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This chapter presents a dynamical systems point of view of the study of systems with delays. The focus is on how advanced tools from bifurcation theory, as implemented for example in the package DDE-BIFTOOL, can be applied to the study of…

Dynamical Systems · Mathematics 2021-08-06 Bernd Krauskopf , Jan Sieber

Mathematical modeling based on time-delay differential equations is an important tool to study the role of delay in biological systems and to evaluate its impact on the asymptotic behavior of their dynamics. Delays are indeed found in many…

Dynamical Systems · Mathematics 2022-03-25 Abdelmalik Moujahid , Fernando Vadillo

Delayed processes are ubiquitous in biological systems and are often characterized by delay differential equations (DDEs) and their extension to include stochastic effects. DDEs do not explicitly incorporate intermediate states associated…

Quantitative Methods · Quantitative Biology 2016-09-28 Jingchen Feng , Stuart Sevier , Bin Huang , Dongya Jia , Herbert Levine

DDEBIFTOOL is a collection of Matlab routines for numerical bifurcation analysis of systems of delay differential equations with discrete constant and state-dependent delays. The package supports continuation and stability analysis of…

Dynamical Systems · Mathematics 2016-09-07 Jan Sieber , Koen Engelborghs , Tatyana Luzyanina , Giovanni Samaey , Dirk Roose

A common task when analysing dynamical systems is the determination of normal forms near local bifurcations of equilibria. As most of these normal forms have been classified and analysed, finding which particular class of normal form one…

Dynamical Systems · Mathematics 2017-12-14 Jan Sieber

Mathematical modelling allows us to concisely describe fundamental principles in biology. Analysis of models can help to both explain known phenomena, and predict the existence of new, unseen behaviours. Model analysis is often a complex…

Quantitative Methods · Quantitative Biology 2020-08-13 Mark Blyth , Ludovic Renson , Lucia Marucci

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

Delays in biological systems may be used to model events for which the underlying dynamics cannot be precisely observed. Mathematical modeling of biological systems with delays is usually based on Delay Differential Equations (DDEs), a kind…

Quantitative Methods · Quantitative Biology 2009-10-08 Roberto Barbuti , Giulio Caravagna , Paolo Milazzo , Andrea Maggiolo-Schettini

A discrete delay is included to model the time between the capture of the prey and its conversion to viable biomass in the simplest classical Gause type predator-prey model that has equilibrium dynamics without delay. As the delay increases…

Dynamical Systems · Mathematics 2020-08-03 Guihong Fan , Gail S. K. Wolkowicz

Boolean Delay Equations (BDEs) are semi-discrete dynamical models with Boolean-valued variables that evolve in continuous time. Systems of BDEs can be classified into conservative or dissipative, in a manner that parallels the…

Cellular Automata and Lattice Gases · Physics 2015-06-26 Michael Ghil , Ilya Zaliapin , Barbara Coluzzi

The numerical convergence of a Telegraph Predator-Prey system is studied. This system of partial differential equations (PDEs) can describe various biological systems with reactive, diffusive and delay effects. Initially, our problem is…

Discontinuities and delayed terms are encountered in the governing equations of a large class of problems ranging from physics and engineering to medicine and economics. These systems cannot be properly modelled and simulated with standard…

Artificial Intelligence · Computer Science 2024-09-27 Thibault Monsel , Onofrio Semeraro , Lionel Mathelin , Guillaume Charpiat

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

In the paper an efficient semi-analytical approach based on the method of steps and differential transformation is proposed for numerical approximation of solutions of retarded logistic models of delayed and neutral type, including models…

Numerical Analysis · Mathematics 2019-01-14 Josef Rebenda , Zdeněk Šmarda

Delay differential equations (DDEs) with large delays play a pivotal role in understanding stability and bifurcations in systems ranging from neural networks to laser dynamics. While prior work has extensively studied DDEs with discrete…

Dynamical Systems · Mathematics 2025-09-09 Isam Al-Darabsah , Sue Ann Campbell , Bootan Rahman

A delayed term in a differential equation reflects the fact that information takes significant time to travel from one place to another within a process being studied. Despite de apparent similarity with ordinary differential equations,…

Dynamical Systems · Mathematics 2023-08-24 Gregory Kozyreff

Pseudospectral approximation reduces DDE (delay differential equations) to ODE (ordinary differential equations). Next one can use ODE tools to perform a numerical bifurcation analysis. By way of an example we show that this yields an…

Dynamical Systems · Mathematics 2021-06-03 Babette de Wolff , Francesca Scarabel , Sjoerd Verduyn Lunel , Odo Diekmann

Time delays are ubiquitous in industry and nature, and they significantly affect both transient dynamics and stability properties. Consequently, it is often necessary to identify and account for the delays when, e.g., designing a…

Dynamical Systems · Mathematics 2024-05-14 Tobias K. S. Ritschel , John Wyller

To model time series accurately is important within a wide range of fields. As the world is generally too complex to be modelled exactly, it is often meaningful to assess the probability of a dynamical system to be in a specific state. This…

Machine Learning · Computer Science 2023-03-16 Mari Dahl Eggen , Alise Danielle Midtfjord

Fractional Differential Equations (FDEs) are essential tools for modelling complex systems in science and engineering. They extend the traditional concepts of differentiation and integration to non-integer orders, enabling a more precise…

Machine Learning · Computer Science 2025-03-27 C. Coelho , M. Fernanda P. Costa , L. L. Ferrás
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