Analytical Solution of Nonlinear Cubic-Quintic. Duffing Oscillator Using Global Error. Minimization Method

Size: px
Start display at page:

Download "Analytical Solution of Nonlinear Cubic-Quintic. Duffing Oscillator Using Global Error. Minimization Method"

Transcription

1 Adv. Studies Theor. Phys., Vol. 6,, o., Aalytical Solutio of Noliear Cubic-Quitic Duffig Oscillator Usig Global Error Miimizatio Method A. Kargar ad M. Akbarzade Departmet of Mechaical Egieerig Qucha Brach, Islamic Azad Uiversity, Qucha, Ira Abstract A modified variatioal approach called Global Error Miimizatio (GEM) method is developed for obtaiig a approximate closed-form aalytical solutio for oliear oscillator differetial equatios. The proposed method coverts the oliear differetial equatio to a equivalet miimizatio problem. A trial solutio is selected with ukow parameters. Next, the GEM method is used to solve the miimizatio problem ad to obtai the ukow parameters. Keywords: Noliear Oscillators; Aalytical approximate solutios; Global Error Miimizatio method. Correspodig author: ali_kargar_57@yahoo.com

2 468 A. Kargar ad M. Akbarzade - Itroductio There are several methods used to fid approximate solutios to oliear problems such as homotopy perturbatio method [], eergy balace method [3] ad Amplitude-Frequecy Formulatio [4] were used to hadle strogly oliear systems. Our cocer i this paper is the derivatio of a approximate aalytical solutio for a oliear oscillatory differetial equatio. To do this we modify the variatioal approach proposed by He [5] ad develop a method called GEM (Global Error Miimizatio) []. - Basic idea I this sectio the Global Error Miimizatio (GEM) method is itroduced ad developed. The method is systematically described ad will result i a approximate aalytic solutio for the strogly oliear oscillator ODEs. Cosider a geeral secod-order oliear oscillator differetial equatio: u + F( u, u, u) =, u() = A, u () = () With iitial coditios: u() = A, u () = B () Defiitio: Cosider the oliear system (); we defie the followig fuctioal for the oscillator equatio, called the global error fuctioal: Eu (, u, u) = T u + Fu (, u, u) dt (3) ( ) π T =, ω is the primary atural frequecy where E is a cotiuous fuctioal. ω The solutio of Eq. () ca be expressed i the form of Fourier series []: (4) ut () = a + a cos( ωt) + bsi( ωt) = ( ) Where a, a, b are costats. These ukow costats could ot be determied for the case of ifiite Fourier series. However, we ca approximate Eq. (4) by a fiite series: m (5) ut () = a + a cos( ωt) + bsi( ωt) = ( ) I this paper, a atural ad efficiet method will be developed for determiig these ukows. The oliear problem () is first coverted to the miimizatio problem

3 Aalytical solutio 469 (3). We directly substitute the trial solutio (5) i the miimizatio problem. The solutios of the miimizatio problem are the ukow costats of Eq. (5). 3- Applicatio A cubic-quitic Duffig oscillator of a coservative autoomous system ca be described by the followig secod-order differetial equatio with cubic-quitic oliearities [8]: u + u+ ε u + u = u = A u = (6) 3 5 ε, (), () We begi the procedure with the simplest trial solutio: u ( t) = Acos( ω t), u () = A, u () = (7) Next, we covert Eq. (6) to the miimizatio problem (3): T 3 5 ( ) π Eu (, u, u) = u + u+ εu + εu dt, T= ω (8) By replacig u () t = A cos( ωt ) i Eq. (8) ad performig the itegratio we get: A 8 4 E = ( 945A ε π + 88A επ + A ε π 9 ω + 4A επ+ 9π 384ωπ + 9ωπ 4 4 ) (9) E The solutio could be foud through the coditio = : ω ω = A ε + 36A ε A ε + 8A ε ε + 8A ε + 64A ε + 536A ε () If we add oe more term to the trail fuctio (Eq. (7)) we ca easily obtai the secod order approximatio. I order to compare with Modified Lidsted-Poicare solutio: Double series Expasio, we write J. H. He s result [6]:

4 47 A. Kargar ad M. Akbarzade ω = + 3 ε A + 5 ε A () Table Compariso of the GEM method with Modified Lidsted-Poicare solutio [6] ( ε = ε = ). A GEM method Modified Lidsted- Poicare I caseε =, ε = ε, Eq. (6) turs to the well-kow Duffig equatio ad its oliear agular frequecy ca be obtaied fromeq. (), which reads: 4 () ω = A ε+ 3 64A ε + 536A ε+ 4 The exact frequecy of the periodic motio of the Duffig equatio is give by [6]: π π + εa dx ωexact = msi x ε A Where m = For compariso, the exact frequecy obtaied by ( + ε A ) itegratig Eq. (3) ad the approximate frequecy computed by Eq. () are listed i Table. (3) Table Compariso of the GEM method with exact solutio. ε A GEM method Exact solutio

5 Aalytical solutio Coclusios The GEM method was successfully applied to oliear Cubic-Quitic Duffig Oscillator. The method is useful to obtai aalytical solutio for all oscillators ad vibratio problems, such as i the fields of civil structures, fluid mechaics, electromagetics ad waves, etc. This paper shows oe step i the attempt to develop a ew oliear aalytical techique i absece of small parameters. Refereces [] Fereidoo A., Rostamiya Y., Akbarzade M., Domiri Gaji Davood, Applicatio of He s homotopy perturbatio method to oliear shock damper dyamics, Archive of Applied Mechaics, 8 (6), () [] Farzaeh V., Akbarzadeh Tootoochi Ali, Global Error Miimizatio method for solvig strogly oliear oscillator differetial equatios, Computers ad Mathematics with Applicatios, 59 () [3] Gaji D. D., Rajbar Malidarreh N.., Akbarzade M., Compariso of Eergy Balace Period for Arisig Noliear Oscillator Equatios (He s eergy balace period for oliear oscillators with ad without discotiuities), Acta Applicadae Mathematicae, 8 (9), [4] He J. H., Some asymptotic methods for strogly oliear equatios, It. J. Mod. Phys. B, (6) [5] He J. H., Variatioal approach for oliear oscillators, Chaos Solitos ad Fractals, 34 (7) [6] Ji-Hua, He, No Perturbative Methods for Strogly Noliear Problems, dissertatio.de -Verlag im iteret GmbH, Berli, (6). Received: December,

Cantilever Beam Experiment

Cantilever Beam Experiment Mechaical Egieerig Departmet Uiversity of Massachusetts Lowell Catilever Beam Experimet Backgroud A disk drive maufacturer is redesigig several disk drive armature mechaisms. This is the result of evaluatio

More information

Sequences and Series

Sequences and Series CHAPTER 9 Sequeces ad Series 9.. Covergece: Defiitio ad Examples Sequeces The purpose of this chapter is to itroduce a particular way of geeratig algorithms for fidig the values of fuctios defied by their

More information

Partial Di erential Equations

Partial Di erential Equations Partial Di eretial Equatios Partial Di eretial Equatios Much of moder sciece, egieerig, ad mathematics is based o the study of partial di eretial equatios, where a partial di eretial equatio is a equatio

More information

Problem Solving with Mathematical Software Packages 1

Problem Solving with Mathematical Software Packages 1 C H A P T E R 1 Problem Solvig with Mathematical Software Packages 1 1.1 EFFICIENT PROBLEM SOLVING THE OBJECTIVE OF THIS BOOK As a egieerig studet or professioal, you are almost always ivolved i umerical

More information

Soving Recurrence Relations

Soving Recurrence Relations Sovig Recurrece Relatios Part 1. Homogeeous liear 2d degree relatios with costat coefficiets. Cosider the recurrece relatio ( ) T () + at ( 1) + bt ( 2) = 0 This is called a homogeeous liear 2d degree

More information

Theorems About Power Series

Theorems About Power Series Physics 6A Witer 20 Theorems About Power Series Cosider a power series, f(x) = a x, () where the a are real coefficiets ad x is a real variable. There exists a real o-egative umber R, called the radius

More information

INFINITE SERIES KEITH CONRAD

INFINITE SERIES KEITH CONRAD INFINITE SERIES KEITH CONRAD. Itroductio The two basic cocepts of calculus, differetiatio ad itegratio, are defied i terms of limits (Newto quotiets ad Riema sums). I additio to these is a third fudametal

More information

Section 11.3: The Integral Test

Section 11.3: The Integral Test Sectio.3: The Itegral Test Most of the series we have looked at have either diverged or have coverged ad we have bee able to fid what they coverge to. I geeral however, the problem is much more difficult

More information

3 Energy. 3.3. Non-Flow Energy Equation (NFEE) Internal Energy. MECH 225 Engineering Science 2

3 Energy. 3.3. Non-Flow Energy Equation (NFEE) Internal Energy. MECH 225 Engineering Science 2 MECH 5 Egieerig Sciece 3 Eergy 3.3. No-Flow Eergy Equatio (NFEE) You may have oticed that the term system kees croig u. It is ecessary, therefore, that before we start ay aalysis we defie the system that

More information

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations CS3A Hadout 3 Witer 00 February, 00 Solvig Recurrece Relatios Itroductio A wide variety of recurrece problems occur i models. Some of these recurrece relatios ca be solved usig iteratio or some other ad

More information

Research Article Sign Data Derivative Recovery

Research Article Sign Data Derivative Recovery Iteratioal Scholarly Research Network ISRN Applied Mathematics Volume 0, Article ID 63070, 7 pages doi:0.540/0/63070 Research Article Sig Data Derivative Recovery L. M. Housto, G. A. Glass, ad A. D. Dymikov

More information

AP Calculus AB 2006 Scoring Guidelines Form B

AP Calculus AB 2006 Scoring Guidelines Form B AP Calculus AB 6 Scorig Guidelies Form B The College Board: Coectig Studets to College Success The College Board is a ot-for-profit membership associatio whose missio is to coect studets to college success

More information

On Formula to Compute Primes. and the n th Prime

On Formula to Compute Primes. and the n th Prime Applied Mathematical cieces, Vol., 0, o., 35-35 O Formula to Compute Primes ad the th Prime Issam Kaddoura Lebaese Iteratioal Uiversity Faculty of Arts ad cieces, Lebao issam.kaddoura@liu.edu.lb amih Abdul-Nabi

More information

Lecture 7: Stationary Perturbation Theory

Lecture 7: Stationary Perturbation Theory Lecture 7: Statioary Perturbatio Theory I most practical applicatios the time idepedet Schrödiger equatio Hψ = Eψ (1) caot be solved exactly ad oe has to resort to some scheme of fidig approximate solutios,

More information

Annuities Under Random Rates of Interest II By Abraham Zaks. Technion I.I.T. Haifa ISRAEL and Haifa University Haifa ISRAEL.

Annuities Under Random Rates of Interest II By Abraham Zaks. Technion I.I.T. Haifa ISRAEL and Haifa University Haifa ISRAEL. Auities Uder Radom Rates of Iterest II By Abraham Zas Techio I.I.T. Haifa ISRAEL ad Haifa Uiversity Haifa ISRAEL Departmet of Mathematics, Techio - Israel Istitute of Techology, 3000, Haifa, Israel I memory

More information

Modified Line Search Method for Global Optimization

Modified Line Search Method for Global Optimization Modified Lie Search Method for Global Optimizatio Cria Grosa ad Ajith Abraham Ceter of Excellece for Quatifiable Quality of Service Norwegia Uiversity of Sciece ad Techology Trodheim, Norway {cria, ajith}@q2s.tu.o

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

More information

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is 0_0605.qxd /5/05 0:45 AM Page 470 470 Chapter 6 Additioal Topics i Trigoometry 6.5 Trigoometric Form of a Complex Number What you should lear Plot complex umbers i the complex plae ad fid absolute values

More information

How To Solve The Phemean Problem Of Polar And Polar Coordiates

How To Solve The Phemean Problem Of Polar And Polar Coordiates ISSN 1 746-733, Eglad, UK World Joural of Modellig ad Simulatio Vol. 8 (1) No. 3, pp. 163-171 Alterate treatmets of jacobia sigularities i polar coordiates withi fiite-differece schemes Alexys Bruo-Alfoso

More information

Building Blocks Problem Related to Harmonic Series

Building Blocks Problem Related to Harmonic Series TMME, vol3, o, p.76 Buildig Blocks Problem Related to Harmoic Series Yutaka Nishiyama Osaka Uiversity of Ecoomics, Japa Abstract: I this discussio I give a eplaatio of the divergece ad covergece of ifiite

More information

CHAPTER 3 THE TIME VALUE OF MONEY

CHAPTER 3 THE TIME VALUE OF MONEY CHAPTER 3 THE TIME VALUE OF MONEY OVERVIEW A dollar i the had today is worth more tha a dollar to be received i the future because, if you had it ow, you could ivest that dollar ad ear iterest. Of all

More information

A probabilistic proof of a binomial identity

A probabilistic proof of a binomial identity A probabilistic proof of a biomial idetity Joatho Peterso Abstract We give a elemetary probabilistic proof of a biomial idetity. The proof is obtaied by computig the probability of a certai evet i two

More information

Queuing Systems: Lecture 1. Amedeo R. Odoni October 10, 2001

Queuing Systems: Lecture 1. Amedeo R. Odoni October 10, 2001 Queuig Systems: Lecture Amedeo R. Odoi October, 2 Topics i Queuig Theory 9. Itroductio to Queues; Little s Law; M/M/. Markovia Birth-ad-Death Queues. The M/G/ Queue ad Extesios 2. riority Queues; State

More information

NEW HIGH PERFORMANCE COMPUTATIONAL METHODS FOR MORTGAGES AND ANNUITIES. Yuri Shestopaloff,

NEW HIGH PERFORMANCE COMPUTATIONAL METHODS FOR MORTGAGES AND ANNUITIES. Yuri Shestopaloff, NEW HIGH PERFORMNCE COMPUTTIONL METHODS FOR MORTGGES ND NNUITIES Yuri Shestopaloff, Geerally, mortgage ad auity equatios do ot have aalytical solutios for ukow iterest rate, which has to be foud usig umerical

More information

CME 302: NUMERICAL LINEAR ALGEBRA FALL 2005/06 LECTURE 8

CME 302: NUMERICAL LINEAR ALGEBRA FALL 2005/06 LECTURE 8 CME 30: NUMERICAL LINEAR ALGEBRA FALL 005/06 LECTURE 8 GENE H GOLUB 1 Positive Defiite Matrices A matrix A is positive defiite if x Ax > 0 for all ozero x A positive defiite matrix has real ad positive

More information

Lecture 3. denote the orthogonal complement of S k. Then. 1 x S k. n. 2 x T Ax = ( ) λ x. with x = 1, we have. i = λ k x 2 = λ k.

Lecture 3. denote the orthogonal complement of S k. Then. 1 x S k. n. 2 x T Ax = ( ) λ x. with x = 1, we have. i = λ k x 2 = λ k. 18.409 A Algorithmist s Toolkit September 17, 009 Lecture 3 Lecturer: Joatha Keler Scribe: Adre Wibisoo 1 Outlie Today s lecture covers three mai parts: Courat-Fischer formula ad Rayleigh quotiets The

More information

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series 8 Fourier Series Our aim is to show that uder reasoable assumptios a give -periodic fuctio f ca be represeted as coverget series f(x) = a + (a cos x + b si x). (8.) By defiitio, the covergece of the series

More information

An Efficient Polynomial Approximation of the Normal Distribution Function & Its Inverse Function

An Efficient Polynomial Approximation of the Normal Distribution Function & Its Inverse Function A Efficiet Polyomial Approximatio of the Normal Distributio Fuctio & Its Iverse Fuctio Wisto A. Richards, 1 Robi Atoie, * 1 Asho Sahai, ad 3 M. Raghuadh Acharya 1 Departmet of Mathematics & Computer Sciece;

More information

Systems Design Project: Indoor Location of Wireless Devices

Systems Design Project: Indoor Location of Wireless Devices Systems Desig Project: Idoor Locatio of Wireless Devices Prepared By: Bria Murphy Seior Systems Sciece ad Egieerig Washigto Uiversity i St. Louis Phoe: (805) 698-5295 Email: bcm1@cec.wustl.edu Supervised

More information

Chapter 7 Methods of Finding Estimators

Chapter 7 Methods of Finding Estimators Chapter 7 for BST 695: Special Topics i Statistical Theory. Kui Zhag, 011 Chapter 7 Methods of Fidig Estimators Sectio 7.1 Itroductio Defiitio 7.1.1 A poit estimator is ay fuctio W( X) W( X1, X,, X ) of

More information

Heat (or Diffusion) equation in 1D*

Heat (or Diffusion) equation in 1D* Heat (or Diffusio) equatio i D* Derivatio of the D heat equatio Separatio of variables (refresher) Worked eamples *Kreysig, 8 th Ed, Sectios.4b Physical assumptios We cosider temperature i a log thi wire

More information

APPLICATION NOTE 30 DFT or FFT? A Comparison of Fourier Transform Techniques

APPLICATION NOTE 30 DFT or FFT? A Comparison of Fourier Transform Techniques APPLICATION NOTE 30 DFT or FFT? A Compariso of Fourier Trasform Techiques This applicatio ote ivestigates differeces i performace betwee the DFT (Discrete Fourier Trasform) ad the FFT(Fast Fourier Trasform)

More information

OPTIMIZATION OF AN ENGINE MOUNTING SYSTEM FOR VIBRO-ACOUSTIC COMFORT IMPROVEMENT

OPTIMIZATION OF AN ENGINE MOUNTING SYSTEM FOR VIBRO-ACOUSTIC COMFORT IMPROVEMENT OPTIMIZATION OF AN ENGINE MOUNTING SYSTEM FOR VIBRO-ACOUSTIC COMFORT IMPROVEMENT Marco La Civita ad Aldo Sestieri Departmet of Mechaics ad Aeroautics Uiversity of Rome "La Sapieza" 184 Rome, ITALY ABSTRACT

More information

Inverse Gaussian Distribution

Inverse Gaussian Distribution 5 Kauhisa Matsuda All rights reserved. Iverse Gaussia Distributio Abstract Kauhisa Matsuda Departmet of Ecoomics The Graduate Ceter The City Uiversity of New York 65 Fifth Aveue New York NY 6-49 Email:

More information

Degree of Approximation of Continuous Functions by (E, q) (C, δ) Means

Degree of Approximation of Continuous Functions by (E, q) (C, δ) Means Ge. Math. Notes, Vol. 11, No. 2, August 2012, pp. 12-19 ISSN 2219-7184; Copyright ICSRS Publicatio, 2012 www.i-csrs.org Available free olie at http://www.gema.i Degree of Approximatio of Cotiuous Fuctios

More information

University of California, Los Angeles Department of Statistics. Distributions related to the normal distribution

University of California, Los Angeles Department of Statistics. Distributions related to the normal distribution Uiversity of Califoria, Los Ageles Departmet of Statistics Statistics 100B Istructor: Nicolas Christou Three importat distributios: Distributios related to the ormal distributio Chi-square (χ ) distributio.

More information

ON THE DENSE TRAJECTORY OF LASOTA EQUATION

ON THE DENSE TRAJECTORY OF LASOTA EQUATION UNIVERSITATIS IAGELLONICAE ACTA MATHEMATICA, FASCICULUS XLIII 2005 ON THE DENSE TRAJECTORY OF LASOTA EQUATION by Atoi Leo Dawidowicz ad Najemedi Haribash Abstract. I preseted paper the dese trajectory

More information

19. LINEAR VISCOUS DAMPING. Linear Viscous Damping Is a Property of the Computational Model And is not a Property of a Real Structure

19. LINEAR VISCOUS DAMPING. Linear Viscous Damping Is a Property of the Computational Model And is not a Property of a Real Structure 19. LINEAR VISCOUS DAMPING Liear Viscous Dampig Is a Property of the Computatioal Model Ad is ot a Property of a Real Structure 19.1 INRODUCION { XE "Viscous Dampig" }I structural egieerig, viscous velocity-depedet

More information

'rj /ifi a a2 a3 a4. (To = Vi/r/2h), are entered in the last column of Table I for different values ECONOMICS AND THE CALCULUS OF VARIATIONS

'rj /ifi a a2 a3 a4. (To = Vi/r/2h), are entered in the last column of Table I for different values ECONOMICS AND THE CALCULUS OF VARIATIONS 90 MA THEMA TICS: G. C. E VA NS PROC. N. A. S. ues for a show i the secod colum, the coefficiets of zi may be easily computed for ay specific value of V/w. The coefficiets A- satisfy the coditio i j! =

More information

Chapter 5: Inner Product Spaces

Chapter 5: Inner Product Spaces Chapter 5: Ier Product Spaces Chapter 5: Ier Product Spaces SECION A Itroductio to Ier Product Spaces By the ed of this sectio you will be able to uderstad what is meat by a ier product space give examples

More information

How To Solve The Homewor Problem Beautifully

How To Solve The Homewor Problem Beautifully Egieerig 33 eautiful Homewor et 3 of 7 Kuszmar roblem.5.5 large departmet store sells sport shirts i three sizes small, medium, ad large, three patters plaid, prit, ad stripe, ad two sleeve legths log

More information

Original Research Comparison of Analytical and Numerical Solutions for Steady, Gradually Varied Open-Channel Flow

Original Research Comparison of Analytical and Numerical Solutions for Steady, Gradually Varied Open-Channel Flow Polis J. of Eviro. Stud. Vol., No. 4 (), 95-9 Origial Researc Compariso of Aalytical ad Numerical Solutios for Steady, Gradually Varied Ope-Cael Flow Jacek Kuratowski* Departmet of Hydroegieerig, West

More information

Properties of MLE: consistency, asymptotic normality. Fisher information.

Properties of MLE: consistency, asymptotic normality. Fisher information. Lecture 3 Properties of MLE: cosistecy, asymptotic ormality. Fisher iformatio. I this sectio we will try to uderstad why MLEs are good. Let us recall two facts from probability that we be used ofte throughout

More information

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions Chapter 5 Uit Aual Amout ad Gradiet Fuctios IET 350 Egieerig Ecoomics Learig Objectives Chapter 5 Upo completio of this chapter you should uderstad: Calculatig future values from aual amouts. Calculatig

More information

Asymptotic Growth of Functions

Asymptotic Growth of Functions CMPS Itroductio to Aalysis of Algorithms Fall 3 Asymptotic Growth of Fuctios We itroduce several types of asymptotic otatio which are used to compare the performace ad efficiecy of algorithms As we ll

More information

Investigation of Atwood s machines as Series and Parallel networks

Investigation of Atwood s machines as Series and Parallel networks Ivestiatio of Atwood s achies as Series ad Parallel etworks Jafari Matehkolaee, Mehdi; Bavad, Air Ahad Islaic Azad uiversity of Shahrood, Shahid Beheshti hih school i Sari, Mazadara, Ira ehdisaraviaria@yahoo.co

More information

The Gompertz Makeham coupling as a Dynamic Life Table. Abraham Zaks. Technion I.I.T. Haifa ISRAEL. Abstract

The Gompertz Makeham coupling as a Dynamic Life Table. Abraham Zaks. Technion I.I.T. Haifa ISRAEL. Abstract The Gompertz Makeham couplig as a Dyamic Life Table By Abraham Zaks Techio I.I.T. Haifa ISRAEL Departmet of Mathematics, Techio - Israel Istitute of Techology, 32000, Haifa, Israel Abstract A very famous

More information

Lecture 4: Cheeger s Inequality

Lecture 4: Cheeger s Inequality Spectral Graph Theory ad Applicatios WS 0/0 Lecture 4: Cheeger s Iequality Lecturer: Thomas Sauerwald & He Su Statemet of Cheeger s Iequality I this lecture we assume for simplicity that G is a d-regular

More information

Department of Computer Science, University of Otago

Department of Computer Science, University of Otago Departmet of Computer Sciece, Uiversity of Otago Techical Report OUCS-2006-09 Permutatios Cotaiig May Patters Authors: M.H. Albert Departmet of Computer Sciece, Uiversity of Otago Micah Colema, Rya Fly

More information

Vladimir N. Burkov, Dmitri A. Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT

Vladimir N. Burkov, Dmitri A. Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT Keywords: project maagemet, resource allocatio, etwork plaig Vladimir N Burkov, Dmitri A Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT The paper deals with the problems of resource allocatio betwee

More information

Irreducible polynomials with consecutive zero coefficients

Irreducible polynomials with consecutive zero coefficients Irreducible polyomials with cosecutive zero coefficiets Theodoulos Garefalakis Departmet of Mathematics, Uiversity of Crete, 71409 Heraklio, Greece Abstract Let q be a prime power. We cosider the problem

More information

BASIC STATISTICS. f(x 1,x 2,..., x n )=f(x 1 )f(x 2 ) f(x n )= f(x i ) (1)

BASIC STATISTICS. f(x 1,x 2,..., x n )=f(x 1 )f(x 2 ) f(x n )= f(x i ) (1) BASIC STATISTICS. SAMPLES, RANDOM SAMPLING AND SAMPLE STATISTICS.. Radom Sample. The radom variables X,X 2,..., X are called a radom sample of size from the populatio f(x if X,X 2,..., X are mutually idepedet

More information

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx SAMPLE QUESTIONS FOR FINAL EXAM REAL ANALYSIS I FALL 006 3 4 Fid the followig usig the defiitio of the Riema itegral: a 0 x + dx 3 Cosider the partitio P x 0 3, x 3 +, x 3 +,......, x 3 3 + 3 of the iterval

More information

On the L p -conjecture for locally compact groups

On the L p -conjecture for locally compact groups Arch. Math. 89 (2007), 237 242 c 2007 Birkhäuser Verlag Basel/Switzerlad 0003/889X/030237-6, ublished olie 2007-08-0 DOI 0.007/s0003-007-993-x Archiv der Mathematik O the L -cojecture for locally comact

More information

THE problem of fitting a circle to a collection of points

THE problem of fitting a circle to a collection of points IEEE TRANACTION ON INTRUMENTATION AND MEAUREMENT, VOL. XX, NO. Y, MONTH 000 A Few Methods for Fittig Circles to Data Dale Umbach, Kerry N. Joes Abstract Five methods are discussed to fit circles to data.

More information

THIN SEQUENCES AND THE GRAM MATRIX PAMELA GORKIN, JOHN E. MCCARTHY, SANDRA POTT, AND BRETT D. WICK

THIN SEQUENCES AND THE GRAM MATRIX PAMELA GORKIN, JOHN E. MCCARTHY, SANDRA POTT, AND BRETT D. WICK THIN SEQUENCES AND THE GRAM MATRIX PAMELA GORKIN, JOHN E MCCARTHY, SANDRA POTT, AND BRETT D WICK Abstract We provide a ew proof of Volberg s Theorem characterizig thi iterpolatig sequeces as those for

More information

ON AN INTEGRAL OPERATOR WHICH PRESERVE THE UNIVALENCE

ON AN INTEGRAL OPERATOR WHICH PRESERVE THE UNIVALENCE Proceedigs of the Iteratioal Coferece o Theory ad Applicatios of Mathematics ad Iformatics ICTAMI 3, Alba Iulia ON AN INTEGRAL OPERATOR WHICH PRESERVE THE UNIVALENCE by Maria E Gageoea ad Silvia Moldoveau

More information

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008 I ite Sequeces Dr. Philippe B. Laval Keesaw State Uiversity October 9, 2008 Abstract This had out is a itroductio to i ite sequeces. mai de itios ad presets some elemetary results. It gives the I ite Sequeces

More information

Optimization of (s, S) Inventory Systems with Random Lead Times and a Service Level Constraint

Optimization of (s, S) Inventory Systems with Random Lead Times and a Service Level Constraint with Radom Lead Times ad a Service Level Costrait Sridhar Bashyam j Michael C. Fu KPMG Peat Marwick LLP, 2300 Claredo Boulevard, Arligto, Virgiia 22201 The Robert H. Smith School of Busiess, Uiversity

More information

Data Analysis and Statistical Behaviors of Stock Market Fluctuations

Data Analysis and Statistical Behaviors of Stock Market Fluctuations 44 JOURNAL OF COMPUTERS, VOL. 3, NO. 0, OCTOBER 2008 Data Aalysis ad Statistical Behaviors of Stock Market Fluctuatios Ju Wag Departmet of Mathematics, Beijig Jiaotog Uiversity, Beijig 00044, Chia Email:

More information

arxiv:1506.03481v1 [stat.me] 10 Jun 2015

arxiv:1506.03481v1 [stat.me] 10 Jun 2015 BEHAVIOUR OF ABC FOR BIG DATA By Wetao Li ad Paul Fearhead Lacaster Uiversity arxiv:1506.03481v1 [stat.me] 10 Ju 2015 May statistical applicatios ivolve models that it is difficult to evaluate the likelihood,

More information

Notes on exponential generating functions and structures.

Notes on exponential generating functions and structures. Notes o expoetial geeratig fuctios ad structures. 1. The cocept of a structure. Cosider the followig coutig problems: (1) to fid for each the umber of partitios of a -elemet set, (2) to fid for each the

More information

Recovery time guaranteed heuristic routing for improving computation complexity in survivable WDM networks

Recovery time guaranteed heuristic routing for improving computation complexity in survivable WDM networks Computer Commuicatios 30 (2007) 1331 1336 wwwelseviercom/locate/comcom Recovery time guarateed heuristic routig for improvig computatio complexity i survivable WDM etworks Lei Guo * College of Iformatio

More information

Estimating Probability Distributions by Observing Betting Practices

Estimating Probability Distributions by Observing Betting Practices 5th Iteratioal Symposium o Imprecise Probability: Theories ad Applicatios, Prague, Czech Republic, 007 Estimatig Probability Distributios by Observig Bettig Practices Dr C Lych Natioal Uiversity of Irelad,

More information

Factors of sums of powers of binomial coefficients

Factors of sums of powers of binomial coefficients ACTA ARITHMETICA LXXXVI.1 (1998) Factors of sums of powers of biomial coefficiets by Neil J. Cali (Clemso, S.C.) Dedicated to the memory of Paul Erdős 1. Itroductio. It is well ow that if ( ) a f,a = the

More information

A Simple Software Application for Simulating Commercially Available Solar Panels

A Simple Software Application for Simulating Commercially Available Solar Panels Soft Coutig Ad Software Egieerig (JSCSE) A Sile Software Applicatio for Simulatig Commercially Available Solar Paels 1* Nalika Ulapae, 2 Suil Abeyrate, 3 Prabath Biduhewa, 4 Chamari Dhaapala, 5 Shyama

More information

Equivalent Linear Programs

Equivalent Linear Programs Appedix A Page 1 Equivalet Liear Programs There are a umber of problems that do ot appear at first to be cadidates for liear programmig (LP) but, i fact, have a equivalet or approximate represetatio that

More information

Finite Element Analysis of Rubber Bumper Used in Air-springs

Finite Element Analysis of Rubber Bumper Used in Air-springs Available olie at www.sciecedirect.com Procedia Egieerig 48 (0 ) 388 395 MMaMS 0 Fiite Elemet Aalysis of Rubber Bumper Used i Air-sprigs amas Makovits a *, amas Szabó b a Departmet of Mechaical Egieerig,

More information

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection The aalysis of the Courot oligopoly model cosiderig the subjective motive i the strategy selectio Shigehito Furuyama Teruhisa Nakai Departmet of Systems Maagemet Egieerig Faculty of Egieerig Kasai Uiversity

More information

LOCATIONAL MARGINAL PRICING FRAMEWORK IN SECURED DISPATCH SCHEDULING UNDER CONTINGENCY CONDITION

LOCATIONAL MARGINAL PRICING FRAMEWORK IN SECURED DISPATCH SCHEDULING UNDER CONTINGENCY CONDITION IJRET: Iteratioal Joural of Research i Egieerig ad Techology eissn: 2319-1163 pissn: 2321-7308 LOCATIONAL MARGINAL PRICING FRAMEWORK IN SECURED DISPATCH SCHEDULING UNDER CONTINGENCY CONDITION R.Maiamda

More information

Project Deliverables. CS 361, Lecture 28. Outline. Project Deliverables. Administrative. Project Comments

Project Deliverables. CS 361, Lecture 28. Outline. Project Deliverables. Administrative. Project Comments Project Deliverables CS 361, Lecture 28 Jared Saia Uiversity of New Mexico Each Group should tur i oe group project cosistig of: About 6-12 pages of text (ca be loger with appedix) 6-12 figures (please

More information

Confidence Intervals for One Mean

Confidence Intervals for One Mean Chapter 420 Cofidece Itervals for Oe Mea Itroductio This routie calculates the sample size ecessary to achieve a specified distace from the mea to the cofidece limit(s) at a stated cofidece level for a

More information

Heavy Traffic Analysis of a Simple Closed Loop Supply Chain

Heavy Traffic Analysis of a Simple Closed Loop Supply Chain Heavy Traffic Aalysis of a Simple Closed Loop Supply Chai Arka Ghosh, Sarah M. Rya, Lizhi Wag, ad Aada Weerasighe April 8, 2 Abstract We cosider a closed loop supply chai where ew products are produced

More information

Nr. 2. Interpolation of Discount Factors. Heinz Cremers Willi Schwarz. Mai 1996

Nr. 2. Interpolation of Discount Factors. Heinz Cremers Willi Schwarz. Mai 1996 Nr 2 Iterpolatio of Discout Factors Heiz Cremers Willi Schwarz Mai 1996 Autore: Herausgeber: Prof Dr Heiz Cremers Quatitative Methode ud Spezielle Bakbetriebslehre Hochschule für Bakwirtschaft Dr Willi

More information

Kinematic Synthesis of Multi-fingered Robotic Hands for Finite and Infinitesimal Tasks

Kinematic Synthesis of Multi-fingered Robotic Hands for Finite and Infinitesimal Tasks Kiematic Sythesis of Multi-figered Robotic Hads for Fiite ad Ifiitesimal Tasks E. Simo-Serra, A. Perez-Gracia, H. Moo ad N. Robso Abstract I this paper we preset a ovel method of desigig multi-figered

More information

THE ABRACADABRA PROBLEM

THE ABRACADABRA PROBLEM THE ABRACADABRA PROBLEM FRANCESCO CARAVENNA Abstract. We preset a detailed solutio of Exercise E0.6 i [Wil9]: i a radom sequece of letters, draw idepedetly ad uiformly from the Eglish alphabet, the expected

More information

SEQUENCES AND SERIES

SEQUENCES AND SERIES Chapter 9 SEQUENCES AND SERIES Natural umbers are the product of huma spirit. DEDEKIND 9.1 Itroductio I mathematics, the word, sequece is used i much the same way as it is i ordiary Eglish. Whe we say

More information

Find the inverse Laplace transform of the function F (p) = Evaluating the residues at the four simple poles, we find. residue at z = 1 is 4te t

Find the inverse Laplace transform of the function F (p) = Evaluating the residues at the four simple poles, we find. residue at z = 1 is 4te t Homework Solutios. Chater, Sectio 7, Problem 56. Fid the iverse Lalace trasform of the fuctio F () (7.6). À Chater, Sectio 7, Problem 6. Fid the iverse Lalace trasform of the fuctio F () usig (7.6). Solutio:

More information

MARTINGALES AND A BASIC APPLICATION

MARTINGALES AND A BASIC APPLICATION MARTINGALES AND A BASIC APPLICATION TURNER SMITH Abstract. This paper will develop the measure-theoretic approach to probability i order to preset the defiitio of martigales. From there we will apply this

More information

Lecture 13. Lecturer: Jonathan Kelner Scribe: Jonathan Pines (2009)

Lecture 13. Lecturer: Jonathan Kelner Scribe: Jonathan Pines (2009) 18.409 A Algorithmist s Toolkit October 27, 2009 Lecture 13 Lecturer: Joatha Keler Scribe: Joatha Pies (2009) 1 Outlie Last time, we proved the Bru-Mikowski iequality for boxes. Today we ll go over the

More information

Institute of Actuaries of India Subject CT1 Financial Mathematics

Institute of Actuaries of India Subject CT1 Financial Mathematics Istitute of Actuaries of Idia Subject CT1 Fiacial Mathematics For 2014 Examiatios Subject CT1 Fiacial Mathematics Core Techical Aim The aim of the Fiacial Mathematics subject is to provide a groudig i

More information

Using Four Types Of Notches For Comparison Between Chezy s Constant(C) And Manning s Constant (N)

Using Four Types Of Notches For Comparison Between Chezy s Constant(C) And Manning s Constant (N) INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH OLUME, ISSUE, OCTOBER ISSN - Usig Four Types Of Notches For Compariso Betwee Chezy s Costat(C) Ad Maig s Costat (N) Joyce Edwi Bategeleza, Deepak

More information

NATIONAL SENIOR CERTIFICATE GRADE 12

NATIONAL SENIOR CERTIFICATE GRADE 12 NATIONAL SENIOR CERTIFICATE GRADE MATHEMATICS P EXEMPLAR 04 MARKS: 50 TIME: 3 hours This questio paper cosists of 8 pages ad iformatio sheet. Please tur over Mathematics/P DBE/04 NSC Grade Eemplar INSTRUCTIONS

More information

Overview on S-Box Design Principles

Overview on S-Box Design Principles Overview o S-Box Desig Priciples Debdeep Mukhopadhyay Assistat Professor Departmet of Computer Sciece ad Egieerig Idia Istitute of Techology Kharagpur INDIA -721302 What is a S-Box? S-Boxes are Boolea

More information

4.3. The Integral and Comparison Tests

4.3. The Integral and Comparison Tests 4.3. THE INTEGRAL AND COMPARISON TESTS 9 4.3. The Itegral ad Compariso Tests 4.3.. The Itegral Test. Suppose f is a cotiuous, positive, decreasig fuctio o [, ), ad let a = f(). The the covergece or divergece

More information

A Faster Clause-Shortening Algorithm for SAT with No Restriction on Clause Length

A Faster Clause-Shortening Algorithm for SAT with No Restriction on Clause Length Joural o Satisfiability, Boolea Modelig ad Computatio 1 2005) 49-60 A Faster Clause-Shorteig Algorithm for SAT with No Restrictio o Clause Legth Evgey Datsi Alexader Wolpert Departmet of Computer Sciece

More information

UC Berkeley Department of Electrical Engineering and Computer Science. EE 126: Probablity and Random Processes. Solutions 9 Spring 2006

UC Berkeley Department of Electrical Engineering and Computer Science. EE 126: Probablity and Random Processes. Solutions 9 Spring 2006 Exam format UC Bereley Departmet of Electrical Egieerig ad Computer Sciece EE 6: Probablity ad Radom Processes Solutios 9 Sprig 006 The secod midterm will be held o Wedesday May 7; CHECK the fial exam

More information

Definition. A variable X that takes on values X 1, X 2, X 3,...X k with respective frequencies f 1, f 2, f 3,...f k has mean

Definition. A variable X that takes on values X 1, X 2, X 3,...X k with respective frequencies f 1, f 2, f 3,...f k has mean 1 Social Studies 201 October 13, 2004 Note: The examples i these otes may be differet tha used i class. However, the examples are similar ad the methods used are idetical to what was preseted i class.

More information

Automatic Tuning for FOREX Trading System Using Fuzzy Time Series

Automatic Tuning for FOREX Trading System Using Fuzzy Time Series utomatic Tuig for FOREX Tradig System Usig Fuzzy Time Series Kraimo Maeesilp ad Pitihate Soorasa bstract Efficiecy of the automatic currecy tradig system is time depedet due to usig fixed parameters which

More information

New exact solutions for the combined sinh-cosh-gordon equation

New exact solutions for the combined sinh-cosh-gordon equation Sociedad Colobiaa de Mateáticas XV Cogreso Nacioal de Mateáticas 2005 Aputes Lecturas Mateáticas Volue Especial (2006), págias 87 93 New exact solutios for the cobied sih-cosh-gordo equatio César A. Góez

More information

Complex Numbers. where x represents a root of Equation 1. Note that the ± sign tells us that quadratic equations will have

Complex Numbers. where x represents a root of Equation 1. Note that the ± sign tells us that quadratic equations will have Comple Numbers I spite of Calvi s discomfiture, imagiar umbers (a subset of the set of comple umbers) eist ad are ivaluable i mathematics, egieerig, ad sciece. I fact, i certai fields, such as electrical

More information

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5 Sectio 13 Kolmogorov-Smirov test. Suppose that we have a i.i.d. sample X 1,..., X with some ukow distributio P ad we would like to test the hypothesis that P is equal to a particular distributio P 0, i.e.

More information

Elements of Dirac Notation

Elements of Dirac Notation Elemets of Dirac Notatio Frak Rioux I the early days of quatum theory, P. A. M. (Paul Adria Maurice) Dirac created a powerful ad cocise formalism for it which is ow referred to as Dirac otatio or bra-ket

More information

What is Computational Fluid Dynamics (CFD)?!

What is Computational Fluid Dynamics (CFD)?! Itroductio Itroductio What is Computatioal Fluid Dyamics CFD? Fiite Differece or Fiite Volume Grid Itroductio Itroductio Usig CFD to solve a problem: Grid must be sufficietly fie to resolve the flow Preparig

More information

Solving Logarithms and Exponential Equations

Solving Logarithms and Exponential Equations Solvig Logarithms ad Epoetial Equatios Logarithmic Equatios There are two major ideas required whe solvig Logarithmic Equatios. The first is the Defiitio of a Logarithm. You may recall from a earlier topic:

More information

Incremental calculation of weighted mean and variance

Incremental calculation of weighted mean and variance Icremetal calculatio of weighted mea ad variace Toy Fich faf@cam.ac.uk dot@dotat.at Uiversity of Cambridge Computig Service February 009 Abstract I these otes I eplai how to derive formulae for umerically

More information

Example 2 Find the square root of 0. The only square root of 0 is 0 (since 0 is not positive or negative, so those choices don t exist here).

Example 2 Find the square root of 0. The only square root of 0 is 0 (since 0 is not positive or negative, so those choices don t exist here). BEGINNING ALGEBRA Roots ad Radicals (revised summer, 00 Olso) Packet to Supplemet the Curret Textbook - Part Review of Square Roots & Irratioals (This portio ca be ay time before Part ad should mostly

More information

Finding the circle that best fits a set of points

Finding the circle that best fits a set of points Fidig the circle that best fits a set of poits L. MAISONOBE October 5 th 007 Cotets 1 Itroductio Solvig the problem.1 Priciples............................... Iitializatio.............................

More information

Entropy of bi-capacities

Entropy of bi-capacities Etropy of bi-capacities Iva Kojadiovic LINA CNRS FRE 2729 Site école polytechique de l uiv. de Nates Rue Christia Pauc 44306 Nates, Frace iva.kojadiovic@uiv-ates.fr Jea-Luc Marichal Applied Mathematics

More information

ADAPTIVE NETWORKS SAFETY CONTROL ON FUZZY LOGIC

ADAPTIVE NETWORKS SAFETY CONTROL ON FUZZY LOGIC 8 th Iteratioal Coferece o DEVELOPMENT AND APPLICATION SYSTEMS S u c e a v a, R o m a i a, M a y 25 27, 2 6 ADAPTIVE NETWORKS SAFETY CONTROL ON FUZZY LOGIC Vadim MUKHIN 1, Elea PAVLENKO 2 Natioal Techical

More information