MATCONT: A MATLAB package for numerical bifurcation analysis of ODEs
TL;DR: The sparsity of the discretized systems for the computation of limit cycles and their bifurcation points is exploited by using the standard Matlab sparse matrix methods.
Abstract: MATCONT is a graphical MATLAB software package for the interactive numerical study of dynamical systems. It allows one to compute curves of equilibria, limit points, Hopf points, limit cycles, period doubling bifurcation points of limit cycles, and fold bifurcation points of limit cycles. All curves are computed by the same function that implements a prediction-correction continuation algorithm based on the Moore-Penrose matrix pseudo-inverse. The continuation of bifurcation points of equilibria and limit cycles is based on bordering methods and minimally extended systems. Hence no additional unknowns such as singular vectors and eigenvectors are used and no artificial sparsity in the systems is created. The sparsity of the discretized systems for the computation of limit cycles and their bifurcation points is exploited by using the standard Matlab sparse matrix methods. The MATLAB environment makes the standard MATLAB Ordinary Differential Equations (ODE) Suite interactively available and provides computational and visualization tools; it also eliminates the compilation stage and so makes installation straightforward. Compared to other packages such as AUTO and CONTENT, adding a new type of curves is easy in the MATLAB environment. We illustrate this by a detailed description of the limit point curve type.
Citations
More filters
TL;DR: This survey of different types of MMOs is given, concentrating its analysis on MMOs whose small-amplitude oscillations are produced by a local, multiple-time-scale “mechanism.”
Abstract: Mixed-mode oscillations (MMOs) are trajectories of a dynamical system in which there is an alternation between oscillations of distinct large and small amplitudes. MMOs have been observed and studied for over thirty years in chemical, physical, and biological systems. Few attempts have been made thus far to classify different patterns of MMOs, in contrast to the classification of the related phenomena of bursting oscillations. This paper gives a survey of different types of MMOs, concentrating its analysis on MMOs whose small-amplitude oscillations are produced by a local, multiple-time-scale “mechanism.” Recent work gives substantially improved insight into the mathematical properties of these mechanisms. In this survey, we unify diverse observations about MMOs and establish a systematic framework for studying their properties. Numerical methods for computing different types of invariant manifolds and their intersections are an important aspect of the analysis described in this paper.
509 citations
TL;DR: Software issues that are in practice important for many users, e.g. how to define a new system starting from an existing one, how to import and export data, system descriptions, and computed results are discussed.
Abstract: Bifurcation software is an essential tool in the study of dynamical systems. From the beginning (the first packages were written in the 1970's) it was also used in the modelling process, in particular to determine the values of critical parameters. More recently, it is used in a systematic way in the design of dynamical models and to determine which parameters are relevant. MatCont and Cl_MatCont are freely available matlab numerical continuation packages for the interactive study of dynamical systems and bifurcations. MatCont is the GUI-version, Cl_MatCont is the command-line version. The work started in 2000 and the first publications appeared in 2003. Since that time many new functionalities were added. Some of these are fairly simple but were never before implemented in continuation codes, e.g. Poincare maps. Others were only available as toolboxes that can be used by experts, e.g. continuation of homoclinic orbits. Several others were never implemented at all, such as periodic normal forms for codimension 1 bifurcations of limit cycles, normal forms for codimension 2 bifurcations of equilibria, detection of codimension 2 bifurcations of limit cycles, automatic computation of phase response curves and their derivatives, continuation of branch points of equilibria and limit cycles. New numerical algorithms for these computations have been published or will appear elsewhere; here we restrict to their software implementation. We further discuss software issues that are in practice important for many users, e.g. how to define a new system starting from an existing one, how to import and export data, system descriptions, and computed results.
398 citations
Cites methods from "MATCONT: A MATLAB package for numer..."
...The adapt system is a very simple model from adaptive control considered as a test example in [12]....
[...]
...MATCONT [12] is an interactive bifurcation environment in MATLAB that is based on CL_MATCONT....
[...]
TL;DR: In this paper, the authors present a survey of the key developments which arose in the field since 2006, and illustrate state-of-the-art techniques using a real-world satellite structure.
353 citations
TL;DR: A predator–prey model incorporating the cost of fear into prey reproduction is proposed, which shows that high levels of fear can stabilize the predator-prey system by excluding the existence of periodic solutions, but relatively low levels ofFear can induce multiple limit cycles via subcritical Hopf bifurcations, leading to a bi-stability phenomenon.
Abstract: A recent field manipulation on a terrestrial vertebrate showed that the fear of predators alone altered anti-predator defences to such an extent that it greatly reduced the reproduction of prey. Because fear can evidently affect the populations of terrestrial vertebrates, we proposed a predator-prey model incorporating the cost of fear into prey reproduction. Our mathematical analyses show that high levels of fear (or equivalently strong anti-predator responses) can stabilize the predator-prey system by excluding the existence of periodic solutions. However, relatively low levels of fear can induce multiple limit cycles via subcritical Hopf bifurcations, leading to a bi-stability phenomenon. Compared to classic predator-prey models which ignore the cost of fear where Hopf bifurcations are typically supercritical, Hopf bifurcations in our model can be both supercritical and subcritical by choosing different sets of parameters. We conducted numerical simulations to explore the relationships between fear effects and other biologically related parameters (e.g. birth/death rate of adult prey), which further demonstrate the impact that fear can have in predator-prey interactions. For example, we found that under the conditions of a Hopf bifurcation, an increase in the level of fear may alter the direction of Hopf bifurcation from supercritical to subcritical when the birth rate of prey increases accordingly. Our simulations also show that the prey is less sensitive in perceiving predation risk with increasing birth rate of prey or increasing death rate of predators, but demonstrate that animals will mount stronger anti-predator defences as the attack rate of predators increases.
300 citations
TL;DR: In this article, a set of mathematical tools that are suitable for addressing the dynamics of oscillatory neural networks, broadening from a standard phase oscillator perspective to provide a practical framework for further successful applications of mathematics to understand network dynamics in neuroscience.
Abstract: The tools of weakly coupled phase oscillator theory have had a profound impact on the neuroscience community, providing insight into a variety of network behaviours ranging from central pattern generation to synchronisation, as well as predicting novel network states such as chimeras. However, there are many instances where this theory is expected to break down, say in the presence of strong coupling, or must be carefully interpreted, as in the presence of stochastic forcing. There are also surprises in the dynamical complexity of the attractors that can robustly appear—for example, heteroclinic network attractors. In this review we present a set of mathematical tools that are suitable for addressing the dynamics of oscillatory neural networks, broadening from a standard phase oscillator perspective to provide a practical framework for further successful applications of mathematics to understanding network dynamics in neuroscience.
259 citations
References
More filters
Book•
01 Aug 1983TL;DR: In this article, the authors introduce differential equations and dynamical systems, including hyperbolic sets, Sympolic Dynamics, and Strange Attractors, and global bifurcations.
Abstract: Contents: Introduction: Differential Equations and Dynamical Systems.- An Introduction to Chaos: Four Examples.- Local Bifurcations.- Averaging and Perturbation from a Geometric Viewpoint.- Hyperbolic Sets, Sympolic Dynamics, and Strange Attractors.- Global Bifurcations.- Local Codimension Two Bifurcations of Flows.- Appendix: Suggestions for Further Reading. Postscript Added at Second Printing. Glossary. References. Index.
12,669 citations
01 Jan 2015
TL;DR: In this paper, the authors introduce differential equations and dynamical systems, including hyperbolic sets, Sympolic Dynamics, and Strange Attractors, and global bifurcations.
Abstract: Contents: Introduction: Differential Equations and Dynamical Systems.- An Introduction to Chaos: Four Examples.- Local Bifurcations.- Averaging and Perturbation from a Geometric Viewpoint.- Hyperbolic Sets, Sympolic Dynamics, and Strange Attractors.- Global Bifurcations.- Local Codimension Two Bifurcations of Flows.- Appendix: Suggestions for Further Reading. Postscript Added at Second Printing. Glossary. References. Index.
12,485 citations
[...]
TL;DR: This paper describes mathematical and software developments for a suite of programs for solving ordinary differential equations in MATLAB.
Abstract: This paper describes mathematical and software developments for a suite of programs for solving ordinary differential equations in MATLAB.
3,330 citations
Book•
01 Jan 1987TL;DR: A very brief tour of XPPAUT can be found in this paper, where the authors present a technique for writing ODE files for Differential Equations for differentially Equations.
Abstract: List of figures Preface 1. Installation 2 A Very Brief Tour of XPPAUT 3. Writing ODE Files for Differential Equations 4. XPPAUT in the Classroom 5. More Advanced Diffferential Equations 6. Spatial Problems, PDEs, and BVPs 7. Using AUTO. Bifurcation and Continuation 8. Animation 9 Tricks and Advanced Methods Appendix A. Colors and Linestyles Appendix B. The Options Appendix C. Numerical Methods Appendix D. Structure of ODE Files Appendix E. Complete Command List Appendix F. Error Messages Appendix G. Cheat Sheet References IndexAppendix C. Numerical Methods Appendix D. Structure of ODE Files Appendix E. Complete Command List Appendix F. Error Messages Appendix G. Cheat Sheet References Index.
1,606 citations
01 Jan 1997
TL;DR: This is a guide to the software package AUTO for continuation and bifurcation problems in ordinary differential equations and the development of HomCont has much benefitted from various pieces of help and advice from, among others, W. W. Norton.
Abstract: Preface This is a guide to the software package AUTO for continuation and bifurcation problems in ordinary differential equations. graphics program PLAUT and the pendula animation program. An earlier graphical user interface for AUTO on SGI machines was written by Taylor & Kevrekidis (1989). Special thanks are due to Sheila Shull, California Institute of Technology, for her cheerful assistance in the distribution of AUTO over a long period of time. Over the years, the development of AUTO has been supported by various agencies through the California Institute of Technology. Work on this updated version was supported by a general research grant from NSERC (Canada). The development of HomCont has much benefitted from various pieces of help and advice from, among others, W. This manual uses the following conventions. command This font is used for commands which you can type in. PAR This font is used for AUTO parameters. filename This font is used for file and directory names. variable This font is used for environment variable. site This font is used for world wide web and ftp sites. function This font is used for function names.
1,417 citations
"MATCONT: A MATLAB package for numer..." refers methods in this paper
...The most widely used are (1) AUTO86/97 [Doedel et al. 1997]....
[...]