Numerical Schemes Based on Non-Standard Methods for Initial Value Problems in Ordinary Differential Equations

Size: px
Start display at page:

Download "Numerical Schemes Based on Non-Standard Methods for Initial Value Problems in Ordinary Differential Equations"

Transcription

1 Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 3 (): Scholarlink Research Institute Journals, 22 (ISSN: 24-76) jeteas.scholarlinkresearch.org Numerical Schemes Based on Non-Standard Methods for Initial Value Problems in Ordinary Differential Equations Ibijola, E. A and Obayomi, A. A. Department of Mathematical Sciences, Ekiti State University, Ado-Ekiti. Nigeria. Corresponding Author: Obayomi, A. A. Abstract In this paper we present new methods of constructing Non-Standard schemes. Two new logical ways for constructing the denominator functions for the discrete derivatives were introduced and schemes were constructed based on Non Local Approximation. The schemes were applied on sampled IVPs in ordinary differential equations to verify whether the schemes are computationally reliable. The results obtained show that the schemes are suitable for problems for which they were proposed. Keywords: local approximations, denominator functions (type A and B), modeling, non-standard method, IVP (Initial Value Problem), rock. INTRODUCTION In this paper we developed computationally reliable Non-Standard difference schemes that support the qualitative properties of the considered initial value problems. Standard Finite difference schemes for differential equations exhibit a level of numerical instability (Mickens 994). Mickens (994, 2), gave valuable reasons for numerical instabilities in some particular investigated cases. Thus, the preservation of the qualitative properties of the considered differential equation with respect to these schemes is of great significance. He proposed a new method of construction of discrete models whose solution have the same qualitative properties as that of the corresponding differential equation for all step size and thus eliminate the elementary numerical instabilities that can arise in finite difference models of differential equations. The major consequence of this result is that such scheme does not allow numerical instabilities to occur (Mickens 994). Anguelov and Lubuma (23) based their works on Mickens (994, 2) and deduced a set of nonstandard modeling techniques using the two rules given below i. The denominator can be replaced by a function φ (h) h + o (h 2 ) as h o and o< φ (h) <, h>o which can be considered as the renormalization of step size h. ii. That the non-linear terms must be approximated non-locally on the computational grid by a suitable function of several points of the mesh 49 Other works of Ibijola and Sunday (2), Sunday, Ibijola and Skwame (2), discussed extensively on Exact Non-standard schemes while further works of Ibijola, Lubuma and Ade-Ibijola 2 present the theory of nonstandard finite difference schemes which can be used to solve some initial value problems in ordinary differential equations. Methods of construction and mode of implementation of these methods were also discussed. The motivation for these work is that of Anguelov & Lubuma (23) and Ibijola & Sunday (2). Throughout this work we shall consider problems of the form y f(t,y), y(t o ) y o () Which occur most often in Biological, Chemical, Physical, Management sciences and Engineering. The aim of this research work is to construct discrete models whose solution have the same qualitative properties as that of the corresponding differential equation for all step size and thus eliminate the elementary numerical instabilities that can arise in finite difference models. Exact Finite-Difference Scheme Definition (Mickens 994) An exact finite-difference scheme is one which the solution to the difference equation has the same general solution as the associated differential equation. Definition 2: Type A denominators (increment functions) are those constructed with the knowledge of analytic solution. Type B denominators are those constructed otherwise. We will exploit the point of intersection between the exact finite difference schemes and the expected

2 solution of the original differential equation and use Mickens rules [Mickens (994)] to develop new Non-Standard finite difference schemes. Non-Standard Finite Difference Modeling Rules A finite difference scheme is called non-standard finite difference method, if at least one of the following conditions is met (Anguelov and Lubuma 23): i. In the discrete derivative, the traditional denominator is replaced by a non-negative function φ such that, φ (h) h + o(h 2 ), as h. ii. Non-linear terms that occur in the differential equation are approximated in a non-local way i.e. by a suitable function of several points of the mesh. Derivation of the New Method The discrete solution of a finite difference scheme can be written as y αy (2) where, : α g(y(x ), y(x )) α is a real valued function. A suitable candidate for the function g is y(x n) y(x n ) which is the exact Scheme (Ibijola and Sunday 2), where y(x )is is the analytic solution at x. i. Consider the non-standard finite difference scheme below for any dimensionless equation of the form (.) given by y y + φf(x y ) or f(x () y ) (3) ii. Consider also the exact scheme in the form Take y n y(x n) y(x n ) α ( ) ( ) y n ; g(y(x ), y(x )) If we compare these schemes in (i) and scheme (ii) above y y + φf(x y ) y(x n) y ( ) ( ) f (x y ) y(x n ) y n Then φ can be chosen as φ ( ) ( ) y ( ) ( ) ( ) y (4) Hence, we have a method of choosing φ y y + φ f(x, y ), φ () (, ) (5) 5 We can consider the point where the expected analytical and the numerical solution coincides i.e y(x ) y then the scheme in (5) can be written as: () ( ) ( ) φ (, ) y x k+ y(x k ) h (6) h (, ) Then taking limit as h approaches zero φ f (x, y ) (, ) φ h (x k, y k ) (7) f(x k, y k ) Where f (x, y) is the derivative of f(x, y) and f (x k, y k ) is the value f (x,y) at point x h may be replaced with higher powers of h to have φ (h) h + o (h 2 ) as h o (Mickens994) Using the following normalization (φ ) functions we will test behavior of each scheme to be developed : ) φ sin h 2) φ e 3) y y ( ) ( ) 4) φ ( ) (, ) solution exact scheme Derived from 5) φ h, (,) Derived from taking (,) derivative Construction of the New Non Standard Schemes Problem : Consider the IVP y 3y; y () 5; (8) with exact solution y(t) 5e a) At the points x x and x x kh; y 5e () and y 5e () Let ( ) ( ) Then, the Exact finite differences scheme is y y e() e () y (9)

3 b) Using 3y 3{ay + ( a)y } a Є R and (3) in (8) we obtainy y 3φ{ay + ( a)y } () Then y ( () Comparing this with the exact Scheme y y we have y y ( and φ ( ) (2) c) Using (5) φ () (, ) we have φ () (3) d) Using (7) φ h( (, ) ) we have (, ) f (x, y ) 3 φ h( (4) Or φ h to protect the fact that φ (h) h + o (h 2 ) as h o e) Using (4) in y y + φf(x y ) Then y 3h + y (5) Problem 2 Consider the IVP y y y() 2 (6) with analytic solution y (x) + e At the points x x hk and x x (k + )h ; y + e, y + e () (7) The Exact finite difference scheme is therefore given by y k e(k)h e kh y k where () (8) a) Let y ay + ( a)y then from (3) and (6) We obtain ay + ( a) y Then a Non-standard scheme is y n (aφ h )y n φ h ) (aφ h φ h ) From (2) and (9) y y φ h n (a a)y n Hence a non standard scheme (9) ( ) ) and y n (aφ h)y n φ h ) (aφ h φ h ) y n (a a)y n b) Using (5) φ () Using (7) (, ) φ h (α)y y (2) (2) c) φ h( (, ) ) (, ) f (x, y ) φ h( φ applied ) to (9). (22) Problem 3 Consider the IVP y'.2y; y () ; (23) with analytic y(t) e. b) At the points x x and x x ; y e.(), y 5e.() The Exact finite difference scheme is y y e.2(k)h e.2(k)h y k (24) b) Using.2y.2{ay + ( a)y } a Є R and (3) in (23) we have y y.2φ{ay + ( a)y }. Then y ( )y.. (25) Comparing this with the Exact finite difference scheme y y then y y ( φ.( ). )y.. (26) and c) Using (5) φ () (, ) we have φ (). (27) d) Using (7) φ h( (, ) (, ), f (x, y ).2 and φ h(.. (28) Or φ h to protect the fact that φ (h) h + o (h 2 ) as h o e) Using (28) in y y + φf(x y ) Then y.2h + y (29) Problem 4 Consider the IVP y λy( y), λ, y() (3) This is a form of logistic equation, the analytic solution is given by y(t) + 9e 5

4 and the Exact finite difference scheme is given by y y (3) Where [ + 9e + 9e () ] a) Let y ay + ( a)y y Then y - y y (ay + ( a)y y ) y (() ) From (() ) Then the new scheme becomes y (() ) ( ) ( ()) b) Using (5) φ () (, ) y (α) y (32), φ (33) (34) c) Using(7) φ h( (, ) ) (, ) f (x, y ) 2y φ h( applied ) () to (32) () Group of scheme 2 for Problem 4 Problem 4 can be modeled into another set of different schemes by representing the non-linear term as given below a) Let y ay y + ( a)y () ay y + ( a)y y using ( ) ( ) φ ( ) ( ) Then the new scheme becomes y ( ) ( ) φ ( ) y (36) y, where (37) a. Using (5) φ () (α) y (, ) (38) b) Using φ h( (, ) ) (, ) f (x, y ) 2y φ h( ) applied to (36) (39) () Graphical Representation of the Numerical Result y 3y, y() 5 h. a phi h/y Fig y 3y, y() 5 h. a phi h Derivative ( 4 ) Exact ( 9 ) DExact ( 3 ) Fig 2 y y, y() 2 a.5 h. phi h/y Derivative ( 4 ) Exact ( 9 ) DExact ( 3 ) ( 2 ) Derivative (22) Exact (8) DExact (2) (2) Fig 3 y y, y() 2 a.5 h. phi h

5 Derivative (22) Derivative () Exact (8) DExact (2) 5 Exact (3) DExact (34) (2) Phi Sine (33) Fig 4 y.2y, y() h. a.5 phi h/y Derivative (28) Fig 8 y y( y), y() ; Group Scheme a.5 h. Phi h 5 5 Exact (24) DExact (27) (25) Fig 6 y.2y, y() h. a.5 phi h Derivative () Exact (3) DExact (34) (33) Derivative (28) Exact (24) DExact (27) (25) Phi Sine Fig 9 y y( y), y() ; Group 2 Schemes a.5 h. Phi h( () ) Fig 7 y y( y), y() ; Group Scheme a.5 h. Phi h( () ) 53

6 y y( y), y() ; Group 2 Schemes a.5 h. phi h 5 5 Fig Group 2 Schemes 5 5 Fig 8 8 Derivative (39) Exact (3) DExact (38) (37) a.5 h. phi h Derivative (39) Exact (3) DExact (38) (37) SUMMARY AND CONCLUSION We have been able to construct two groups or family of schemes for the last three IVP s and one group each for the first two. The schemes have been tested numerically in terms of their consistency with the known behavior of the analytic solution of the particular initial value problem. The last equation is a form of the logistic equation. The Non-standard schemes developed are not consistent with the analytic solution for a>. It can be seen that the schemes oscillate close to the fixed point (y ). The result is expected to be different if the equation is represented in its dimensionless form. The methods based on type B denominators will behave better if it is modified to satisfy the non-standard modeling rules. This is because the phi tends to produce a linear scheme most especially when they are applied directly to the non-standard Finite difference scheme(3). The advantage of the last technique is that the analytic solution does not have to be known provided it exist. The construction of phi to satisfy the Mickens rules is sacrosanct to the validity of this new techniques. An area of improvement is to develop a method of modifying phi accordingly to satisfy the requirement of Non-standard schemes.the numerical experiment has shown that: The denominator function can be constructed in the following ways (in the tested cases) φ sin(h), e i.e using classical functions (Mickens 994) φ () (,), α g [y(x ), y(x )], y(x)is the known analytic solution. φ (,) (,) n. All the schemes have been found to be consistent with literature and compared favorably in a many cases. However the schemes ( and 39) do not exhibit the same qualitative property of the corresponding IVP. even where phi(φ) is an exponential or sine function. REFERENCES Anguelov R, Lubuma JMS (2). On Mathematical Foundation of the Nonstandard finite Differential Method, in Fiedler B, Grooger K, Sprekels J (Eds), Proceeding of the International Conference on Differential Equations, EQUADIFF 99 Word Scientific, Singapore, Anguelov R, Lubuma JMS (2). Nonstandard finite difference method,by Non-local Approximation Keynote address at the South Africa Mathematical Society, Pretoria, South Africa 6-8 October, Notices of S. A. Math. Soc. 3: Anguelov R, Lubuma JMS (23). Nonstandard finite difference method by nonlocal approximation, Mathematics and Computers in simulation 6: Ibijola, E. A., and Sunday J. (2). A comparative study of Standard and Exact Finite Difference Schemes for Numerical of ODEs Emanating fro the Radioactive decay of Substances. Australian Journal of Basic and Applied Sciences, 4(4): Lambert J. D. (99). Numerical Methods for Ordinary Differential System; Wiley, New York. Mickens R.E (994). Nonstandard Finite Difference Models of Differential Equations, World Scientific, Singapore. Pp -5, Mickens R.E. (2). Applications of Nonstandard Methods for initial value problems, World Scientific, Singapore. 54

7 Simmons G. F. (98): Differential Equations with Applications and Historical Notes. T M H edition McGraw-hill publishing. Sunday J.,Ibijola E. A., and Skwame Y. (2) On the Theory and Application of Non-standard Finite Difference Methods for Singular ODEs. Journal of emerging Trends in Engineering and Applied Sciences UK, 294): Waiter W (998). Ordinary Differential Equations, Springer, Berlin. Zill D G, Cullen R M (25) Differential Equations with boundary value problems (sixth Edition) Brooks /Cole Thompson Learning Academic Resource Center. Pp 4-2,

Construction of new Non-standard Finite Difference Schemes for the. Solution of a free un-damped Harmonic Oscillator Equation

Construction of new Non-standard Finite Difference Schemes for the. Solution of a free un-damped Harmonic Oscillator Equation Construction of new Non-standard Finite Difference Schemes for the Abstract Solution of a free un-damped Harmonic Oscillator Equation Adesoji A.Obayomi * Adetolaju Olu Sunday Department of Mathematical

More information

ARTICLE IN PRESS Mathematical and Computer Modelling ( )

ARTICLE IN PRESS Mathematical and Computer Modelling ( ) Mathematical and Computer Modelling Contents lists available at ScienceDirect Mathematical and Computer Modelling ournal homepage: wwwelseviercom/locate/mcm Total variation diminishing nonstandard finite

More information

On the Computational Procedure of Solving Boundary Value Problems of Class M Using the Power Series Method

On the Computational Procedure of Solving Boundary Value Problems of Class M Using the Power Series Method Australian Journal of Basic and Applied Sciences, 4(6): 1007-1014, 2010 ISSN 1991-8178 On the Computational Procedure of Solving Boundary Value Problems of Class M Using the Power Series Method 1 2 E.A.

More information

. For each initial condition y(0) = y 0, there exists a. unique solution. In fact, given any point (x, y), there is a unique curve through this point,

. For each initial condition y(0) = y 0, there exists a. unique solution. In fact, given any point (x, y), there is a unique curve through this point, 1.2. Direction Fields: Graphical Representation of the ODE and its Solution Section Objective(s): Constructing Direction Fields. Interpreting Direction Fields. Definition 1.2.1. A first order ODE of the

More information

A New Numerical Approach for Solving Initial Value Problems of Ordinary Differential Equations

A New Numerical Approach for Solving Initial Value Problems of Ordinary Differential Equations Annals of Pure and Applied Mathematics Vol. 17, No. 2, 2018, 157-162 ISSN: 2279-087X (P), 2279-0888(online) Published on 28 May 2018 www.researchmathsci.org DOI: http://dx.doi.org/10.22457/apam.v17n2a2

More information

NONSTANDARD NUMERICAL METHODS FOR A CLASS OF PREDATOR-PREY MODELS WITH PREDATOR INTERFERENCE

NONSTANDARD NUMERICAL METHODS FOR A CLASS OF PREDATOR-PREY MODELS WITH PREDATOR INTERFERENCE Sixth Mississippi State Conference on Differential Equations and Computational Simulations, Electronic Journal of Differential Equations, Conference 15 (2007), pp. 67 75. ISSN: 1072-6691. URL: http://ejde.math.txstate.edu

More information

DIFFERENTIAL EQUATIONS

DIFFERENTIAL EQUATIONS DIFFERENTIAL EQUATIONS Chapter 1 Introduction and Basic Terminology Most of the phenomena studied in the sciences and engineering involve processes that change with time. For example, it is well known

More information

A Monotone Scheme for Hamilton-Jacobi Equations via the Nonstandard Finite Difference Method

A Monotone Scheme for Hamilton-Jacobi Equations via the Nonstandard Finite Difference Method A Monotone Scheme for Hamilton-Jacobi Equations via the Nonstandard Finite Difference Method Roumen Anguelov, Jean M-S Lubuma and Froduald Minani Department of Mathematics and Applied Mathematics University

More information

Development of a New One-Step Scheme for the Solution of Initial Value Problem (IVP) in Ordinary Differential Equations

Development of a New One-Step Scheme for the Solution of Initial Value Problem (IVP) in Ordinary Differential Equations International Journal of Theoretical and Applied Mathematics 2017; 3(2): 58-63 http://www.sciencepublishinggroup.com/j/ijtam doi: 10.11648/j.ijtam.20170302.12 Development of a New One-Step Scheme for the

More information

Modified block method for the direct solution of second order ordinary differential equations

Modified block method for the direct solution of second order ordinary differential equations c Copyright, Darbose International Journal of Applied Mathematics and Computation Volume 3(3),pp 181 188, 2011 http://ijamc.psit.in Modified block method for the direct solution of second order ordinary

More information

Nonstandard Finite Difference Methods For Predator-Prey Models With General Functional Response

Nonstandard Finite Difference Methods For Predator-Prey Models With General Functional Response Nonstandard Finite Difference Methods For Predator-Prey Models With General Functional Response Dobromir T. Dimitrov Hristo V. Kojouharov Technical Report 2007-0 http://www.uta.edu/math/preprint/ NONSTANDARD

More information

Lecture 2. Introduction to Differential Equations. Roman Kitsela. October 1, Roman Kitsela Lecture 2 October 1, / 25

Lecture 2. Introduction to Differential Equations. Roman Kitsela. October 1, Roman Kitsela Lecture 2 October 1, / 25 Lecture 2 Introduction to Differential Equations Roman Kitsela October 1, 2018 Roman Kitsela Lecture 2 October 1, 2018 1 / 25 Quick announcements URL for the class website: http://www.math.ucsd.edu/~rkitsela/20d/

More information

Math 132 Information for Test 2

Math 132 Information for Test 2 Math 13 Information for Test Test will cover material from Sections 5.6, 5.7, 5.8, 6.1, 6., 6.3, 7.1, 7., and 7.3. The use of graphing calculators will not be allowed on the test. Some practice questions

More information

Problem set 7 Math 207A, Fall 2011 Solutions

Problem set 7 Math 207A, Fall 2011 Solutions Problem set 7 Math 207A, Fall 2011 s 1. Classify the equilibrium (x, y) = (0, 0) of the system x t = x, y t = y + x 2. Is the equilibrium hyperbolic? Find an equation for the trajectories in (x, y)- phase

More information

Ordinary Differential Equations (ODEs)

Ordinary Differential Equations (ODEs) c01.tex 8/10/2010 22: 55 Page 1 PART A Ordinary Differential Equations (ODEs) Chap. 1 First-Order ODEs Sec. 1.1 Basic Concepts. Modeling To get a good start into this chapter and this section, quickly

More information

A New Generalised Inverse Polynomial Model in the Exploration of Response Surface Methodology

A New Generalised Inverse Polynomial Model in the Exploration of Response Surface Methodology Journal of Emerging Trends in Engineering Applied Sciences (JETEAS) (6): 1059-1063 Scholarlink Research Institute Journals 011 (ISSN: 141-7016) jeteas.scholarlinkresearch.org Journal of Emerging Trends

More information

DIFFERENT DIFFERENCES

DIFFERENT DIFFERENCES DIFFERENT DIFFERENCES Ron Buckmire ron@oxy.edu Professor of Mathematics Occidental College Los Angeles, CA Pomona College Claremont, CA March 21, 2016 ABSTRACT From calculus we know that a derivative of

More information

Fusion Higher -Order Parallel Splitting Methods for. Parabolic Partial Differential Equations

Fusion Higher -Order Parallel Splitting Methods for. Parabolic Partial Differential Equations International Mathematical Forum, Vol. 7, 0, no. 3, 567 580 Fusion Higher -Order Parallel Splitting Methods for Parabolic Partial Differential Equations M. A. Rehman Department of Mathematics, University

More information

2. Algebraic functions, power functions, exponential functions, trig functions

2. Algebraic functions, power functions, exponential functions, trig functions Math, Prep: Familiar Functions (.,.,.5, Appendix D) Name: Names of collaborators: Main Points to Review:. Functions, models, graphs, tables, domain and range. Algebraic functions, power functions, exponential

More information

Solution of a Fourth Order Singularly Perturbed Boundary Value Problem Using Quintic Spline

Solution of a Fourth Order Singularly Perturbed Boundary Value Problem Using Quintic Spline International Mathematical Forum, Vol. 7, 202, no. 44, 279-290 Solution of a Fourth Order Singularly Perturbed Boundary Value Problem Using Quintic Spline Ghazala Akram and Nadia Amin Department of Mathematics

More information

Solution of Population Growth and Decay Problems by Using Mohand Transform

Solution of Population Growth and Decay Problems by Using Mohand Transform Solution of Population Growth and Decay Problems by Using Mohand Transform 1 *Sudhanshu Aggarwal, 2 Nidhi Sharma, 3 Raman Chauhan 1 Assistant Professor, Department of Mathematics, National P.G. College

More information

Four Point Gauss Quadrature Runge Kuta Method Of Order 8 For Ordinary Differential Equations

Four Point Gauss Quadrature Runge Kuta Method Of Order 8 For Ordinary Differential Equations International journal of scientific and technical research in engineering (IJSTRE) www.ijstre.com Volume Issue ǁ July 206. Four Point Gauss Quadrature Runge Kuta Method Of Order 8 For Ordinary Differential

More information

Journal of the Vol. 36, pp , 2017 Nigerian Mathematical Society c Nigerian Mathematical Society

Journal of the Vol. 36, pp , 2017 Nigerian Mathematical Society c Nigerian Mathematical Society Journal of the Vol. 36, pp. 47-54, 2017 Nigerian Mathematical Society c Nigerian Mathematical Society A CLASS OF GENERALIZATIONS OF THE LOTKA-VOLTERRA PREDATOR-PREY EQUATIONS HAVING EXACTLY SOLUBLE SOLUTIONS

More information

Cubic B-spline Collocation Method for Fourth Order Boundary Value Problems. 1 Introduction

Cubic B-spline Collocation Method for Fourth Order Boundary Value Problems. 1 Introduction ISSN 1749-3889 print, 1749-3897 online International Journal of Nonlinear Science Vol.142012 No.3,pp.336-344 Cubic B-spline Collocation Method for Fourth Order Boundary Value Problems K.N.S. Kasi Viswanadham,

More information

Introduction to Differential Equations

Introduction to Differential Equations Chapter 1 Introduction to Differential Equations 1.1 Basic Terminology Most of the phenomena studied in the sciences and engineering involve processes that change with time. For example, it is well known

More information

Second Order ODEs. CSCC51H- Numerical Approx, Int and ODEs p.130/177

Second Order ODEs. CSCC51H- Numerical Approx, Int and ODEs p.130/177 Second Order ODEs Often physical or biological systems are best described by second or higher-order ODEs. That is, second or higher order derivatives appear in the mathematical model of the system. For

More information

Solving differential equations (Sect. 7.4) Review: Overview of differential equations.

Solving differential equations (Sect. 7.4) Review: Overview of differential equations. Solving differential equations (Sect. 7.4 Previous class: Overview of differential equations. Exponential growth. Separable differential equations. Review: Overview of differential equations. Definition

More information

Solution of First Order Initial Value Problem by Sixth Order Predictor Corrector Method

Solution of First Order Initial Value Problem by Sixth Order Predictor Corrector Method Global Journal of Pure and Applied Mathematics. ISSN 0973-1768 Volume 13, Number 6 (2017), pp. 2277 2290 Research India Publications http://www.ripublication.com/gjpam.htm Solution of First Order Initial

More information

1.1 Motivation: Why study differential equations?

1.1 Motivation: Why study differential equations? Chapter 1 Introduction Contents 1.1 Motivation: Why stu differential equations?....... 1 1.2 Basics............................... 2 1.3 Growth and decay........................ 3 1.4 Introduction to Ordinary

More information

MTH210 DIFFERENTIAL EQUATIONS. Dr. Gizem SEYHAN ÖZTEPE

MTH210 DIFFERENTIAL EQUATIONS. Dr. Gizem SEYHAN ÖZTEPE MTH210 DIFFERENTIAL EQUATIONS Dr. Gizem SEYHAN ÖZTEPE 1 References Logan, J. David. A first course in differential equations. Springer, 2015. Zill, Dennis G. A first course in differential equations with

More information

Mini project ODE, TANA22

Mini project ODE, TANA22 Mini project ODE, TANA22 Filip Berglund (filbe882) Linh Nguyen (linng299) Amanda Åkesson (amaak531) October 2018 1 1 Introduction Carl David Tohmé Runge (1856 1927) was a German mathematician and a prominent

More information

1.2. Direction Fields: Graphical Representation of the ODE and its Solution Let us consider a first order differential equation of the form dy

1.2. Direction Fields: Graphical Representation of the ODE and its Solution Let us consider a first order differential equation of the form dy .. Direction Fields: Graphical Representation of the ODE and its Solution Let us consider a first order differential equation of the form dy = f(x, y). In this section we aim to understand the solution

More information

Math 2a Prac Lectures on Differential Equations

Math 2a Prac Lectures on Differential Equations Math 2a Prac Lectures on Differential Equations Prof. Dinakar Ramakrishnan 272 Sloan, 253-37 Caltech Office Hours: Fridays 4 5 PM Based on notes taken in class by Stephanie Laga, with a few added comments

More information

Math 23: Differential Equations (Winter 2017) Midterm Exam Solutions

Math 23: Differential Equations (Winter 2017) Midterm Exam Solutions Math 3: Differential Equations (Winter 017) Midterm Exam Solutions 1. [0 points] or FALSE? You do not need to justify your answer. (a) [3 points] Critical points or equilibrium points for a first order

More information

Math 225 Differential Equations Notes Chapter 1

Math 225 Differential Equations Notes Chapter 1 Math 225 Differential Equations Notes Chapter 1 Michael Muscedere September 9, 2004 1 Introduction 1.1 Background In science and engineering models are used to describe physical phenomena. Often these

More information

MATH 1231 MATHEMATICS 1B Calculus Section 3A: - First order ODEs.

MATH 1231 MATHEMATICS 1B Calculus Section 3A: - First order ODEs. MATH 1231 MATHEMATICS 1B 2010. For use in Dr Chris Tisdell s lectures. Calculus Section 3A: - First order ODEs. Created and compiled by Chris Tisdell S1: What is an ODE? S2: Motivation S3: Types and orders

More information

Partial Derivatives October 2013

Partial Derivatives October 2013 Partial Derivatives 14.3 02 October 2013 Derivative in one variable. Recall for a function of one variable, f (a) = lim h 0 f (a + h) f (a) h slope f (a + h) f (a) h a a + h Partial derivatives. For a

More information

M A : Ordinary Differential Equations

M A : Ordinary Differential Equations M A 2 0 5 1: Ordinary Differential Equations Essential Class Notes & Graphics D 19 * 2018-2019 Sections D07 D11 & D14 1 1. INTRODUCTION CLASS 1 ODE: Course s Overarching Functions An introduction to the

More information

Continuous Block Hybrid-Predictor-Corrector method for the solution of y = f (x, y, y )

Continuous Block Hybrid-Predictor-Corrector method for the solution of y = f (x, y, y ) International Journal of Mathematics and Soft Computing Vol., No. 0), 5-4. ISSN 49-8 Continuous Block Hybrid-Predictor-Corrector method for the solution of y = f x, y, y ) A.O. Adesanya, M.R. Odekunle

More information

DIFFERENTIAL EQUATIONS

DIFFERENTIAL EQUATIONS DIFFERENTIAL EQUATIONS Basic Terminology A differential equation is an equation that contains an unknown function together with one or more of its derivatives. 1 Examples: 1. y = 2x + cos x 2. dy dt =

More information

MATH 353 LECTURE NOTES: WEEK 1 FIRST ORDER ODES

MATH 353 LECTURE NOTES: WEEK 1 FIRST ORDER ODES MATH 353 LECTURE NOTES: WEEK 1 FIRST ORDER ODES J. WONG (FALL 2017) What did we cover this week? Basic definitions: DEs, linear operators, homogeneous (linear) ODEs. Solution techniques for some classes

More information

A Numerical Integration for Solving First Order Differential Equations Using Gompertz Function Approach

A Numerical Integration for Solving First Order Differential Equations Using Gompertz Function Approach American Journal of Computational and Applied Mathematics 2017, 7(6): 143-148 DOI: 10.5923/j.ajcam.20170706.01 A Numerical Integration for Solving First Order Differential Equations Using Gompertz Function

More information

First Order ODEs, Part I

First Order ODEs, Part I Craig J. Sutton craig.j.sutton@dartmouth.edu Department of Mathematics Dartmouth College Math 23 Differential Equations Winter 2013 Outline 1 2 in General 3 The Definition & Technique Example Test for

More information

Example: Limit definition. Geometric meaning. Geometric meaning, y. Notes. Notes. Notes. f (x, y) = x 2 y 3 :

Example: Limit definition. Geometric meaning. Geometric meaning, y. Notes. Notes. Notes. f (x, y) = x 2 y 3 : Partial Derivatives 14.3 02 October 2013 Derivative in one variable. Recall for a function of one variable, f (a) = lim h 0 f (a + h) f (a) h slope f (a + h) f (a) h a a + h Partial derivatives. For a

More information

Lecture Notes in Mathematics. Arkansas Tech University Department of Mathematics

Lecture Notes in Mathematics. Arkansas Tech University Department of Mathematics Lecture Notes in Mathematics Arkansas Tech University Department of Mathematics Introductory Notes in Ordinary Differential Equations for Physical Sciences and Engineering Marcel B. Finan c All Rights

More information

Mathematics II. Tutorial 2 First order differential equations. Groups: B03 & B08

Mathematics II. Tutorial 2 First order differential equations. Groups: B03 & B08 Tutorial 2 First order differential equations Groups: B03 & B08 February 1, 2012 Department of Mathematics National University of Singapore 1/15 : First order linear differential equations In this question,

More information

Physics 250 Green s functions for ordinary differential equations

Physics 250 Green s functions for ordinary differential equations Physics 25 Green s functions for ordinary differential equations Peter Young November 25, 27 Homogeneous Equations We have already discussed second order linear homogeneous differential equations, which

More information

F-TRANSFORM FOR NUMERICAL SOLUTION OF TWO-POINT BOUNDARY VALUE PROBLEM

F-TRANSFORM FOR NUMERICAL SOLUTION OF TWO-POINT BOUNDARY VALUE PROBLEM Iranian Journal of Fuzzy Systems Vol. 14, No. 6, (2017) pp. 1-13 1 F-TRANSFORM FOR NUMERICAL SOLUTION OF TWO-POINT BOUNDARY VALUE PROBLEM I. PERFILIEVA, P. ŠTEVULIÁKOVÁ AND R. VALÁŠEK Abstract. We propose

More information

Chapter1. Ordinary Differential Equations

Chapter1. Ordinary Differential Equations Chapter1. Ordinary Differential Equations In the sciences and engineering, mathematical models are developed to aid in the understanding of physical phenomena. These models often yield an equation that

More information

Design Collocation Neural Network to Solve Singular Perturbed Problems with Initial Conditions

Design Collocation Neural Network to Solve Singular Perturbed Problems with Initial Conditions Article International Journal of Modern Engineering Sciences, 204, 3(): 29-38 International Journal of Modern Engineering Sciences Journal homepage:www.modernscientificpress.com/journals/ijmes.aspx ISSN:

More information

Polynomial Interpolation

Polynomial Interpolation Polynomial Interpolation (Com S 477/577 Notes) Yan-Bin Jia Sep 1, 017 1 Interpolation Problem In practice, often we can measure a physical process or quantity (e.g., temperature) at a number of points

More information

Exponential Growth and Decay

Exponential Growth and Decay Exponential Growth and Decay Warm-up 1. If (A + B)x 2A =3x +1forallx, whatarea and B? (Hint: if it s true for all x, thenthecoe cients have to match up, i.e. A + B =3and 2A =1.) 2. Find numbers (maybe

More information

0.1 Solution by Inspection

0.1 Solution by Inspection 1 Modeling with Differential Equations: Introduction to the Issues c 2002 Donald Kreider and Dwight Lahr A differential equation is an equation involving derivatives and functions. In the last section,

More information

Different Approaches to the Solution of Damped Forced Oscillator Problem by Decomposition Method

Different Approaches to the Solution of Damped Forced Oscillator Problem by Decomposition Method Australian Journal of Basic and Applied Sciences, 3(3): 2249-2254, 2009 ISSN 1991-8178 Different Approaches to the Solution of Damped Forced Oscillator Problem by Decomposition Method A.R. Vahidi Department

More information

1.1 Differential Equation Models. Jiwen He

1.1 Differential Equation Models. Jiwen He 1.1 Math 3331 Differential Equations 1.1 Differential Equation Models Jiwen He Department of Mathematics, University of Houston jiwenhe@math.uh.edu math.uh.edu/ jiwenhe/math3331 Jiwen He, University of

More information

Integration of Ordinary Differential Equations

Integration of Ordinary Differential Equations Integration of Ordinary Differential Equations Com S 477/577 Nov 7, 00 1 Introduction The solution of differential equations is an important problem that arises in a host of areas. Many differential equations

More information

Uniform Order Legendre Approach for Continuous Hybrid Block Methods for the Solution of First Order Ordinary Differential Equations

Uniform Order Legendre Approach for Continuous Hybrid Block Methods for the Solution of First Order Ordinary Differential Equations IOSR Journal of Mathematics (IOSR-JM) e-issn: 8-58, p-issn: 319-65X. Volume 11, Issue 1 Ver. IV (Jan - Feb. 015), PP 09-14 www.iosrjournals.org Uniform Order Legendre Approach for Continuous Hybrid Block

More information

Today. Calculus. Linear Regression. Lagrange Multipliers

Today. Calculus. Linear Regression. Lagrange Multipliers Today Calculus Lagrange Multipliers Linear Regression 1 Optimization with constraints What if I want to constrain the parameters of the model. The mean is less than 10 Find the best likelihood, subject

More information

Analyse 3 NA, FINAL EXAM. * Monday, January 8, 2018, *

Analyse 3 NA, FINAL EXAM. * Monday, January 8, 2018, * Analyse 3 NA, FINAL EXAM * Monday, January 8, 08, 4.00 7.00 * Motivate each answer with a computation or explanation. The maximum amount of points for this exam is 00. No calculators!. (Holomorphic functions)

More information

Calculus II/III Summer Packet

Calculus II/III Summer Packet Calculus II/III Summer Packet First of all, have a great summer! Enjoy your time away from school. Come back fired up and ready to learn. I know that I will be ready to have a great year of calculus with

More information

then the substitution z = ax + by + c reduces this equation to the separable one.

then the substitution z = ax + by + c reduces this equation to the separable one. 7 Substitutions II Some of the topics in this lecture are optional and will not be tested at the exams. However, for a curious student it should be useful to learn a few extra things about ordinary differential

More information

9.2 Euler s Method. (1) t k = a + kh for k = 0, 1,..., M where h = b a. The value h is called the step size. We now proceed to solve approximately

9.2 Euler s Method. (1) t k = a + kh for k = 0, 1,..., M where h = b a. The value h is called the step size. We now proceed to solve approximately 464 CHAP. 9 SOLUTION OF DIFFERENTIAL EQUATIONS 9. Euler s Method The reader should be convinced that not all initial value problems can be solved explicitly, and often it is impossible to find a formula

More information

Numerical Methods for Initial Value Problems; Harmonic Oscillators

Numerical Methods for Initial Value Problems; Harmonic Oscillators 1 Numerical Methods for Initial Value Problems; Harmonic Oscillators Lab Objective: Implement several basic numerical methods for initial value problems (IVPs), and use them to study harmonic oscillators.

More information

Autonomous systems. Ordinary differential equations which do not contain the independent variable explicitly are said to be autonomous.

Autonomous systems. Ordinary differential equations which do not contain the independent variable explicitly are said to be autonomous. Autonomous equations Autonomous systems Ordinary differential equations which do not contain the independent variable explicitly are said to be autonomous. i f i(x 1, x 2,..., x n ) for i 1,..., n As you

More information

MATH 308 Differential Equations

MATH 308 Differential Equations MATH 308 Differential Equations Summer, 2014, SET 1 JoungDong Kim Set 1: Section 1.1, 1.2, 1.3, 2.1 Chapter 1. Introduction 1. Why do we study Differential Equation? Many of the principles, or laws, underlying

More information

Propagation of discontinuities in solutions of First Order Partial Differential Equations

Propagation of discontinuities in solutions of First Order Partial Differential Equations Propagation of discontinuities in solutions of First Order Partial Differential Equations Phoolan Prasad Department of Mathematics Indian Institute of Science, Bangalore 560 012 E-mail: prasad@math.iisc.ernet.in

More information

SMA 208: Ordinary differential equations I

SMA 208: Ordinary differential equations I SMA 208: Ordinary differential equations I Modeling with First Order differential equations Lecturer: Dr. Philip Ngare (Contacts: pngare@uonbi.ac.ke, Tue 12-2 PM) School of Mathematics, University of Nairobi

More information

y0 = F (t0)+c implies C = y0 F (t0) Integral = area between curve and x-axis (where I.e., f(t)dt = F (b) F (a) wheref is any antiderivative 2.

y0 = F (t0)+c implies C = y0 F (t0) Integral = area between curve and x-axis (where I.e., f(t)dt = F (b) F (a) wheref is any antiderivative 2. Calulus pre-requisites you must know. Derivative = slope of tangent line = rate. Integral = area between curve and x-axis (where area can be negative). The Fundamental Theorem of Calculus: Suppose f continuous

More information

Linearization of Two Dimensional Complex-Linearizable Systems of Second Order Ordinary Differential Equations

Linearization of Two Dimensional Complex-Linearizable Systems of Second Order Ordinary Differential Equations Applied Mathematical Sciences, Vol. 9, 2015, no. 58, 2889-2900 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ams.2015.4121002 Linearization of Two Dimensional Complex-Linearizable Systems of

More information

HIGH ORDER VARIABLE MESH EXPONENTIAL FINITE DIFFERENCE METHOD FOR THE NUMERICAL SOLUTION OF THE TWO POINTS BOUNDARY VALUE PROBLEMS

HIGH ORDER VARIABLE MESH EXPONENTIAL FINITE DIFFERENCE METHOD FOR THE NUMERICAL SOLUTION OF THE TWO POINTS BOUNDARY VALUE PROBLEMS JOURNAL OF THE INTERNATIONAL MATHEMATICAL VIRTUAL INSTITUTE ISSN (p) 2303-4866, ISSN (o) 2303-4947 www.imvibl.org /JOURNALS / JOURNAL Vol. 8(2018), 19-33 DOI: 10.7251/JMVI1801019P Former BULLETIN OF THE

More information

4 Stability analysis of finite-difference methods for ODEs

4 Stability analysis of finite-difference methods for ODEs MATH 337, by T. Lakoba, University of Vermont 36 4 Stability analysis of finite-difference methods for ODEs 4.1 Consistency, stability, and convergence of a numerical method; Main Theorem In this Lecture

More information

1. If (A + B)x 2A =3x +1forallx, whatarea and B? (Hint: if it s true for all x, thenthecoe cients have to match up, i.e. A + B =3and 2A =1.

1. If (A + B)x 2A =3x +1forallx, whatarea and B? (Hint: if it s true for all x, thenthecoe cients have to match up, i.e. A + B =3and 2A =1. Warm-up. If (A + B)x 2A =3x +forallx, whatarea and B? (Hint: if it s true for all x, thenthecoe cients have to match up, i.e. A + B =3and 2A =.) 2. Find numbers (maybe not integers) A and B which satisfy

More information

ON SOME RESULTS ON LINEAR ORTHOGONALITY SPACES

ON SOME RESULTS ON LINEAR ORTHOGONALITY SPACES ASIAN JOURNAL OF MATHEMATICS AND APPLICATIONS Volume 2014, Article ID ama0155, 11 pages ISSN 2307-7743 http://scienceasia.asia ON SOME RESULTS ON LINEAR ORTHOGONALITY SPACES KANU, RICHMOND U. AND RAUF,

More information

Second-Order Linear ODEs

Second-Order Linear ODEs C0.tex /4/011 16: 3 Page 13 Chap. Second-Order Linear ODEs Chapter presents different types of second-order ODEs and the specific techniques on how to solve them. The methods are systematic, but it requires

More information

Lecture 29. Convolution Integrals and Their Applications

Lecture 29. Convolution Integrals and Their Applications Math 245 - Mathematics of Physics and Engineering I Lecture 29. Convolution Integrals and Their Applications March 3, 212 Konstantin Zuev (USC) Math 245, Lecture 29 March 3, 212 1 / 13 Agenda Convolution

More information

Section 9.3 Phase Plane Portraits (for Planar Systems)

Section 9.3 Phase Plane Portraits (for Planar Systems) Section 9.3 Phase Plane Portraits (for Planar Systems) Key Terms: Equilibrium point of planer system yꞌ = Ay o Equilibrium solution Exponential solutions o Half-line solutions Unstable solution Stable

More information

Edexcel past paper questions. Core Mathematics 4. Parametric Equations

Edexcel past paper questions. Core Mathematics 4. Parametric Equations Edexcel past paper questions Core Mathematics 4 Parametric Equations Edited by: K V Kumaran Email: kvkumaran@gmail.com C4 Maths Parametric equations Page 1 Co-ordinate Geometry A parametric equation of

More information

Generalised definitions of certain functions and their uses

Generalised definitions of certain functions and their uses arxiv:math-ph/0307065v2 6 Aug 2003 Generalised definitions of certain functions and their uses Debasis Biswas 1 and Asoke P. Chattopadhyay 2 1 Department of Physics and 2 Department of Chemistry University

More information

The Unifying View on Ordinary Differential Equations and Automatic Differentiation, yet with a Gap to Fill Alexander Gofen.

The Unifying View on Ordinary Differential Equations and Automatic Differentiation, yet with a Gap to Fill Alexander Gofen. The Unifying View on Ordinary Differential Equations and Automatic Differentiation, yet with a Gap to Fill Alexander Gofen Conventions Differentiation is understood as for holomorphic functions in the

More information

Backward error analysis

Backward error analysis Backward error analysis Brynjulf Owren July 28, 2015 Introduction. The main source for these notes is the monograph by Hairer, Lubich and Wanner [2]. Consider ODEs in R d of the form ẏ = f(y), y(0) = y

More information

Ordinary Differential Equations

Ordinary Differential Equations Ordinary Differential Equations (MA102 Mathematics II) Shyamashree Upadhyay IIT Guwahati Shyamashree Upadhyay ( IIT Guwahati ) Ordinary Differential Equations 1 / 1 Books Shyamashree Upadhyay ( IIT Guwahati

More information

Series Solution of Linear Ordinary Differential Equations

Series Solution of Linear Ordinary Differential Equations Series Solution of Linear Ordinary Differential Equations Department of Mathematics IIT Guwahati Aim: To study methods for determining series expansions for solutions to linear ODE with variable coefficients.

More information

2.12: Derivatives of Exp/Log (cont d) and 2.15: Antiderivatives and Initial Value Problems

2.12: Derivatives of Exp/Log (cont d) and 2.15: Antiderivatives and Initial Value Problems 2.12: Derivatives of Exp/Log (cont d) and 2.15: Antiderivatives and Initial Value Problems Mathematics 3 Lecture 14 Dartmouth College February 03, 2010 Derivatives of the Exponential and Logarithmic Functions

More information

Separable Differential Equations

Separable Differential Equations Separable Differential Equations MATH 6 Calculus I J. Robert Buchanan Department of Mathematics Fall 207 Background We have previously solved differential equations of the forms: y (t) = k y(t) (exponential

More information

The Fundamental Theorem of Calculus: Suppose f continuous on [a, b]. 1.) If G(x) = x. f(t)dt = F (b) F (a) where F is any antiderivative

The Fundamental Theorem of Calculus: Suppose f continuous on [a, b]. 1.) If G(x) = x. f(t)dt = F (b) F (a) where F is any antiderivative 1 Calulus pre-requisites you must know. Derivative = slope of tangent line = rate. Integral = area between curve and x-axis (where area can be negative). The Fundamental Theorem of Calculus: Suppose f

More information

MATH 312 Section 1.2: Initial Value Problems

MATH 312 Section 1.2: Initial Value Problems MATH 312 Section 1.2: Initial Value Problems Prof. Jonathan Duncan Walla Walla College Spring Quarter, 2007 Outline 1 Introduction to Initial Value Problems 2 Existence and Uniqueness 3 Conclusion Families

More information

Physics 307. Mathematical Physics. Luis Anchordoqui. Wednesday, August 31, 16

Physics 307. Mathematical Physics. Luis Anchordoqui. Wednesday, August 31, 16 Physics 307 Mathematical Physics Luis Anchordoqui 1 Bibliography L. A. Anchordoqui and T. C. Paul, ``Mathematical Models of Physics Problems (Nova Publishers, 2013) G. F. D. Duff and D. Naylor, ``Differential

More information

Scientific Computing: An Introductory Survey

Scientific Computing: An Introductory Survey Scientific Computing: An Introductory Survey Chapter 9 Initial Value Problems for Ordinary Differential Equations Prof. Michael T. Heath Department of Computer Science University of Illinois at Urbana-Champaign

More information

Module 10: Finite Difference Methods for Boundary Value Problems Lecture 42: Special Boundary Value Problems. The Lecture Contains:

Module 10: Finite Difference Methods for Boundary Value Problems Lecture 42: Special Boundary Value Problems. The Lecture Contains: The Lecture Contains: Finite Difference Method Boundary conditions of the second and third kind Solution of the difference scheme: Linear case Solution of the difference scheme: nonlinear case Problems

More information

Dynamics of Vertically and Horizontally Transmitted Parasites: Continuous vs Discrete Models

Dynamics of Vertically and Horizontally Transmitted Parasites: Continuous vs Discrete Models International Journal of Difference Equations ISSN 973-669 Volume 13 Number 2 pp 139 156 218) http://campusmstedu/ijde Dynamics of Vertically and Horizontally Transmitted Parasites: Continuous vs Discrete

More information

6.0 INTRODUCTION TO DIFFERENTIAL EQUATIONS

6.0 INTRODUCTION TO DIFFERENTIAL EQUATIONS 6.0 Introduction to Differential Equations Contemporary Calculus 1 6.0 INTRODUCTION TO DIFFERENTIAL EQUATIONS This chapter is an introduction to differential equations, a major field in applied and theoretical

More information

From Enzyme Kinetics to Epidemiological Models with Michaelis-Menten Contact Rate: Design of Nonstandard Finite Difference Schemes

From Enzyme Kinetics to Epidemiological Models with Michaelis-Menten Contact Rate: Design of Nonstandard Finite Difference Schemes From Enzyme Kinetics to Epidemiological Models with Michaelis-Menten Contact Rate: Design of Nonstandard Finite Difference Schemes Michael Chapwanya a, Jean M-S Lubuma a,, Ronald E Mickens b a Department

More information

A Model of Evolutionary Dynamics with Quasiperiodic Forcing

A Model of Evolutionary Dynamics with Quasiperiodic Forcing paper presented at Society for Experimental Mechanics (SEM) IMAC XXXIII Conference on Structural Dynamics February 2-5, 205, Orlando FL A Model of Evolutionary Dynamics with Quasiperiodic Forcing Elizabeth

More information

Numerical Methods for Initial Value Problems; Harmonic Oscillators

Numerical Methods for Initial Value Problems; Harmonic Oscillators Lab 1 Numerical Methods for Initial Value Problems; Harmonic Oscillators Lab Objective: Implement several basic numerical methods for initial value problems (IVPs), and use them to study harmonic oscillators.

More information

NUMERICAL TREATMENT OF THE RLC SMOOTHING CIRCUIT USING LEAPFROG METHOD

NUMERICAL TREATMENT OF THE RLC SMOOTHING CIRCUIT USING LEAPFROG METHOD International Journal of Pure and Applied Mathematics Volume 106 No. 2 2016, 631-637 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu doi: 10.12732/ijpam.v106i2.25

More information

Introduction to standard and non-standard Numerical Methods

Introduction to standard and non-standard Numerical Methods Introduction to standard and non-standard Numerical Methods Dr. Mountaga LAM AMS : African Mathematic School 2018 May 23, 2018 One-step methods Runge-Kutta Methods Nonstandard Finite Difference Scheme

More information

Math 251 December 14, 2005 Answer Key to Final Exam. 1 18pt 2 16pt 3 12pt 4 14pt 5 12pt 6 14pt 7 14pt 8 16pt 9 20pt 10 14pt Total 150pt

Math 251 December 14, 2005 Answer Key to Final Exam. 1 18pt 2 16pt 3 12pt 4 14pt 5 12pt 6 14pt 7 14pt 8 16pt 9 20pt 10 14pt Total 150pt Name Section Math 51 December 14, 5 Answer Key to Final Exam There are 1 questions on this exam. Many of them have multiple parts. The point value of each question is indicated either at the beginning

More information

-Stable Second Derivative Block Multistep Formula for Stiff Initial Value Problems

-Stable Second Derivative Block Multistep Formula for Stiff Initial Value Problems IAENG International Journal of Applied Mathematics, :3, IJAM 3_7 -Stable Second Derivative Bloc Multistep Formula for Stiff Initial Value Problems (Advance online publication: 3 August ) IAENG International

More information

LECTURE 4-1 INTRODUCTION TO ORDINARY DIFFERENTIAL EQUATIONS

LECTURE 4-1 INTRODUCTION TO ORDINARY DIFFERENTIAL EQUATIONS 130 LECTURE 4-1 INTRODUCTION TO ORDINARY DIFFERENTIAL EQUATIONS DIFFERENTIAL EQUATIONS: A differential equation (DE) is an equation involving an unknown function and one or more of its derivatives. A differential

More information

UNIT 5: DERIVATIVES OF EXPONENTIAL AND TRIGONOMETRIC FUNCTIONS. Qu: What do you remember about exponential and logarithmic functions?

UNIT 5: DERIVATIVES OF EXPONENTIAL AND TRIGONOMETRIC FUNCTIONS. Qu: What do you remember about exponential and logarithmic functions? UNIT 5: DERIVATIVES OF EXPONENTIAL AND TRIGONOMETRIC FUNCTIONS 5.1 DERIVATIVES OF EXPONENTIAL FUNCTIONS, y = e X Qu: What do you remember about exponential and logarithmic functions? e, called Euler s

More information