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Self-regulatory models are common in nature, as described e.g. in (\cite{mur}), (\cite{ha}) and (\cite{Gb}).\\ Let us consider a system made up of a number of glands as a motivation. Each gland secretes a hormone that allows secretion in…

Dynamical Systems · Mathematics 2016-10-28 Pablo Amster , Carlos Alliera

Many biological systems are governed by difference equations and exhibit discrete-time dynamics. Examples include the size of a population when generations are non-overlapping, and the incidence of a disease when infections are recorded at…

Populations and Evolution · Quantitative Biology 2025-09-25 Shuyun Jiao , David Waxman

In this paper, we present error estimates of fully discrete Runge--Kutta discontinuous Galerkin (DG) schemes for linear time-dependent partial differential equations. The analysis applies to explicit Runge--Kutta time discretizations of any…

Numerical Analysis · Mathematics 2020-01-07 Zheng Sun , Chi-Wang Shu

This paper proposes two nonlinear dynamics to solve constrained distributed optimization problem for resource allocation over a multi-agent network. In this setup, coupling constraint refers to resource-demand balance which is preserved at…

Systems and Control · Electrical Eng. & Systems 2023-10-30 Mohammadreza Doostmohammadian , Alireza Aghasi , Maria Vrakopoulou , Hamid R. Rabiee , Usman A. Khan , Themistoklis Charalambou

Delay-coupled networks are investigated with nonidentical delay times and the effects of such heterogeneity on the emergent dynamics of complex systems are characterized. A simple decomposition method is presented that decouples the…

Adaptation and Self-Organizing Systems · Physics 2017-04-25 Róbert Szalai , Gábor Orosz

One of the most widely used methods for solving large-scale stochastic optimization problems is distributed asynchronous stochastic gradient descent (DASGD), a family of algorithms that result from parallelizing stochastic gradient descent…

Optimization and Control · Mathematics 2021-07-08 Zhengyuan Zhou , Panayotis Mertikopoulos , Nicholas Bambos , Peter W. Glynn , Yinyu Ye

Complex dynamical networks appear in a wide range of physical, biological, and engineering systems. The coupling of subsystems with varying time scales often results in multirate behavior. During the simulation of highly integrated…

Numerical Analysis · Mathematics 2015-04-27 Stefan Klus

We address in this paper the approximation problem of distributed delays. Such elements are convolution operators with kernel having bounded support, and appear in the control of time-delay systems. From the rich literature on this topic,…

Optimization and Control · Mathematics 2010-09-10 Hao Lu , Michael Di Loreto , Damien Eberard , Jean-Pierre Simon

There exist excellent codes for an efficient numerical treatment of stiff and differential-algebraic problems. Let us mention {\sc Radau5} which is based on the $3$-stage Radau IIA collocation method, and its extension to problems with…

Numerical Analysis · Mathematics 2024-01-23 Nicola Guglielmi , Ernst Hairer

To improve the utility of learning applications and render machine learning solutions feasible for complex applications, a substantial amount of heavy computations is needed. Thus, it is essential to delegate the computations among several…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-04-29 Homa Esfahanizadeh , Alejandro Cohen , Muriel Medard

We develop an approximate theoretical method to study discrete stochastic birth and death models that include a delay time. We analyze the effect of the delay in the fluctuations of the system and obtain that it can qualitatively alter…

Statistical Mechanics · Physics 2012-09-24 Luis F. Lafuerza , Raul Toral

We develop and analyze an asynchronous algorithm for distributed convex optimization when the objective writes a sum of smooth functions, local to each worker, and a non-smooth function. Unlike many existing methods, our distributed…

Optimization and Control · Mathematics 2019-12-13 Konstantin Mishchenko , Franck Iutzeler , Jérôme Malick

Learning dynamical systems through purely data-driven methods is challenging as they do not learn the underlying conservation laws that enable them to correctly generalize. Existing port-Hamiltonian neural network methods have recently been…

Machine Learning · Computer Science 2026-02-18 Maximino Linares , Guillaume Doras , Thomas Hélie

Analytic, first-principles performance modeling of distributed-memory applications is difficult due to a wide spectrum of random disturbances caused by the application and the system. These disturbances (commonly called "noise") destroy the…

Performance · Computer Science 2020-06-25 Ayesha Afzal , Georg Hager , Gerhard Wellein

Linear scalar differential equations with distributed delays appear in the study of the local stability of nonlinear differential equations with feedback, which are common in biology and physics. Negative feedback loops tend to promote…

Dynamical Systems · Mathematics 2009-10-26 Samuel Bernard

Classical distributed estimation scenarios typically assume timely and reliable exchanges of information over the sensor network. This paper, in contrast, considers single time-scale distributed estimation via a sensor network subject to…

Systems and Control · Electrical Eng. & Systems 2021-09-08 Mohammadreza Doostmohammadian , Usman A. Khan , Mohammad Pirani , Themistoklis Charalambous

This paper proposes methods to handle the problem of delay range stability analysis for a linear coupled differential-difference system (CDDS) with distributed delays subject to dissipative constraints. The model of linear CDDS contains…

Systems and Control · Computer Science 2018-06-21 Qian Feng , Sing Kiong Nguang

In this paper we present a new method for deriving It\^{o} stochastic delay differential equations (SDDEs) from delayed chemical master equations (DCMEs). Considering alternative formulations of SDDEs that can be derived from the same DCME,…

Chaotic Dynamics · Physics 2023-05-09 F. Fatehi , Y. N. Kyrychko , K. B. Blyuss

Parallel multiphysics simulations often suffer from load imbalances originating from the applied coupling of algorithms with spatially and temporally varying workloads. It is thus desirable to minimize these imbalances to reduce the time to…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-12-03 Christoph Rettinger , Ulrich Rüde

Proposed to study the dynamics of physiological systems in which the evolution depends on the state in a previous time, the Mackey-Glass model exhibits a rich variety of behaviors including periodic or chaotic solutions in vast regions of…

Disordered Systems and Neural Networks · Physics 2021-12-22 Juan P. Tarigo , Cecilia Stari , Cecilia Cabeza , Arturo C. Marti