Discrete-time Signals & Systems
|
|
- Melinda Hancock
- 5 years ago
- Views:
Transcription
1 Discrete-time Signals & Systems S Wongsa Dept. of Control Systems and Instrumentation Engineering, KMU JAN, Overview Signals & Systems Continuous & Discrete ime Sampling Sampling in Frequency Domain Sampling heorem Aliasing & Anti-Aliasing Filter 2
2 Lecture plan Lecture Date opic 1 4 & 5 Jan 11 Discrete-time signals and systems; Sampling of continuous-time signals 2 11 & 12 Jan 11 Discrete-ime Fourier ransform (DF) & Discrete-Fourier ransform (DF) 3 18 & 19 Jan 11 Fast Fourier ransform (FF) & Applications (Lab I) 4 25 & 26 Jan 11 z-ransform 5 1 & 2 Feb 11 ransform-domain analysis and LI systems 6 8 & 9 Feb 11 Discrete-time system analysis Lab (II) 7 15 & 16 Feb 11 utorial Course website: 3 Grading 1.) Graded homework worth 10% 2.) Laboratory assignments worth 10% 3.) Final MALAB exam worth 5% 4.) Final exam worth 25% 4
3 Recommended extbooks 1. Fundamentals of Signals and Systems Using MALAB, Edward W. Kamen and Bonnie S. Heck, Prentice Hall International Inc. 2. Discrete-time signal processing, A.V. Oppenheim, R.W. Schafer, and J. R. Buck, 2nd edition, Prentice Hall, Signals and Systems, Alan v. Oppenheim et al., 2nd Edition, Prentice Hall. 4. Signals and Systems, Simon Haykin & Barry Van Veen, 2nd edition, Wiley, Signals & Systems A signal is a varying phenomenon that can be measured. A system responses to particular signals by producing other signals. Source: Signals & Systems, MI, Fall
4 Signals & Systems An image is also a signal! Source: Yao Wang, Introduction, Review of Signals & Systems, Image Quality Metrics, Polytechnic University, Brooklyn, NY 7 Discrete-time processing of continuous-time signals Sampling Reconstruction e.g. DSP, Controller etc. Most of the signals in the physical world are C signals, e.g. voltage & current, pressure, temperature, velocity, etc. But digital computations are done in discrete time. Source: Signals & Systems, MI, Fall
5 Discrete-time processing of continuous-time signals Source: Prof. Mark Fowler, EECE 301 Signals & Systems, Binghamton University. 9 Discrete-time processing of continuous-time signals Sampling Reconstruction e.g. DSP, Controller etc. 10
6 DSP for Detection of Weld Defects Defects? Original image After DSP Porosity Incomplete penetration Source: W.Yuttiwat et al., Visual Inspection of Weld Defects by Radiography Image Processing, IE Network DSP: Biomedical Imaging X-Ray C MRI Magnetic Resonance Imaging make use of radiation to get an internal view of the body. be blocked by some form of dense tissue, therefore the image quality when looking at soft tissues will be poor. can pose the risk of irradiation. use a series of X-ray beams to create cross-sectional images. DSP is used to generate a 3D image of the internals of an object from a large series of 2D X-ray images taken around a single axis of rotation uses magnetic fields in conjunction with radio waves to give high detail in the soft tissues. No biological hazards have been reported with the use of the MRI. Source:
7 Audio Signal Processing Music Speech Generation e.g. ext-to-speech Synthesis, Voice conversion Speech Recognition Source: Discrete-time processing of continuous-time signals Sampling Reconstruction Source: Signals & Systems, MI, Fall
8 Sampling Sampling is the process of getting a discrete signal from a continuous one. It enables the processing of signal by digital computer. x (t) (t) x s Discrete-time signal x s ( t) = x( n ) = x[ n], n= 0, ± 1, ± 2,K where is a sampling time. 15 Sampling We would like to sample in a way that preserves information, which may not seem possible because information between samples is lost. How can we minimise the distortion of reconstructed signal? Source: Signals & Systems, MI, Fall
9 Sampling x(t) (t) x s (t) δ X x ( t) = x( t) δ ( t) s where n= δ ( t ) = δ ( t n ) 17 Sampling in frequency domain he Fourier transform of x s (t) : 1 X s ( ω) = X ( ω kωs ) k= where 2π ωs = is the sampling frequency in rad/sec. Goal: Determine under what conditions we get: Reconstructed C signal = Original C signal 18
10 Sampling in frequency domain If x(t) has bandwidth B and if ωs > 2B x(t) is a bandlimited signal. 1 X s ( ω) = X ( ω kωs ) k= he high frequency copies can be removed with a low-pass and then multiplying by to undo the amplitude scaling. 19 Sampling theorem A bandlimited signal with bandwidth B can be reconstructed completely and exactly from its samples as long as they are taken at rateωs > 2B ωs = 2B is called the Nyquist sampling frequency / Nyquist rate. NB: Sampling at Nyquist rate is only possible if an IDEAL lowpass filter is used. In practice we generally need to choose a sampling rate above the Nyquist rate. 20
11 What if the samples are not taken fast enough? (ω) X s Aliasing Aliasing -B B he high frequency components of x(t) will be transposed to low-frequency components, leading to a phenomenon called aliasing. 21 What if the signal is not bandlimited? For non-bandlimited signal aliasing always happens regardless of ω s value. 22
12 Aliasing What are the consequences of aliasing? - it makes two continuous sinusoids of different frequencies indistinguishable when sampled. 3 2 Amplitude ime (sec) Aliasing: a 52 Hz sinusoid sampled at 50 Hz. 23 Aliasing What are the consequences of aliasing? - a distorted version of the original signal x(t). Example: original music sampled at 44.1kHz (CD-quality) he at 4kHz downsampled version. 24
13 Anti-Aliasing Filter o avoid aliasing, in practice we use a C lowpass filter before the ADC to restrict the bandwidth of a signal to approximately satisfy the sampling theorem. Fs = 44.1 khz Source: Prof. Mark Fowler, EECE 301 Signals & Systems, Binghamton University. 25 Suggested Readings Steven W. Smith, Chapter 3: ADC and DAC, he Scientist and Engineer's Guide to Digital Signal Processing 26
14 Review Questions 1. If we used x(t) below and sampled it at 20 khz, how many samples would we have after 60 ms? x( t) = 3cos(2π 404t+ π / 4) + 2cos(2π 6510) + cos(2π 660t π / 5) 2. x(t) = 2 cos(2π700t 5π/2) + 3 cos(2π450t) + cos(2π630t + 2π/5) What is the minimum sampling rate for this signal? 3. A periodic signal with a period of 0.1 ms is sampled at 44 khz. o what frequency does the eighth harmonic alias? 27 Summary 28
Discrete-time Signals & Systems
Discrete-time Signals & Systems S Wongsa Dept. of Control Systems and Instrumentation Engineering, KMU JAN, 2010 1 Overview Signals & Systems Continuous & Discrete ime Sampling Sampling in Frequency Domain
More information6.003: Signals and Systems. Sampling
6.003: Signals and Systems Sampling April 27, 200 Mid-term Examination #3 om orrow: W ednesday, A pril 2 8, 7 : 3 0-9 : 3 0 pm. No recitations tomorrow. Coverage: Lectures 20 Recitations 20 Homeworks Homework
More information!"!#"#$% Lecture 2: Media Creation. Some materials taken from Prof. Yao Wang s slides RECAP
Lecture 2: Media Creation Some materials taken from Prof. Yao Wang s slides RECAP #% A Big Umbrella Content Creation: produce the media, compress it to a format that is portable/ deliverable Distribution:
More informationSampling of Continuous-Time Signals. Reference chapter 4 in Oppenheim and Schafer.
Sampling of Continuous-Time Signals Reference chapter 4 in Oppenheim and Schafer. Periodic Sampling of Continuous Signals T = sampling period fs = sampling frequency when expressing frequencies in radians
More informationContinuous vs. Discrete signals. Sampling. Analog to Digital Conversion. CMPT 368: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals
Continuous vs. Discrete signals CMPT 368: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University January 22,
More informationEE 351M Digital Signal Processing
EE 351M Digital Signal Processing Course Details Objective Establish a background in Digital Signal Processing Theory Required Text Discrete-Time Signal Processing, Prentice Hall, 2 nd Edition Alan Oppenheim,
More informationLaboratory Assignment 5 Amplitude Modulation
Laboratory Assignment 5 Amplitude Modulation PURPOSE In this assignment, you will explore the use of digital computers for the analysis, design, synthesis, and simulation of an amplitude modulation (AM)
More informationIslamic University of Gaza. Faculty of Engineering Electrical Engineering Department Spring-2011
Islamic University of Gaza Faculty of Engineering Electrical Engineering Department Spring-2011 DSP Laboratory (EELE 4110) Lab#4 Sampling and Quantization OBJECTIVES: When you have completed this assignment,
More informationMusic 270a: Fundamentals of Digital Audio and Discrete-Time Signals
Music 270a: Fundamentals of Digital Audio and Discrete-Time Signals Tamara Smyth, trsmyth@ucsd.edu Department of Music, University of California, San Diego October 3, 2016 1 Continuous vs. Discrete signals
More informationExperiment 8: Sampling
Prepared By: 1 Experiment 8: Sampling Objective The objective of this Lab is to understand concepts and observe the effects of periodically sampling a continuous signal at different sampling rates, changing
More informationCMPT 318: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals
CMPT 318: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University January 16, 2006 1 Continuous vs. Discrete
More informationSampling and Reconstruction of Analog Signals
Sampling and Reconstruction of Analog Signals Chapter Intended Learning Outcomes: (i) Ability to convert an analog signal to a discrete-time sequence via sampling (ii) Ability to construct an analog signal
More informationDesign IV. E232 Spring 07
Design IV Spring 07 Class 8 Bruce McNair bmcnair@stevens.edu 8-1/38 Computerized Data Acquisition Measurement system architecture System under test sensor sensor sensor sensor signal conditioning signal
More informationPulse Code Modulation (PCM)
Project Title: e-laboratories for Physics and Engineering Education Tempus Project: contract # 517102-TEMPUS-1-2011-1-SE-TEMPUS-JPCR 1. Experiment Category: Electrical Engineering >> Communications 2.
More informationSignals and Systems. Lecture 13 Wednesday 6 th December 2017 DR TANIA STATHAKI
Signals and Systems Lecture 13 Wednesday 6 th December 2017 DR TANIA STATHAKI READER (ASSOCIATE PROFFESOR) IN SIGNAL PROCESSING IMPERIAL COLLEGE LONDON Continuous time versus discrete time Continuous time
More informationDigital Signal Processing
Digital Signal Processing Lecture 9 Discrete-Time Processing of Continuous-Time Signals Alp Ertürk alp.erturk@kocaeli.edu.tr Analog to Digital Conversion Most real life signals are analog signals These
More informationOutline. Introduction to Biosignal Processing. Overview of Signals. Measurement Systems. -Filtering -Acquisition Systems (Quantisation and Sampling)
Outline Overview of Signals Measurement Systems -Filtering -Acquisition Systems (Quantisation and Sampling) Digital Filtering Design Frequency Domain Characterisations - Fourier Analysis - Power Spectral
More informationInterfacing a Microprocessor to the Analog World
Interfacing a Microprocessor to the Analog World In many systems, the embedded processor must interface to the non-digital, analog world. The issues involved in such interfacing are complex, and go well
More informationSyllabus Cosines Sampled Signals. Lecture 1: Cosines. ECE 401: Signal and Image Analysis. University of Illinois 1/19/2017
Lecture 1: Cosines ECE 401: Signal and Image Analysis University of Illinois 1/19/2017 1 Syllabus 2 Cosines 3 Sampled Signals Outline 1 Syllabus 2 Cosines 3 Sampled Signals Who should take this course?
More informationLecture Schedule: Week Date Lecture Title
http://elec3004.org Sampling & More 2014 School of Information Technology and Electrical Engineering at The University of Queensland Lecture Schedule: Week Date Lecture Title 1 2-Mar Introduction 3-Mar
More informationFinal Exam Solutions June 7, 2004
Name: Final Exam Solutions June 7, 24 ECE 223: Signals & Systems II Dr. McNames Write your name above. Keep your exam flat during the entire exam period. If you have to leave the exam temporarily, close
More informationDIGITAL SIGNAL PROCESSING. Chapter 1 Introduction to Discrete-Time Signals & Sampling
DIGITAL SIGNAL PROCESSING Chapter 1 Introduction to Discrete-Time Signals & Sampling by Dr. Norizam Sulaiman Faculty of Electrical & Electronics Engineering norizam@ump.edu.my OER Digital Signal Processing
More informationBased with permission on lectures by John Getty Laboratory Electronics II (PHSX262) Spring 2011 Lecture 9 Page 1
Today 3// Lecture 9 Analog Digital Conversion Sampled Data Acquisition Systems Discrete Sampling and Nyquist Digital to Analog Conversion Analog to Digital Conversion Homework Study for Exam next week
More informationPYKC 27 Feb 2017 EA2.3 Electronics 2 Lecture PYKC 27 Feb 2017 EA2.3 Electronics 2 Lecture 11-2
In this lecture, I will introduce the mathematical model for discrete time signals as sequence of samples. You will also take a first look at a useful alternative representation of discrete signals known
More information! Where are we on course map? ! What we did in lab last week. " How it relates to this week. ! Sampling/Quantization Review
! Where are we on course map?! What we did in lab last week " How it relates to this week! Sampling/Quantization Review! Nyquist Shannon Sampling Rate! Next Lab! References Lecture #2 Nyquist-Shannon Sampling
More informationSpectrogram Review The Sampling Problem: 2π Ambiguity Fourier Series. Lecture 6: Sampling. ECE 401: Signal and Image Analysis. University of Illinois
Lecture 6: Sampling ECE 401: Signal and Image Analysis University of Illinois 2/7/2017 1 Spectrogram Review 2 The Sampling Problem: 2π Ambiguity 3 Fourier Series Outline 1 Spectrogram Review 2 The Sampling
More informationEE422G Solution to Homework #8
EE4G Solution to Homework #8. MATLAB >> H = tf([ 4],[ 6 6]); >> H = tf([ ],[ - 5 5 4]); >> step(h).7 Step Response.6.5 Amplitude.4... 4 5 6 >> step(h) Time (sec).5 Step Response.5 Amplitude.5.5.5..5..5..5.4.45
More informationEE 230 Lecture 39. Data Converters. Time and Amplitude Quantization
EE 230 Lecture 39 Data Converters Time and Amplitude Quantization Review from Last Time: Time Quantization How often must a signal be sampled so that enough information about the original signal is available
More informationAnalog-Digital Interface
Analog-Digital Interface Tuesday 24 November 15 Summary Previous Class Dependability Today: Redundancy Error Correcting Codes Analog-Digital Interface Converters, Sensors / Actuators Sampling DSP Frequency
More informationDigital Processing of Continuous-Time Signals
Chapter 4 Digital Processing of Continuous-Time Signals 清大電機系林嘉文 cwlin@ee.nthu.edu.tw 03-5731152 Original PowerPoint slides prepared by S. K. Mitra 4-1-1 Digital Processing of Continuous-Time Signals Digital
More informationData Acquisition Systems. Signal DAQ System The Answer?
Outline Analysis of Waveforms and Transforms How many Samples to Take Aliasing Negative Spectrum Frequency Resolution Synchronizing Sampling Non-repetitive Waveforms Picket Fencing A Sampled Data System
More informationDigital Processing of
Chapter 4 Digital Processing of Continuous-Time Signals 清大電機系林嘉文 cwlin@ee.nthu.edu.tw 03-5731152 Original PowerPoint slides prepared by S. K. Mitra 4-1-1 Digital Processing of Continuous-Time Signals Digital
More informationLecture 7 Frequency Modulation
Lecture 7 Frequency Modulation Fundamentals of Digital Signal Processing Spring, 2012 Wei-Ta Chu 2012/3/15 1 Time-Frequency Spectrum We have seen that a wide range of interesting waveforms can be synthesized
More informationDSP First, 2/e. This Lecture: LECTURE #1 Sinusoids. Appendix B: MATLAB
DSP First, 2/e LECURE #1 Sinusoids READING ASSIGNMENS his Lecture: Chapter 2, Sections 2-1 and 2-2 Chapter 1: Introduction Appendix B: MALAB Review Appendix A on Complex Numbers Aug 2016 2003-2016, JH
More informationDigital Signal Processing Lecture 1
Remote Sensing Laboratory Dept. of Information Engineering and Computer Science University of Trento Via Sommarive, 14, I-38123 Povo, Trento, Italy Digital Signal Processing Lecture 1 Prof. Begüm Demir
More informationSampling and Signal Processing
Sampling and Signal Processing Sampling Methods Sampling is most commonly done with two devices, the sample-and-hold (S/H) and the analog-to-digital-converter (ADC) The S/H acquires a continuous-time signal
More informationENGR 210 Lab 12: Sampling and Aliasing
ENGR 21 Lab 12: Sampling and Aliasing In the previous lab you examined how A/D converters actually work. In this lab we will consider some of the consequences of how fast you sample and of the signal processing
More informationECEGR Lab #8: Introduction to Simulink
Page 1 ECEGR 317 - Lab #8: Introduction to Simulink Objective: By: Joe McMichael This lab is an introduction to Simulink. The student will become familiar with the Help menu, go through a short example,
More informationECE 556 BASICS OF DIGITAL SPEECH PROCESSING. Assıst.Prof.Dr. Selma ÖZAYDIN Spring Term-2017 Lecture 2
ECE 556 BASICS OF DIGITAL SPEECH PROCESSING Assıst.Prof.Dr. Selma ÖZAYDIN Spring Term-2017 Lecture 2 Analog Sound to Digital Sound Characteristics of Sound Amplitude Wavelength (w) Frequency ( ) Timbre
More informationLaboratory Assignment 4. Fourier Sound Synthesis
Laboratory Assignment 4 Fourier Sound Synthesis PURPOSE This lab investigates how to use a computer to evaluate the Fourier series for periodic signals and to synthesize audio signals from Fourier series
More informationBasic Signals and Systems
Chapter 2 Basic Signals and Systems A large part of this chapter is taken from: C.S. Burrus, J.H. McClellan, A.V. Oppenheim, T.W. Parks, R.W. Schafer, and H. W. Schüssler: Computer-based exercises for
More informationNON-UNIFORM SIGNALING OVER BAND-LIMITED CHANNELS: A Multirate Signal Processing Approach. Omid Jahromi, ID:
NON-UNIFORM SIGNALING OVER BAND-LIMITED CHANNELS: A Multirate Signal Processing Approach ECE 1520S DATA COMMUNICATIONS-I Final Exam Project By: Omid Jahromi, ID: 009857325 Systems Control Group, Dept.
More informationEECE 301 Signals & Systems Prof. Mark Fowler
EECE 301 Signals & Systems Prof. Mark Fowler Note Set #16 C-T Signals: Using FT Properties 1/12 Recall that FT Properties can be used for: 1. Expanding use of the FT table 2. Understanding real-world concepts
More informationFinal Exam Solutions June 14, 2006
Name or 6-Digit Code: PSU Student ID Number: Final Exam Solutions June 14, 2006 ECE 223: Signals & Systems II Dr. McNames Keep your exam flat during the entire exam. If you have to leave the exam temporarily,
More informationEEE33350 Signals and Data Communications
Palestine Technical College Engineering Professions Department EEE33350 Signals and Data Communications Syllabus Nasser M. Sabah Teaching & Learning Strategies 2 Teaching Strategies Presentation Lecture
More informationCommunications IB Paper 6 Handout 3: Digitisation and Digital Signals
Communications IB Paper 6 Handout 3: Digitisation and Digital Signals Jossy Sayir Signal Processing and Communications Lab Department of Engineering University of Cambridge jossy.sayir@eng.cam.ac.uk Lent
More informationMassachusetts Institute of Technology Dept. of Electrical Engineering and Computer Science Fall Semester, Introduction to EECS 2
Massachusetts Institute of Technology Dept. of Electrical Engineering and Computer Science Fall Semester, 2006 6.082 Introduction to EECS 2 Modulation and Demodulation Introduction A communication system
More informationANALOGUE AND DIGITAL COMMUNICATION
ANALOGUE AND DIGITAL COMMUNICATION Syed M. Zafi S. Shah Umair M. Qureshi Lecture xxx: Analogue to Digital Conversion Topics Pulse Modulation Systems Advantages & Disadvantages Pulse Code Modulation Pulse
More informationece 429/529 digital signal processing robin n. strickland ece dept, university of arizona ECE 429/529 RNS
ece 429/529 digital signal processing robin n. strickland ece dept, university of arizona 2007 SPRING 2007 SCHEDULE All dates are tentative. Lesson Day Date Learning outcomes to be Topics Textbook HW/PROJECT
More informationDigital Video and Audio Processing. Winter term 2002/ 2003 Computer-based exercises
Digital Video and Audio Processing Winter term 2002/ 2003 Computer-based exercises Rudolf Mester Institut für Angewandte Physik Johann Wolfgang Goethe-Universität Frankfurt am Main 6th November 2002 Chapter
More informationThe Fundamentals of Mixed Signal Testing
The Fundamentals of Mixed Signal Testing Course Information The Fundamentals of Mixed Signal Testing course is designed to provide the foundation of knowledge that is required for testing modern mixed
More informationDigital Signal Processing Lecture 1 - Introduction
Digital Signal Processing - Electrical Engineering and Computer Science University of Tennessee, Knoxville August 20, 2015 Overview 1 2 3 4 Basic building blocks in DSP Frequency analysis Sampling Filtering
More informationCS3291: Digital Signal Processing
CS39 Exam Jan 005 //08 /BMGC University of Manchester Department of Computer Science First Semester Year 3 Examination Paper CS39: Digital Signal Processing Date of Examination: January 005 Answer THREE
More informationChapter 1 INTRODUCTION TO DIGITAL SIGNAL PROCESSING 1.6 Analog Filters 1.7 Applications of Analog Filters
Chapter 1 INTRODUCTION TO DIGITAL SIGNAL PROCESSING 1.6 Analog Filters 1.7 Applications of Analog Filters Copyright c 2005 Andreas Antoniou Victoria, BC, Canada Email: aantoniou@ieee.org July 14, 2018
More informationSystem on a Chip. Prof. Dr. Michael Kraft
System on a Chip Prof. Dr. Michael Kraft Lecture 5: Data Conversion ADC Background/Theory Examples Background Physical systems are typically analogue To apply digital signal processing, the analogue signal
More informationRecall. Sampling. Why discrete time? Why discrete time? Many signals are continuous-time signals Light Object wave CCD
Recall Many signals are continuous-time signals Light Object wave CCD Sampling mic Lens change of voltage change of voltage 2 Why discrete time? With the advance of computer technology, we want to process
More informationESE 531: Digital Signal Processing
ESE 531: Digital Signal Processing Lec 1: January 17, 2019 Introduction and Overview Lecture Outline! Course Topics Overview! Learning Objectives! Course Structure! Course Policies! Course Content! What
More informationDSP First, 2/e. LECTURE #1 Sinusoids. Aug , JH McClellan & RW Schafer
DSP First, 2/e LECTURE #1 Sinusoids Aug 2016 2003-2016, JH McClellan & RW Schafer 1 License Info for DSPFirst Slides This work released under a Creative Commons License with the following terms: Attribution
More informationA Low-Cost Programmable Arbitrary Function Generator for Educational Environment
Paper ID #5740 A Low-Cost Programmable Arbitrary Function Generator for Educational Environment Mr. Mani Dargahi Fadaei, Azad University Mani Dargahi Fadaei received B.S. in electrical engineering from
More informationHideo Okawara s Mixed Signal Lecture Series. DSP-Based Testing Fundamentals 6 Spectrum Analysis -- FFT
Hideo Okawara s Mixed Signal Lecture Series DSP-Based Testing Fundamentals 6 Spectrum Analysis -- FFT Verigy Japan October 008 Preface to the Series ADC and DAC are the most typical mixed signal devices.
More informationfor amateur radio applications and beyond...
for amateur radio applications and beyond... Table of contents Numerically Controlled Oscillator (NCO) Basic implementation Optimization for reduced ROM table sizes Achievable performance with FPGA implementations
More informationSignals and Systems Lecture 6: Fourier Applications
Signals and Systems Lecture 6: Fourier Applications Farzaneh Abdollahi Department of Electrical Engineering Amirkabir University of Technology Winter 2012 arzaneh Abdollahi Signal and Systems Lecture 6
More informationCT111 Introduction to Communication Systems Lecture 9: Digital Communications
CT111 Introduction to Communication Systems Lecture 9: Digital Communications Yash M. Vasavada Associate Professor, DA-IICT, Gandhinagar 31st January 2018 Yash M. Vasavada (DA-IICT) CT111: Intro to Comm.
More informationFig 1 describes the proposed system. Keywords IIR, FIR, inverse Chebyshev, Elliptic, LMS, RLS.
Design of approximately linear phase sharp cut-off discrete-time IIR filters using adaptive linear techniques of channel equalization. IIT-Madras R.Sharadh, Dual Degree--Communication Systems rsharadh@yahoo.co.in
More informationECE Digital Signal Processing
University of Louisville Instructor:Professor Aly A. Farag Department of Electrical and Computer Engineering Spring 2006 ECE 520 - Digital Signal Processing Catalog Data: Office hours: Objectives: ECE
More informationIntroduction to Digital Signal Processing (Discrete-time Signal Processing)
Introduction to Digital Signal Processing (Discrete-time Signal Processing) Prof. Chu-Song Chen Research Center for Info. Tech. Innovation, Academia Sinica, Taiwan Dept. CSIE & GINM National Taiwan University
More informationChapter 9. Chapter 9 275
Chapter 9 Chapter 9: Multirate Digital Signal Processing... 76 9. Decimation... 76 9. Interpolation... 8 9.. Linear Interpolation... 85 9.. Sampling rate conversion by Non-integer factors... 86 9.. Illustration
More informationEEE 311: Digital Signal Processing I
EEE 311: Digital Signal Processing I Course Teacher: Dr Newaz Md Syur Rahim Associated Proessor, Dept o EEE, BUET, Dhaka 1000 Syllabus: As mentioned in your course calendar Reerence Books: 1 Digital Signal
More informationMultirate Signal Processing, DSV2 Introduction Lecture: Mi., 9-10:30 HU 010 Seminar: Do. 9-10:30, K2032
Multirate Signal Processing, DSV2 Introduction Lecture: Mi., 9-10:30 HU 010 Seminar: Do. 9-10:30, K2032 Website contains the slides www.tu-ilmenau.de/mt Lehrveranstaltungen Master Multirate Signal Processing
More informationSpring 2018 EE 445S Real-Time Digital Signal Processing Laboratory Prof. Evans. Homework #1 Sinusoids, Transforms and Transfer Functions
Spring 2018 EE 445S Real-Time Digital Signal Processing Laboratory Prof. Homework #1 Sinusoids, Transforms and Transfer Functions Assigned on Friday, February 2, 2018 Due on Friday, February 9, 2018, by
More informationEDISP (English) Digital Signal Processing
EDISP (English) Digital Signal Processing Jacek Misiurewicz e-mail: jmisiure@elka.pw.edu.pl lecturer: Damian Gromek e-mail: dgromek@ise.pw.edu.pl Institute of Electronic Systems Warsaw University of Technology
More informationLAB #7: Digital Signal Processing
LAB #7: Digital Signal Processing Equipment: Pentium PC with NI PCI-MIO-16E-4 data-acquisition board NI BNC 2120 Accessory Box VirtualBench Instrument Library version 2.6 Function Generator (Tektronix
More informationMultirate Signal Processing Lecture 7, Sampling Gerald Schuller, TU Ilmenau
Multirate Signal Processing Lecture 7, Sampling Gerald Schuller, TU Ilmenau (Also see: Lecture ADSP, Slides 06) In discrete, digital signal we use the normalized frequency, T = / f s =: it is without a
More informationDigital Signal Processing (Subject Code: 7EC2)
CIITM, JAIPUR (DEPARTMENT OF ELECTRONICS & COMMUNICATION) Notes Digital Signal Processing (Subject Code: 7EC2) Prepared Class: B. Tech. IV Year, VII Semester Syllabus UNIT 1: SAMPLING - Discrete time processing
More informationDigital Signal Processing +
Digital Signal Processing + Nikil Dutt UC Irvine ICS 212 Winter 2005 + Material adapted from Tony Givargis & Rajesh Gupta Templates from Prabhat Mishra ICS212 WQ05 (Dutt) DSP 1 Introduction Any interesting
More informationLecture 3 Review of Signals and Systems: Part 2. EE4900/EE6720 Digital Communications
EE4900/EE6720: Digital Communications 1 Lecture 3 Review of Signals and Systems: Part 2 Block Diagrams of Communication System Digital Communication System 2 Informatio n (sound, video, text, data, ) Transducer
More informationMoving from continuous- to discrete-time
Moving from continuous- to discrete-time Sampling ideas Uniform, periodic sampling rate, e.g. CDs at 44.1KHz First we will need to consider periodic signals in order to appreciate how to interpret discrete-time
More informationYEDITEPE UNIVERSITY ENGINEERING FACULTY COMMUNICATION SYSTEMS LABORATORY EE 354 COMMUNICATION SYSTEMS
YEDITEPE UNIVERSITY ENGINEERING FACULTY COMMUNICATION SYSTEMS LABORATORY EE 354 COMMUNICATION SYSTEMS EXPERIMENT 3: SAMPLING & TIME DIVISION MULTIPLEX (TDM) Objective: Experimental verification of the
More information16.30 Learning Objectives and Practice Problems - - Lectures 16 through 20
16.30 Learning Objectives and Practice Problems - - Lectures 16 through 20 IV. Lectures 16-20 IVA : Sampling, Aliasing, and Reconstruction JVV 9.5, Lecture Notes on Shannon - Understand the mathematical
More informationSIGNALS AND SYSTEMS LABORATORY 13: Digital Communication
SIGNALS AND SYSTEMS LABORATORY 13: Digital Communication INTRODUCTION Digital Communication refers to the transmission of binary, or digital, information over analog channels. In this laboratory you will
More informationProblems from the 3 rd edition
(2.1-1) Find the energies of the signals: a) sin t, 0 t π b) sin t, 0 t π c) 2 sin t, 0 t π d) sin (t-2π), 2π t 4π Problems from the 3 rd edition Comment on the effect on energy of sign change, time shifting
More informationDesign of a Sharp Linear-Phase FIR Filter Using the α-scaled Sampling Kernel
Proceedings of the 6th WSEAS International Conference on SIGNAL PROCESSING, Dallas, Texas, USA, March 22-24, 2007 129 Design of a Sharp Linear-Phase FIR Filter Using the -scaled Sampling Kernel K.J. Kim,
More informationPROBLEM SET 5. Reminder: Quiz 1will be on March 6, during the regular class hour. Details to follow. z = e jω h[n] H(e jω ) H(z) DTFT.
PROBLEM SET 5 Issued: 2/4/9 Due: 2/22/9 Reading: During the past week we continued our discussion of the impact of pole/zero locations on frequency response, focusing on allpass systems, minimum and maximum-phase
More informationMultirate Digital Signal Processing
Multirate Digital Signal Processing Basic Sampling Rate Alteration Devices Up-sampler - Used to increase the sampling rate by an integer factor Down-sampler - Used to increase the sampling rate by an integer
More informationMultirate DSP, part 3: ADC oversampling
Multirate DSP, part 3: ADC oversampling Li Tan - May 04, 2008 Order this book today at www.elsevierdirect.com or by calling 1-800-545-2522 and receive an additional 20% discount. Use promotion code 92562
More informationEECE 323 Fundamentals of Digital Signal Processing. Spring Section A. Practical Homework MATLAB Application on Aliasing and Antialiasing
EECE 323 Fundamentals of Digital Signal Processing Spring 2013 Section A Practical Homework MATLAB Application on Aliasing and Antialiasing Student Name: Sharbel Dahlan ID: 1004018456 Instructor: Dr. Jinane
More informationAdvantages of Analog Representation. Varies continuously, like the property being measured. Represents continuous values. See Figure 12.
Analog Signals Signals that vary continuously throughout a defined range. Representative of many physical quantities, such as temperature and velocity. Usually a voltage or current level. Digital Signals
More informationExperiment 4 Sampling and Aliasing
Experiment 4 ampling and Aliasing INTRODUCTION One of the basic processes found in digital communications is sampling. Continuous signals from analog sources such as voice, music, video or other forms
More informationBeyond Nyquist. Joel A. Tropp. Applied and Computational Mathematics California Institute of Technology
Beyond Nyquist Joel A. Tropp Applied and Computational Mathematics California Institute of Technology jtropp@acm.caltech.edu With M. Duarte, J. Laska, R. Baraniuk (Rice DSP), D. Needell (UC-Davis), and
More informationA102 Signals and Systems for Hearing and Speech: Final exam answers
A12 Signals and Systems for Hearing and Speech: Final exam answers 1) Take two sinusoids of 4 khz, both with a phase of. One has a peak level of.8 Pa while the other has a peak level of. Pa. Draw the spectrum
More informationInfocommunication. Sampling, Quantization. - Bálint TÓTH, BME TMIT -
Infocommunication Sampling, Quantization - Bálint TÓTH, BME TMIT - Overview PPT is for demonstration, not for learning! Analog signals problem: noise, distortion Digital signals what are the benefits?
More informationChapter-2 SAMPLING PROCESS
Chapter-2 SAMPLING PROCESS SAMPLING: A message signal may originate from a digital or analog source. If the message signal is analog in nature, then it has to be converted into digital form before it can
More informationExperiment No. 6. Audio Tone Control Amplifier
Experiment No. 6. Audio Tone Control Amplifier By: Prof. Gabriel M. Rebeiz The University of Michigan EECS Dept. Ann Arbor, Michigan Goal: The goal of Experiment #6 is to build and test a tone control
More informationChapter 2: Digitization of Sound
Chapter 2: Digitization of Sound Acoustics pressure waves are converted to electrical signals by use of a microphone. The output signal from the microphone is an analog signal, i.e., a continuous-valued
More informationSpectrum Analysis - Elektronikpraktikum
Spectrum Analysis Introduction Why measure a spectra? In electrical engineering we are most often interested how a signal develops over time. For this time-domain measurement we use the Oscilloscope. Like
More informationAudio Restoration Based on DSP Tools
Audio Restoration Based on DSP Tools EECS 451 Final Project Report Nan Wu School of Electrical Engineering and Computer Science University of Michigan Ann Arbor, MI, United States wunan@umich.edu Abstract
More informationECE 201: Introduction to Signal Analysis
ECE 201: Introduction to Signal Analysis Prof. Paris Last updated: October 9, 2007 Part I Spectrum Representation of Signals Lecture: Sums of Sinusoids (of different frequency) Introduction Sum of Sinusoidal
More informationProject 2 - Speech Detection with FIR Filters
Project 2 - Speech Detection with FIR Filters ECE505, Fall 2015 EECS, University of Tennessee (Due 10/30) 1 Objective The project introduces a practical application where sinusoidal signals are used to
More informationPROBLEM SET 6. Note: This version is preliminary in that it does not yet have instructions for uploading the MATLAB problems.
PROBLEM SET 6 Issued: 2/32/19 Due: 3/1/19 Reading: During the past week we discussed change of discrete-time sampling rate, introducing the techniques of decimation and interpolation, which is covered
More information2: Audio Basics. Audio Basics. Mark Handley
2: Audio Basics Mark Handley Audio Basics Analog to Digital Conversion Sampling Quantization Aliasing effects Filtering Companding PCM encoding Digital to Analog Conversion 1 Analog Audio Sound Waves (compression
More information