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

Size: px
Start display at page:

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

Transcription

1 CHAPTER 4 FOURIER SERIES 1 S A B A R I N A I S M A I L

2 Outline Introduction of the Fourier series. The properties of the Fourier series. Symmetry consideration Application of the Fourier series to circuit analysis. 2

3 Fourier Series While studying heat flow, Fourier discovered that a nonsinusoidal periodic function can be expressed as an infinite sum of sinusoidal functions. Recall that a periodic function satisfies: f t f t nt Where n is an integer and T is the period of the function. 3

4 Trigonometric Fourier Series According to the Fourier theorem, any practical periodic function of frequency ω can be expressed as an infinite sum of sine or cosine functions. f t a a cos n t b sin n t n n dc n1 ac Where ω =2/T is called the fundamental frequency in radians per second. Its resolves the function into a dc component and an ac component. The constants a n and b n are called the Fourier coefficients. 4

5 Cont d To find a : a 1 T T o f t dt To find a n : To find b n : T 2 an f tcos ntdt T o T 2 b n f t sin ntdt T o 5

6 Harmonics The sinusoid sin(nω t) or cos(nω t) is called the n th harmonic of f(t). If n is odd, the function is called the odd harmonic. If n is even, the function is called the even harmonic. For a function to be expressed as a Fourier series it must meet certain requirements: 1. f(t) must be single valued everywhere. 2. It must have a finite number of finite discontinuities per period. 3. It must have a finite number of maximum and minima per period. 6

7 Cont d The last requirement is that t T t f t dt for anyt These conditions are called the Dirichlet conditions. A major task in Fourier series is the determination of the Fourier coefficients. The process of finding these is called Fourier analysis. 7

8 Example Find the Fourier series of the square wave given in figure below. 8

9 Amplitude-Phase Form An alternative is called the amplitude phase form: Where: f t a A cos n t n n n1 A a b tan n n n n The frequency spectrum of a signal consists of the plots of amplitude and phases of the harmonics versus frequency b a n n 9

10 Symmetry Considerations The series consists of only sine terms. If the series contains only sine or cosine, it is considered to have a certain symmetry. There is a technique for identifying the three symmetries that exist, even, odd, and halfwave. 1

11 Even Symmetry The function is symmetrical about the vertical axis: f t f t 11 A main property of an even function is that: T/2 T/2 f t dt 2 f t dt e T /2 e

12 Cont d The Fourier coefficients for an even function become: T /2 2 a f tdt T T /2 Its become a Fourier cosine series. 4 an f tcos ntdt T b n 12

13 Odd Symmetry A function is said to be odd if its plot is antisymmetrical about the vertical axis. f t f t Examples; t, t 3, and sint An add function has this major characteristic: T /2 T /2 f t dt 13

14 Cont d This comes about because the integration from T/2 to is the negative of the integration from to T/2 The coefficients are: This gives the Fourier sine series. a a T /2 4 b n f t sin ntdt T n 14

15 Properties of Odd and Even 1. The product of two even functions is also an even function. 2. The product of two odd functions is an even function. 3. The product of an even function and an odd function is an odd function. 4. The sum (or difference) of two even functions is also an even function. 5. The sum (or difference) of two odd functions is an odd function. 6. The sum (or difference) of an even function and an odd function is neither even nor odd. 15

16 Half Wave Symmetry Half wave symmetry compares one half of a period to the other half. T f t f t 2 16 This means that each half-cycle is the mirror image of the next halfcycle.

17 Cont d The Fourier coefficients for the half wave symmetric function are: a a n 4 T T /2 f t cos n tdt for n odd for n even b n 4 T T /2 f t sin n tdt for n odd for n even Note that the half wave symmetric functions only contain the odd harmonics. 17

18 Example 18 Find the Fourier series expansion of f(t) in Figure below.

19 Exercise 19 Find the Fourier series expansion of f(t) in Figure below.

20 2 Common Functions

21 21 Cont d

22 Circuit Applications Fourier analysis can be helpful in analyzing circuits driven by non-sinusoidal waves. The procedure involves four steps: 1. Express the excitation as a Fourier series. 2. Transform the circuit from the time domain to the frequency domain. 3. Find the response of the dc and ac components in the Fourier series. 4. Add the individual dc and ac responses using the superposition principle. 22

23 Example A Fourier series expanded periodic voltage source. v t V V cos n t n n n1 23

24 On inspection, this can be represented by a dc source and a set of sinusoidal sources connected in series. Each source would have its own amplitude and frequency. Each source can be analyzed on its own by turning off the others. For each source, the circuit can be transformed to frequency domain and solved for the voltage and currents. The results will have to be transformed back to the time domain before being added back together by way of the superposition principle. 24

25 25

26 Example 26 Find the response v o (t) of the given circuit if v s (t) is apply to the circuit.

27 Average Power and RMS Fourier analysis can be applied to find average power and RMS values. To find the average power absorbed by a circuit due to a periodic excitation, we write the voltage and current in amplitude-phase form: v t V V cos n t dc n n n1 i t I I cos m t dc m m m1 27

28 For periodic voltages and currents, the total average power is the sum of the average powers in each harmonically related voltage and current: 1 P V I V I cos dc dc n n n n 2 n1 A RMS value is: 1 F a a b rms n n 2 n1 28 Parseval s theorem defines the power dissipated in a hypothetical 1Ω resistor 1 p F a a b rms n n 2 n1

29 Example Find the RMS value of the periodic current 29 i( t) 8 3cos2t 2sin 2t 15cos4t 1sin 4tA

30 Exponential Fourier Series A compact way of expressing the Fourier series is to put it in exponential form. This is done by representing the sine and cosine functions in exponential form using Euler s law. 1 cos n t e e 2 sin 1 jn t jn t n t e jnt e jnt 2 j 3

31 The complex or exponential Fourier series representation and can be written as: c e jn f t n The values of c n are: n 1 T jn t cn f t e dt T t 31

32 The exponential Fourier series of a periodic function describes the spectrum in terms of the amplitude and phase angle of ac components at positive and negative harmonic frequencies. The coefficients of the three forms of Fourier series (sine-cosine, amplitude-phase, and exponential form) are related by: A a jb 2c n n n n n 32

33 Example Obtain the complex Fourier series of the function f(t). 33

34 Exercise Obtain the complex Fourier series of the function f(t) and plot the amplitude and phase spectra. 34

35 35

Fourier Series and Fourier Transforms

Fourier Series and Fourier Transforms Fourier Series and Fourier Transforms EECS2 (6.082), MIT Fall 2006 Lectures 2 and 3 Fourier Series From your differential equations course, 18.03, you know Fourier s expression representing a T -periodic

More information

Chapter 10: Sinusoidal Steady-State Analysis

Chapter 10: Sinusoidal Steady-State Analysis Chapter 10: Sinusoidal Steady-State Analysis 1 Objectives : sinusoidal functions Impedance use phasors to determine the forced response of a circuit subjected to sinusoidal excitation Apply techniques

More information

ω 0 = 2π/T 0 is called the fundamental angular frequency and ω 2 = 2ω 0 is called the

ω 0 = 2π/T 0 is called the fundamental angular frequency and ω 2 = 2ω 0 is called the he ime-frequency Concept []. Review of Fourier Series Consider the following set of time functions {3A sin t, A sin t}. We can represent these functions in different ways by plotting the amplitude versus

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

Chapter 4 The Fourier Series and Fourier Transform

Chapter 4 The Fourier Series and Fourier Transform Chapter 4 The Fourier Series and Fourier Transform Representation of Signals in Terms of Frequency Components Consider the CT signal defined by N xt () = Acos( ω t+ θ ), t k = 1 k k k The frequencies `present

More information

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

Circuit Analysis-III. Circuit Analysis-II Lecture # 3 Friday 06 th April, 18

Circuit Analysis-III. Circuit Analysis-II Lecture # 3 Friday 06 th April, 18 Circuit Analysis-III Sinusoids Example #1 ü Find the amplitude, phase, period and frequency of the sinusoid: v (t ) =12cos(50t +10 ) Signal Conversion ü From sine to cosine and vice versa. ü sin (A ± B)

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

(Refer Slide Time: 01:30)

(Refer Slide Time: 01:30) Networks and Systems Prof V.G K.Murti Department of Electrical Engineering Indian Institute of Technology, Madras Lecture - 11 Fourier Series (5) Continuing our discussion of Fourier series today, we will

More information

Chapter 4 The Fourier Series and Fourier Transform

Chapter 4 The Fourier Series and Fourier Transform Chapter 4 The Fourier Series and Fourier Transform Fourier Series Representation of Periodic Signals Let x(t) be a CT periodic signal with period T, i.e., xt ( + T) = xt ( ), t R Example: the rectangular

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

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

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

The Fourier Transform (and more )

The Fourier Transform (and more ) The Fourier Transform (and more ) imrod Peleg ov. 5 Outline Introduce Fourier series and transforms Introduce Discrete Time Fourier Transforms, (DTFT) Introduce Discrete Fourier Transforms (DFT) Consider

More information

SEISMIC WAVE PROPAGATION. Lecture 2: Fourier Analysis

SEISMIC WAVE PROPAGATION. Lecture 2: Fourier Analysis SEISMIC WAVE PROPAGATION Lecture 2: Fourier Analysis Fourier Series & Fourier Transforms Fourier Series Review of trigonometric identities Analysing the square wave Fourier Transform Transforms of some

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

Chapter 10: Sinusoids and Phasors

Chapter 10: Sinusoids and Phasors Chapter 10: Sinusoids and Phasors 1. Motivation 2. Sinusoid Features 3. Phasors 4. Phasor Relationships for Circuit Elements 5. Impedance and Admittance 6. Kirchhoff s Laws in the Frequency Domain 7. Impedance

More information

IB Paper 6: Signal and Data Analysis

IB Paper 6: Signal and Data Analysis IB Paper 6: Signal and Data Analysis Handout 2: Fourier Series S Godsill Signal Processing and Communications Group, Engineering Department, Cambridge, UK Lent 2015 1 / 1 Fourier Series Revision of Basics

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

Solutions to Assignment 4

Solutions to Assignment 4 EE35 Spectrum Analysis and Discrete Time Systems (Fall 5) Solutions to Assignment. Consider the continuous-time periodic signal: x(t) = sin(t 3) + sin(6t) (8) [] (a) Obviously, the fundamental frequency

More information

ELEG 3124 SYSTEMS AND SIGNALS Ch. 5 Fourier Transform

ELEG 3124 SYSTEMS AND SIGNALS Ch. 5 Fourier Transform Department of Electrical Engineering University of Arkansas ELEG 3124 SYSTEMS AND SIGNALS Ch. 5 Fourier Transform Dr. Jingxian Wu wuj@uark.edu OUTLINE 2 Introduction Fourier Transform Properties of Fourier

More information

EDEXCEL NATIONAL CERTIFICATE UNIT 28 FURTHER MATHEMATICS FOR TECHNICIANS OUTCOME 3 TUTORIAL 1 - TRIGONOMETRICAL GRAPHS

EDEXCEL NATIONAL CERTIFICATE UNIT 28 FURTHER MATHEMATICS FOR TECHNICIANS OUTCOME 3 TUTORIAL 1 - TRIGONOMETRICAL GRAPHS EDEXCEL NATIONAL CERTIFICATE UNIT 28 FURTHER MATHEMATICS FOR TECHNICIANS OUTCOME 3 TUTORIAL 1 - TRIGONOMETRICAL GRAPHS CONTENTS 3 Be able to understand how to manipulate trigonometric expressions and apply

More information

SIGNALS AND SYSTEMS: PAPER 3C1 HANDOUT 6a. Dr David Corrigan 1. Electronic and Electrical Engineering Dept.

SIGNALS AND SYSTEMS: PAPER 3C1 HANDOUT 6a. Dr David Corrigan 1. Electronic and Electrical Engineering Dept. SIGNALS AND SYSTEMS: PAPER 3C HANDOUT 6a. Dr David Corrigan. Electronic and Electrical Engineering Dept. corrigad@tcd.ie www.mee.tcd.ie/ corrigad FOURIER SERIES Have seen how the behaviour of systems can

More information

Fourier Transform. Find the Fourier series for a periodic waveform Determine the output of a filter when the input is a periodic function

Fourier Transform. Find the Fourier series for a periodic waveform Determine the output of a filter when the input is a periodic function Objectives: Be able to Fourier Transform Find the Fourier series for a periodic waveform Determine the output of a filter when the input is a periodic function Filters with a Single Sinusoidal Input: Suppose

More information

Basic Electronics. Introductory Lecture Course for. Technology and Instrumentation in Particle Physics Chicago, Illinois June 9-14, 2011

Basic Electronics. Introductory Lecture Course for. Technology and Instrumentation in Particle Physics Chicago, Illinois June 9-14, 2011 Basic Electronics Introductory Lecture Course for Technology and Instrumentation in Particle Physics 2011 Chicago, Illinois June 9-14, 2011 Presented By Gary Drake Argonne National Laboratory Session 2

More information

Amplitude and Phase A(0) 2. We start with the Fourier series representation of X(t) in real notation: n=1

Amplitude and Phase A(0) 2. We start with the Fourier series representation of X(t) in real notation: n=1 VI. Power Spectra Amplitude and Phase We start with the Fourier series representation of X(t) in real notation: A() X(t) = + [ A(n) cos(nωt) + B(n) sin(nωt)] 2 n=1 he waveform of the observed segment exactly

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

Lecture 27 Frequency Response 2

Lecture 27 Frequency Response 2 Lecture 27 Frequency Response 2 Fundamentals of Digital Signal Processing Spring, 2012 Wei-Ta Chu 2012/6/12 1 Application of Ideal Filters Suppose we can generate a square wave with a fundamental period

More information

Chapter 2. Signals. Static and Dynamic Characteristics of Signals. Signals classified as

Chapter 2. Signals. Static and Dynamic Characteristics of Signals. Signals classified as Chapter 2 Static and Dynamic Characteristics of Signals Signals Signals classified as. Analog continuous in time and takes on any magnitude in range of operations 2. Discrete Time measuring a continuous

More information

General Physics I. Lecture 14: Sinusoidal Waves. Prof. WAN, Xin ( 万歆 )

General Physics I. Lecture 14: Sinusoidal Waves. Prof. WAN, Xin ( 万歆 ) General Physics I Lecture 14: Sinusoidal Waves Prof. WAN, Xin ( 万歆 ) xinwan@zju.edu.cn http://zimp.zju.edu.cn/~xinwan/ Motivation When analyzing a linear medium that is, one in which the restoring force

More information

Experiment 7: Fourier Series

Experiment 7: Fourier Series Experiment 7: Fourier Series Theory A Fourier series is an infinite sum of harmonic functions (sines and cosines) with every term in the series having a frequency which is an integral multiple of some

More information

Lab Fourier Analysis Do prelab before lab starts. PHSX 262 Spring 2011 Lecture 5 Page 1. Based with permission on lectures by John Getty

Lab Fourier Analysis Do prelab before lab starts. PHSX 262 Spring 2011 Lecture 5 Page 1. Based with permission on lectures by John Getty Today /5/ Lecture 5 Fourier Series Time-Frequency Decomposition/Superposition Fourier Components (Ex. Square wave) Filtering Spectrum Analysis Windowing Fast Fourier Transform Sweep Frequency Analyzer

More information

3.2 Complex Sinusoids and Frequency Response of LTI Systems

3.2 Complex Sinusoids and Frequency Response of LTI Systems 3. Introduction. A signal can be represented as a weighted superposition of complex sinusoids. x(t) or x[n]. LTI system: LTI System Output = A weighted superposition of the system response to each complex

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

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

EE 435. Lecture 30. Data Converters. Spectral Performance

EE 435. Lecture 30. Data Converters. Spectral Performance EE 435 Lecture 30 Data Converters Spectral Performance . Review from last lecture. INL Often Not a Good Measure of Linearity Four identical INL with dramatically different linearity X OUT X OUT X REF X

More information

MODULE I. Transient Response:

MODULE I. Transient Response: Transient Response: MODULE I The Transient Response (also known as the Natural Response) is the way the circuit responds to energies stored in storage elements, such as capacitors and inductors. If a capacitor

More information

Name (print): Lab (circle): W8 Th8 Th11 Th2 F8. θ (radians) θ (degrees) cos θ sin θ π/ /2 1/2 π/4 45 2/2 2/2 π/3 60 1/2 3/2 π/

Name (print): Lab (circle): W8 Th8 Th11 Th2 F8. θ (radians) θ (degrees) cos θ sin θ π/ /2 1/2 π/4 45 2/2 2/2 π/3 60 1/2 3/2 π/ Name (print): Lab (circle): W8 Th8 Th11 Th2 F8 Trigonometric Identities ( cos(θ) = cos(θ) sin(θ) = sin(θ) sin(θ) = cos θ π ) 2 Cosines and Sines of common angles Euler s Formula θ (radians) θ (degrees)

More information

The Fourier series are applicable to periodic signals. They were discovered by the

The Fourier series are applicable to periodic signals. They were discovered by the 3.1 Fourier Series The Fourier series are applicable to periodic signals. They were discovered by the famous French mathematician Joseph Fourier in 1807. By using the Fourier series, a periodic signal

More information

Continuous-time Fourier Methods

Continuous-time Fourier Methods ELEC 321-001 SIGNALS and SYSTEMS Continuous-time Fourier Methods Chapter 6 1 Representing a Signal The convolution method for finding the response of a system to an excitation takes advantage of the linearity

More information

Topic 3: Fourier Series (FS)

Topic 3: Fourier Series (FS) ELEC264: Signals And Systems Topic 3: Fourier Series (FS) o o o o Introduction to frequency analysis of signals CT FS Fourier series of CT periodic signals Signal Symmetry and CT Fourier Series Properties

More information

Signals and systems Lecture (S3) Square Wave Example, Signal Power and Properties of Fourier Series March 18, 2008

Signals and systems Lecture (S3) Square Wave Example, Signal Power and Properties of Fourier Series March 18, 2008 Signals and systems Lecture (S3) Square Wave Example, Signal Power and Properties of Fourier Series March 18, 2008 Today s Topics 1. Derivation of a Fourier series representation of a square wave signal

More information

Representing a Signal

Representing a Signal The Fourier Series Representing a Signal The convolution method for finding the response of a system to an excitation takes advantage of the linearity and timeinvariance of the system and represents the

More information

EA2.3 - Electronics 2 1

EA2.3 - Electronics 2 1 In the previous lecture, I talked about the idea of complex frequency s, where s = σ + jω. Using such concept of complex frequency allows us to analyse signals and systems with better generality. In this

More information

Introduction to Vibration. Professor Mike Brennan

Introduction to Vibration. Professor Mike Brennan Introduction to Vibration Professor Mie Brennan Introduction to Vibration Nature of vibration of mechanical systems Free and forced vibrations Frequency response functions Fundamentals For free vibration

More information

Solutions to Problems in Chapter 4

Solutions to Problems in Chapter 4 Solutions to Problems in Chapter 4 Problems with Solutions Problem 4. Fourier Series of the Output Voltage of an Ideal Full-Wave Diode Bridge Rectifier he nonlinear circuit in Figure 4. is a full-wave

More information

Fourier Series & The Fourier Transform

Fourier Series & The Fourier Transform Fourier Series & The Fourier Transform What is the Fourier Transform? Anharmonic Waves Fourier Cosine Series for even functions Fourier Sine Series for odd functions The continuous limit: the Fourier transform

More information

EE 435. Lecture 28. Data Converters Linearity INL/DNL Spectral Performance

EE 435. Lecture 28. Data Converters Linearity INL/DNL Spectral Performance EE 435 Lecture 8 Data Converters Linearity INL/DNL Spectral Performance Performance Characterization of Data Converters Static characteristics Resolution Least Significant Bit (LSB) Offset and Gain Errors

More information

Analytic Trigonometry. Copyright Cengage Learning. All rights reserved.

Analytic Trigonometry. Copyright Cengage Learning. All rights reserved. Analytic Trigonometry Copyright Cengage Learning. All rights reserved. 7.4 Basic Trigonometric Equations Copyright Cengage Learning. All rights reserved. Objectives Basic Trigonometric Equations Solving

More information

LECTURE 12 Sections Introduction to the Fourier series of periodic signals

LECTURE 12 Sections Introduction to the Fourier series of periodic signals Signals and Systems I Wednesday, February 11, 29 LECURE 12 Sections 3.1-3.3 Introduction to the Fourier series of periodic signals Chapter 3: Fourier Series of periodic signals 3. Introduction 3.1 Historical

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

FOURIER ANALYSIS. (a) Fourier Series

FOURIER ANALYSIS. (a) Fourier Series (a) Fourier Series FOURIER ANAYSIS (b) Fourier Transforms Useful books: 1. Advanced Mathematics for Engineers and Scientists, Schaum s Outline Series, M. R. Spiegel - The course text. We follow their notation

More information

CS711008Z Algorithm Design and Analysis

CS711008Z Algorithm Design and Analysis CS711008Z Algorithm Design and Analysis Lecture 5 FFT and Divide and Conquer Dongbo Bu Institute of Computing Technology Chinese Academy of Sciences, Beijing, China 1 / 56 Outline DFT: evaluate a polynomial

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

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

2.3 Oscillation. The harmonic oscillator equation is the differential equation. d 2 y dt 2 r y (r > 0). Its solutions have the form

2.3 Oscillation. The harmonic oscillator equation is the differential equation. d 2 y dt 2 r y (r > 0). Its solutions have the form 2. Oscillation So far, we have used differential equations to describe functions that grow or decay over time. The next most common behavior for a function is to oscillate, meaning that it increases and

More information

A1 Time-Frequency Analysis

A1 Time-Frequency Analysis A 20 / A Time-Frequency Analysis David Murray david.murray@eng.ox.ac.uk www.robots.ox.ac.uk/ dwm/courses/2tf Hilary 20 A 20 2 / Content 8 Lectures: 6 Topics... From Signals to Complex Fourier Series 2

More information

Fourier Series : Dr. Mohammed Saheb Khesbak Page 34

Fourier Series : Dr. Mohammed Saheb Khesbak Page 34 Fourier Series : Dr. Mohammed Saheb Khesbak Page 34 Dr. Mohammed Saheb Khesbak Page 35 Example 1: Dr. Mohammed Saheb Khesbak Page 36 Dr. Mohammed Saheb Khesbak Page 37 Dr. Mohammed Saheb Khesbak Page 38

More information

ENSC327 Communications Systems 2: Fourier Representations. Jie Liang School of Engineering Science Simon Fraser University

ENSC327 Communications Systems 2: Fourier Representations. Jie Liang School of Engineering Science Simon Fraser University ENSC327 Communications Systems 2: Fourier Representations Jie Liang School of Engineering Science Simon Fraser University 1 Outline Chap 2.1 2.5: Signal Classifications Fourier Transform Dirac Delta Function

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

Properties of Fourier Series - GATE Study Material in PDF

Properties of Fourier Series - GATE Study Material in PDF Properties of Fourier Series - GAE Study Material in PDF In the previous article, we learnt the Basics of Fourier Series, the different types and all about the different Fourier Series spectrums. Now,

More information

Continuous Time Signal Analysis: the Fourier Transform. Lathi Chapter 4

Continuous Time Signal Analysis: the Fourier Transform. Lathi Chapter 4 Continuous Time Signal Analysis: the Fourier Transform Lathi Chapter 4 Topics Aperiodic signal representation by the Fourier integral (CTFT) Continuous-time Fourier transform Transforms of some useful

More information

Line Spectra and their Applications

Line Spectra and their Applications In [ ]: cd matlab pwd Line Spectra and their Applications Scope and Background Reading This session concludes our introduction to Fourier Series. Last time (http://nbviewer.jupyter.org/github/cpjobling/eg-47-

More information

Introduction to Vibration. Mike Brennan UNESP, Ilha Solteira São Paulo Brazil

Introduction to Vibration. Mike Brennan UNESP, Ilha Solteira São Paulo Brazil Introduction to Vibration Mike Brennan UNESP, Ilha Solteira São Paulo Brazil Vibration Most vibrations are undesirable, but there are many instances where vibrations are useful Ultrasonic (very high

More information

Pre-Calculus MATH 119 Fall Section 1.1. Section objectives. Section 1.3. Section objectives. Section A.10. Section objectives

Pre-Calculus MATH 119 Fall Section 1.1. Section objectives. Section 1.3. Section objectives. Section A.10. Section objectives Pre-Calculus MATH 119 Fall 2013 Learning Objectives Section 1.1 1. Use the Distance Formula 2. Use the Midpoint Formula 4. Graph Equations Using a Graphing Utility 5. Use a Graphing Utility to Create Tables

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

Then r (t) can be expanded into a linear combination of the complex exponential signals ( e j2π(kf 0)t ) k= as. c k e j2π(kf0)t + c k e j2π(kf 0)t

Then r (t) can be expanded into a linear combination of the complex exponential signals ( e j2π(kf 0)t ) k= as. c k e j2π(kf0)t + c k e j2π(kf 0)t .3 ourier Series Definition.37. Exponential ourier series: Let the real or complex signal r t be a periodic signal with period. Suppose the following Dirichlet conditions are satisfied: a r t is absolutely

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

A. Incorrect! This equality is true for all values of x. Therefore, this is an identity and not a conditional equation.

A. Incorrect! This equality is true for all values of x. Therefore, this is an identity and not a conditional equation. CLEP-Precalculus - Problem Drill : Trigonometric Identities No. of 0 Instructions: () Read the problem and answer choices carefully () Work the problems on paper as. Which of the following equalities is

More information

Fourier Series Representation of

Fourier Series Representation of Fourier Series Representation of Periodic Signals Rui Wang, Assistant professor Dept. of Information and Communication Tongji University it Email: ruiwang@tongji.edu.cn Outline The response of LIT system

More information

Sinusoids and Phasors

Sinusoids and Phasors CHAPTER 9 Sinusoids and Phasors We now begins the analysis of circuits in which the voltage or current sources are time-varying. In this chapter, we are particularly interested in sinusoidally time-varying

More information

I. Impedance of an R-L circuit.

I. Impedance of an R-L circuit. I. Impedance of an R-L circuit. [For inductor in an AC Circuit, see Chapter 31, pg. 1024] Consider the R-L circuit shown in Figure: 1. A current i(t) = I cos(ωt) is driven across the circuit using an AC

More information

The Phasor Solution Method

The Phasor Solution Method APPENDIX A The Phasor Solution Method This appendix is intended as a review of the important phasor methods of solving electric circuits and other linear systems in which the excitation is a singlefrequency

More information

Handout 11: AC circuit. AC generator

Handout 11: AC circuit. AC generator Handout : AC circuit AC generator Figure compares the voltage across the directcurrent (DC) generator and that across the alternatingcurrent (AC) generator For DC generator, the voltage is constant For

More information

General Inner Product and The Fourier Series

General Inner Product and The Fourier Series A Linear Algebra Approach Department of Mathematics University of Puget Sound 4-20-14 / Spring Semester Outline 1 2 Inner Product The inner product is an algebraic operation that takes two vectors and

More information

EE292: Fundamentals of ECE

EE292: Fundamentals of ECE EE292: Fundamentals of ECE Fall 2012 TTh 10:00-11:15 SEB 1242 Lecture 18 121025 http://www.ee.unlv.edu/~b1morris/ee292/ 2 Outline Review RMS Values Complex Numbers Phasors Complex Impedance Circuit Analysis

More information

8. Introduction and Chapter Objectives

8. Introduction and Chapter Objectives Real Analog - Circuits Chapter 8: Second Order Circuits 8. Introduction and Chapter Objectives Second order systems are, by definition, systems whose input-output relationship is a second order differential

More information

Physics 6303 Lecture 11 September 24, LAST TIME: Cylindrical coordinates, spherical coordinates, and Legendre s equation

Physics 6303 Lecture 11 September 24, LAST TIME: Cylindrical coordinates, spherical coordinates, and Legendre s equation Physics 6303 Lecture September 24, 208 LAST TIME: Cylindrical coordinates, spherical coordinates, and Legendre s equation, l l l l l l. Consider problems that are no axisymmetric; i.e., the potential depends

More information

ENT 315 Medical Signal Processing CHAPTER 2 DISCRETE FOURIER TRANSFORM. Dr. Lim Chee Chin

ENT 315 Medical Signal Processing CHAPTER 2 DISCRETE FOURIER TRANSFORM. Dr. Lim Chee Chin ENT 315 Medical Signal Processing CHAPTER 2 DISCRETE FOURIER TRANSFORM Dr. Lim Chee Chin Outline Introduction Discrete Fourier Series Properties of Discrete Fourier Series Time domain aliasing due to frequency

More information

Sinusoidal Steady State Analysis (AC Analysis) Part II

Sinusoidal Steady State Analysis (AC Analysis) Part II Sinusoidal Steady State Analysis (AC Analysis) Part II Amin Electronics and Electrical Communications Engineering Department (EECE) Cairo University elc.n102.eng@gmail.com http://scholar.cu.edu.eg/refky/

More information

Project Components. MC34063 or equivalent. Bread Board. Energy Systems Research Laboratory, FIU

Project Components. MC34063 or equivalent. Bread Board. Energy Systems Research Laboratory, FIU Project Components MC34063 or equivalent Bread Board PSpice Software OrCAD designer Lite version http://www.cadence.com/products/orcad/pages/downloads.aspx#pspice More Details on the Introduction CONVERTER

More information

LINEAR CIRCUIT ANALYSIS (EED) U.E.T. TAXILA 09

LINEAR CIRCUIT ANALYSIS (EED) U.E.T. TAXILA 09 LINEAR CIRCUIT ANALYSIS (EED) U.E.T. TAXILA 09 ENGR. M. MANSOOR ASHRAF INTRODUCTION Thus far our analysis has been restricted for the most part to dc circuits: those circuits excited by constant or time-invariant

More information

Revision of Basic A.C. Theory

Revision of Basic A.C. Theory Revision of Basic A.C. Theory 1 Revision of Basic AC Theory (Much of this material has come from Electrical & Electronic Principles & Technology by John Bird) Electricity is generated in power stations

More information

Frequency Response & Filter Analysis. Week Date Lecture Title. 4-Mar Introduction & Systems Overview 6-Mar [Linear Dynamical Systems] 2

Frequency Response & Filter Analysis. Week Date Lecture Title. 4-Mar Introduction & Systems Overview 6-Mar [Linear Dynamical Systems] 2 http://elec34.com Frequency Response & Filter Analysis 4 School of Information Technology and Electrical Engineering at The University of Queensland Lecture Schedule: Week Date Lecture Title 4-Mar Introduction

More information

Review of Linear Time-Invariant Network Analysis

Review of Linear Time-Invariant Network Analysis D1 APPENDIX D Review of Linear Time-Invariant Network Analysis Consider a network with input x(t) and output y(t) as shown in Figure D-1. If an input x 1 (t) produces an output y 1 (t), and an input x

More information

THE FOURIER TRANSFORM (Fourier series for a function whose period is very, very long) Reading: Main 11.3

THE FOURIER TRANSFORM (Fourier series for a function whose period is very, very long) Reading: Main 11.3 THE FOURIER TRANSFORM (Fourier series for a function whose period is very, very long) Reading: Main 11.3 Any periodic function f(t) can be written as a Fourier Series a 0 2 + a n cos( nωt) + b n sin n

More information

Fourier Series. Fourier Transform

Fourier Series. Fourier Transform Math Methods I Lia Vas Fourier Series. Fourier ransform Fourier Series. Recall that a function differentiable any number of times at x = a can be represented as a power series n= a n (x a) n where the

More information

Electric Circuit Theory

Electric Circuit Theory Electric Circuit Theory Nam Ki Min nkmin@korea.ac.kr 010-9419-2320 Chapter 11 Sinusoidal Steady-State Analysis Nam Ki Min nkmin@korea.ac.kr 010-9419-2320 Contents and Objectives 3 Chapter Contents 11.1

More information

A3. Frequency Representation of Continuous Time and Discrete Time Signals

A3. Frequency Representation of Continuous Time and Discrete Time Signals A3. Frequency Representation of Continuous Time and Discrete Time Signals Objectives Define the magnitude and phase plots of continuous time sinusoidal signals Extend the magnitude and phase plots to discrete

More information

Periodic functions: simple harmonic oscillator

Periodic functions: simple harmonic oscillator Periodic functions: simple harmonic oscillator Recall the simple harmonic oscillator (e.g. mass-spring system) d 2 y dt 2 + ω2 0y = 0 Solution can be written in various ways: y(t) = Ae iω 0t y(t) = A cos

More information

Fourier transform. XE31EO2 - Pavel Máša. EO2 Lecture 2. XE31EO2 - Pavel Máša - Fourier Transform

Fourier transform. XE31EO2 - Pavel Máša. EO2 Lecture 2. XE31EO2 - Pavel Máša - Fourier Transform Fourier transform EO2 Lecture 2 Pavel Máša - Fourier Transform INTRODUCTION We already know complex form of Fourier series f(t) = 1X k= 1 A k e jk! t A k = 1 T Series frequency spectra is discrete Circuits

More information

4 The Continuous Time Fourier Transform

4 The Continuous Time Fourier Transform 96 4 The Continuous Time ourier Transform ourier (or frequency domain) analysis turns out to be a tool of even greater usefulness Extension of ourier series representation to aperiodic signals oundation

More information

3 Fourier Series Representation of Periodic Signals

3 Fourier Series Representation of Periodic Signals 65 66 3 Fourier Series Representation of Periodic Signals Fourier (or frequency domain) analysis constitutes a tool of great usefulness Accomplishes decomposition of broad classes of signals using complex

More information

11. AC Circuit Power Analysis

11. AC Circuit Power Analysis . AC Circuit Power Analysis Often an integral part of circuit analysis is the determination of either power delivered or power absorbed (or both). In this chapter First, we begin by considering instantaneous

More information

General Appendix A Transmission Line Resonance due to Reflections (1-D Cavity Resonances)

General Appendix A Transmission Line Resonance due to Reflections (1-D Cavity Resonances) A 1 General Appendix A Transmission Line Resonance due to Reflections (1-D Cavity Resonances) 1. Waves Propagating on a Transmission Line General A transmission line is a 1-dimensional medium which can

More information

The Continuous-time Fourier

The Continuous-time Fourier The Continuous-time Fourier Transform Rui Wang, Assistant professor Dept. of Information and Communication Tongji University it Email: ruiwang@tongji.edu.cn Outline Representation of Aperiodic signals:

More information

PS403 - Digital Signal processing

PS403 - Digital Signal processing PS403 - Digital Signal processing III. DSP - Digital Fourier Series and Transforms Key Text: Digital Signal Processing with Computer Applications (2 nd Ed.) Paul A Lynn and Wolfgang Fuerst, (Publisher:

More information

Chapter 2: Functions, Limits and Continuity

Chapter 2: Functions, Limits and Continuity Chapter 2: Functions, Limits and Continuity Functions Limits Continuity Chapter 2: Functions, Limits and Continuity 1 Functions Functions are the major tools for describing the real world in mathematical

More information

Name: Lab: M8 M2 W8 Th8 Th11 Th2 F8. cos( θ) = cos(θ) sin( θ) = sin(θ) sin(θ) = cos. θ (radians) θ (degrees) cos θ sin θ π/6 30

Name: Lab: M8 M2 W8 Th8 Th11 Th2 F8. cos( θ) = cos(θ) sin( θ) = sin(θ) sin(θ) = cos. θ (radians) θ (degrees) cos θ sin θ π/6 30 Name: Lab: M8 M2 W8 Th8 Th11 Th2 F8 Trigonometric Identities cos(θ) = cos(θ) sin(θ) = sin(θ) sin(θ) = cos Cosines and Sines of common angles Euler s Formula θ (radians) θ (degrees) cos θ sin θ 0 0 1 0

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