Fourier Series : Dr. Mohammed Saheb Khesbak Page 34

Size: px
Start display at page:

Download "Fourier Series : Dr. Mohammed Saheb Khesbak Page 34"

Transcription

1 Fourier Series : Dr. Mohammed Saheb Khesbak Page 34

2 Dr. Mohammed Saheb Khesbak Page 35

3 Example 1: Dr. Mohammed Saheb Khesbak Page 36

4 Dr. Mohammed Saheb Khesbak Page 37

5 Dr. Mohammed Saheb Khesbak Page 38

6 Derivation of the Euler Formulas: Theorem 1: Proof: Dr. Mohammed Saheb Khesbak Page 39

7 Example 2: Dr. Mohammed Saheb Khesbak Page 40

8 Example 3: Dr. Mohammed Saheb Khesbak Page 41

9 Example 3: Dr. Mohammed Saheb Khesbak Page 42

10 Exercises of Fourier Series Showing the details of your work, find the Fourier series of the given f(x), which is assumed to have period 2π. Dr. Mohammed Saheb Khesbak Page 43

11 Even and Odd Functions : Half-Range Expansions : Theorem 1 Dr. Mohammed Saheb Khesbak Page 44

12 Dr. Mohammed Saheb Khesbak Page 45

13 Example 1 Example 2 Dr. Mohammed Saheb Khesbak Page 46

14 Dr. Mohammed Saheb Khesbak Page 47

15 Half-Range Expansions: Half range expansions are Fourier series. We want to represent f(x) in Fig 267a by a Fourier series. Dr. Mohammed Saheb Khesbak Page 48

16 Dr. Mohammed Saheb Khesbak Page 49

17 Dr. Mohammed Saheb Khesbak Page 50

18 Dr. Mohammed Saheb Khesbak Page 51

19 Fourier Series Summary and Notes: Dr. Mohammed Saheb Khesbak Page 52

20 Review of integration by parts: Dr. Mohammed Saheb Khesbak Page 53

21 EXAMPLE 2 Find Dr. Mohammed Saheb Khesbak Page 54

22 EXAMPLE 3: Thus; EXAMPLE 4: Dr. Mohammed Saheb Khesbak Page 55

23 Then; Dr. Mohammed Saheb Khesbak Page 56

24 Exercises and Examples Find the Fourier series expansion. Dr. Mohammed Saheb Khesbak Page 57

25 eq (a) Now; we use the Integration by parts method eq (b) Using Integration By Parts again Dr. Mohammed Saheb Khesbak Page 58

26 Substituting in equation (b0 and (a) to get ; Dr. Mohammed Saheb Khesbak Page 59

27 eq (c) Substituting in to equation (c), get; Dr. Mohammed Saheb Khesbak Page 60

28 Home Work1: Show that the Fourier Series expansion of x 3 is: Home Work2: ANSWER:,, Example 3 : Find the F.S. expansion for ; Solution: X is an even function, so Dr. Mohammed Saheb Khesbak Page 61

29 Since the function is even and the sine is odd, then b n =0. It will be shown in details below; Dr. Mohammed Saheb Khesbak Page 62

30 Home Work3: Find the Fourier Series Expansion of the function: Answer: Example 4: Find the F.S. expansion for ; Dr. Mohammed Saheb Khesbak Page 63

31 Home Work4: Find the Fourier Series Expansion of the function: Answer Dr. Mohammed Saheb Khesbak Page 64

32 Exercises: 1- Find the Fourier series expansion for the periodic function f(t) in Fig Find the half range Fourier series expansion for the non-periodic function m(t) in Fig.2. Fig ρ 2- f(t) 4 t Fig.2 4 m(t) 2 t 3- Find the Fourier series expansion for the periodic function f(t) in Fig Find the half range Fourier series expansion for the non-periodic function m(t) in Fig.4. 1 f(t) 4 m(t) - 4 Fig.3 ρ 2 4 t Fig.4 2 t 5- Find the Fourier series expansion for the periodic function f(t) in Fig Find the half range Fourier series expansion for the non-periodic function m(t) in Fig.6. Fig ρ 1- f(t) 2 t -4 2 m(t) t Fig.6 Dr. Mohammed Saheb Khesbak Page 65

33 Fourier Transform Let f(t) be the time domain non-periodic function. Then the frequency domain Fourier transform FT (exponential form) corresponding function is ( ) ( ) While the Inverse Fourier Transform (IFT) is defined as; Example: ( ) ( ) Find the FT of f(t)=1 Solution: ( ) [ ] ( ) ( ) Example: Find the FT of ( ) { where a is a constant Solution: ( ) ( ) Dr. Mohammed Saheb Khesbak Page 66

34 ( ) ( ) [ ( ) ] ( ) Exercises: 9- ( ) 10- ( ) Dr. Mohammed Saheb Khesbak Page 67

35 Some Useful Identities Dr. Mohammed Saheb Khesbak Page 68

36 Some Useful Integrations Dr. Mohammed Saheb Khesbak Page 69

37 Dr. Mohammed Saheb Khesbak Page 70

3 rd class Mech. Eng. Dept. hamdiahmed.weebly.com Fourier Series

3 rd class Mech. Eng. Dept. hamdiahmed.weebly.com Fourier Series Definition 1 Fourier Series A function f is said to be piecewise continuous on [a, b] if there exists finitely many points a = x 1 < x 2

More information

in a given order. Each of and so on represents a number. These are the terms of the sequence. For example the sequence

in a given order. Each of and so on represents a number. These are the terms of the sequence. For example the sequence INFINITE SEQUENCES AND SERIES Infinite series sometimes have a finite sum, as in Other infinite series do not have a finite sum, as with The sum of the first few terms gets larger and larger as we add

More information

LECTURE TWO BLOCK DIAGRAM REDUCTION

LECTURE TWO BLOCK DIAGRAM REDUCTION 3rd Yearomputer ommunication EngineeringU ontrol Theory LETUE TWO BLOK DIAGAM EDUTION Block diagram is a pictorial representation of a control system showing interrelation between the transfer function

More information

Discrete State Space Models

Discrete State Space Models Discrete State Space Models In this lecture we will discuss the relation between transfer function and state space model for a discrete time system and various standard or canonical state variable models.

More information

CHAPTER 4 FOURIER SERIES S A B A R I N A I S M A I L

CHAPTER 4 FOURIER SERIES S A B A R I N A I S M A I L CHAPTER 4 FOURIER SERIES 1 S A B A R I N A I S M A I L Outline Introduction of the Fourier series. The properties of the Fourier series. Symmetry consideration Application of the Fourier series to circuit

More information

f (t) K(t, u) d t. f (t) K 1 (t, u) d u. Integral Transform Inverse Fourier Transform

f (t) K(t, u) d t. f (t) K 1 (t, u) d u. Integral Transform Inverse Fourier Transform Integral Transforms Massoud Malek An integral transform maps an equation from its original domain into another domain, where it might be manipulated and solved much more easily than in the original domain.

More information

Stability Analysis Techniques

Stability Analysis Techniques Stability Analysis Techniques In this section the stability analysis techniques for the Linear Time-Invarient (LTI) discrete system are emphasized. In general the stability techniques applicable to LTI

More information

Examples of the Fourier Theorem (Sect. 10.3). The Fourier Theorem: Continuous case.

Examples of the Fourier Theorem (Sect. 10.3). The Fourier Theorem: Continuous case. s of the Fourier Theorem (Sect. 1.3. The Fourier Theorem: Continuous case. : Using the Fourier Theorem. The Fourier Theorem: Piecewise continuous case. : Using the Fourier Theorem. The Fourier Theorem:

More information

multiply both sides of eq. by a and projection overlap

multiply both sides of eq. by a and projection overlap Fourier Series n x n x f xa ancos bncos n n periodic with period x consider n, sin x x x March. 3, 7 Any function with period can be represented with a Fourier series Examples (sawtooth) (square wave)

More information

PHYS 502 Lecture 3: Fourier Series

PHYS 502 Lecture 3: Fourier Series PHYS 52 Lecture 3: Fourier Series Fourier Series Introduction In mathematics, a Fourier series decomposes periodic functions or periodic signals into the sum of a (possibly infinite) set of simple oscillating

More information

Exercise 11. Isao Sasano

Exercise 11. Isao Sasano Exercise Isao Sasano Exercise Calculate the value of the following series by using the Parseval s equality for the Fourier series of f(x) x on the range [, π] following the steps ()-(5). () Calculate the

More information

Chapter 4 Sequences and Series

Chapter 4 Sequences and Series Chapter 4 Sequences and Series 4.1 Sequence Review Sequence: a set of elements (numbers or letters or a combination of both). The elements of the set all follow the same rule (logical progression). The

More information

Fourier Transform in Image Processing. CS/BIOEN 6640 U of Utah Guido Gerig (slides modified from Marcel Prastawa 2012)

Fourier Transform in Image Processing. CS/BIOEN 6640 U of Utah Guido Gerig (slides modified from Marcel Prastawa 2012) Fourier Transform in Image Processing CS/BIOEN 6640 U of Utah Guido Gerig (slides modified from Marcel Prastawa 2012) Basis Decomposition Write a function as a weighted sum of basis functions f ( x) wibi(

More information

14 Fourier analysis. Read: Boas Ch. 7.

14 Fourier analysis. Read: Boas Ch. 7. 14 Fourier analysis Read: Boas Ch. 7. 14.1 Function spaces A function can be thought of as an element of a kind of vector space. After all, a function f(x) is merely a set of numbers, one for each point

More information

Fourier series

Fourier series 11.1-11.2. Fourier series Yurii Lyubarskii, NTNU September 5, 2016 Periodic functions Function f defined on the whole real axis has period p if Properties f (t) = f (t + p) for all t R If f and g have

More information

Limits of Exponential, Logarithmic, and Trigonometric Functions

Limits of Exponential, Logarithmic, and Trigonometric Functions Limits of Exponential, Logarithmic, and Trigonometric Functions by CHED on January 02, 2018 lesson duration of 3 minutes under Basic Calculus generated on January 02, 2018 at 01:54 am Tags: Limits and

More information

Fourier Integral. Dr Mansoor Alshehri. King Saud University. MATH204-Differential Equations Center of Excellence in Learning and Teaching 1 / 22

Fourier Integral. Dr Mansoor Alshehri. King Saud University. MATH204-Differential Equations Center of Excellence in Learning and Teaching 1 / 22 Dr Mansoor Alshehri King Saud University MATH4-Differential Equations Center of Excellence in Learning and Teaching / Fourier Cosine and Sine Series Integrals The Complex Form of Fourier Integral MATH4-Differential

More information

12.7 Heat Equation: Modeling Very Long Bars.

12.7 Heat Equation: Modeling Very Long Bars. 568 CHAP. Partial Differential Equations (PDEs).7 Heat Equation: Modeling Very Long Bars. Solution by Fourier Integrals and Transforms Our discussion of the heat equation () u t c u x in the last section

More information

1st Year-Computer Communication Engineering-RUC. 4- P-N Junction

1st Year-Computer Communication Engineering-RUC. 4- P-N Junction 4- P-N Junction We begin our study of semiconductor devices with the junction for three reasons. (1) The device finds application in many electronic systems, e.g., in adapters that charge the batteries

More information

Math 56 Homework 5 Michael Downs

Math 56 Homework 5 Michael Downs 1. (a) Since f(x) = cos(6x) = ei6x 2 + e i6x 2, due to the orthogonality of each e inx, n Z, the only nonzero (complex) fourier coefficients are ˆf 6 and ˆf 6 and they re both 1 2 (which is also seen from

More information

FOURIER SERIES. Chapter Introduction

FOURIER SERIES. Chapter Introduction Chapter 1 FOURIER SERIES 1.1 Introduction Fourier series introduced by a French physicist Joseph Fourier (1768-1830), is a mathematical tool that converts some specific periodic signals into everlasting

More information

Lecture 2: Series Expansion

Lecture 2: Series Expansion Lecture 2: Series Expansion Key points Maclaurin series : For, Taylor expansion: Maple commands series convert taylor, Student[NumericalAnalysis][Taylor] 1 Maclaurin series of elementary functions for

More information

MATHEMATICS Lecture. 4 Chapter.8 TECHNIQUES OF INTEGRATION By Dr. Mohammed Ramidh

MATHEMATICS Lecture. 4 Chapter.8 TECHNIQUES OF INTEGRATION By Dr. Mohammed Ramidh MATHEMATICS Lecture. 4 Chapter.8 TECHNIQUES OF INTEGRATION By TECHNIQUES OF INTEGRATION OVERVIEW The Fundamental Theorem connects antiderivatives and the definite integral. Evaluating the indefinite integral,

More information

More on Fourier Series

More on Fourier Series More on Fourier Series R. C. Trinity University Partial Differential Equations Lecture 6.1 New Fourier series from old Recall: Given a function f (x, we can dilate/translate its graph via multiplication/addition,

More information

Today s lecture. The Fourier transform. Sampling, aliasing, interpolation The Fast Fourier Transform (FFT) algorithm

Today s lecture. The Fourier transform. Sampling, aliasing, interpolation The Fast Fourier Transform (FFT) algorithm Today s lecture The Fourier transform What is it? What is it useful for? What are its properties? Sampling, aliasing, interpolation The Fast Fourier Transform (FFT) algorithm Jean Baptiste Joseph Fourier

More information

Chapter 17. Fourier series

Chapter 17. Fourier series Chapter 17. Fourier series We have already met the simple periodic functions, of the form cos(ωt θ). In this chapter we shall look at periodic functions of more complicated nature. 1. The basic results

More information

THE UNIVERSITY OF WESTERN ONTARIO. Applied Mathematics 375a Instructor: Matt Davison. Final Examination December 14, :00 12:00 a.m.

THE UNIVERSITY OF WESTERN ONTARIO. Applied Mathematics 375a Instructor: Matt Davison. Final Examination December 14, :00 12:00 a.m. THE UNIVERSITY OF WESTERN ONTARIO London Ontario Applied Mathematics 375a Instructor: Matt Davison Final Examination December 4, 22 9: 2: a.m. 3 HOURS Name: Stu. #: Notes: ) There are 8 question worth

More information

Integration. Tuesday, December 3, 13

Integration. Tuesday, December 3, 13 4 Integration 4.3 Riemann Sums and Definite Integrals Objectives n Understand the definition of a Riemann sum. n Evaluate a definite integral using properties of definite integrals. 3 Riemann Sums 4 Riemann

More information

Chapter Two. Integers ASSIGNMENT EXERCISES H I J 8. 4 K C B

Chapter Two. Integers ASSIGNMENT EXERCISES H I J 8. 4 K C B Chapter Two Integers ASSIGNMENT EXERCISES. +1 H 4. + I 6. + J 8. 4 K 10. 5 C 1. 6 B 14. 5, 0, 8, etc. 16. 0 18. For any integer, there is always at least one smaller 0. 0 >. 5 < 8 4. 1 < 8 6. 8 8 8. 0

More information

Review Sol. of More Long Answer Questions

Review Sol. of More Long Answer Questions Review Sol. of More Long Answer Questions 1. Solve the integro-differential equation t y (t) e t v y(v)dv = t; y()=. (1) Solution. The key is to recognize the convolution: t e t v y(v) dv = e t y. () Now

More information

10.2-3: Fourier Series.

10.2-3: Fourier Series. 10.2-3: Fourier Series. 10.2-3: Fourier Series. O. Costin: Fourier Series, 10.2-3 1 Fourier series are very useful in representing periodic functions. Examples of periodic functions. A function is periodic

More information

17 Source Problems for Heat and Wave IB- VPs

17 Source Problems for Heat and Wave IB- VPs 17 Source Problems for Heat and Wave IB- VPs We have mostly dealt with homogeneous equations, homogeneous b.c.s in this course so far. Recall that if we have non-homogeneous b.c.s, then we want to first

More information

UNIVERSITI MALAYSIA PERLIS

UNIVERSITI MALAYSIA PERLIS UNIVERSITI MALAYSIA PERLIS SCHOOL OF COMPUTER & COMMUNICATIONS ENGINEERING EKT 230 SIGNALS AND SYSTEMS LABORATORY MODULE LAB 5 : LAPLACE TRANSFORM & Z-TRANSFORM 1 LABORATORY OUTCOME Ability to describe

More information

Signals and Systems Lecture (S2) Orthogonal Functions and Fourier Series March 17, 2008

Signals and Systems Lecture (S2) Orthogonal Functions and Fourier Series March 17, 2008 Signals and Systems Lecture (S) Orthogonal Functions and Fourier Series March 17, 008 Today s Topics 1. Analogy between functions of time and vectors. Fourier series Take Away Periodic complex exponentials

More information

23.4. Convergence. Introduction. Prerequisites. Learning Outcomes

23.4. Convergence. Introduction. Prerequisites. Learning Outcomes Convergence 3.4 Introduction In this Section we examine, briefly, the convergence characteristics of a Fourier series. We have seen that a Fourier series can be found for functions which are not necessarily

More information

Computer Problems for Fourier Series and Transforms

Computer Problems for Fourier Series and Transforms Computer Problems for Fourier Series and Transforms 1. Square waves are frequently used in electronics and signal processing. An example is shown below. 1 π < x < 0 1 0 < x < π y(x) = 1 π < x < 2π... and

More information

11.10a Taylor and Maclaurin Series

11.10a Taylor and Maclaurin Series 11.10a 1 11.10a Taylor and Maclaurin Series Let y = f(x) be a differentiable function at x = a. In first semester calculus we saw that (1) f(x) f(a)+f (a)(x a), for all x near a The right-hand side of

More information

TS Method Summary. T k (x,y j 1 ) f(x j 1,y j 1 )+ 2 f (x j 1,y j 1 ) + k 1

TS Method Summary. T k (x,y j 1 ) f(x j 1,y j 1 )+ 2 f (x j 1,y j 1 ) + k 1 TS Method Summary Let T k (x,y j 1 ) denote the first k +1 terms of the Taylor series expanded about the discrete approximation, (x j 1,y j 1 ), and ẑ k,j (x) be the polynomial approximation (to y(x))

More information

Chapter 10: Partial Differential Equations

Chapter 10: Partial Differential Equations 1.1: Introduction Chapter 1: Partial Differential Equations Definition: A differential equations whose dependent variable varies with respect to more than one independent variable is called a partial differential

More information

06EC44-Signals and System Chapter Fourier Representation for four Signal Classes

06EC44-Signals and System Chapter Fourier Representation for four Signal Classes Chapter 5.1 Fourier Representation for four Signal Classes 5.1.1Mathematical Development of Fourier Transform If the period is stretched without limit, the periodic signal no longer remains periodic but

More information

23.6. The Complex Form. Introduction. Prerequisites. Learning Outcomes

23.6. The Complex Form. Introduction. Prerequisites. Learning Outcomes he Complex Form 3.6 Introduction In this Section we show how a Fourier series can be expressed more concisely if we introduce the complex number i where i =. By utilising the Euler relation: e iθ cos θ

More information

MATH 425, HOMEWORK 5, SOLUTIONS

MATH 425, HOMEWORK 5, SOLUTIONS MATH 425, HOMEWORK 5, SOLUTIONS Exercise (Uniqueness for the heat equation on R) Suppose that the functions u, u 2 : R x R t R solve: t u k 2 xu = 0, x R, t > 0 u (x, 0) = φ(x), x R and t u 2 k 2 xu 2

More information

(a) For an accumulation point a of S, the number l is the limit of f(x) as x approaches a, or lim x a f(x) = l, iff

(a) For an accumulation point a of S, the number l is the limit of f(x) as x approaches a, or lim x a f(x) = l, iff Chapter 4: Functional Limits and Continuity Definition. Let S R and f : S R. (a) For an accumulation point a of S, the number l is the limit of f(x) as x approaches a, or lim x a f(x) = l, iff ε > 0, δ

More information

Notes 07 largely plagiarized by %khc

Notes 07 largely plagiarized by %khc Notes 07 largely plagiarized by %khc Warning This set of notes covers the Fourier transform. However, i probably won t talk about everything here in section; instead i will highlight important properties

More information

Polynomial Chaos and Karhunen-Loeve Expansion

Polynomial Chaos and Karhunen-Loeve Expansion Polynomial Chaos and Karhunen-Loeve Expansion 1) Random Variables Consider a system that is modeled by R = M(x, t, X) where X is a random variable. We are interested in determining the probability of the

More information

Solutions - Homework # 3

Solutions - Homework # 3 ECE-34: Signals and Systems Summer 23 PROBLEM One period of the DTFS coefficients is given by: X[] = (/3) 2, 8. Solutions - Homewor # 3 a) What is the fundamental period 'N' of the time-domain signal x[n]?

More information

Modern Methods of Data Analysis - WS 07/08

Modern Methods of Data Analysis - WS 07/08 Modern Methods of Data Analysis Lecture VIc (19.11.07) Contents: Maximum Likelihood Fit Maximum Likelihood (I) Assume N measurements of a random variable Assume them to be independent and distributed according

More information

ORDINARY DIFFERENTIAL EQUATIONS

ORDINARY DIFFERENTIAL EQUATIONS ORDINARY DIFFERENTIAL EQUATIONS GABRIEL NAGY Mathematics Department, Michigan State University, East Lansing, MI, 4884 NOVEMBER 9, 7 Summary This is an introduction to ordinary differential equations We

More information

Summary of basic probability theory Math 218, Mathematical Statistics D Joyce, Spring 2016

Summary of basic probability theory Math 218, Mathematical Statistics D Joyce, Spring 2016 8. For any two events E and F, P (E) = P (E F ) + P (E F c ). Summary of basic probability theory Math 218, Mathematical Statistics D Joyce, Spring 2016 Sample space. A sample space consists of a underlying

More information

FOURIER SERIES, TRANSFORMS, AND BOUNDARY VALUE PROBLEMS

FOURIER SERIES, TRANSFORMS, AND BOUNDARY VALUE PROBLEMS fc FOURIER SERIES, TRANSFORMS, AND BOUNDARY VALUE PROBLEMS Second Edition J. RAY HANNA Professor Emeritus University of Wyoming Laramie, Wyoming JOHN H. ROWLAND Department of Mathematics and Department

More information

A Library of Functions

A Library of Functions LibraryofFunctions.nb 1 A Library of Functions Any study of calculus must start with the study of functions. Functions are fundamental to mathematics. In its everyday use the word function conveys to us

More information

JUST THE MATHS UNIT NUMBER DIFFERENTIATION APPLICATIONS 5 (Maclaurin s and Taylor s series) A.J.Hobson

JUST THE MATHS UNIT NUMBER DIFFERENTIATION APPLICATIONS 5 (Maclaurin s and Taylor s series) A.J.Hobson JUST THE MATHS UNIT NUMBER.5 DIFFERENTIATION APPLICATIONS 5 (Maclaurin s and Taylor s series) by A.J.Hobson.5. Maclaurin s series.5. Standard series.5.3 Taylor s series.5.4 Exercises.5.5 Answers to exercises

More information

Lecture 34. Fourier Transforms

Lecture 34. Fourier Transforms Lecture 34 Fourier Transforms In this section, we introduce the Fourier transform, a method of analyzing the frequency content of functions that are no longer τ-periodic, but which are defined over the

More information

7 PDES, FOURIER SERIES AND TRANSFORMS Last Updated: July 16, 2012

7 PDES, FOURIER SERIES AND TRANSFORMS Last Updated: July 16, 2012 Problem List 7.1 Fourier series expansion of absolute value function 7.2 Fourier series expansion of step function 7.3 Orthogonality of functions 7.4 Fourier transform of sinusoidal pulse 7.5 Introducing

More information

X b n sin nπx L. n=1 Fourier Sine Series Expansion. a n cos nπx L 2 + X. n=1 Fourier Cosine Series Expansion ³ L. n=1 Fourier Series Expansion

X b n sin nπx L. n=1 Fourier Sine Series Expansion. a n cos nπx L 2 + X. n=1 Fourier Cosine Series Expansion ³ L. n=1 Fourier Series Expansion 3 Fourier Series 3.1 Introduction Although it was not apparent in the early historical development of the method of separation of variables what we are about to do is the analog for function spaces of

More information

Lecture 16: Bessel s Inequality, Parseval s Theorem, Energy convergence

Lecture 16: Bessel s Inequality, Parseval s Theorem, Energy convergence Introductory lecture notes on Partial Differential Equations - c Anthony Peirce. ot to be copied, used, or revised without explicit written permission from the copyright owner. ecture 6: Bessel s Inequality,

More information

REVIEW FOR PRELIM 1 SOLUTIONS

REVIEW FOR PRELIM 1 SOLUTIONS REVIEW FOR PRELIM 1 SOLUTIONS MATH 1106, Spring 2017 Tutorial 9 Solutions Wednesday 02/22/17 Tutorial 9.1. Linear approximation (a) Let C(x) = 3x 2 + 200. (i) Use C (x) to approximate C when x = 1 and

More information

Module 9 : Numerical Relaying II : DSP Perspective

Module 9 : Numerical Relaying II : DSP Perspective Module 9 : Numerical Relaying II : DSP Perspective Lecture 32 : Fourier Analysis Objectives In this lecture, we will show that Trignometric fourier series is nothing but LS approximate of a periodic signal

More information

natural frequency of the spring/mass system is ω = k/m, and dividing the equation through by m gives

natural frequency of the spring/mass system is ω = k/m, and dividing the equation through by m gives 77 6. More on Fourier series 6.. Harmonic response. One of the main uses of Fourier series is to express periodic system responses to general periodic signals. For example, if we drive an undamped spring

More information

Chapter 8: Taylor s theorem and L Hospital s rule

Chapter 8: Taylor s theorem and L Hospital s rule Chapter 8: Taylor s theorem and L Hospital s rule Theorem: [Inverse Mapping Theorem] Suppose that a < b and f : [a, b] R. Given that f (x) > 0 for all x (a, b) then f 1 is differentiable on (f(a), f(b))

More information

Turbulent Flows. U (n) (m s 1 ) on the nth repetition of a turbulent flow experiment. CHAPTER 3: THE RANDOM NATURE OF TURBULENCE

Turbulent Flows. U (n) (m s 1 ) on the nth repetition of a turbulent flow experiment. CHAPTER 3: THE RANDOM NATURE OF TURBULENCE U (n) (m s ) 5 5 2 4 n Figure 3.: Sketch of the value U (n) of the random velocity variable U on the nth repetition of a turbulent flow experiment. (a) x (t) 2-2 (b) (c) x (t) 2-2 4 2 x (t) x (t) -2-4

More information

18.01 EXERCISES. Unit 3. Integration. 3A. Differentials, indefinite integration. 3A-1 Compute the differentials df(x) of the following functions.

18.01 EXERCISES. Unit 3. Integration. 3A. Differentials, indefinite integration. 3A-1 Compute the differentials df(x) of the following functions. 8. EXERCISES Unit 3. Integration 3A. Differentials, indefinite integration 3A- Compute the differentials df(x) of the following functions. a) d(x 7 + sin ) b) d x c) d(x 8x + 6) d) d(e 3x sin x) e) Express

More information

The One-Dimensional Heat Equation

The One-Dimensional Heat Equation The One-Dimensional Heat Equation R. C. Trinity University Partial Differential Equations February 24, 2015 Introduction The heat equation Goal: Model heat (thermal energy) flow in a one-dimensional object

More information

MA 201: Differentiation and Integration of Fourier Series Applications of Fourier Series Lecture - 10

MA 201: Differentiation and Integration of Fourier Series Applications of Fourier Series Lecture - 10 MA 201: Differentiation and Integration of Fourier Series Applications of Fourier Series ecture - 10 Fourier Series: Orthogonal Sets We begin our treatment with some observations: For m,n = 1,2,3,... cos

More information

FOURIER TRANSFORMS. At, is sometimes taken as 0.5 or it may not have any specific value. Shifting at

FOURIER TRANSFORMS. At, is sometimes taken as 0.5 or it may not have any specific value. Shifting at Chapter 2 FOURIER TRANSFORMS 2.1 Introduction The Fourier series expresses any periodic function into a sum of sinusoids. The Fourier transform is the extension of this idea to non-periodic functions by

More information

Assignment 3 Solutions

Assignment 3 Solutions Assignment Solutions Networks and systems August 8, 7. Consider an LTI system with transfer function H(jw) = input is sin(t + π 4 ), what is the output? +jw. If the Solution : C For an LTI system with

More information

Math 425 Fall All About Zero

Math 425 Fall All About Zero Math 425 Fall 2005 All About Zero These notes supplement the discussion of zeros of analytic functions presented in 2.4 of our text, pp. 127 128. Throughout: Unless stated otherwise, f is a function analytic

More information

Appendix C: Recapitulation of Numerical schemes

Appendix C: Recapitulation of Numerical schemes Appendix C: Recapitulation of Numerical schemes August 31, 2009) SUMMARY: Certain numerical schemes of general use are regrouped here in order to facilitate implementations of simple models C1 The tridiagonal

More information

Maximum and Minimum Values section 4.1

Maximum and Minimum Values section 4.1 Maximum and Minimum Values section 4.1 Definition. Consider a function f on its domain D. (i) We say that f has absolute maximum at a point x 0 D if for all x D we have f(x) f(x 0 ). (ii) We say that f

More information

Mathematical Methods: Fourier Series. Fourier Series: The Basics

Mathematical Methods: Fourier Series. Fourier Series: The Basics 1 Mathematical Methods: Fourier Series Fourier Series: The Basics Fourier series are a method of representing periodic functions. It is a very useful and powerful tool in many situations. It is sufficiently

More information

Strauss PDEs 2e: Section Exercise 1 Page 1 of 6

Strauss PDEs 2e: Section Exercise 1 Page 1 of 6 Strauss PDEs 2e: Section 3 - Exercise Page of 6 Exercise Carefully derive the equation of a string in a medium in which the resistance is proportional to the velocity Solution There are two ways (among

More information

Fourier series. XE31EO2 - Pavel Máša. Electrical Circuits 2 Lecture1. XE31EO2 - Pavel Máša - Fourier Series

Fourier series. XE31EO2 - Pavel Máša. Electrical Circuits 2 Lecture1. XE31EO2 - Pavel Máša - Fourier Series Fourier series Electrical Circuits Lecture - Fourier Series Filtr RLC defibrillator MOTIVATION WHAT WE CAN'T EXPLAIN YET Source voltage rectangular waveform Resistor voltage sinusoidal waveform - Fourier

More information

In this worksheet we will use the eigenfunction expansion to solve nonhomogeneous equation.

In this worksheet we will use the eigenfunction expansion to solve nonhomogeneous equation. Eigen Function Expansion and Applications. In this worksheet we will use the eigenfunction expansion to solve nonhomogeneous equation. a/ The theory. b/ Example: Solving the Euler equation in two ways.

More information

Name: Solutions Exam 4

Name: Solutions Exam 4 Instructions. Answer each of the questions on your own paper. Put your name on each page of your paper. Be sure to show your work so that partial credit can be adequately assessed. Credit will not be given

More information

GATE EE Topic wise Questions SIGNALS & SYSTEMS

GATE EE Topic wise Questions SIGNALS & SYSTEMS www.gatehelp.com GATE EE Topic wise Questions YEAR 010 ONE MARK Question. 1 For the system /( s + 1), the approximate time taken for a step response to reach 98% of the final value is (A) 1 s (B) s (C)

More information

23 Elements of analytic ODE theory. Bessel s functions

23 Elements of analytic ODE theory. Bessel s functions 23 Elements of analytic ODE theory. Bessel s functions Recall I am changing the variables) that we need to solve the so-called Bessel s equation 23. Elements of analytic ODE theory Let x 2 u + xu + x 2

More information

MA6351-TRANSFORMS AND PARTIAL DIFFERENTIAL EQUATIONS. Question Bank. Department of Mathematics FATIMA MICHAEL COLLEGE OF ENGINEERING & TECHNOLOGY

MA6351-TRANSFORMS AND PARTIAL DIFFERENTIAL EQUATIONS. Question Bank. Department of Mathematics FATIMA MICHAEL COLLEGE OF ENGINEERING & TECHNOLOGY MA6351-TRANSFORMS AND PARTIAL DIFFERENTIAL EQUATIONS Question Bank Department of Mathematics FATIMA MICHAEL COLLEGE OF ENGINEERING & TECHNOLOGY MADURAI 625 020, Tamilnadu, India 1. Define PDE and Order

More information

Time-Frequency Analysis

Time-Frequency Analysis Time-Frequency Analysis Basics of Fourier Series Philippe B. aval KSU Fall 015 Philippe B. aval (KSU) Fourier Series Fall 015 1 / 0 Introduction We first review how to derive the Fourier series of a function.

More information

CODE: GR17A1003 GR 17 SET - 1

CODE: GR17A1003 GR 17 SET - 1 SET - 1 I B. Tech II Semester Regular Examinations, May 18 Transform Calculus and Fourier Series (Common to all branches) Time: 3 hours Max Marks: 7 PART A Answer ALL questions. All questions carry equal

More information

X(t)e 2πi nt t dt + 1 T

X(t)e 2πi nt t dt + 1 T HOMEWORK 31 I) Use the Fourier-Euler formulae to show that, if X(t) is T -periodic function which admits a Fourier series decomposition X(t) = n= c n exp (πi n ) T t, then (1) if X(t) is even c n are all

More information

MATH 241 Practice Second Midterm Exam - Fall 2012

MATH 241 Practice Second Midterm Exam - Fall 2012 MATH 41 Practice Second Midterm Exam - Fall 1 1. Let f(x = { 1 x for x 1 for 1 x (a Compute the Fourier sine series of f(x. The Fourier sine series is b n sin where b n = f(x sin dx = 1 = (1 x cos = 4

More information

1. Decide for each of the following expressions: Is it a function? If so, f is a function. (i) Domain: R. Codomain: R. Range: R. (iii) Yes surjective.

1. Decide for each of the following expressions: Is it a function? If so, f is a function. (i) Domain: R. Codomain: R. Range: R. (iii) Yes surjective. Homework 2 2/14/2018 SOLUTIONS Exercise 6. 1. Decide for each of the following expressions: Is it a function? If so, (i) what is its domain, codomain, and image? (iii) is it surjective? (ii) is it injective?

More information

Solutions to Assignment 7

Solutions to Assignment 7 MTHE 237 Fall 215 Solutions to Assignment 7 Problem 1 Show that the Laplace transform of cos(αt) satisfies L{cosαt = s s 2 +α 2 L(cos αt) e st cos(αt)dt A s α e st sin(αt)dt e stsin(αt) α { e stsin(αt)

More information

MATH 5640: Fourier Series

MATH 5640: Fourier Series MATH 564: Fourier Series Hung Phan, UMass Lowell September, 8 Power Series A power series in the variable x is a series of the form a + a x + a x + = where the coefficients a, a,... are real or complex

More information

Ph 219b/CS 219b. Exercises Due: Wednesday 4 December 2013

Ph 219b/CS 219b. Exercises Due: Wednesday 4 December 2013 1 Ph 219b/CS 219b Exercises Due: Wednesday 4 December 2013 4.1 The peak in the Fourier transform In the period finding algorithm we prepared the periodic state A 1 1 x 0 + jr, (1) A j=0 where A is the

More information

Communication Signals (Haykin Sec. 2.4 and Ziemer Sec Sec. 2.4) KECE321 Communication Systems I

Communication Signals (Haykin Sec. 2.4 and Ziemer Sec Sec. 2.4) KECE321 Communication Systems I Communication Signals (Haykin Sec..4 and iemer Sec...4-Sec..4) KECE3 Communication Systems I Lecture #3, March, 0 Prof. Young-Chai Ko 년 3 월 일일요일 Review Signal classification Phasor signal and spectra Representation

More information

Partition of Integers into Distinct Summands with Upper Bounds. Partition of Integers into Even Summands. An Example

Partition of Integers into Distinct Summands with Upper Bounds. Partition of Integers into Even Summands. An Example Partition of Integers into Even Summands We ask for the number of partitions of m Z + into positive even integers The desired number is the coefficient of x m in + x + x 4 + ) + x 4 + x 8 + ) + x 6 + x

More information

Dr. Abdulla Eid. Section 3.8 Derivative of the inverse function and logarithms 3 Lecture. Dr. Abdulla Eid. MATHS 101: Calculus I. College of Science

Dr. Abdulla Eid. Section 3.8 Derivative of the inverse function and logarithms 3 Lecture. Dr. Abdulla Eid. MATHS 101: Calculus I. College of Science Section 3.8 Derivative of the inverse function and logarithms 3 Lecture College of Science MATHS 101: Calculus I (University of Bahrain) Logarithmic Differentiation 1 / 19 Topics 1 Inverse Functions (1

More information

8.5 Taylor Polynomials and Taylor Series

8.5 Taylor Polynomials and Taylor Series 8.5. TAYLOR POLYNOMIALS AND TAYLOR SERIES 50 8.5 Taylor Polynomials and Taylor Series Motivating Questions In this section, we strive to understand the ideas generated by the following important questions:

More information

Problem 1. Arfken

Problem 1. Arfken All Arfken problems are reproduced at the end of this assignment Problem 1. Arfken 11.2.11. Problem 2. (a) Do Arfken 11.3.3 (b) The integral Integrals 4 3i 3+4i (x 2 iy 2 ) dz (1) is not defined without

More information

ENGIN 211, Engineering Math. Fourier Series and Transform

ENGIN 211, Engineering Math. Fourier Series and Transform ENGIN 11, Engineering Math Fourier Series and ransform 1 Periodic Functions and Harmonics f(t) Period: a a+ t Frequency: f = 1 Angular velocity (or angular frequency): ω = ππ = π Such a periodic function

More information

Ph 219b/CS 219b. Exercises Due: Wednesday 11 February 2009

Ph 219b/CS 219b. Exercises Due: Wednesday 11 February 2009 1 Ph 219b/CS 219b Exercises Due: Wednesday 11 February 2009 5.1 The peak in the Fourier transform In the period finding algorithm we prepared the periodic state A 1 1 x 0 + jr, (1) A j=0 where A is the

More information

Notes on Fourier Series and Integrals Fourier Series

Notes on Fourier Series and Integrals Fourier Series Notes on Fourier Series and Integrals Fourier Series et f(x) be a piecewise linear function on [, ] (This means that f(x) may possess a finite number of finite discontinuities on the interval). Then f(x)

More information

a n b n ) n N is convergent with b n is convergent.

a n b n ) n N is convergent with b n is convergent. 32 Series Let s n be the n-th partial sum of n N and let t n be the n-th partial sum of n N. For k n we then have n n s n s k = a i a i = t n t k. i=k+1 i=k+1 Since t n n N is convergent by assumption,

More information

Correlation Functions and Fourier Transforms

Correlation Functions and Fourier Transforms Correlation Functions and Fourier Transforms Introduction The importance of these functions in condensed matter physics Correlation functions (aside convolution) Fourier transforms The diffraction pattern

More information

Checking the Radioactive Decay Euler Algorithm

Checking the Radioactive Decay Euler Algorithm Lecture 2: Checking Numerical Results Review of the first example: radioactive decay The radioactive decay equation dn/dt = N τ has a well known solution in terms of the initial number of nuclei present

More information

δ Substituting into the differential equation gives: x i+1 x i δ f(t i,x i ) (3)

δ Substituting into the differential equation gives: x i+1 x i δ f(t i,x i ) (3) Solving Differential Equations Numerically Differential equations are ubiquitous in Physics since the laws of nature often take on a simple form when expressed in terms of infinitesimal changes of the

More information

Do not turn over until you are told to do so by the Invigilator.

Do not turn over until you are told to do so by the Invigilator. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 216 17 INTRODUCTION TO NUMERICAL ANALYSIS MTHE612B Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions.

More information

Math 54: Mock Final. December 11, y y 2y = cos(x) sin(2x). The auxiliary equation for the corresponding homogeneous problem is

Math 54: Mock Final. December 11, y y 2y = cos(x) sin(2x). The auxiliary equation for the corresponding homogeneous problem is Name: Solutions Math 54: Mock Final December, 25 Find the general solution of y y 2y = cos(x) sin(2x) The auxiliary equation for the corresponding homogeneous problem is r 2 r 2 = (r 2)(r + ) = r = 2,

More information

Ch.11 The Discrete-Time Fourier Transform (DTFT)

Ch.11 The Discrete-Time Fourier Transform (DTFT) EE2S11 Signals and Systems, part 2 Ch.11 The Discrete-Time Fourier Transform (DTFT Contents definition of the DTFT relation to the -transform, region of convergence, stability frequency plots convolution

More information