2 Wave equation in one dimension
|
|
- Hollie Fisher
- 7 years ago
- Views:
Transcription
1 2 Wave equation in one dimension Here we will consider in detail the wave equation in one dimension (x), for a function H(x,t). H could be, for example, a component of an EM field, the pressure of air in a sound wave moving along the x axis, or it could be the displacement of a string, for a wave moving along a taught string. The one-dimensional wave equation is 2 H(x,t) x 2 = 1 c 2 2 H(x,t) 2 or equivalently 2 H(x,t) = c 2 2 H(x,t) 2 x 2 where c is the speed of the wave. Note that it is a linear homogeneous PDE. In the next section we consider d Alembert s very general solution of the wave function. After that we consider standing then travelling wave solutions, before finishing with the application of boundary conditions. 2.1 d Alembert s solution The 18th century mathematician and physicist Jean le Rond d Alembert showed that the solution, H, to the one-dimensional wave equation can always be written as the sum of two travelling waves. We call these two waves W F, and W B (F for forward and B for back). Both W F and W B depend only on a single variable, unlike H which depends on two: x and t. W F depends on the variable u = x ct, and W B depends on the variable v = x + ct. So d Alembert said that we could always write the solution of the wave PDE as H(x,t) = W F (x ct) + W B (x + ct) = W F (u) + W B (v) Note that this is not trivial because the left-hand side is a function of two variables, while each of the two functions on the right-hand side is just a function of one variable. This is a solution for the wave equation, whatever W F and W B are, i.e., these functions can be anything. As we will see W F and W B are usually taken to be sine or cosine waves, i.e., sin(x ct) or cos(x ct) for W F, or the closely related exponentials exp(ik(x ct)). But they can be any function: polynomials, Gaussians, etc. The basic physics behind d Alembert s solution is that solutions of the wave equation don t change shape as time advances, they just translate with unchanged shape (to the right or left, depending on the direction of the wave) Proof that d Alembert s W F (u) is a solution to the wave PDE To see that W F (u), with u = x ct, is a solution to the wave equation, we just substitute it into both sides of this PDE. Then by use of the chain rule of differentiation, we can show that for any function of u the LHS equals the RHS and it must be a solution. We start with the left-hand side LHS = 2 W F (x,t) x 2 = x x = ( WF (u) ) = x x x 7
2 because / x = 1. Continuing LHS = x Now for the right-hand side RHS = 1 c 2 2 W F (x,t) 2 = 1 c 2 = because / = c. Continuing RHS = 1 ( ) = 1 ( ) c c x = = 2 W F (u) 2 = 1 ( ) = 1 ( ) ( c) c 2 c 2 ( ) = 1 c ( ) ( c) = 2 W F (u) 2 So, both sides of the wave equation are just the second derivative with respect to u, and so are equal to each other, proving that any function W F (x ct) is a solution to the wave equation. The proof that W B (x + ct) is also a solution, is very similar. 2.2 Solution of the one-dimensional wave equation via separation of variables: the standing-wave solution A standard way of solving PDEs such as the wave equation, diffusion equation, Schrödinger s equation, etc, is to start by assuming that the solution, e.g., H(x,t), can be written as a product of functions, each of which is a function of only one of the variables. The idea is that H(x,t) is a function of x only, call it X(x), times a function of t only, call it T(t): H(x,t) = X(x)T(t) Note that T(t) is a function of t, not the temperature. At the moment, X and T are unknown functions. Now, by assuming that we can write the solution to the PDE as a product of a function of x times a function of t, we can obtain a solution of PDE but we will not obtain the general solution to the PDE. Typically (as we will see below) we use this method to obtain solutions, which are sine and cosine waves, and then we sum many of these waves (with different wavelengths) in a Fourier series to obtain the particular solution that we want, i.e., one that satisfies the boundary conditions on the solution. If we substitute H(x,t) = X(x)T(t) into the one-dimensional wave equation we get T(t) 2 X(x) x 2 = 1 c 2X(x) 2 T(t) 2 because we can take T out of the x differentiation as it is independent of x, and similarly we can take X out of the t differentiation. If we divide both sides by XT, we get 1 2 X(x) = T(t) X(x) x 2 c 2 T(t) 2 Now, we notice that the left-hand side is a function of x but not of t while the right-hand side is a function of t but not of x. So the LHS tells us that the equation cannot depend on t, and the RHS 8
3 tells us that it cannot depend on x. Therefore it cannot depend on either x or t, and so must be a constant. We will call this constant k 2. As we will see the minus sign will give us the sine and cosine functions we want 2. The fact that k is squared is just to make some of the later equations look neater. So we have 1 2 X(x) = T(t) = k 2 X(x) x 2 c 2 T(t) 2 which gives us the two ODEs The solutions of these ODEs are 2 X(x) x 2 = k 2 X(x) and 2 T(t) 2 = k 2 c 2 T(t) X(x) = A cos(kx) + B sin(kx) and T(t) = C cos(kct) + D sin(kct) where A, B, C and D are constants. You can check this by substituting these solutions back into the ODEs and checking that the LHS equals the RHS. These ODEs were covered in the semester 1 ODE course, please refer to your notes or to a textbook if you are unsure about these solutions. You need to understand how to solve these simple ODEs if you are to understand how to solve the PDEs. We can multiply X and T together and get the solution for H or H(x,t) = X(x)T(t) = [A cos(kx) + B sin(kx)] [C cos(kct) + D sin(kct)] H(x,t) = AC cos(kx) cos(kct) + AD cos(kx) sin(kct) + BC sin(kx) cos(kct) + BD sin(kx) sin(kct) Defining the four new constants I = AC, J = AD, P = BC and Q = BD we have that the solution is H(x,t) = I cos(kx) cos(kct) + J cos(kx) sin(kct) + P sin(kx) cos(kct) + Q sin(kx) sin(kct) This solution has four terms: the four combinations of sines and cosines as functions of space and of time. It is a solution but not the most general solution. However, as the wave equation is a linear homogeneous PDE then the sum of any solutions of this PDE is also a solution to the PDE. In other words we can add lots of terms like cos(kx) cos(kct), with different k s, and the sum is also a solution, e.g., H(x,t) = I 1 cos(k 1 x) cos(k 1 ct) + I 2 cos(k 2 x) sin(k 2 ct) is a solution of the PDE, for any values of the constants I 1 and I 2, and of the wavevectors k 1 and k 2. This means that we can add lots of these terms together and vary the constants, and so get an expression which satisfies the boundary conditions. This is how we can use a Fourier series to obtain a particular solution of a PDE. To write a Fourier series general solution to the wave PDE we add subscript n s to the I, J, P, Q and k to indicate that we could have many terms like these with different values of I, k, etc. Then we have H(x,t) = [I n cos(k n x) cos(k n ct) + J n cos(k n x) sin(k n ct) + P n sin(k n x) cos(k n ct) + Q n sin(k n x) sin(k n ct)] n=1 2 We choose the sign as we wanted sine and cosine functions. If we picked a + sign, we would get exponentials, which are not useful for the problems we study here but might be in other problems. 9
4 Figure 2: A plot of a square wave H(x) of wavelength L = 1, plus two sine wave series approximations to it. The square wave is the black solid curve. A sine wave of the same wavelength is shown as a dot-dashed green (grey) curve. This is a sine series approximation to the square wave, truncated after the first term. A sum of up to the n = 9 terms is shown as the dashed red (grey) curve. We see that the dashed curve follows the square wave much better than the dot-dashed curve but it is still an approximation, only an infinite series perfectly follows the square wave. h x Note that for each solution all the constants are different, the I n, J n, P n, Q n and k n are all different. k n = 2π/λ n is the wavevector of the nth term in the sum, and so the nth term is 4 waves, each with the same wavelength, but each term has a different wavelength. The boundary conditions will determine the values of the constants I n, J n, P n and Q n, and of the k n and then once these values are determined we have the particular solution. 2.3 Travelling wave solutions The method of separation of variables gives us the solution in terms of standing waves, i.e., a sine (or cosine) of kx times a sine (or cosine) of kct, e.g., sin(kx) sin(kct). Any solution of the wave PDE can be expressed as a sum of standing wavs. However, any solution of the wave PDE can also be written in terms of a sum of travelling waves, i.e., functions like sin(k(x ct)). So, we can also write the solution as H(x,t) = [A n cos(k n (x ct)) + B n sin(k n (x ct)) + C n cos(k n (x + ct)) + D n sin(k n (x + ct))] n=1 The first two terms are sine and cosine waves moving to the right, with speed c, whereas the last two terms are sine and cosine waves moving to the left, with speed c. For example a simple sine wave with wavelength λ = 2π/k, amplitude B, moving with speed c is H(x,t) = B sin(k n (x ct)) This just gives a sine curve of course, but other shapes can be built up from a sum of sines (and/or 10
5 cosines). We can consider a simple example: the square wave, defined by { +1 0 < x < L/2 H(x,t = 0) = 1 L/2 < x < L This can be written as the sum of sine waves H(x,t = 0) = n=2,6,10,14,... 8 ( nπx ) nπ sin L Note that for the square wave, the sum only includes every 4th term, the n = 3, 4 and 5 terms are zero, the n = 6 term is non-zero, the n = 7, 8and9 terms are zero, and so on. Starting with this square wave at t = 0, a square wave moving with speed c is then obtained by just subtracting ct from x in the argument of the sine waves, i.e., The first few terms are H(x,t) = H(x,t) = 4 π sin ( 2π(x ct) L n=2,6,10,14, Applying boundary conditions 8 nπ sin ) + 4 ( ) 6π(x ct) 3π sin L ( ) nπ(x ct) L + 4 5π sin ( ) 10π(x ct) + L Above we started with the wave at time t = 0, and if we know the direction the wave is travelling in, then we can just subtract ct from x in the sine functions, to get the solution at any time t. When we did this we were effectively specifying boundary conditions: these were the initial condition, which is the wave at t = 0, plus a direction. Here we will look at two more examples of the application of boundary conditions to solutions of the wave PDE. One to a standing wave solution and another to a travelling wave solution. First the standing wave solution Simple example boundary conditions applied to a standing wave solution In general the solution will be an infinite sum of waves (also called Fourier modes), each with a different k, i.e., with a different wavelength. But here we will consider a simple example, where there is only one standing wave, a wavelength λ, with a corresponding wavevector k = 2π/λ. In this case the solution is just H(x,t) = I cos(kx) cos(kct) + J cos(kx) sin(kct) + P sin(kx) cos(kct) + Q sin(kx) sin(kct) As a simple example of how boundary conditions are applied, we consider boundary conditions that are initial conditions. The first initial condition is that at time t = 0, the function H(x,t = 0) is given by H(x,t = 0) = 10 cos(kx) and the second initial condition is that the time derivative is zero, i.e., the string is stationary at t = 0 = 0 11
6 where the subscript t = 0 on the brackets indicates that we evaluate the time derivative at t = 0. Now, having written down the boundary conditions that the particular solution must satisfy, we must apply these boundary conditions. We start 3 by applying the boundary condition on H at t = 0 H(x,t = 0) = 10 cos(kx) = I cos(kx) cos(0) + J cos(kx) sin(0) + P sin(kx) cos(0) + Q sin(kx) sin(0) and as sin(0) = 0 and cos(0) = 1, this simplifies to 10 cos(kx) = I cos(kx) + P sin(kx) So I = 10 and P = 0. Putting these values in our expression for H(x,t) we get H(x,t) = 10 cos(kx) cos(kct) + J cos(kx) sin(kct) + Q sin(kx) sin(kct) Now we apply the boundary condition on the initial time derivative. First we take the time derivative of H H(x, t) = 10kc cos(kx) sin(kct) + Jkc cos(kx) cos(kct) + Qkc sin(kx) cos(kct) At t = 0, this time derivative equals zero = 0 = 10kc cos(kx) sin(0) + Jkc cos(kx) cos(0) + Qkc sin(kx) cos(0) 0 = Jkc cos(kx) + Qkc sin(kx) so both J and Q are zero, J = 0, and Q = 0. So the particular solution that satisfies both boundary conditions is H(x,t) = 10 cos(kx) cos(kct) Simple example boundary conditions applied to a travelling wave solution We will now look at exactly the same boundary conditions but with a travelling wave. The general travelling wave solution for one fixed value of k is H(x,t) = A cos(k(x ct)) + B sin(k(x ct)) + C cos(k(x + ct)) + D sin(k(x + ct)) As before, the first initial condition is that at time t = 0, the function H(x,t = 0) is given by so we have H(x,t = 0) = 10 cos(kx) H(x,t = 0) = 10 cos(kx) = A cos(kx) + B sin(kx) + C cos(kx) + D sin(kx) H(x,t = 0) = (A + C) cos(kx) + (B + D) sin(kx) To satisfy this boundary condition, A + C = 10 and B + D = 0. 3 We start with this boundary condition as it simplifies the solution by eliminating some terms. Note that in principle we can apply the boundary conditions in any order, but that in practice some orders are a lot easier than others to do. 12
7 The second initial condition is that the time derivative is zero at t = 0. The time derivative of the solution is H(x, t) = Akc sin(k(x ct)) Bkc cos(k(x ct)) Ckc sin(k(x + ct)) + Dkc cos(k(x + ct)) At t = 0 this derivative is zero = Akc sin(kx) BkcB cos(kx) Ckc sin(kx) + Dkc cos(kx) = kc(a C) sin(kx) + kc(d B) cos(kx) = 0 so to satisfy this boundary condition A C = 0 and D B = 0. By combining the equations for A and C from the two boundary conditions we obtain two simultaneous linear equations for A and C A + C = 10 A C = 0 which have the solution A = C = 5. For B and D we have two simultaneous linear equations B + D = 0 D B = 0 which have the solution B = D = 0. So the particular travelling wave solution that satisfies these boundary conditions is H(x,t) = 5 cos(k(x ct)) + 5 cos(k(x + ct)) These are two cosine travelling waves, one travelling left to right and the other right to left. These two travelling waves sum to give the standing wave we found in the previous section, i.e., the two solutions we found, one in terms of a standing wave, and the other in terms of two travelling waves, are completely equivalent. We can choose to use one or the other, whichever we find more convenient for the problem we are studying. 13
Second Order Linear Partial Differential Equations. Part I
Second Order Linear Partial Differential Equations Part I Second linear partial differential equations; Separation of Variables; - point boundary value problems; Eigenvalues and Eigenfunctions Introduction
More information3.2. Solving quadratic equations. Introduction. Prerequisites. Learning Outcomes. Learning Style
Solving quadratic equations 3.2 Introduction A quadratic equation is one which can be written in the form ax 2 + bx + c = 0 where a, b and c are numbers and x is the unknown whose value(s) we wish to find.
More informationLS.6 Solution Matrices
LS.6 Solution Matrices In the literature, solutions to linear systems often are expressed using square matrices rather than vectors. You need to get used to the terminology. As before, we state the definitions
More informationSolving Linear Equations in One Variable. Worked Examples
Solving Linear Equations in One Variable Worked Examples Solve the equation 30 x 1 22x Solve the equation 30 x 1 22x Our goal is to isolate the x on one side. We ll do that by adding (or subtracting) quantities
More informationSecond Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients. y + p(t) y + q(t) y = g(t), g(t) 0.
Second Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients We will now turn our attention to nonhomogeneous second order linear equations, equations with the standard
More informationCopyrighted Material. Chapter 1 DEGREE OF A CURVE
Chapter 1 DEGREE OF A CURVE Road Map The idea of degree is a fundamental concept, which will take us several chapters to explore in depth. We begin by explaining what an algebraic curve is, and offer two
More informationYear 9 set 1 Mathematics notes, to accompany the 9H book.
Part 1: Year 9 set 1 Mathematics notes, to accompany the 9H book. equations 1. (p.1), 1.6 (p. 44), 4.6 (p.196) sequences 3. (p.115) Pupils use the Elmwood Press Essential Maths book by David Raymer (9H
More informationThe one dimensional heat equation: Neumann and Robin boundary conditions
The one dimensional heat equation: Neumann and Robin boundary conditions Ryan C. Trinity University Partial Differential Equations February 28, 2012 with Neumann boundary conditions Our goal is to solve:
More informationMATH 425, PRACTICE FINAL EXAM SOLUTIONS.
MATH 45, PRACTICE FINAL EXAM SOLUTIONS. Exercise. a Is the operator L defined on smooth functions of x, y by L u := u xx + cosu linear? b Does the answer change if we replace the operator L by the operator
More informationThe Heat Equation. Lectures INF2320 p. 1/88
The Heat Equation Lectures INF232 p. 1/88 Lectures INF232 p. 2/88 The Heat Equation We study the heat equation: u t = u xx for x (,1), t >, (1) u(,t) = u(1,t) = for t >, (2) u(x,) = f(x) for x (,1), (3)
More information2x + y = 3. Since the second equation is precisely the same as the first equation, it is enough to find x and y satisfying the system
1. Systems of linear equations We are interested in the solutions to systems of linear equations. A linear equation is of the form 3x 5y + 2z + w = 3. The key thing is that we don t multiply the variables
More informationCore Maths C1. Revision Notes
Core Maths C Revision Notes November 0 Core Maths C Algebra... Indices... Rules of indices... Surds... 4 Simplifying surds... 4 Rationalising the denominator... 4 Quadratic functions... 4 Completing the
More informationPartial Fractions. Combining fractions over a common denominator is a familiar operation from algebra:
Partial Fractions Combining fractions over a common denominator is a familiar operation from algebra: From the standpoint of integration, the left side of Equation 1 would be much easier to work with than
More informationIntroduction to Complex Fourier Series
Introduction to Complex Fourier Series Nathan Pflueger 1 December 2014 Fourier series come in two flavors. What we have studied so far are called real Fourier series: these decompose a given periodic function
More informationApplication of Fourier Transform to PDE (I) Fourier Sine Transform (application to PDEs defined on a semi-infinite domain)
Application of Fourier Transform to PDE (I) Fourier Sine Transform (application to PDEs defined on a semi-infinite domain) The Fourier Sine Transform pair are F. T. : U = 2/ u x sin x dx, denoted as U
More information7. Beats. sin( + λ) + sin( λ) = 2 cos(λ) sin( )
34 7. Beats 7.1. What beats are. Musicians tune their instruments using beats. Beats occur when two very nearby pitches are sounded simultaneously. We ll make a mathematical study of this effect, using
More informationDifferentiation and Integration
This material is a supplement to Appendix G of Stewart. You should read the appendix, except the last section on complex exponentials, before this material. Differentiation and Integration Suppose we have
More informationMATRIX ALGEBRA AND SYSTEMS OF EQUATIONS
MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS Systems of Equations and Matrices Representation of a linear system The general system of m equations in n unknowns can be written a x + a 2 x 2 + + a n x n b a
More informationTaylor and Maclaurin Series
Taylor and Maclaurin Series In the preceding section we were able to find power series representations for a certain restricted class of functions. Here we investigate more general problems: Which functions
More informationSection 10.4 Vectors
Section 10.4 Vectors A vector is represented by using a ray, or arrow, that starts at an initial point and ends at a terminal point. Your textbook will always use a bold letter to indicate a vector (such
More informationScientific Programming
1 The wave equation Scientific Programming Wave Equation The wave equation describes how waves propagate: light waves, sound waves, oscillating strings, wave in a pond,... Suppose that the function h(x,t)
More informationFind all of the real numbers x that satisfy the algebraic equation:
Appendix C: Factoring Algebraic Expressions Factoring algebraic equations is the reverse of expanding algebraic expressions discussed in Appendix B. Factoring algebraic equations can be a great help when
More informationMethod To Solve Linear, Polynomial, or Absolute Value Inequalities:
Solving Inequalities An inequality is the result of replacing the = sign in an equation with ,, or. For example, 3x 2 < 7 is a linear inequality. We call it linear because if the < were replaced with
More informationFigure 1.1 Vector A and Vector F
CHAPTER I VECTOR QUANTITIES Quantities are anything which can be measured, and stated with number. Quantities in physics are divided into two types; scalar and vector quantities. Scalar quantities have
More information1 The 1-D Heat Equation
The 1-D Heat Equation 18.303 Linear Partial Differential Equations Matthew J. Hancock Fall 006 1 The 1-D Heat Equation 1.1 Physical derivation Reference: Guenther & Lee 1.3-1.4, Myint-U & Debnath.1 and.5
More informationBiggar High School Mathematics Department. National 5 Learning Intentions & Success Criteria: Assessing My Progress
Biggar High School Mathematics Department National 5 Learning Intentions & Success Criteria: Assessing My Progress Expressions & Formulae Topic Learning Intention Success Criteria I understand this Approximation
More informationAn Introduction to Partial Differential Equations in the Undergraduate Curriculum
An Introduction to Partial Differential Equations in the Undergraduate Curriculum J. Tolosa & M. Vajiac LECTURE 11 Laplace s Equation in a Disk 11.1. Outline of Lecture The Laplacian in Polar Coordinates
More information5.5. Solving linear systems by the elimination method
55 Solving linear systems by the elimination method Equivalent systems The major technique of solving systems of equations is changing the original problem into another one which is of an easier to solve
More informationInvestigation of Chebyshev Polynomials
Investigation of Chebyshev Polynomials Leon Loo April 25, 2002 1 Introduction Prior to taking part in this Mathematics Research Project, I have been responding to the Problems of the Week in the Math Forum
More informationIntroduction to Complex Numbers in Physics/Engineering
Introduction to Complex Numbers in Physics/Engineering ference: Mary L. Boas, Mathematical Methods in the Physical Sciences Chapter 2 & 14 George Arfken, Mathematical Methods for Physicists Chapter 6 The
More informationBasic numerical skills: EQUATIONS AND HOW TO SOLVE THEM. x + 5 = 7 2 + 5-2 = 7-2 5 + (2-2) = 7-2 5 = 5. x + 5-5 = 7-5. x + 0 = 20.
Basic numerical skills: EQUATIONS AND HOW TO SOLVE THEM 1. Introduction (really easy) An equation represents the equivalence between two quantities. The two sides of the equation are in balance, and solving
More information2 Session Two - Complex Numbers and Vectors
PH2011 Physics 2A Maths Revision - Session 2: Complex Numbers and Vectors 1 2 Session Two - Complex Numbers and Vectors 2.1 What is a Complex Number? The material on complex numbers should be familiar
More informationUsing a table of derivatives
Using a table of derivatives In this unit we construct a Table of Derivatives of commonly occurring functions. This is done using the knowledge gained in previous units on differentiation from first principles.
More informationMATH10212 Linear Algebra. Systems of Linear Equations. Definition. An n-dimensional vector is a row or a column of n numbers (or letters): a 1.
MATH10212 Linear Algebra Textbook: D. Poole, Linear Algebra: A Modern Introduction. Thompson, 2006. ISBN 0-534-40596-7. Systems of Linear Equations Definition. An n-dimensional vector is a row or a column
More informationA few words about imaginary numbers (and electronics) Mark Cohen mscohen@g.ucla.edu
A few words about imaginary numbers (and electronics) Mark Cohen mscohen@guclaedu While most of us have seen imaginary numbers in high school algebra, the topic is ordinarily taught in abstraction without
More informationTrigonometric Functions and Equations
Contents Trigonometric Functions and Equations Lesson 1 Reasoning with Trigonometric Functions Investigations 1 Proving Trigonometric Identities... 271 2 Sum and Difference Identities... 276 3 Extending
More informationSolving systems by elimination
December 1, 2008 Solving systems by elimination page 1 Solving systems by elimination Here is another method for solving a system of two equations. Sometimes this method is easier than either the graphing
More information5 Homogeneous systems
5 Homogeneous systems Definition: A homogeneous (ho-mo-jeen -i-us) system of linear algebraic equations is one in which all the numbers on the right hand side are equal to : a x +... + a n x n =.. a m
More information10.2 ITERATIVE METHODS FOR SOLVING LINEAR SYSTEMS. The Jacobi Method
578 CHAPTER 1 NUMERICAL METHODS 1. ITERATIVE METHODS FOR SOLVING LINEAR SYSTEMS As a numerical technique, Gaussian elimination is rather unusual because it is direct. That is, a solution is obtained after
More information4.5 Linear Dependence and Linear Independence
4.5 Linear Dependence and Linear Independence 267 32. {v 1, v 2 }, where v 1, v 2 are collinear vectors in R 3. 33. Prove that if S and S are subsets of a vector space V such that S is a subset of S, then
More informationWeek 13 Trigonometric Form of Complex Numbers
Week Trigonometric Form of Complex Numbers Overview In this week of the course, which is the last week if you are not going to take calculus, we will look at how Trigonometry can sometimes help in working
More informationSecond-Order Linear Differential Equations
Second-Order Linear Differential Equations A second-order linear differential equation has the form 1 Px d 2 y dx 2 dy Qx dx Rxy Gx where P, Q, R, and G are continuous functions. We saw in Section 7.1
More informationOn Black-Scholes Equation, Black- Scholes Formula and Binary Option Price
On Black-Scholes Equation, Black- Scholes Formula and Binary Option Price Abstract: Chi Gao 12/15/2013 I. Black-Scholes Equation is derived using two methods: (1) risk-neutral measure; (2) - hedge. II.
More informationSecond Order Linear Differential Equations
CHAPTER 2 Second Order Linear Differential Equations 2.. Homogeneous Equations A differential equation is a relation involving variables x y y y. A solution is a function f x such that the substitution
More informationLecture - 4 Diode Rectifier Circuits
Basic Electronics (Module 1 Semiconductor Diodes) Dr. Chitralekha Mahanta Department of Electronics and Communication Engineering Indian Institute of Technology, Guwahati Lecture - 4 Diode Rectifier Circuits
More informationLinear Equations ! 25 30 35$ & " 350 150% & " 11,750 12,750 13,750% MATHEMATICS LEARNING SERVICE Centre for Learning and Professional Development
MathsTrack (NOTE Feb 2013: This is the old version of MathsTrack. New books will be created during 2013 and 2014) Topic 4 Module 9 Introduction Systems of to Matrices Linear Equations Income = Tickets!
More informationEquations, Inequalities & Partial Fractions
Contents Equations, Inequalities & Partial Fractions.1 Solving Linear Equations 2.2 Solving Quadratic Equations 1. Solving Polynomial Equations 1.4 Solving Simultaneous Linear Equations 42.5 Solving Inequalities
More informationCOMPLEX NUMBERS. a bi c di a c b d i. a bi c di a c b d i For instance, 1 i 4 7i 1 4 1 7 i 5 6i
COMPLEX NUMBERS _4+i _-i FIGURE Complex numbers as points in the Arg plane i _i +i -i A complex number can be represented by an expression of the form a bi, where a b are real numbers i is a symbol with
More informationANALYTICAL METHODS FOR ENGINEERS
UNIT 1: Unit code: QCF Level: 4 Credit value: 15 ANALYTICAL METHODS FOR ENGINEERS A/601/1401 OUTCOME - TRIGONOMETRIC METHODS TUTORIAL 1 SINUSOIDAL FUNCTION Be able to analyse and model engineering situations
More information3.1. Solving linear equations. Introduction. Prerequisites. Learning Outcomes. Learning Style
Solving linear equations 3.1 Introduction Many problems in engineering reduce to the solution of an equation or a set of equations. An equation is a type of mathematical expression which contains one or
More informationProperties of Real Numbers
16 Chapter P Prerequisites P.2 Properties of Real Numbers What you should learn: Identify and use the basic properties of real numbers Develop and use additional properties of real numbers Why you should
More information1 Lecture: Integration of rational functions by decomposition
Lecture: Integration of rational functions by decomposition into partial fractions Recognize and integrate basic rational functions, except when the denominator is a power of an irreducible quadratic.
More informationIntroduction to the Finite Element Method (FEM)
Introduction to the Finite Element Method (FEM) ecture First and Second Order One Dimensional Shape Functions Dr. J. Dean Discretisation Consider the temperature distribution along the one-dimensional
More informationSECOND-ORDER LINEAR DIFFERENTIAL EQUATIONS
SECOND-ORDER LINEAR DIFFERENTIAL EQUATIONS A second-order linear differential equation has the form 1 Px d y dx dy Qx dx Rxy Gx where P, Q, R, and G are continuous functions. Equations of this type arise
More information2 Integrating Both Sides
2 Integrating Both Sides So far, the only general method we have for solving differential equations involves equations of the form y = f(x), where f(x) is any function of x. The solution to such an equation
More informationDirect Translation is the process of translating English words and phrases into numbers, mathematical symbols, expressions, and equations.
Section 1 Mathematics has a language all its own. In order to be able to solve many types of word problems, we need to be able to translate the English Language into Math Language. is the process of translating
More informationLectures 5-6: Taylor Series
Math 1d Instructor: Padraic Bartlett Lectures 5-: Taylor Series Weeks 5- Caltech 213 1 Taylor Polynomials and Series As we saw in week 4, power series are remarkably nice objects to work with. In particular,
More informationSection V.3: Dot Product
Section V.3: Dot Product Introduction So far we have looked at operations on a single vector. There are a number of ways to combine two vectors. Vector addition and subtraction will not be covered here,
More informationDefinition 8.1 Two inequalities are equivalent if they have the same solution set. Add or Subtract the same value on both sides of the inequality.
8 Inequalities Concepts: Equivalent Inequalities Linear and Nonlinear Inequalities Absolute Value Inequalities (Sections 4.6 and 1.1) 8.1 Equivalent Inequalities Definition 8.1 Two inequalities are equivalent
More informationApplications of Fermat s Little Theorem and Congruences
Applications of Fermat s Little Theorem and Congruences Definition: Let m be a positive integer. Then integers a and b are congruent modulo m, denoted by a b mod m, if m (a b). Example: 3 1 mod 2, 6 4
More informationTRIGONOMETRY Compound & Double angle formulae
TRIGONOMETRY Compound & Double angle formulae In order to master this section you must first learn the formulae, even though they will be given to you on the matric formula sheet. We call these formulae
More informationcorrect-choice plot f(x) and draw an approximate tangent line at x = a and use geometry to estimate its slope comment The choices were:
Topic 1 2.1 mode MultipleSelection text How can we approximate the slope of the tangent line to f(x) at a point x = a? This is a Multiple selection question, so you need to check all of the answers that
More informationCHAPTER 2. Eigenvalue Problems (EVP s) for ODE s
A SERIES OF CLASS NOTES FOR 005-006 TO INTRODUCE LINEAR AND NONLINEAR PROBLEMS TO ENGINEERS, SCIENTISTS, AND APPLIED MATHEMATICIANS DE CLASS NOTES 4 A COLLECTION OF HANDOUTS ON PARTIAL DIFFERENTIAL EQUATIONS
More informationCorrelation and Convolution Class Notes for CMSC 426, Fall 2005 David Jacobs
Correlation and Convolution Class otes for CMSC 46, Fall 5 David Jacobs Introduction Correlation and Convolution are basic operations that we will perform to extract information from images. They are in
More informationMATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m
MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS 1. SYSTEMS OF EQUATIONS AND MATRICES 1.1. Representation of a linear system. The general system of m equations in n unknowns can be written a 11 x 1 + a 12 x 2 +
More informationSection 8.2 Solving a System of Equations Using Matrices (Guassian Elimination)
Section 8. Solving a System of Equations Using Matrices (Guassian Elimination) x + y + z = x y + 4z = x 4y + z = System of Equations x 4 y = 4 z A System in matrix form x A x = b b 4 4 Augmented Matrix
More informationSYSTEMS OF EQUATIONS AND MATRICES WITH THE TI-89. by Joseph Collison
SYSTEMS OF EQUATIONS AND MATRICES WITH THE TI-89 by Joseph Collison Copyright 2000 by Joseph Collison All rights reserved Reproduction or translation of any part of this work beyond that permitted by Sections
More informationa 1 x + a 0 =0. (3) ax 2 + bx + c =0. (4)
ROOTS OF POLYNOMIAL EQUATIONS In this unit we discuss polynomial equations. A polynomial in x of degree n, where n 0 is an integer, is an expression of the form P n (x) =a n x n + a n 1 x n 1 + + a 1 x
More informationEuler s Formula Math 220
Euler s Formula Math 0 last change: Sept 3, 05 Complex numbers A complex number is an expression of the form x+iy where x and y are real numbers and i is the imaginary square root of. For example, + 3i
More informationSolutions to Linear First Order ODE s
First Order Linear Equations In the previous session we learned that a first order linear inhomogeneous ODE for the unknown function x = x(t), has the standard form x + p(t)x = q(t) () (To be precise we
More informationa 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2.
Chapter 1 LINEAR EQUATIONS 1.1 Introduction to linear equations A linear equation in n unknowns x 1, x,, x n is an equation of the form a 1 x 1 + a x + + a n x n = b, where a 1, a,..., a n, b are given
More informationAn Introduction to Partial Differential Equations
An Introduction to Partial Differential Equations Andrew J. Bernoff LECTURE 2 Cooling of a Hot Bar: The Diffusion Equation 2.1. Outline of Lecture An Introduction to Heat Flow Derivation of the Diffusion
More informationHomework #2 Solutions
MAT Spring Problems Section.:, 8,, 4, 8 Section.5:,,, 4,, 6 Extra Problem # Homework # Solutions... Sketch likely solution curves through the given slope field for dy dx = x + y...8. Sketch likely solution
More informationGeorgia Department of Education Kathy Cox, State Superintendent of Schools 7/19/2005 All Rights Reserved 1
Accelerated Mathematics 3 This is a course in precalculus and statistics, designed to prepare students to take AB or BC Advanced Placement Calculus. It includes rational, circular trigonometric, and inverse
More informationTWO-DIMENSIONAL TRANSFORMATION
CHAPTER 2 TWO-DIMENSIONAL TRANSFORMATION 2.1 Introduction As stated earlier, Computer Aided Design consists of three components, namely, Design (Geometric Modeling), Analysis (FEA, etc), and Visualization
More informationThe Quantum Harmonic Oscillator Stephen Webb
The Quantum Harmonic Oscillator Stephen Webb The Importance of the Harmonic Oscillator The quantum harmonic oscillator holds a unique importance in quantum mechanics, as it is both one of the few problems
More informationFive fundamental operations. mathematics: addition, subtraction, multiplication, division, and modular forms
The five fundamental operations of mathematics: addition, subtraction, multiplication, division, and modular forms UC Berkeley Trinity University March 31, 2008 This talk is about counting, and it s about
More informationFurther Mathematics for Engineering Technicians
Unit 28: Further Mathematics for Engineering Technicians Unit code: QCF Level 3: Credit value: 10 Guided learning hours: 60 Aim and purpose H/600/0280 BTEC Nationals This unit aims to enhance learners
More informationLimits and Continuity
Math 20C Multivariable Calculus Lecture Limits and Continuity Slide Review of Limit. Side limits and squeeze theorem. Continuous functions of 2,3 variables. Review: Limits Slide 2 Definition Given a function
More informationAlgebra Practice Problems for Precalculus and Calculus
Algebra Practice Problems for Precalculus and Calculus Solve the following equations for the unknown x: 1. 5 = 7x 16 2. 2x 3 = 5 x 3. 4. 1 2 (x 3) + x = 17 + 3(4 x) 5 x = 2 x 3 Multiply the indicated polynomials
More informationNonhomogeneous Linear Equations
Nonhomogeneous Linear Equations In this section we learn how to solve second-order nonhomogeneous linear differential equations with constant coefficients, that is, equations of the form ay by cy G x where
More informationVector Math Computer Graphics Scott D. Anderson
Vector Math Computer Graphics Scott D. Anderson 1 Dot Product The notation v w means the dot product or scalar product or inner product of two vectors, v and w. In abstract mathematics, we can talk about
More informationSystems of Linear Equations
Chapter 1 Systems of Linear Equations 1.1 Intro. to systems of linear equations Homework: [Textbook, Ex. 13, 15, 41, 47, 49, 51, 65, 73; page 11-]. Main points in this section: 1. Definition of Linear
More informationAlgebra I Vocabulary Cards
Algebra I Vocabulary Cards Table of Contents Expressions and Operations Natural Numbers Whole Numbers Integers Rational Numbers Irrational Numbers Real Numbers Absolute Value Order of Operations Expression
More informationf x a 0 n 1 a 0 a 1 cos x a 2 cos 2x a 3 cos 3x b 1 sin x b 2 sin 2x b 3 sin 3x a n cos nx b n sin nx n 1 f x dx y
Fourier Series When the French mathematician Joseph Fourier (768 83) was tring to solve a problem in heat conduction, he needed to epress a function f as an infinite series of sine and cosine functions:
More informationSo far, we have looked at homogeneous equations
Chapter 3.6: equations Non-homogeneous So far, we have looked at homogeneous equations L[y] = y + p(t)y + q(t)y = 0. Homogeneous means that the right side is zero. Linear homogeneous equations satisfy
More informationALGEBRA. sequence, term, nth term, consecutive, rule, relationship, generate, predict, continue increase, decrease finite, infinite
ALGEBRA Pupils should be taught to: Generate and describe sequences As outcomes, Year 7 pupils should, for example: Use, read and write, spelling correctly: sequence, term, nth term, consecutive, rule,
More informationSOLVING TRIGONOMETRIC EQUATIONS
Mathematics Revision Guides Solving Trigonometric Equations Page 1 of 17 M.K. HOME TUITION Mathematics Revision Guides Level: AS / A Level AQA : C2 Edexcel: C2 OCR: C2 OCR MEI: C2 SOLVING TRIGONOMETRIC
More informationA Concrete Introduction. to the Abstract Concepts. of Integers and Algebra using Algebra Tiles
A Concrete Introduction to the Abstract Concepts of Integers and Algebra using Algebra Tiles Table of Contents Introduction... 1 page Integers 1: Introduction to Integers... 3 2: Working with Algebra Tiles...
More informationNumerical Solution of Differential
Chapter 13 Numerical Solution of Differential Equations We have considered numerical solution procedures for two kinds of equations: In chapter 10 the unknown was a real number; in chapter 6 the unknown
More informationThe Basics of FEA Procedure
CHAPTER 2 The Basics of FEA Procedure 2.1 Introduction This chapter discusses the spring element, especially for the purpose of introducing various concepts involved in use of the FEA technique. A spring
More informationEDEXCEL NATIONAL CERTIFICATE/DIPLOMA UNIT 5 - ELECTRICAL AND ELECTRONIC PRINCIPLES NQF LEVEL 3 OUTCOME 4 - ALTERNATING CURRENT
EDEXCEL NATIONAL CERTIFICATE/DIPLOMA UNIT 5 - ELECTRICAL AND ELECTRONIC PRINCIPLES NQF LEVEL 3 OUTCOME 4 - ALTERNATING CURRENT 4 Understand single-phase alternating current (ac) theory Single phase AC
More information8.2. Solution by Inverse Matrix Method. Introduction. Prerequisites. Learning Outcomes
Solution by Inverse Matrix Method 8.2 Introduction The power of matrix algebra is seen in the representation of a system of simultaneous linear equations as a matrix equation. Matrix algebra allows us
More informationCAHSEE on Target UC Davis, School and University Partnerships
UC Davis, School and University Partnerships CAHSEE on Target Mathematics Curriculum Published by The University of California, Davis, School/University Partnerships Program 006 Director Sarah R. Martinez,
More informationLINEAR EQUATIONS IN TWO VARIABLES
66 MATHEMATICS CHAPTER 4 LINEAR EQUATIONS IN TWO VARIABLES The principal use of the Analytic Art is to bring Mathematical Problems to Equations and to exhibit those Equations in the most simple terms that
More information4.5 Chebyshev Polynomials
230 CHAP. 4 INTERPOLATION AND POLYNOMIAL APPROXIMATION 4.5 Chebyshev Polynomials We now turn our attention to polynomial interpolation for f (x) over [ 1, 1] based on the nodes 1 x 0 < x 1 < < x N 1. Both
More informationGRE Prep: Precalculus
GRE Prep: Precalculus Franklin H.J. Kenter 1 Introduction These are the notes for the Precalculus section for the GRE Prep session held at UCSD in August 2011. These notes are in no way intended to teach
More informationGraphs of Polar Equations
Graphs of Polar Equations In the last section, we learned how to graph a point with polar coordinates (r, θ). We will now look at graphing polar equations. Just as a quick review, the polar coordinate
More information1.2. Successive Differences
1. An Application of Inductive Reasoning: Number Patterns In the previous section we introduced inductive reasoning, and we showed how it can be applied in predicting what comes next in a list of numbers
More information