Lab7 (Signal & System) Instructor: Anan Osothsilp Date: 20 Feb 07 Due Date 03 April 07.

Slides:



Advertisements
Similar presentations
DCSP-3: Fourier Transform (continuous time) Jianfeng Feng
Advertisements

DCSP-3: Fourier Transform Jianfeng Feng Department of Computer Science Warwick Univ., UK
DCSP-11 Jianfeng Feng
10.1 fourier analysis of signals using the DFT 10.2 DFT analysis of sinusoidal signals 10.3 the time-dependent fourier transform Chapter 10 fourier analysis.
Lab5 (Signal & System) Instructor: Anan Osothsilp Date: 20 Feb 07 Due Date 09 March 07.
Physics 145 Introduction to Experimental Physics I Instructor: Karine Chesnel Office: N319 ESC Tel: Office hours: on appointment.
Properties of continuous Fourier Transforms
Gerald Leung.  Implementation Goal of Phase Vocoder  Spectral Analysis and Manipulation  Matlab Implementation  Result Discussion and Conclusion.
1 Speech Parametrisation Compact encoding of information in speech Accentuates important info –Attempts to eliminate irrelevant information Accentuates.
Fourier Series.
Lab8 (Signal & System) Instructor: Anan Osothsilp Date: 17 April 07.
Lab1 (Signal & System) Instructor: Anan Osothsilp Date: 30 Jan 07.
Lab2 (Signal & System) Instructor: Anan Osothsilp Date: 07 Feb 07.
S. Mandayam/ ECOMMS/ECE Dept./Rowan University Electrical Communication Systems ECE Spring 2008 Shreekanth Mandayam ECE Department Rowan University.
Lab9 (Signal & System) Instructor: Anan Osothsilp Date: 17 April 07.
Fourier Transforms on Simulated Pulsar Data Gamma-ray Large Area Space Telescope.
Image Fourier Transform Faisal Farooq Q: How many signal processing engineers does it take to change a light bulb? A: Three. One to Fourier transform the.
PROPERTIES OF FOURIER REPRESENTATIONS
Lab3 (Signal & System) Instructor: Anan Osothsilp Date: 13 Feb 07.
S. Mandayam/ ECOMMS/ECE Dept./Rowan University Electrical Communication Systems ECE Spring 2009 Shreekanth Mandayam ECE Department Rowan University.
Waveform and Spectrum A visual Fourier Analysis. String with fixed ends.
Fourier Series. is the “fundamental frequency” Fourier Series is the “fundamental frequency”
Time and Frequency Representation
Discrete Time Periodic Signals A discrete time signal x[n] is periodic with period N if and only if for all n. Definition: Meaning: a periodic signal keeps.
Chapter 15 Fourier Series and Fourier Transform
Leo Lam © Signals and Systems EE235 Lecture 23.
Systems: Definition Filter
Basics of Signal Processing. frequency = 1/T  speed of sound × T, where T is a period sine wave period (frequency) amplitude phase.
Q factor of an underdamped oscillator large if  is small compared to  0 Damping time or "1/e" time is  = 1/   (>> 1/   if  is very small)
Basics of Signal Processing. SIGNALSOURCE RECEIVER describe waves in terms of their significant features understand the way the waves originate effect.
Motivation Music as a combination of sounds at different frequencies
Fourier series. The frequency domain It is sometimes preferable to work in the frequency domain rather than time –Some mathematical operations are easier.
Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 Chapter 19.
ME- 495 Mechanical and Thermal Systems Lab Fall 2011 Chapter 4 - THE ANALOG MEASURAND: TIME-DEPENDANT CHARACTERISTICS Professor: Sam Kassegne.
Chapter 17 The Fourier Series
Chapter 4 Fourier transform Prepared by Dr. Taha MAhdy.
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.
Fourier Analysis of Discrete-Time Systems
Copyright © SEL 2012 A Comparison of Different Signal Selection Options and Signal Processing Techniques for Subsynchronous Resonance Detection Yu Xia,
Eeng Chapter4 Bandpass Signalling  Definitions  Complex Envelope Representation  Representation of Modulated Signals  Spectrum of Bandpass Signals.
11/20/2015 Fourier Series Chapter /20/2015 Fourier Series Chapter 6 2.
Signals and Systems Using MATLAB Luis F. Chaparro
Part 4 Chapter 16 Fourier Analysis PowerPoints organized by Prof. Steve Chapra, University All images copyright © The McGraw-Hill Companies, Inc. Permission.
Signals & Systems Lecture 13: Chapter 3 Spectrum Representation.
421 Pendulum Lab (5pt) Equation 1 Conclusions: We concluded that we have an numerically accurate model to describe the period of a pendulum at all angles.
Lecture 7 Transformations in frequency domain 1.Basic steps in frequency domain transformation 2.Fourier transformation theory in 1-D.
SUNY-New Paltz Computer Simulation Lab Electrical and Computer Engineering Department SUNY – New Paltz “Lecture 12”
Fourier Transform.
ECE 8443 – Pattern Recognition ECE 3163 – Signals and Systems Objectives: Frequency Response Response of a Sinusoid DT MA Filter Filter Design DT WMA Filter.
Lecture 11: EE 221: Signals Analysis and Systems Instructor: Dr. Ghazi Al Sukkar Dept. of Electrical Engineering The University of Jordan
Gustavo Cancelo Analysis of the phase shift error between A and B signals in BPMs BPM project.
Periodicity Prepare by Ji Kim, Bokman Kim. FFT spectrum FFT Spectrum Analyzers, such as the SR760, SR770, SR780 and SR785, take a time varying input signal,
The Spectrum n Jean Baptiste Fourier ( ) discovered a fundamental tenet of wave theory.
Eeng360 1 Chapter 2 Fourier Transform and Spectra Topics:  Fourier transform (FT) of a waveform  Properties of Fourier Transforms  Parseval’s Theorem.
Fourier Transform and Spectra
Welcome to the Fundamentals of Mathematics for Engineers Lab ENGR 2194 MATLAB Supplemental Instruction #1.
Dr S D AL_SHAMMA Dr S D AL_SHAMMA11.
Part 4 Chapter 16 Fourier Analysis
Net 222: Communications and networks fundamentals (Practical Part)
8 DIGITAL SIGNAL SPECTRA
Signal Processing: Propaedeutics
Fourier Series: Examples
Sound shadow effect Depends on the size of the obstructing object and the wavelength of the sound. If comparable: Then sound shadow occurs. I:\users\mnshriv\3032.
Digital Signal Processing
Fourier Transform and Spectra
Signals and Systems EE235 Lecture 23 Leo Lam ©
6. Time and Frequency Characterization of Signals and Systems
Signals and Systems EE235 Lecture 23 Leo Lam ©
Continuous-Time Fourier Transform
Discrete Fourier Transform
Presentation transcript:

Lab7 (Signal & System) Instructor: Anan Osothsilp Date: 20 Feb 07 Due Date 03 April 07

Anan OsothsilpPage 1 Lab7 Date: 03 April 07 Objective: Learn how to use for create GUI for fourier transform technique

Anan OsothsilpPage 2 Lab7 Instruction: Step 1: Review Lab5 Fourier series Step 2: Review Lab6 For GUI creation Step 3: create GUI program for Fourier transform in Exercise 1 Date: 03 April 07

Anan OsothsilpPage 3 Lab7 Exercise 1: Create GUI for interactive Fourier series (vary frequency & N) Frequency N points Magnitude Spectrum Phase Spectrum f(t) = 5*sin(2*pi*f*t) Date: 03 April 07

Anan OsothsilpPage 4 Lab7 Exercise 1: Create GUI for interactive Fourier series (vary frequency & N) In your Lab report also make conclusion about the effect of 1. Frequency parameter for actual waveform and frequency spectrum 2. N point parameter for actual waveform and frequency spectrum Date: 03 April 07

Anan OsothsilpPage 5 Lab7 Fourier series code Date: 03 April 07 for n = [1 3 5 ]; %alternative for n = 1:2:N sum =sum+ (-2/(n*pi))*(5*sin(2*pi*n*t)); end

Anan OsothsilpPage 6 Lab7 Frequency Spectrum of Fourier series Matlab code x = [ ]; y = 2*x; stem(x,y); N = 10; Wo = f*pi; for n = [-N:-1,1:N], Dn = 2/(j*n*Wo); stem(n*Wo,abs(Dn)) hold on; pause(1); end Generate magnitude spectrum of signal Date: 03 April 07

Anan OsothsilpPage 7 Lab7 N = 10; Wo = f*pi; for n = [-N:-1, 1:N], Dn = 2/(j*n*Wo); stem(n*Wo,angle(Dn)*180/pi) hold on; end Generate phase spectrum of signal Date: 03 April 07