Unconventional Means of Preventing Chaos in the Economy
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Stability Analysis of Fitzhughâ•Finagumo With
Proceedings of GREAT Day Volume 2011 Article 4 2012 Stability Analysis of FitzHugh–Nagumo with Smooth Periodic Forcing Tyler Massaro SUNY Geneseo Follow this and additional works at: https://knightscholar.geneseo.edu/proceedings-of-great-day Creative Commons Attribution 4.0 License This work is licensed under a Creative Commons Attribution 4.0 License. Recommended Citation Massaro, Tyler (2012) "Stability Analysis of FitzHugh–Nagumo with Smooth Periodic Forcing," Proceedings of GREAT Day: Vol. 2011 , Article 4. Available at: https://knightscholar.geneseo.edu/proceedings-of-great-day/vol2011/iss1/4 This Article is brought to you for free and open access by the GREAT Day at KnightScholar. It has been accepted for inclusion in Proceedings of GREAT Day by an authorized editor of KnightScholar. For more information, please contact [email protected]. Massaro: Stability Analysis of FitzHugh–Nagumo with Smooth Periodic Forcin Stability Analysis of FitzHugh – Nagumo with Smooth Periodic Forcing Tyler Massaro 1 Background Since the concentration of K+ ions is so much higher inside the cell than outside, there is a As Izhikevich so aptly put it, tendency for K+ to flow out of these leak channels “If somebody were to put a gun to the head of along its concentration gradient. When this the author of this book and ask him to name the happens, there is a negative charge left behind by single most important concept in brain science, he the K+ ions immediately leaving the cell. This would say it is the concept of a neuron[16].” build-up of negative charge is actually enough to, in a sense, catch the K+ ions in the act of leaving By no means are the concepts forwarded in his and momentarily halt the flow of charge across the book restricted to brain science. -
Learning from Benoit Mandelbrot
2/28/18, 7(59 AM Page 1 of 1 February 27, 2018 Learning from Benoit Mandelbrot If you've been reading some of my recent posts, you will have noted my, and the Investment Masters belief, that many of the investment theories taught in most business schools are flawed. And they can be dangerous too, the recent Financial Crisis is evidence of as much. One man who, prior to the Financial Crisis, issued a challenge to regulators including the Federal Reserve Chairman Alan Greenspan, to recognise these flaws and develop more realistic risk models was Benoit Mandelbrot. Over the years I've read a lot of investment books, and the name Benoit Mandelbrot comes up from time to time. I recently finished his book 'The (Mis)Behaviour of Markets - A Fractal View of Risk, Ruin and Reward'. So who was Benoit Mandelbrot, why is he famous, and what can we learn from him? Benoit Mandelbrot was a Polish-born mathematician and polymath, a Sterling Professor of Mathematical Sciences at Yale University and IBM Fellow Emeritus (Physics) who developed a new branch of mathematics known as 'Fractal' geometry. This geometry recognises the hidden order in the seemingly disordered, the plan in the unplanned, the regular pattern in the irregularity and roughness of nature. It has been successfully applied to the natural sciences helping model weather, study river flows, analyse brainwaves and seismic tremors. A 'fractal' is defined as a rough or fragmented shape that can be split into parts, each of which is at least a close approximation of its original-self. -
At Work in Qualitative Analysis: a Case Study of the Opposite
HISTORIA MATHEMATICA 25 (1998), 379±411 ARTICLE NO. HM982211 The ``Essential Tension'' at Work in Qualitative Analysis: A Case Study of the Opposite Points of View of Poincare and Enriques on the Relationships between Analysis and Geometry* View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Giorgio Israel and Marta Menghini Dipartimento di Matematica, UniversitaÁ di Roma ``La Sapienza,'' P. le A. Moro, 2, I00185 Rome, Italy An analysis of the different philosophic and scienti®c visions of Henri Poincare and Federigo Enriques relative to qualitative analysis provides us with a complex and interesting image of the ``essential tension'' between ``tradition'' and ``innovation'' within the history of science. In accordance with his scienti®c paradigm, Poincare viewed qualitative analysis as a means for preserving the nucleus of the classical reductionist program, even though it meant ``bending the rules'' somewhat. To Enriques's mind, qualitative analysis represented the af®rmation of a synthetic, geometrical vision that would supplant the analytical/quantitative conception characteristic of 19th-century mathematics and mathematical physics. Here, we examine the two different answers given at the turn of the century to the question of the relationship between geometry and analysis and between mathematics, on the one hand, and mechanics and physics, on the other. 1998 Academic Press Un'analisi delle diverse posizioni ®loso®che e scienti®che di Henri Poincare e Federigo Enriques nei riguardi dell'analisi qualitativa fornisce un'immagine complessa e interessante della ``tensione essenziale'' tra ``tradizione'' e ``innovazione'' nell'ambito della storia della scienza. -
Writing the History of Dynamical Systems and Chaos
Historia Mathematica 29 (2002), 273–339 doi:10.1006/hmat.2002.2351 Writing the History of Dynamical Systems and Chaos: View metadata, citation and similar papersLongue at core.ac.uk Dur´ee and Revolution, Disciplines and Cultures1 brought to you by CORE provided by Elsevier - Publisher Connector David Aubin Max-Planck Institut fur¨ Wissenschaftsgeschichte, Berlin, Germany E-mail: [email protected] and Amy Dahan Dalmedico Centre national de la recherche scientifique and Centre Alexandre-Koyre,´ Paris, France E-mail: [email protected] Between the late 1960s and the beginning of the 1980s, the wide recognition that simple dynamical laws could give rise to complex behaviors was sometimes hailed as a true scientific revolution impacting several disciplines, for which a striking label was coined—“chaos.” Mathematicians quickly pointed out that the purported revolution was relying on the abstract theory of dynamical systems founded in the late 19th century by Henri Poincar´e who had already reached a similar conclusion. In this paper, we flesh out the historiographical tensions arising from these confrontations: longue-duree´ history and revolution; abstract mathematics and the use of mathematical techniques in various other domains. After reviewing the historiography of dynamical systems theory from Poincar´e to the 1960s, we highlight the pioneering work of a few individuals (Steve Smale, Edward Lorenz, David Ruelle). We then go on to discuss the nature of the chaos phenomenon, which, we argue, was a conceptual reconfiguration as -
Role of Nonlinear Dynamics and Chaos in Applied Sciences
v.;.;.:.:.:.;.;.^ ROLE OF NONLINEAR DYNAMICS AND CHAOS IN APPLIED SCIENCES by Quissan V. Lawande and Nirupam Maiti Theoretical Physics Oivisipn 2000 Please be aware that all of the Missing Pages in this document were originally blank pages BARC/2OOO/E/OO3 GOVERNMENT OF INDIA ATOMIC ENERGY COMMISSION ROLE OF NONLINEAR DYNAMICS AND CHAOS IN APPLIED SCIENCES by Quissan V. Lawande and Nirupam Maiti Theoretical Physics Division BHABHA ATOMIC RESEARCH CENTRE MUMBAI, INDIA 2000 BARC/2000/E/003 BIBLIOGRAPHIC DESCRIPTION SHEET FOR TECHNICAL REPORT (as per IS : 9400 - 1980) 01 Security classification: Unclassified • 02 Distribution: External 03 Report status: New 04 Series: BARC External • 05 Report type: Technical Report 06 Report No. : BARC/2000/E/003 07 Part No. or Volume No. : 08 Contract No.: 10 Title and subtitle: Role of nonlinear dynamics and chaos in applied sciences 11 Collation: 111 p., figs., ills. 13 Project No. : 20 Personal authors): Quissan V. Lawande; Nirupam Maiti 21 Affiliation ofauthor(s): Theoretical Physics Division, Bhabha Atomic Research Centre, Mumbai 22 Corporate authoifs): Bhabha Atomic Research Centre, Mumbai - 400 085 23 Originating unit : Theoretical Physics Division, BARC, Mumbai 24 Sponsors) Name: Department of Atomic Energy Type: Government Contd...(ii) -l- 30 Date of submission: January 2000 31 Publication/Issue date: February 2000 40 Publisher/Distributor: Head, Library and Information Services Division, Bhabha Atomic Research Centre, Mumbai 42 Form of distribution: Hard copy 50 Language of text: English 51 Language of summary: English 52 No. of references: 40 refs. 53 Gives data on: Abstract: Nonlinear dynamics manifests itself in a number of phenomena in both laboratory and day to day dealings. -
Table of Contents More Information
Cambridge University Press 978-1-107-03042-8 - Lyapunov Exponents: A Tool to Explore Complex Dynamics Arkady Pikovsky and Antonio Politi Table of Contents More information Contents Preface page xi 1Introduction 1 1.1 Historical considerations 1 1.1.1 Early results 1 1.1.2 Biography of Aleksandr Lyapunov 3 1.1.3 Lyapunov’s contribution 4 1.1.4 The recent past 5 1.2 Outline of the book 6 1.3 Notations 8 2Thebasics 10 2.1 The mathematical setup 10 2.2 One-dimensional maps 11 2.3 Oseledets theorem 12 2.3.1 Remarks 13 2.3.2 Oseledets splitting 15 2.3.3 “Typical perturbations” and time inversion 16 2.4 Simple examples 17 2.4.1 Stability of fixed points and periodic orbits 17 2.4.2 Stability of independent and driven systems 18 2.5 General properties 18 2.5.1 Deterministic vs. stochastic systems 18 2.5.2 Relationship with instabilities and chaos 19 2.5.3 Invariance 20 2.5.4 Volume contraction 21 2.5.5 Time parametrisation 22 2.5.6 Symmetries and zero Lyapunov exponents 24 2.5.7 Symplectic systems 26 3 Numerical methods 28 3.1 The largest Lyapunov exponent 28 3.2 Full spectrum: QR decomposition 29 3.2.1 Gram-Schmidt orthogonalisation 31 3.2.2 Householder reflections 31 v © in this web service Cambridge University Press www.cambridge.org Cambridge University Press 978-1-107-03042-8 - Lyapunov Exponents: A Tool to Explore Complex Dynamics Arkady Pikovsky and Antonio Politi Table of Contents More information vi Contents 3.3 Continuous methods 33 3.4 Ensemble averages 35 3.5 Numerical errors 36 3.5.1 Orthogonalisation 37 3.5.2 Statistical error 38 3.5.3 -
The Development of Hierarchical Knowledge in Robot Systems
THE DEVELOPMENT OF HIERARCHICAL KNOWLEDGE IN ROBOT SYSTEMS A Dissertation Presented by STEPHEN W. HART Submitted to the Graduate School of the University of Massachusetts Amherst in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY September 2009 Computer Science c Copyright by Stephen W. Hart 2009 All Rights Reserved THE DEVELOPMENT OF HIERARCHICAL KNOWLEDGE IN ROBOT SYSTEMS A Dissertation Presented by STEPHEN W. HART Approved as to style and content by: Roderic Grupen, Chair Andrew Barto, Member David Jensen, Member Rachel Keen, Member Andrew Barto, Department Chair Computer Science To R. Daneel Olivaw. ACKNOWLEDGMENTS This dissertation would not have been possible without the help and support of many people. Most of all, I would like to extend my gratitude to Rod Grupen for many years of inspiring work, our discussions, and his guidance. Without his sup- port and vision, I cannot imagine that the journey would have been as enormously enjoyable and rewarding as it turned out to be. I am very excited about what we discovered during my time at UMass, but there is much more to be done. I look forward to what comes next! In addition to providing professional inspiration, Rod was a great person to work with and for|creating a warm and encouraging labora- tory atmosphere, motivating us to stay in shape for his annual half-marathons, and ensuring a sufficient amount of cake at the weekly lab meetings. Thanks for all your support, Rod! I am very grateful to my thesis committee|Andy Barto, David Jensen, and Rachel Keen|for many encouraging and inspirational discussions. -
Mild Vs. Wild Randomness: Focusing on Those Risks That Matter
with empirical sense1. Granted, it has been Mild vs. Wild Randomness: tinkered with using such methods as Focusing on those Risks that complementary “jumps”, stress testing, regime Matter switching or the elaborate methods known as GARCH, but while they represent a good effort, Benoit Mandelbrot & Nassim Nicholas Taleb they fail to remediate the bell curve’s irremediable flaws. Forthcoming in, The Known, the Unknown and the The problem is that measures of uncertainty Unknowable in Financial Institutions Frank using the bell curve simply disregard the possibility Diebold, Neil Doherty, and Richard Herring, of sharp jumps or discontinuities. Therefore they editors, Princeton: Princeton University Press. have no meaning or consequence. Using them is like focusing on the grass and missing out on the (gigantic) trees. Conventional studies of uncertainty, whether in statistics, economics, finance or social science, In fact, while the occasional and unpredictable have largely stayed close to the so-called “bell large deviations are rare, they cannot be dismissed curve”, a symmetrical graph that represents a as “outliers” because, cumulatively, their impact in probability distribution. Used to great effect to the long term is so dramatic. describe errors in astronomical measurement by The good news, especially for practitioners, is the 19th-century mathematician Carl Friedrich that the fractal model is both intuitively and Gauss, the bell curve, or Gaussian model, has computationally simpler than the Gaussian. It too since pervaded our business and scientific culture, has been around since the sixties, which makes us and terms like sigma, variance, standard deviation, wonder why it was not implemented before. correlation, R-square and Sharpe ratio are all The traditional Gaussian way of looking at the directly linked to it. -
Bézier Curves Are Attractors of Iterated Function Systems
New York Journal of Mathematics New York J. Math. 13 (2007) 107–115. All B´ezier curves are attractors of iterated function systems Chand T. John Abstract. The fields of computer aided geometric design and fractal geom- etry have evolved independently of each other over the past several decades. However, the existence of so-called smooth fractals, i.e., smooth curves or sur- faces that have a self-similar nature, is now well-known. Here we describe the self-affine nature of quadratic B´ezier curves in detail and discuss how these self-affine properties can be extended to other types of polynomial and ra- tional curves. We also show how these properties can be used to control shape changes in complex fractal shapes by performing simple perturbations to smooth curves. Contents 1. Introduction 107 2. Quadratic B´ezier curves 108 3. Iterated function systems 109 4. An IFS with a QBC attractor 110 5. All QBCs are attractors of IFSs 111 6. Controlling fractals with B´ezier curves 112 7. Conclusion and future work 114 References 114 1. Introduction In the late 1950s, advancements in hardware technology made it possible to effi- ciently manufacture curved 3D shapes out of blocks of wood or steel. It soon became apparent that the bottleneck in mass production of curved 3D shapes was the lack of adequate software for designing these shapes. B´ezier curves were first introduced in the 1960s independently by two engineers in separate French automotive compa- nies: first by Paul de Casteljau at Citro¨en, and then by Pierre B´ezier at R´enault. -
Voltage Control Using Limited Communication**This Work Was
20th IFAC World Congress 2017 IFAC PapersOnline Volume 50, Issue 1 Toulouse, France 9-14 July 2017 Part 1 of 24 Editors: Denis Dochain Didier Henrion Dimitri Peaucelle ISBN: 978-1-5108-5071-2 Printed from e-media with permission by: Curran Associates, Inc. 57 Morehouse Lane Red Hook, NY 12571 Some format issues inherent in the e-media version may also appear in this print version. Copyright© (2017) by IFAC (International Federation of Automatic Control) All rights reserved. Printed by Curran Associates, Inc. (2018) For permission requests, please contact the publisher, Elsevier Limited at the address below. Elsevier Limited 360 Park Ave South New York, NY 10010 Additional copies of this publication are available from: Curran Associates, Inc. 57 Morehouse Lane Red Hook, NY 12571 USA Phone: 845-758-0400 Fax: 845-758-2633 Email: [email protected] Web: www.proceedings.com TABLE OF CONTENTS PART 1 VOLTAGE CONTROL USING LIMITED COMMUNICATION*............................................................................................................1 Sindri Magnússon, Carlo Fischione, Na Li A LOCAL STABILITY CONDITION FOR DC GRIDS WITH CONSTANT POWER LOADS* .........................................................7 José Arocas-Pérez, Robert Griño VSC-HVDC SYSTEM ROBUST STABILITY ANALYSIS BASED ON A MODIFIED MIXED SMALL GAIN AND PASSIVITY THEOREM .......................................................................................................................................................................13 Y. Song, C. Breitholtz -
Towards a Theory of Social Fractal Discourse: Some Tentative Ideas
Page 1 of 16 ANZAM 2012 Towards a Theory of Social Fractal Discourse: Some Tentative Ideas Dr James Latham Faculty of Business and Enterprise, Swinburne University of Technology, Victoria, Australia Email: [email protected] Amanda Muhleisen PhD Candidate, Faculty of Business and Enterprise, Swinburne University of Technology, Victoria, Australia Email: [email protected] Prof Robert Jones Faculty of Business and Enterprise, Swinburne University of Technology, Victoria, Australia Email: [email protected] ANZAM 2012 Page 2 of 16 ABSTRACT The development of chaos theory and fractal geometry has made significant contribution to our understanding of the natural world. As students of organization, chaos theory provides an opportunity to broaden our thinking beyond the linear and predictable with its presumed stability, in order to embrace chaos rather than stability as the ‘default’ state for organization. This demands we think in new ways about organizational theory and practice. It also creates a schism in the fabric of our knowledge - a divide to be bridged. By taking the scientific concept of fractals and applying it to a social theory of discourse, this paper hopes to emerge some tentative ideas around developing a theory of social fractal discourse. Keywords: chaos theory, instability, organizing as process, critical discourse analysis, complexity The aim of this paper is to outline a number of tentative ideas around the development of a theory of social fractal discourse. It will focus on qualities and features of fractal and chaotic systems. Drawing on ideas from chaos and complexity theory, we will argue that discourse can be fractal. While there is some difference in theoretical constructs within the complexity literature, we will use the terms fractal and chaos interchangeably throughout this paper. -
Maps, Chaos, and Fractals
MATH305 Summer Research Project 2006-2007 Maps, Chaos, and Fractals Phillips Williams Department of Mathematics and Statistics University of Canterbury Maps, Chaos, and Fractals Phillipa Williams* MATH305 Mathematics Project University of Canterbury 9 February 2007 Abstract The behaviour and properties of one-dimensional discrete mappings are explored by writing Matlab code to iterate mappings and draw graphs. Fixed points, periodic orbits, and bifurcations are described and chaos is introduced using the logistic map. Symbolic dynamics are used to show that the doubling map and the logistic map have the properties of chaos. The significance of a period-3 orbit is examined and the concept of universality is introduced. Finally the Cantor Set provides a brief example of the use of iterative processes to generate fractals. *supervised by Dr. Alex James, University of Canterbury. 1 Introduction Devaney [1992] describes dynamical systems as "the branch of mathematics that attempts to describe processes in motion)) . Dynamical systems are mathematical models of systems that change with time and can be used to model either discrete or continuous processes. Contin uous dynamical systems e.g. mechanical systems, chemical kinetics, or electric circuits can be modeled by differential equations. Discrete dynamical systems are physical systems that involve discrete time intervals, e.g. certain types of population growth, daily fluctuations in the stock market, the spread of cases of infectious diseases, and loans (or deposits) where interest is compounded at fixed intervals. Discrete dynamical systems can be modeled by iterative maps. This project considers one-dimensional discrete dynamical systems. In the first section, the behaviour and properties of one-dimensional maps are examined using both analytical and graphical methods.