractional Laplacian) and a non-local singular convolution kernel. Each of those singular equations…

Probability · Mathematics 2025-01-07 Christian Olivera , Marielle Simon

Finding accurate reduced descriptions for large, complex, dynamically evolving networks is a crucial enabler to their simulation, analysis, and, ultimately, design. Here we propose and illustrate a systematic and powerful approach to…

Chaotic Dynamics · Physics 2017-05-02 Tom Bertalan , Yan Wu , Carlo Laing , C. William Gear , Ioannis G. Kevrekidis

We deal with a class of semilinear nonlocal differential equations in Hilbert spaces which is a general model for some anomalous diffusion equations. By using the theory of integral equations with completely positive kernel together with…

Analysis of PDEs · Mathematics 2018-12-07 Tran Dinh Ke , Nguyen Nhu Thang , Lam Tran Phuong Thuy

We study identification and inference in nonlinear dynamic systems defined on unknown interaction networks. The system evolves through an unobserved dependence matrix governing cross-sectional shock propagation via a nonlinear operator. We…

Machine Learning · Statistics 2026-04-08 Diego Vallarino

Inspired by classical sensitivity results for nonlinear optimization, we derive and discuss new quantitative bounds to characterize the solution map and dual variables of a parametrized nonlinear program. In particular, we derive explicit…

Optimization and Control · Mathematics 2020-06-19 Irina Subotić , Adrian Hauswirth , Florian Dörfler

We examine robust output feedback control of discrete-time nonlinear systems with bounded uncertainties affecting the dynamics and measurements. Specifically, we demonstrate how to construct semi-infinite programs that produce gains to…

Systems and Control · Electrical Eng. & Systems 2024-09-16 Jad Wehbeh , Eric C. Kerrigan

This paper is devoted to prove the existence of positive solutions of a second order differential equation with a nonhomogeneous Dirichlet conditions given by a parameter dependence integral. The studied problem is a nonlocal perturbation…

Classical Analysis and ODEs · Mathematics 2021-04-15 Alberto Cabada , Javier Iglesias

Nonlinear Programs (NLPs) are prevalent in optimization-based control of nonlinear systems. Solving general NLPs is computationally expensive, necessitating the development of fast hardware or tractable suboptimal approximations. This paper…

Systems and Control · Electrical Eng. & Systems 2024-06-05 Leila Gharavi , Changrui Liu , Bart De Schutter , Simone Baldi

Two approaches to incorporate heterogeneity in discrete models are compared. In the first, standard approach, the heterogeneity is dictated by geometrical structure of the discrete system. In the second approach, the heterogeneity is…

Computational Engineering, Finance, and Science · Computer Science 2025-06-26 Jan Raisinger , Qiwei Zhang , John E. Bolander , Jan Eliáš

We prove a higher regularity result for weak solutions to nonlinear nonlocal equations along the integrability scale of Bessel potential spaces $H^{s,p}$ under a mild continuity assumption on the kernel. By embedding, this also yields…

Analysis of PDEs · Mathematics 2020-08-13 Simon Nowak

We study the local behavior of weak solutions, with possible singularities, of nonlocal nonlinear equations. We first prove that sets of capacity zero are removable for weak solutions under certain integrability conditions. We then…

Analysis of PDEs · Mathematics 2025-07-09 Minhyun Kim , Se-Chan Lee

Recent articles indicate that deep neural networks are efficient models for various learning problems. However they are often highly sensitive to various changes that cannot be detected by an independent observer. As our understanding of…

Machine Learning · Computer Science 2020-06-15 Bálint Daróczy