SIGNAL AND SYSTEM CT Fourier Transform. Fourier’s Derivation of the CT Fourier Transform x(t) -an aperiodic signal -view it as the limit of a periodic.

Slides:



Advertisements
Similar presentations
Chapter 5 The Fourier Transform. Basic Idea We covered the Fourier Transform which to represent periodic signals We assumed periodic continuous signals.
Advertisements

Familiar Properties of Linear Transforms
Properties of continuous Fourier Transforms
Autumn Analog and Digital Communications Autumn
PROPERTIES OF FOURIER REPRESENTATIONS
Lecture 8: Fourier Series and Fourier Transform
EE-2027 SaS, L11 1/13 Lecture 11: Discrete Fourier Transform 4 Sampling Discrete-time systems (2 lectures): Sampling theorem, discrete Fourier transform.
Lecture 9: Fourier Transform Properties and Examples
Discrete-Time Fourier Methods
Leo Lam © Signals and Systems EE235. Leo Lam © Fourier Transform Q: What did the Fourier transform of the arbitrary signal say to.
PA214 Waves and Fields Fourier Methods Blue book New chapter 12 Fourier sine series Application to the wave equation Fourier cosine series Fourier full.
Leo Lam © Signals and Systems EE235. Leo Lam © x squared equals 9 x squared plus 1 equals y Find value of y.
Discrete-Time Fourier Series
ECE 8443 – Pattern Recognition EE 3512 – Signals: Continuous and Discrete Objectives: Linearity Time Shift and Time Reversal Multiplication Integration.
Fourier Transforms Section Kamen and Heck.
1 Fourier Representation of Signals and LTI Systems. CHAPTER 3 EKT 232.
Signals and Systems (Lab) Resource Person : Hafiz Muhammad Ijaz COMSATS Institute of Information Technology Lahore Campus.
Basic signals Why use complex exponentials? – Because they are useful building blocks which can be used to represent large and useful classes of signals.
ECE 8443 – Pattern Recognition ECE 3163 – Signals and Systems Objectives: Derivation Transform Pairs Response of LTI Systems Transforms of Periodic Signals.
1 Review of Continuous-Time Fourier Series. 2 Example 3.5 T/2 T1T1 -T/2 -T 1 This periodic signal x(t) repeats every T seconds. x(t)=1, for |t|
ECE 8443 – Pattern Recognition EE 3512 – Signals: Continuous and Discrete Objectives: Review Resources: Wiki: Superheterodyne Receivers RE: Superheterodyne.
Lecture 24: CT Fourier Transform
The Continuous - Time Fourier Transform (CTFT). Extending the CTFS The CTFS is a good analysis tool for systems with periodic excitation but the CTFS.
Signal and Systems Prof. H. Sameti Chapter 5: The Discrete Time Fourier Transform Examples of the DT Fourier Transform Properties of the DT Fourier Transform.
Fourier Series. Introduction Decompose a periodic input signal into primitive periodic components. A periodic sequence T2T3T t f(t)f(t)
1 Fourier Representations of Signals & Linear Time-Invariant Systems Chapter 3.
Signal and Systems Prof. H. Sameti Chapter 3: Fourier Series Representation of Periodic Signals Complex Exponentials as Eigenfunctions of LTI Systems Fourier.
EE104: Lecture 5 Outline Review of Last Lecture Introduction to Fourier Transforms Fourier Transform from Fourier Series Fourier Transform Pair and Signal.
Signal and System I The unit step response of an LTI system.
Husheng Li, UTK-EECS, Fall  Fourier transform is used to study the frequency spectrum of signals.  Basically, it says that a signal can be represented.
1 Fourier Representation of Signals and LTI Systems. CHAPTER 3 EKT 232.
Course Outline (Tentative) Fundamental Concepts of Signals and Systems Signals Systems Linear Time-Invariant (LTI) Systems Convolution integral and sum.
Linearity Recall our expressions for the Fourier Transform and its inverse: The property of linearity: Proof: (synthesis) (analysis)
Signals and Systems Using MATLAB Luis F. Chaparro
Fourier Analysis of Signals and Systems
5.0 Discrete-time Fourier Transform 5.1 Discrete-time Fourier Transform Representation for discrete-time signals Chapters 3, 4, 5 Chap 3 Periodic Fourier.
Signals and Systems Prof. H. Sameti Chapter 4: The Continuous Time Fourier Transform Derivation of the CT Fourier Transform pair Examples of Fourier Transforms.
EE 207 Dr. Adil Balghonaim Chapter 4 The Fourier Transform.
ECE 8443 – Pattern Recognition EE 3512 – Signals: Continuous and Discrete Objectives: Eigenfunctions Fourier Series of CT Signals Trigonometric Fourier.
Signals and Systems Fall 2003 Lecture #6 23 September CT Fourier series reprise, properties, and examples 2. DT Fourier series 3. DT Fourier series.
1 “Figures and images used in these lecture notes by permission, copyright 1997 by Alan V. Oppenheim and Alan S. Willsky” Signals and Systems Spring 2003.
1 Convergence of Fourier Series Can we get Fourier Series representation for all periodic signals. I.e. are the coefficients from eqn 3.39 finite or in.
1 Roadmap SignalSystem Input Signal Output Signal characteristics Given input and system information, solve for the response Solving differential equation.
ECE 8443 – Pattern Recognition ECE 3163 – Signals and Systems Objectives: Eigenfunctions Fourier Series of CT Signals Trigonometric Fourier Series Dirichlet.
Leo Lam © Signals and Systems EE235 Lecture 25.
Professor Brendan Morris, SEB 3216, EE360: Signals and System I Fourier Series Motivation.
بسم الله الرحمن الرحيم University of Khartoum Department of Electrical and Electronic Engineering Third Year – 2015 Dr. Iman AbuelMaaly Abdelrahman
ENEE 322: Continuous-Time Fourier Transform (Chapter 4)
Dr S D AL_SHAMMA Dr S D AL_SHAMMA11.
EE104: Lecture 6 Outline Announcements: HW 1 due today, HW 2 posted Review of Last Lecture Additional comments on Fourier transforms Review of time window.
Convergence of Fourier series It is known that a periodic signal x(t) has a Fourier series representation if it satisfies the following Dirichlet conditions:
Hülya Yalçın ©1 Fourier Series. Hülya Yalçın ©2 3.
Introduction to Signal Processing Summer DTFT Properties and Examples 2.Duality in FS & FT 3.Magnitude/Phase of Transforms and Frequency Responses.
LECTURE 11: FOURIER TRANSFORM PROPERTIES
UNIT II Analysis of Continuous Time signal
EE360: Signals and System I
Signals and Systems Using MATLAB Luis F. Chaparro
Notes Assignments Tutorial problems
Fourier Series September 18, 2000 EE 64, Section 1 ©Michael R. Gustafson II Pratt School of Engineering.
Signals & Systems (CNET - 221) Chapter-4 Fourier Series
Signals & Systems (CNET - 221) Chapter-5 Fourier Transform
Continuous-Time Fourier Transform
Signals & Systems (CNET - 221) Chapter-4
4. The Continuous time Fourier Transform
Signals and Systems EE235 Leo Lam ©
10.3 The Inverse z-Transform
Chapter 5 The Fourier Transform.
Signals and Systems Using MATLAB Luis F. Chaparro
LECTURE 11: FOURIER TRANSFORM PROPERTIES
Signals and Systems Lecture 11
Presentation transcript:

SIGNAL AND SYSTEM CT Fourier Transform

Fourier’s Derivation of the CT Fourier Transform x(t) -an aperiodic signal -view it as the limit of a periodic signal as T→ ∞ For a periodic signal, the harmonic components are spaced ω0= 2π/T apart... As T→ ∞, ω0→0, and harmonic components are spaced closer and closer in frequency ⇓ Fourier series Fourier integral

Motivating Example: Square wave

Derivation

Derivation(continued)

For what kind of signals we do this

Example

CT Fourier Transforms of Periodic Signals

Example

Properties

Properties(continued)

5.Differentiation and Integration 6.Duality

Properties(continued) 7.Parseval’s Relation 8.Multiplication Property 9.Convolution Property

LTI System characterized by Differential Equations (Some slides are referred from MIT )