A Simple Exchange Economy with Complex Dynamics

Size: px
Start display at page:

Download "A Simple Exchange Economy with Complex Dynamics"

Transcription

1 FH-Kiel Universitf Alie Sciences Prof. Dr. Anreas Thiemer, 00 A Simle Exchange Economy with Comlex Dynamics (Revision: Aril 00) Summary: Mukherji (999) shows that a stanar iscrete tatonnement rocess within the context of a very simle exchange economy (two goos, two ersons with Cobb-Douglas utility functions) exhibits comlex ynamics of the rice ajustment. This worksheet gives you the numerical tools to exlore the henomenon of erio oubling bifurcation an chaos in this moel. A.Thiemer, 00 mukherji.mc,

2 . Imortant efinitions A, B: iniviuals : rice of goo x relative to goo y E : equilibrium rice x, y : absolute rices of x an y u A, u B : utilitf iniviual A an B x, y: quantities of goos x o, : enowments of goos Z: excess eman of goo x. Basic assumtions The references of iniviual A are given by: u A ( x, y, α) x α. y α with 0< α < The references of iniviual B are given by: u B ( x, y, β) x β. y β with 0< β< We efine the rice of goo y as a numeraire: y Thus the relative rice is written as: x y x Iniviual A ossesses the enowment (x o, 0) an B has the enowment (0, ). Therefore, the buget constraints are x. o x. y for iniviual A x. y for iniviual B A.Thiemer, 00 mukherji.mc,

3 3. The exchange equilibrium With these buget constraints the first orer conitions of utility maximization yiel the eman functions for goo x of iniviual A an B: x A, α, x o x u A x, x. o x., α auflösen, x α. x o x B, β, x u B x, x., β auflösen, x β. Now we summarize the eman behaviour by the excess eman function Z ( ) for goo x: Z, β, α, x o, x B, β, x A, α, x o x o β. α. x o x o The market is in equilibrium if Z( ) = 0. Hence the unique equilibrium rice is etermine by: E β, α, x o, Z, β, α, x o, auflösen, β. x. o ( α ) 4. Introucing ajustment ynamics Consier the stanar ajustment on rices in isequilibrium (the "tatonnement") i i γ. Z i, β, α, x o, where γ> 0 is some constant see of ajustment.we can rewrite this equation as an iterate ma: y f ( ) γ. Z, β, α, x o, γ. o β. α. x o x o First orer coniton gives: f ( ) auflösen, γβ.. γβ.. A.Thiemer, 00 3 mukherji.mc,

4 Insert the ositive solution into the secon orer conition: f ( ) ersetzen, γβ... γ. β. γβ.. 3 Because the secon erivate becomes ositive we know that f() attains a minimum value at ' γβ.. given by f γβ.. vereinfachen γ.. β. x. o γβ.. α. x. o γβ.. γβ..... or more simlifie (by han an not by Mathca): f' ( ). γβ.. γ. ( α ). x 0 In orer to guarantee ositive rices f( ' ) > 0 must hol. Defining Κ γ. ( α ) x o β.. this is ensure if Κ < 4. A.Thiemer, 00 4 mukherji.mc,

5 5. Some roerties of the ajustment ynamics For the roofs of the following cite claims, see Mukherij (999). Claim : Κ < E is locally stable for the rocess f(). Claim 3: For < Κ <.5 there exists a stable -cycle. Let Κ n enote the critical value of Κ where a n cycle is born; then Κ an Κ.5. Using the Feigenbaum constant F const can be aroximate by: the value of κ lim n Κ n κ F. const Κ Κ F const κ =.636 Claim 4: For Κ ( 3.0, 3.6) the ma f() exhibits toological chaos. Claim 5: For Κ = 5/9, the ma f() exhibits ergoic chaos; in aition there exists Κ such that f() exhibits ergoic chaos. 6. Numerical Exlorations To exlore the behaviour of the attractors for ifferent values of K, Mukherji (999,.745) fixes the values of all arameters excet the ajustment coefficient γ with β. an ( α ). x o 6 so that Κ 36. γ. Then the iterate ma takes the articular form: f (, Κ ) 6 Κ 36 Notice, that uner these arameter restrictions the value of the equilibrium rice is ineenent from Κ: E f (, Κ ) auflösen, 6 A.Thiemer, 00 5 mukherji.mc,

6 Choosing a numerical value for Κ, the iterate ma is rawn in the following figure: Κ 5 9 max 0,.0.. max Iterate Ma an Equilibrium E 0.8 fκ (, ) Given an initial value 0 of the first rice offer an using the Κ-value from above, the ajustment rocess is comute for T max erios. 0.5 T max 50 i 0.. T max i f i, Κ 0.6 Price Ajustment rice E time A.Thiemer, 00 6 mukherji.mc,

7 This ajustment rocess may be also resente by a cobweb lot. Cobweb Plot of the Price Ajustment 0.5 E 0.4 (time+) iterate ma f(,k) (time) = (time+) trajectory (time) A.Thiemer, 00 7 mukherji.mc,

8 Observe the bifurcations by lotting the Feigenbaum iagram an the Lyaunov exonent. Use these figures to choose K such that you obtain stable cycles of ifferent erioicitr irregular cycles of. Resolution of grah: RES 3 (,,.., 0) Range of lotte values: Κ bottom.9 Κ to 3.6 bottom 0 to.5.5 Feigenbaum iagram.5 rice bifurcation arameter Κ A.Thiemer, 00 8 mukherji.mc,

9 Lyaunov exonent L 3 bifurcation arameter Κ Note: Positive values of the Lyaunov exonent inicate chaotic behaviour of! Literature: Anjan Mukherji: A Simle Examle of Comlex Dynamics. In: Economic Theory, vol.4 (999), A.Thiemer, 00 9 mukherji.mc,

Monopoly Part III: Multiple Local Equilibria and Adaptive Search

Monopoly Part III: Multiple Local Equilibria and Adaptive Search FH-Kiel University of Applie Sciences Prof Dr Anreas Thiemer, 00 e-mail: anreasthiemer@fh-kiele Monopoly Part III: Multiple Local Equilibria an Aaptive Search Summary: The information about market eman

More information

7. Introduction to Large Sample Theory

7. Introduction to Large Sample Theory 7. Introuction to Large Samle Theory Hayashi. 88-97/109-133 Avance Econometrics I, Autumn 2010, Large-Samle Theory 1 Introuction We looke at finite-samle roerties of the OLS estimator an its associate

More information

Colin Cameron: Asymptotic Theory for OLS

Colin Cameron: Asymptotic Theory for OLS Colin Cameron: Asymtotic Theory for OLS. OLS Estimator Proerties an Samling Schemes.. A Roama Consier the OLS moel with just one regressor y i = βx i + u i. The OLS estimator b β = ³ P P i= x iy i canbewrittenas

More information

IERCU. Institute of Economic Research, Chuo University 50th Anniversary Special Issues. Discussion Paper No.210

IERCU. Institute of Economic Research, Chuo University 50th Anniversary Special Issues. Discussion Paper No.210 IERCU Institute of Economic Research, Chuo University 50th Anniversary Special Issues Discussion Paper No.210 Discrete an Continuous Dynamics in Nonlinear Monopolies Akio Matsumoto Chuo University Ferenc

More information

Skiba without unstable equlibrium in a linear quadratic framework

Skiba without unstable equlibrium in a linear quadratic framework Skiba without unstable equlibrium in a linear quaratic framework Richar F. Hartl Institute of Management, University of Vienna, Brünnerstraße 8, -0 Vienna, ustria Richar.Hartl@univie.ac.at Tel. +43--477-3809

More information

The thermal wind 1. v g

The thermal wind 1. v g The thermal win The thermal win Introuction The geostrohic win is etermine by the graient of the isobars (on a horizontal surface) or isohyses (on a ressure surface). On a ressure surface the graient of

More information

Survey Sampling. 1 Design-based Inference. Kosuke Imai Department of Politics, Princeton University. February 19, 2013

Survey Sampling. 1 Design-based Inference. Kosuke Imai Department of Politics, Princeton University. February 19, 2013 Survey Sampling Kosuke Imai Department of Politics, Princeton University February 19, 2013 Survey sampling is one of the most commonly use ata collection methos for social scientists. We begin by escribing

More information

Convergence Analysis of Terminal ILC in the z Domain

Convergence Analysis of Terminal ILC in the z Domain 25 American Control Conference June 8-, 25 Portlan, OR, USA WeA63 Convergence Analysis of erminal LC in the Domain Guy Gauthier, an Benoit Boulet, Member, EEE Abstract his aer shows how we can aly -transform

More information

Colin Cameron: Brief Asymptotic Theory for 240A

Colin Cameron: Brief Asymptotic Theory for 240A Colin Cameron: Brief Asymtotic Theory for 240A For 240A we o not go in to great etail. Key OLS results are in Section an 4. The theorems cite in sections 2 an 3 are those from Aenix A of Cameron an Trivei

More information

ELEC3114 Control Systems 1

ELEC3114 Control Systems 1 ELEC34 Control Systems Linear Systems - Moelling - Some Issues Session 2, 2007 Introuction Linear systems may be represente in a number of ifferent ways. Figure shows the relationship between various representations.

More information

Lie symmetry and Mei conservation law of continuum system

Lie symmetry and Mei conservation law of continuum system Chin. Phys. B Vol. 20, No. 2 20 020 Lie symmetry an Mei conservation law of continuum system Shi Shen-Yang an Fu Jing-Li Department of Physics, Zhejiang Sci-Tech University, Hangzhou 3008, China Receive

More information

Web Appendix to Firm Heterogeneity and Aggregate Welfare (Not for Publication)

Web Appendix to Firm Heterogeneity and Aggregate Welfare (Not for Publication) Web ppeni to Firm Heterogeneity an ggregate Welfare Not for Publication Marc J. Melitz Harvar University, NBER, an CEPR Stephen J. Reing Princeton University, NBER, an CEPR March 6, 203 Introuction his

More information

A method of constructing the half-rate QC-LDPC codes with linear encoder, maximum column weight three and inevitable girth 26

A method of constructing the half-rate QC-LDPC codes with linear encoder, maximum column weight three and inevitable girth 26 Communications 20; 2(): 22-4 Publishe online January 1 2015 (htt://www.scienceublishinggrou.com/j/com) oi: 10.11648/j.com.20020.11 ISSN: 228-5966 (Print); ISSN: 228-592 (Online) A metho of constructing

More information

Switching Time Optimization in Discretized Hybrid Dynamical Systems

Switching Time Optimization in Discretized Hybrid Dynamical Systems Switching Time Optimization in Discretize Hybri Dynamical Systems Kathrin Flaßkamp, To Murphey, an Sina Ober-Blöbaum Abstract Switching time optimization (STO) arises in systems that have a finite set

More information

Robust Control of Robot Manipulators Using Difference Equations as Universal Approximator

Robust Control of Robot Manipulators Using Difference Equations as Universal Approximator Proceeings of the 5 th International Conference of Control, Dynamic Systems, an Robotics (CDSR'18) Niagara Falls, Canaa June 7 9, 218 Paer No. 139 DOI: 1.11159/csr18.139 Robust Control of Robot Maniulators

More information

Online Appendix for Trade Policy under Monopolistic Competition with Firm Selection

Online Appendix for Trade Policy under Monopolistic Competition with Firm Selection Online Appenix for Trae Policy uner Monopolistic Competition with Firm Selection Kyle Bagwell Stanfor University an NBER Seung Hoon Lee Georgia Institute of Technology September 6, 2018 In this Online

More information

Submitted to the Journal of Hydraulic Engineering, ASCE, January, 2006 NOTE ON THE ANALYSIS OF PLUNGING OF DENSITY FLOWS

Submitted to the Journal of Hydraulic Engineering, ASCE, January, 2006 NOTE ON THE ANALYSIS OF PLUNGING OF DENSITY FLOWS Submitte to the Journal of Hyraulic Engineering, ASCE, January, 006 NOTE ON THE ANALYSIS OF PLUNGING OF DENSITY FLOWS Gary Parker 1, Member, ASCE an Horacio Toniolo ABSTRACT This note is evote to the correction

More information

Web-Based Technical Appendix: Multi-Product Firms and Trade Liberalization

Web-Based Technical Appendix: Multi-Product Firms and Trade Liberalization Web-Base Technical Appeni: Multi-Prouct Firms an Trae Liberalization Anrew B. Bernar Tuck School of Business at Dartmouth & NBER Stephen J. Reing LSE, Yale School of Management & CEPR Peter K. Schott Yale

More information

He s Homotopy Perturbation Method for solving Linear and Non-Linear Fredholm Integro-Differential Equations

He s Homotopy Perturbation Method for solving Linear and Non-Linear Fredholm Integro-Differential Equations nternational Journal of Theoretical an Alie Mathematics 2017; 3(6): 174-181 htt://www.scienceublishinggrou.com/j/ijtam oi: 10.11648/j.ijtam.20170306.11 SSN: 2575-5072 (Print); SSN: 2575-5080 (Online) He

More information

Mod p 3 analogues of theorems of Gauss and Jacobi on binomial coefficients

Mod p 3 analogues of theorems of Gauss and Jacobi on binomial coefficients ACTA ARITHMETICA 2.2 (200 Mo 3 analogues of theorems of Gauss an Jacobi on binomial coefficients by John B. Cosgrave (Dublin an Karl Dilcher (Halifax. Introuction. One of the most remarkable congruences

More information

Lenny Jones Department of Mathematics, Shippensburg University, Shippensburg, Pennsylvania Daniel White

Lenny Jones Department of Mathematics, Shippensburg University, Shippensburg, Pennsylvania Daniel White #A10 INTEGERS 1A (01): John Selfrige Memorial Issue SIERPIŃSKI NUMBERS IN IMAGINARY QUADRATIC FIELDS Lenny Jones Deartment of Mathematics, Shiensburg University, Shiensburg, Pennsylvania lkjone@shi.eu

More information

Novel Algorithm for Sparse Solutions to Linear Inverse. Problems with Multiple Measurements

Novel Algorithm for Sparse Solutions to Linear Inverse. Problems with Multiple Measurements Novel Algorithm for Sarse Solutions to Linear Inverse Problems with Multile Measurements Lianlin Li, Fang Li Institute of Electronics, Chinese Acaemy of Sciences, Beijing, China Lianlinli1980@gmail.com

More information

θ x = f ( x,t) could be written as

θ x = f ( x,t) could be written as 9. Higher orer PDEs as systems of first-orer PDEs. Hyperbolic systems. For PDEs, as for ODEs, we may reuce the orer by efining new epenent variables. For example, in the case of the wave equation, (1)

More information

Consistency and asymptotic normality

Consistency and asymptotic normality Consistency an asymtotic normality Class notes for Econ 842 Robert e Jong March 2006 1 Stochastic convergence The asymtotic theory of minimization estimators relies on various theorems from mathematical

More information

Lecture 6 : Dimensionality Reduction

Lecture 6 : Dimensionality Reduction CPS290: Algorithmic Founations of Data Science February 3, 207 Lecture 6 : Dimensionality Reuction Lecturer: Kamesh Munagala Scribe: Kamesh Munagala In this lecture, we will consier the roblem of maing

More information

Sliding mode approach to congestion control in connection-oriented communication networks

Sliding mode approach to congestion control in connection-oriented communication networks JOURNAL OF APPLIED COMPUTER SCIENCE Vol. xx. No xx (200x), pp. xx-xx Sliing moe approach to congestion control in connection-oriente communication networks Anrzej Bartoszewicz, Justyna Żuk Technical University

More information

New Technology, Human Capital and Growth for Developing Countries.

New Technology, Human Capital and Growth for Developing Countries. New Technology, Human Capital an Growth for Developing Countries Cuong Le Van, Manh-Hung Nguyen an Thai Bao Luong Centre Economie e la Sorbonne, Université Paris-1, Pantheon-Sorbonne 106-112 B e l Hôpital,

More information

Econometrics I. September, Part I. Department of Economics Stanford University

Econometrics I. September, Part I. Department of Economics Stanford University Econometrics I Deartment of Economics Stanfor University Setember, 2008 Part I Samling an Data Poulation an Samle. ineenent an ientical samling. (i.i..) Samling with relacement. aroximates samling without

More information

Learning in Monopolies with Delayed Price Information

Learning in Monopolies with Delayed Price Information Learning in Monopolies with Delaye Price Information Akio Matsumoto y Chuo University Ferenc Sziarovszky z University of Pécs February 28, 2013 Abstract We call the intercept of the price function with

More information

Dynamical Systems and a Brief Introduction to Ergodic Theory

Dynamical Systems and a Brief Introduction to Ergodic Theory Dynamical Systems an a Brief Introuction to Ergoic Theory Leo Baran Spring 2014 Abstract This paper explores ynamical systems of ifferent types an orers, culminating in an examination of the properties

More information

Introduction to the Vlasov-Poisson system

Introduction to the Vlasov-Poisson system Introuction to the Vlasov-Poisson system Simone Calogero 1 The Vlasov equation Consier a particle with mass m > 0. Let x(t) R 3 enote the position of the particle at time t R an v(t) = ẋ(t) = x(t)/t its

More information

TMA 4195 Matematisk modellering Exam Tuesday December 16, :00 13:00 Problems and solution with additional comments

TMA 4195 Matematisk modellering Exam Tuesday December 16, :00 13:00 Problems and solution with additional comments Problem F U L W D g m 3 2 s 2 0 0 0 0 2 kg 0 0 0 0 0 0 Table : Dimension matrix TMA 495 Matematisk moellering Exam Tuesay December 6, 2008 09:00 3:00 Problems an solution with aitional comments The necessary

More information

Consistency and asymptotic normality

Consistency and asymptotic normality Consistency an ymtotic normality Cls notes for Econ 842 Robert e Jong Aril 2007 1 Stochtic convergence The ymtotic theory of minimization estimators relies on various theorems from mathematical statistics.

More information

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs Lectures - Week 10 Introuction to Orinary Differential Equations (ODES) First Orer Linear ODEs When stuying ODEs we are consiering functions of one inepenent variable, e.g., f(x), where x is the inepenent

More information

arxiv: v1 [math.pr] 28 Jan 2018

arxiv: v1 [math.pr] 28 Jan 2018 Submitte to the Annals of Probability WAVELET ANALYSIS OF THE BESOV REGULARITY OF LÉVY WHITE NOISES arxiv:80.09245v [math.pr] 28 Jan 208 By Shayan Azizneja, Julien Fageot an Michael Unser Ecole olytechnique

More information

6 General properties of an autonomous system of two first order ODE

6 General properties of an autonomous system of two first order ODE 6 General properties of an autonomous system of two first orer ODE Here we embark on stuying the autonomous system of two first orer ifferential equations of the form ẋ 1 = f 1 (, x 2 ), ẋ 2 = f 2 (, x

More information

3.7 Implicit Differentiation -- A Brief Introduction -- Student Notes

3.7 Implicit Differentiation -- A Brief Introduction -- Student Notes Fin these erivatives of these functions: y.7 Implicit Differentiation -- A Brief Introuction -- Stuent Notes tan y sin tan = sin y e = e = Write the inverses of these functions: y tan y sin How woul we

More information

The Effect of a Finite Measurement Volume on Power Spectra from a Burst Type LDA

The Effect of a Finite Measurement Volume on Power Spectra from a Burst Type LDA The Effect of a Finite Measurement Volume on Power Sectra from a Burst Tye LDA Preben Buchhave 1,*, Clara M. Velte, an William K. George 3 1. Intarsia Otics, Birkerø, Denmark. Technical University of Denmark,

More information

Learning Markov Graphs Up To Edit Distance

Learning Markov Graphs Up To Edit Distance Learning Markov Grahs U To Eit Distance Abhik Das, Praneeth Netraalli, Sujay Sanghavi an Sriram Vishwanath Deartment of ECE, The University of Texas at Austin, USA Abstract This aer resents a rate istortion

More information

Multiplicity Results of Positive Solutions for Nonlinear Three-Point Boundary Value Problems on Time Scales

Multiplicity Results of Positive Solutions for Nonlinear Three-Point Boundary Value Problems on Time Scales Avances in Dynamical Systems an Applications ISSN 973-532, Volume 4, Number 2, pp. 243 253 (29) http://campus.mst.eu/asa Multiplicity Results of Positive Solutions for Nonlinear Three-Point Bounary Value

More information

Capacity Allocation. Outline Two-class allocation Multiple-class allocation Demand dependence Bid prices. Based on Phillips (2005) Chapter 7.

Capacity Allocation. Outline Two-class allocation Multiple-class allocation Demand dependence Bid prices. Based on Phillips (2005) Chapter 7. Caacity Allocation utallas.eu/~metin Page Outline Two-class allocation Multile-class allocation Deman eenence Bi rices Base on Phillis (2005) Chater 7 Booking Limits or 2 Fare Classes utallas.eu/~metin

More information

18 EVEN MORE CALCULUS

18 EVEN MORE CALCULUS 8 EVEN MORE CALCULUS Chapter 8 Even More Calculus Objectives After stuing this chapter you shoul be able to ifferentiate an integrate basic trigonometric functions; unerstan how to calculate rates of change;

More information

University of Bath DEPARTMENT OF ECONOMICS COURSEWORK TEST 1: SUGGESSTED SOLUTIONS

University of Bath DEPARTMENT OF ECONOMICS COURSEWORK TEST 1: SUGGESSTED SOLUTIONS University of Bath DEPARTMENT OF ECONOMICS COURSEWORK TEST 1: SUGGESSTED SOLUTIONS First Year INTRODUCTORY MICROECONOMICS (ES10001) 3 RD NOVEMBER 2017, 17:30 18.45 (75 minutes) ANSWER ALL QUESTIONS The

More information

Dynamic Equations and Nonlinear Dynamics of Cascade Two-Photon Laser

Dynamic Equations and Nonlinear Dynamics of Cascade Two-Photon Laser Commun. Theor. Phys. (Beiing, China) 45 (6) pp. 4 48 c International Acaemic Publishers Vol. 45, No. 6, June 5, 6 Dynamic Equations an Nonlinear Dynamics of Cascae Two-Photon Laser XIE Xia,,, HUANG Hong-Bin,

More information

Energy behaviour of the Boris method for charged-particle dynamics

Energy behaviour of the Boris method for charged-particle dynamics Version of 25 April 218 Energy behaviour of the Boris metho for charge-particle ynamics Ernst Hairer 1, Christian Lubich 2 Abstract The Boris algorithm is a wiely use numerical integrator for the motion

More information

Probabilistic Learning

Probabilistic Learning Statistical Machine Learning Notes 11 Instructor: Justin Domke Probabilistic Learning Contents 1 Introuction 2 2 Maximum Likelihoo 2 3 Examles of Maximum Likelihoo 3 3.1 Binomial......................................

More information

Exponential Tracking Control of Nonlinear Systems with Actuator Nonlinearity

Exponential Tracking Control of Nonlinear Systems with Actuator Nonlinearity Preprints of the 9th Worl Congress The International Feeration of Automatic Control Cape Town, South Africa. August -9, Exponential Tracking Control of Nonlinear Systems with Actuator Nonlinearity Zhengqiang

More information

Generalized logistic map and its application in chaos based cryptography

Generalized logistic map and its application in chaos based cryptography Journal of Physics: Conference Series PAPER OPEN ACCESS Generalized logistic ma and its alication in chaos based crytograhy To cite this article: M Lawnik 207 J. Phys.: Conf. Ser. 936 0207 View the article

More information

RANDOM WALKS AND PERCOLATION: AN ANALYSIS OF CURRENT RESEARCH ON MODELING NATURAL PROCESSES

RANDOM WALKS AND PERCOLATION: AN ANALYSIS OF CURRENT RESEARCH ON MODELING NATURAL PROCESSES RANDOM WALKS AND PERCOLATION: AN ANALYSIS OF CURRENT RESEARCH ON MODELING NATURAL PROCESSES AARON ZWIEBACH Abstract. In this aer we will analyze research that has been recently done in the field of discrete

More information

Dissipative numerical methods for the Hunter-Saxton equation

Dissipative numerical methods for the Hunter-Saxton equation Dissipative numerical methos for the Hunter-Saton equation Yan Xu an Chi-Wang Shu Abstract In this paper, we present further evelopment of the local iscontinuous Galerkin (LDG) metho esigne in [] an a

More information

Schrödinger s equation.

Schrödinger s equation. Physics 342 Lecture 5 Schröinger s Equation Lecture 5 Physics 342 Quantum Mechanics I Wenesay, February 3r, 2010 Toay we iscuss Schröinger s equation an show that it supports the basic interpretation of

More information

Lecture 10: Logistic growth models #2

Lecture 10: Logistic growth models #2 Lecture 1: Logistic growth moels #2 Fugo Takasu Dept. Information an Computer Sciences Nara Women s University takasu@ics.nara-wu.ac.jp 6 July 29 1 Analysis of the stochastic process of logistic growth

More information

Application of Measurement System R&R Analysis in Ultrasonic Testing

Application of Measurement System R&R Analysis in Ultrasonic Testing 17th Worl Conference on Nonestructive Testing, 5-8 Oct 8, Shanghai, China Alication of Measurement System & Analysis in Ultrasonic Testing iao-hai ZHANG, Bing-ya CHEN, Yi ZHU Deartment of Testing an Control

More information

State-Space Model for a Multi-Machine System

State-Space Model for a Multi-Machine System State-Space Moel for a Multi-Machine System These notes parallel section.4 in the text. We are ealing with classically moele machines (IEEE Type.), constant impeance loas, an a network reuce to its internal

More information

05 The Continuum Limit and the Wave Equation

05 The Continuum Limit and the Wave Equation Utah State University DigitalCommons@USU Founations of Wave Phenomena Physics, Department of 1-1-2004 05 The Continuum Limit an the Wave Equation Charles G. Torre Department of Physics, Utah State University,

More information

arxiv: v1 [hep-lat] 19 Nov 2013

arxiv: v1 [hep-lat] 19 Nov 2013 HU-EP-13/69 SFB/CPP-13-98 DESY 13-225 Applicability of Quasi-Monte Carlo for lattice systems arxiv:1311.4726v1 [hep-lat] 19 ov 2013, a,b Tobias Hartung, c Karl Jansen, b Hernan Leovey, Anreas Griewank

More information

Calculus of Variations

Calculus of Variations Calculus of Variations Lagrangian formalism is the main tool of theoretical classical mechanics. Calculus of Variations is a part of Mathematics which Lagrangian formalism is base on. In this section,

More information

NON-ADIABATIC COMBUSTION WAVES FOR GENERAL LEWIS NUMBERS: WAVE SPEED AND EXTINCTION CONDITIONS

NON-ADIABATIC COMBUSTION WAVES FOR GENERAL LEWIS NUMBERS: WAVE SPEED AND EXTINCTION CONDITIONS ANZIAM J. 46(2004), 1 16 NON-ADIABATIC COMBUSTION WAVES FOR GENERAL LEWIS NUMBERS: WAVE SPEED AND EXTINCTION CONDITIONS A. C. MCINTOSH 1,R.O.WEBER 2 ang.n.mercer 2 (Receive 14 August, 2002) Abstract This

More information

arxiv: v1 [physics.flu-dyn] 8 May 2014

arxiv: v1 [physics.flu-dyn] 8 May 2014 Energetics of a flui uner the Boussinesq approximation arxiv:1405.1921v1 [physics.flu-yn] 8 May 2014 Kiyoshi Maruyama Department of Earth an Ocean Sciences, National Defense Acaemy, Yokosuka, Kanagawa

More information

Stability of steady states in kinetic Fokker-Planck equations for Bosons and Fermions

Stability of steady states in kinetic Fokker-Planck equations for Bosons and Fermions www.oeaw.ac.at Stability of steay states in kinetic Fokker-Planck equations for Bosons an Fermions L. Neumann, C. Sarber RICAM-Reort 2006-34 www.ricam.oeaw.ac.at STABILITY OF STEADY STATES IN KINETIC FOKKER-PLANCK

More information

Unit 5: Chemical Kinetics and Equilibrium UNIT 5: CHEMICAL KINETICS AND EQUILIBRIUM

Unit 5: Chemical Kinetics and Equilibrium UNIT 5: CHEMICAL KINETICS AND EQUILIBRIUM UNIT 5: CHEMICAL KINETICS AND EQUILIBRIUM Chapter 14: Chemical Kinetics 14.4 & 14.6: Activation Energy, Temperature Depenence on Reaction Rates & Catalysis Reaction Rates: - the spee of which the concentration

More information

Optimized Schwarz Methods with the Yin-Yang Grid for Shallow Water Equations

Optimized Schwarz Methods with the Yin-Yang Grid for Shallow Water Equations Optimize Schwarz Methos with the Yin-Yang Gri for Shallow Water Equations Abessama Qaouri Recherche en prévision numérique, Atmospheric Science an Technology Directorate, Environment Canaa, Dorval, Québec,

More information

LINEAR DIFFERENTIAL EQUATIONS OF ORDER 1. where a(x) and b(x) are functions. Observe that this class of equations includes equations of the form

LINEAR DIFFERENTIAL EQUATIONS OF ORDER 1. where a(x) and b(x) are functions. Observe that this class of equations includes equations of the form LINEAR DIFFERENTIAL EQUATIONS OF ORDER 1 We consier ifferential equations of the form y + a()y = b(), (1) y( 0 ) = y 0, where a() an b() are functions. Observe that this class of equations inclues equations

More information

A note on the Mooney-Rivlin material model

A note on the Mooney-Rivlin material model A note on the Mooney-Rivlin material moel I-Shih Liu Instituto e Matemática Universiae Feeral o Rio e Janeiro 2945-97, Rio e Janeiro, Brasil Abstract In finite elasticity, the Mooney-Rivlin material moel

More information

Calculus in the AP Physics C Course The Derivative

Calculus in the AP Physics C Course The Derivative Limits an Derivatives Calculus in the AP Physics C Course The Derivative In physics, the ieas of the rate change of a quantity (along with the slope of a tangent line) an the area uner a curve are essential.

More information

The canonical controllers and regular interconnection

The canonical controllers and regular interconnection Systems & Control Letters ( www.elsevier.com/locate/sysconle The canonical controllers an regular interconnection A.A. Julius a,, J.C. Willems b, M.N. Belur c, H.L. Trentelman a Department of Applie Mathematics,

More information

MINIMAL MAHLER MEASURE IN REAL QUADRATIC FIELDS. 1. Introduction

MINIMAL MAHLER MEASURE IN REAL QUADRATIC FIELDS. 1. Introduction INIAL AHLER EASURE IN REAL QUADRATIC FIELDS TODD COCHRANE, R.. S. DISSANAYAKE, NICHOLAS DONOHOUE,. I.. ISHAK, VINCENT PIGNO, CHRIS PINNER, AND CRAIG SPENCER Abstract. We consier uer an lower bouns on the

More information

Lecture Notes Di erentiating Trigonometric Functions page 1

Lecture Notes Di erentiating Trigonometric Functions page 1 Lecture Notes Di erentiating Trigonometric Functions age (sin ) 7 sin () sin 8 cos 3 (tan ) sec tan + 9 tan + 4 (cot ) csc cot 0 cot + 5 sin (sec ) cos sec tan sec jj 6 (csc ) sin csc cot csc jj c Hiegkuti,

More information

Section 2.1 The Derivative and the Tangent Line Problem

Section 2.1 The Derivative and the Tangent Line Problem Chapter 2 Differentiation Course Number Section 2.1 The Derivative an the Tangent Line Problem Objective: In this lesson you learne how to fin the erivative of a function using the limit efinition an unerstan

More information

cosh x sinh x So writing t = tan(x/2) we have 6.4 Integration using tan(x/2) = 2 2t 1 + t 2 cos x = 1 t2 We will revisit the double angle identities:

cosh x sinh x So writing t = tan(x/2) we have 6.4 Integration using tan(x/2) = 2 2t 1 + t 2 cos x = 1 t2 We will revisit the double angle identities: 6.4 Integration using tanx/) We will revisit the ouble angle ientities: sin x = sinx/) cosx/) = tanx/) sec x/) = tanx/) + tan x/) cos x = cos x/) sin x/) tan x = = tan x/) sec x/) tanx/) tan x/). = tan

More information

Bivariate distributions characterized by one family of conditionals and conditional percentile or mode functions

Bivariate distributions characterized by one family of conditionals and conditional percentile or mode functions Journal of Multivariate Analysis 99 2008) 1383 1392 www.elsevier.com/locate/jmva Bivariate istributions characterize by one family of conitionals an conitional ercentile or moe functions Barry C. Arnol

More information

Calculus of Variations

Calculus of Variations 16.323 Lecture 5 Calculus of Variations Calculus of Variations Most books cover this material well, but Kirk Chapter 4 oes a particularly nice job. x(t) x* x*+ αδx (1) x*- αδx (1) αδx (1) αδx (1) t f t

More information

arxiv:hep-th/ v1 3 Feb 1993

arxiv:hep-th/ v1 3 Feb 1993 NBI-HE-9-89 PAR LPTHE 9-49 FTUAM 9-44 November 99 Matrix moel calculations beyon the spherical limit arxiv:hep-th/93004v 3 Feb 993 J. Ambjørn The Niels Bohr Institute Blegamsvej 7, DK-00 Copenhagen Ø,

More information

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson JUST THE MATHS UNIT NUMBER 10.2 DIFFERENTIATION 2 (Rates of change) by A.J.Hobson 10.2.1 Introuction 10.2.2 Average rates of change 10.2.3 Instantaneous rates of change 10.2.4 Derivatives 10.2.5 Exercises

More information

COMMUNICATION BETWEEN SHAREHOLDERS 1

COMMUNICATION BETWEEN SHAREHOLDERS 1 COMMUNICATION BTWN SHARHOLDRS 1 A B. O A : A D Lemma B.1. U to µ Z r 2 σ2 Z + σ2 X 2r ω 2 an additive constant that does not deend on a or θ, the agents ayoffs can be written as: 2r rθa ω2 + θ µ Y rcov

More information

A. Exclusive KL View of the MLE

A. Exclusive KL View of the MLE A. Exclusive KL View of the MLE Lets assume a change-of-variable moel p Z z on the ranom variable Z R m, such as the one use in Dinh et al. 2017: z 0 p 0 z 0 an z = ψz 0, where ψ is an invertible function

More information

Continuous observer design for nonlinear systems with sampled and delayed output measurements

Continuous observer design for nonlinear systems with sampled and delayed output measurements Preprints of th9th Worl Congress The International Feeration of Automatic Control Continuous observer esign for nonlinear systems with sample an elaye output measurements Daoyuan Zhang Yanjun Shen Xiaohua

More information

inflow outflow Part I. Regular tasks for MAE598/494 Task 1

inflow outflow Part I. Regular tasks for MAE598/494 Task 1 MAE 494/598, Fall 2016 Project #1 (Regular tasks = 20 points) Har copy of report is ue at the start of class on the ue ate. The rules on collaboration will be release separately. Please always follow the

More information

Iterated Point-Line Configurations Grow Doubly-Exponentially

Iterated Point-Line Configurations Grow Doubly-Exponentially Iterate Point-Line Configurations Grow Doubly-Exponentially Joshua Cooper an Mark Walters July 9, 008 Abstract Begin with a set of four points in the real plane in general position. A to this collection

More information

Linear First-Order Equations

Linear First-Order Equations 5 Linear First-Orer Equations Linear first-orer ifferential equations make up another important class of ifferential equations that commonly arise in applications an are relatively easy to solve (in theory)

More information

Dead Zone Model Based Adaptive Backstepping Control for a Class of Uncertain Saturated Systems

Dead Zone Model Based Adaptive Backstepping Control for a Class of Uncertain Saturated Systems Milano (Italy) August - September, 11 Dea Zone Moel Base Aaptive Backstepping Control for a Class of Uncertain Saturate Systems Seyye Hossein Mousavi Alireza Khayatian School of Electrical an Computer

More information

A Weak First Digit Law for a Class of Sequences

A Weak First Digit Law for a Class of Sequences International Mathematical Forum, Vol. 11, 2016, no. 15, 67-702 HIKARI Lt, www.m-hikari.com http://x.oi.org/10.1288/imf.2016.6562 A Weak First Digit Law for a Class of Sequences M. A. Nyblom School of

More information

Synchronization of Diffusively Coupled Oscillators: Theory and Experiment

Synchronization of Diffusively Coupled Oscillators: Theory and Experiment American Journal of Electrical an Electronic Engineering 2015 Vol 3 No 2 37-3 Available online at http://pubssciepubcom/ajeee/3/2/3 Science an Eucation Publishing DOI:12691/ajeee-3-2-3 Synchronization

More information

By completing this chapter, the reader will be able to:

By completing this chapter, the reader will be able to: hater 4. Mechanics of Particles Particle mechanics governs many rinciles of article measurement instrumentation an air cleaning technologies. Therefore, this chater rovies the funamentals of article mechanics.

More information

Least-Squares Regression on Sparse Spaces

Least-Squares Regression on Sparse Spaces Least-Squares Regression on Sparse Spaces Yuri Grinberg, Mahi Milani Far, Joelle Pineau School of Computer Science McGill University Montreal, Canaa {ygrinb,mmilan1,jpineau}@cs.mcgill.ca 1 Introuction

More information

Meshless Methods for Scientific Computing Final Project

Meshless Methods for Scientific Computing Final Project Meshless Methods for Scientific Comuting Final Project D0051008 洪啟耀 Introduction Floating island becomes an imortant study in recent years, because the lands we can use are limit, so eole start thinking

More information

Laplacian Cooperative Attitude Control of Multiple Rigid Bodies

Laplacian Cooperative Attitude Control of Multiple Rigid Bodies Laplacian Cooperative Attitue Control of Multiple Rigi Boies Dimos V. Dimarogonas, Panagiotis Tsiotras an Kostas J. Kyriakopoulos Abstract Motivate by the fact that linear controllers can stabilize the

More information

Adaptive Gain-Scheduled H Control of Linear Parameter-Varying Systems with Time-Delayed Elements

Adaptive Gain-Scheduled H Control of Linear Parameter-Varying Systems with Time-Delayed Elements Aaptive Gain-Scheule H Control of Linear Parameter-Varying Systems with ime-delaye Elements Yoshihiko Miyasato he Institute of Statistical Mathematics 4-6-7 Minami-Azabu, Minato-ku, okyo 6-8569, Japan

More information

Normalized Ordinal Distance; A Performance Metric for Ordinal, Probabilistic-ordinal or Partial-ordinal Classification Problems

Normalized Ordinal Distance; A Performance Metric for Ordinal, Probabilistic-ordinal or Partial-ordinal Classification Problems Normalize rinal Distance; A Performance etric for rinal, Probabilistic-orinal or Partial-orinal Classification Problems ohamma Hasan Bahari, Hugo Van hamme Center for rocessing seech an images, KU Leuven,

More information

A Model of Discovery

A Model of Discovery Moel of Discovery Michele olrin an Davi K. Levine 1 his version: December 26, 2008 First version: December 13, 2008 Prepare for the 2008 merican Economic ssociation Meetings. Session itle: Intellectual

More information

NOTES ON EULER-BOOLE SUMMATION (1) f (l 1) (n) f (l 1) (m) + ( 1)k 1 k! B k (y) f (k) (y) dy,

NOTES ON EULER-BOOLE SUMMATION (1) f (l 1) (n) f (l 1) (m) + ( 1)k 1 k! B k (y) f (k) (y) dy, NOTES ON EULER-BOOLE SUMMATION JONATHAN M BORWEIN, NEIL J CALKIN, AND DANTE MANNA Abstract We stuy a connection between Euler-MacLaurin Summation an Boole Summation suggeste in an AMM note from 196, which

More information

'HVLJQ &RQVLGHUDWLRQ LQ 0DWHULDO 6HOHFWLRQ 'HVLJQ 6HQVLWLYLW\,1752'8&7,21

'HVLJQ &RQVLGHUDWLRQ LQ 0DWHULDO 6HOHFWLRQ 'HVLJQ 6HQVLWLYLW\,1752'8&7,21 Large amping in a structural material may be either esirable or unesirable, epening on the engineering application at han. For example, amping is a esirable property to the esigner concerne with limiting

More information

5. THERMAL CONVERSION OF SOLAR RADIATION. Content

5. THERMAL CONVERSION OF SOLAR RADIATION. Content 5. Introuction 5. THEMAL CONVESION OF SOLA ADIATION Content 5. Introuction 5. Collectors without concentration 5.. Otical efficiency of the flat collector 5.. Thermal efficiency of the flat collector 5..3

More information

Balancing Expected and Worst-Case Utility in Contracting Models with Asymmetric Information and Pooling

Balancing Expected and Worst-Case Utility in Contracting Models with Asymmetric Information and Pooling Balancing Expecte an Worst-Case Utility in Contracting Moels with Asymmetric Information an Pooling R.B.O. erkkamp & W. van en Heuvel & A.P.M. Wagelmans Econometric Institute Report EI2018-01 9th January

More information

A Note on Exact Solutions to Linear Differential Equations by the Matrix Exponential

A Note on Exact Solutions to Linear Differential Equations by the Matrix Exponential Avances in Applie Mathematics an Mechanics Av. Appl. Math. Mech. Vol. 1 No. 4 pp. 573-580 DOI: 10.4208/aamm.09-m0946 August 2009 A Note on Exact Solutions to Linear Differential Equations by the Matrix

More information

Lecture 2 Lagrangian formulation of classical mechanics Mechanics

Lecture 2 Lagrangian formulation of classical mechanics Mechanics Lecture Lagrangian formulation of classical mechanics 70.00 Mechanics Principle of stationary action MATH-GA To specify a motion uniquely in classical mechanics, it suffices to give, at some time t 0,

More information

LeChatelier Dynamics

LeChatelier Dynamics LeChatelier Dynamics Robert Gilmore Physics Department, Drexel University, Philaelphia, Pennsylvania 1914, USA (Date: June 12, 28, Levine Birthay Party: To be submitte.) Dynamics of the relaxation of a

More information

model considered before, but the prey obey logistic growth in the absence of predators. In

model considered before, but the prey obey logistic growth in the absence of predators. In 5.2. First Orer Systems of Differential Equations. Phase Portraits an Linearity. Section Objective(s): Moifie Preator-Prey Moel. Graphical Representations of Solutions. Phase Portraits. Vector Fiels an

More information

The Impact of Collusion on the Price of Anarchy in Nonatomic and Discrete Network Games

The Impact of Collusion on the Price of Anarchy in Nonatomic and Discrete Network Games The Impact of Collusion on the Price of Anarchy in Nonatomic an Discrete Network Games Tobias Harks Institute of Mathematics, Technical University Berlin, Germany harks@math.tu-berlin.e Abstract. Hayrapetyan,

More information

Fluctuating epidemics on adaptive networks

Fluctuating epidemics on adaptive networks PHYSCAL REVEW E 77, 6611 28 Fluctuating eiemics on aative networks Leah B. Shaw Deartment of Alie Science, College of William an Mary, Williamsburg, Virginia 23187, USA ra B. Schwartz US Naval Research

More information