Digital Signal Processing Instructor: Prof. Peng Yu Tel : 15904510911 : Office : Room 523, Bldg. 2A, Science Park Automatic Test and.

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Presentation transcript:

Digital Signal Processing Instructor: Prof. Peng Yu Tel : : Office : Room 523, Bldg. 2A, Science Park Automatic Test and Control Institute ( 53 专业) School of electrical engineering and automation Harbin Institute of Technology 2008 教育部双语教学示范课程

Three Questions about Digital Signal Processing Q1: WHAT is DSP? Q2: WHY is DSP? Q3: HOW to DSP? How to understand the concept of digital signal processing? What is the relationship between other courses, signal and system, etc. WHY we need DSP? It’s advantages and disadvantages? General procedure of DSP. How to implement DSP algorithm.

Introduction 1 Basic Concepts about Signal Definition Definition A Signal carries information and can be described as a function of independent variables in mathematics. A Signal carries information and can be described as a function of independent variables in mathematics. 本课程讨论的信号为随时间变化的一维电信号。

Classification of Signal Classification of Signal AnalogDigitalVS Time continuous discrete Time continuous discrete Amplitude continuous discrete ADC So, the signal is discrete-time signal in a strict manner. In undergraduate course, we only consider time discretization problem. In postgraduate course, amplitude quantization problem will be learned.

Signal Processing Signal Processing Computer, Semiconduct and Information Science  1960’s-1970’s  1960’s-1970’s Representation, transformation and manipulation Representation, transformation and manipulation of signals and the information they contain. of signals and the information they contain. Signal operation include: (1) Transform, filter, inspection, spectrum analysis; (1) Transform, filter, inspection, spectrum analysis; (2) Modulation and coding; (2) Modulation and coding; (3) Analog Signal Processing; (3) Analog Signal Processing; (4) Digital Signal Processing. (4) Digital Signal Processing.

IMAGE PROCESSING Pattern recognition Pattern recognition Robotic vision Robotic vision Image enhancement Image enhancement Satellite weather map Satellite weather map animation animation IMAGE PROCESSING Pattern recognition Pattern recognition Robotic vision Robotic vision Image enhancement Image enhancement Satellite weather map Satellite weather map animation animation INSTRUMENTATION & CONTROL Spectrum analysis Spectrum analysis Position and rate control Position and rate control Noise reduction Noise reduction Data compression Data compression INSTRUMENTATION & CONTROL Spectrum analysis Spectrum analysis Position and rate control Position and rate control Noise reduction Noise reduction Data compression Data compression SPEECH & AUDIO Speech recognition Speech recognition Speech synthesis Speech synthesis Text to speech Text to speech digital audio digital audio SPEECH & AUDIO Speech recognition Speech recognition Speech synthesis Speech synthesis Text to speech Text to speech digital audio digital audio MILITARY Secure communication Secure communication Radar processing Radar processing Sonar processing Sonar processing Missile guidance Missile guidanceMILITARY Secure communication Secure communication Radar processing Radar processing Sonar processing Sonar processing Missile guidance Missile guidance TELECOMMUNICATION Echo cancellation Echo cancellation Adaptive equalization Adaptive equalization Video conferencing Video conferencing data communication data communicationTELECOMMUNICATION Echo cancellation Echo cancellation Adaptive equalization Adaptive equalization Video conferencing Video conferencing data communication data communication Biomedical Patient monitoring Patient monitoring Scanners Scanners ECG (Electrocardiograph) ECG (Electrocardiograph) X-ray storage/enhancement X-ray storage/enhancementBiomedical Patient monitoring Patient monitoring Scanners Scanners ECG (Electrocardiograph) ECG (Electrocardiograph) X-ray storage/enhancement X-ray storage/enhancement Consumer applications digital, cellar mobile phones digital, cellar mobile phones universal mobile telecommunication system universal mobile telecommunication system digital television digital television digital camera digital camera internet music, phones and video internet music, phones and video digital answer machines, fax and modems digital answer machines, fax and modems voice mail system voice mail system interactive entertainment systems interactive entertainment systems Consumer applications digital, cellar mobile phones digital, cellar mobile phones universal mobile telecommunication system universal mobile telecommunication system digital television digital television digital camera digital camera internet music, phones and video internet music, phones and video digital answer machines, fax and modems digital answer machines, fax and modems voice mail system voice mail system interactive entertainment systems interactive entertainment systems

2 Basic concepts about system (1) System Device or technology of signal processing. Device or technology of signal processing. (2) Analog system System with analog input and output. System with analog input and output. (3) Digital system System with digital input and output. System with digital input and output.

Signals and Systems Basic model: Input: x Output: y Input: x Output: y DSP 、 FPGA 、 SOPC 、 SoC 、 Algorithm Codes

x y Given x and h, find yanalysis Given h and y, find xcontrol Given x and y, find hdesign or synthesis h Three Problems

3 Processing of analog signal with digital methods (1) Digitalized process for analog signals SampleQuantizerCoder x a (t) x(n) (2) Digital processing method A/DDSPD/A x a (t) y a (t) Filter x(n)y(n) Filter

4 Feature of Digital System (1) High accuracy: Floating point-8,16,32,64 bits (2) High reliability: VLSI (analog: drift, calibration) (3) Flexible: DSP, Software, FPGA, VHDL (4) Easy to integrate (5) Deal with high dimensional signals (6) Low costs: reusable, reconfigurable Advantages (7) Data logging (8) Adaptive capability

Disadvantages Complex: cost and speedComplex: cost and speed KXa(t)Ya(t) Analog Signal Processing A/DDSPD/A x a (t) y a (t) Filter x(n)y(n) Filter Digital Signal Processing

5 Study Case current SignalConditioning voltage freq temp humidity AnalogSwitches CPU A/DMEMODISP PC Printer Electrical/non- electrical measurement Automatic test system Analog/Digital Circuits Digital Signal Processing Environment monitoring System

When you speak, your voice is picked up by an analog sensor in the cell phone’s microphone An analog-to-digital converter chip converts your voice, which is an analog signal, into digital signals, represented by 1s and 0s. The DSP compresses the digital signals and removes background noise. In the listener’s cell phone, a digital-to-analog converter chip changes the digital signals back to an analog voice signal. Your voice exits the phone through the speaker. MORE APPLICATIONS

A MP3 Player

(3) Noise process  Digital filter (1) Selective of A/D  Signal representation - Sampling (2) Manipulation and transform  feature extraction and analysis 6. Objective of Digital Signal Processing Digital Signals Manipulation Digital filter Measurement Digital Signals Spectrum analysis Spectrum analysis Frequency division Frequency division Disturbance attenuation Disturbance attenuation

7. Research objectives 1-dimentional DSP, multi-dimentional DSP and the realization of DSP system 1D DSP: 1D discrete-time signals and system1D DSP: 1D discrete-time signals and system multi-D DSP: 2D or 3D image processing, etc.multi-D DSP: 2D or 3D image processing, etc. Realization of DSP system:Realization of DSP system: Realization of theoretical algorithm and system (filter) on software and hardware: including system architecture, chip selective, development of the software and hardware, etc. Realization of theoretical algorithm and system (filter) on software and hardware: including system architecture, chip selective, development of the software and hardware, etc.

8. Theory of digital signal processing Sampling of analog signalsSampling of analog signals A/D conversion, sampling theory, analysis of quantization errors; A/D conversion, sampling theory, analysis of quantization errors; Discrete-time signal analysisDiscrete-time signal analysis Time-domain and frequency-domain analysis, Fourier transform, z - transform, Hilbert transform; Time-domain and frequency-domain analysis, Fourier transform, z - transform, Hilbert transform; Discrete-time system analysisDiscrete-time system analysis System representation, causality and stability, time-invariant system, convolution, frequency response, digital filter design; System representation, causality and stability, time-invariant system, convolution, frequency response, digital filter design; Fast algorithm for signal processingFast algorithm for signal processing FFT, fast convolution and correlation; FFT, fast convolution and correlation; Special algorithm for signal processingSpecial algorithm for signal processing Interpolation, singular value analysis, deconvolution. Interpolation, singular value analysis, deconvolution.

9. Implementation of DSP system General-purpose computer;General-purpose computer; Micro-control unit;Micro-control unit; General-purpose DSP chip;General-purpose DSP chip; Specific-design DSP chip;Specific-design DSP chip; TI (leading manufacture, 70%) TI (leading manufacture, 70%) AD, Motorala, Lucent, NEC AD, Motorala, Lucent, NEC

10. Objectives of our learning Understand the concept: Main idea: solve the problem of analog signals with digital method with digital method Sample Sample Transform: time-domain  frequency domain Transform: time-domain  frequency domain Spectrum analysis Spectrum analysis Filter design Filter design Important tools: Method to design digital filter

11. Proposed syllabus for the course Total period: 50; Class: 40 Experiment: 10 Discrete-time signals and system Discrete-time signals and system Discrete Fourier transform Discrete Fourier transform FFT and its applications FFT and its applications Design of IIR digital filters Design of IIR digital filters Design of FIR digital filters Design of FIR digital filters

How to Learn ?

Curriculum in Signal Processing MathematicsMathematics Signals and SystemsSignals and Systems Signal processing theory and systemsSignal processing theory and systems Communications theory and systemsCommunications theory and systems Control theory and systemsControl theory and systems Applications and researchApplications and research

Mathematics for Signal Processing Algebra, calculus, differential equationsAlgebra, calculus, differential equations Linear algebra, matrices, vector spaces, functional analysisLinear algebra, matrices, vector spaces, functional analysis Probability, statistics, random processesProbability, statistics, random processes Computational mathematics, numerical analysis, algorithmsComputational mathematics, numerical analysis, algorithms Computer Science and EngineeringComputer Science and Engineering Math now has an experimental laboratoryMath now has an experimental laboratory

Modern Engineering is Design Science studies and describes what nature created, what already existsScience studies and describes what nature created, what already exists Engineering creates and builds what society wants and needs, what does not already existEngineering creates and builds what society wants and needs, what does not already exist Engineering uses mathematics in a different way from scienceEngineering uses mathematics in a different way from science

History of Teaching and Learning Engineering Engineering was first a trade which was learned through apprenticeshipEngineering was first a trade which was learned through apprenticeship Next, it was a profession which was learned through trainingNext, it was a profession which was learned through training Now it is a discipline which is learned through education. Modern liberal artsNow it is a discipline which is learned through education. Modern liberal arts

Training vs. Education Old Engineering: How do I build a bridge across the river?Old Engineering: How do I build a bridge across the river? New Engineering: How do I satisfy people ’ s desire to interact across the river?New Engineering: How do I satisfy people ’ s desire to interact across the river?

Training vs. Education Old system: Learn enough in the university to last your professional lifetimeOld system: Learn enough in the university to last your professional lifetime New system: In the university, learn the methods to continue to learn all of your life.New system: In the university, learn the methods to continue to learn all of your life. Old: study, work, then retire.Old: study, work, then retire. New: study and work and retire without boundaryNew: study and work and retire without boundary Transition from old to new system occurred around 50 years ago but education has not changedTransition from old to new system occurred around 50 years ago but education has not changed

Research in the New World In the old system, research was done by a small number of specialist in laboratories and graduate schoolIn the old system, research was done by a small number of specialist in laboratories and graduate school In the new system, research will be done by everybody in all levels of school and workIn the new system, research will be done by everybody in all levels of school and work Same true for “ Design ”Same true for “ Design ”

Education in the New System Shift emphasis from –Training to education –Teaching to learning (teacher to student) –Passive to active (and interactive) –Process to concept (concept inventory) –Understand to discover Need research in learning technical material

Technology for Education Matlab, Mathematica, Maple, LabViewMatlab, Mathematica, Maple, LabView OCW, Connexions, Wikipedia, GoogleOCW, Connexions, Wikipedia, Google Desktop, laptop, hand-held, mobile phone plus Internet; social software systemsDesktop, laptop, hand-held, mobile phone plus Internet; social software systems

Open Educational Resources The Open Educational Resource (OER) movement was inspired by the Open Source movement in software. Open Course Ware “ OCW ” (MIT)Open Course Ware “ OCW ” (MIT) Connexions “ Cnx ” (Rice)Connexions “ Cnx ” (Rice) Wikipedia (Wikibooks, etc.)Wikipedia (Wikibooks, etc.) Creative Commons “ CC ” (Stanford, Duke)Creative Commons “ CC ” (Stanford, Duke) Curriki, PLoS, EOL, Shuttleworth's Siyavula Project, CK-12 Project, OSI, etc.Curriki, PLoS, EOL, Shuttleworth's Siyavula Project, CK-12 Project, OSI, etc.

Interactive, Dynamic Virtual Lab

Multimedia

Matlab

Connexions Now Usage Repository: 7300 modules, 20,000 revisions, 405 courses or books, 7200 author accounts, 147 countries, print-on-demand books In Oct. 2008: 17M hits, 1.0M pages views, 520K unique users from 157 countries Globalization Europe: Germany, Norway, England, etc. Asia: China, India, Pakistan, Japan, Vietnam, Korea Africa: South Africa LACCEI: (conversation with Mexico, Argentina, Brazil, Chile, and Uruguay started)

Signal Processing Web Sites DSP an Rice: DSP at MIT: Connexions at Rice: OCW at MIT: Georgia Tech, Univ. of Illinois, University of Texas, Princeton, Stanford

Curriculum schedule Class: , , ; 66 students Lectures : 正心 226 4th-14th week, Mon: 5~6; Wen: 7~8; Experiments: 12th-13th week, G601, Thu, 5~6 Examination: 正心 42, 17th week, Thu, 10:00~12:00

12 Student Commitment Assignment Assignment Attendance in classes is mandatory ! Attendance in classes is mandatory ! Scores Scores Assignment + Experiment + Report: 10% Assignment + Experiment + Report: 10% Examination: 100% Examination: 100%

Presentation Project : 3~5 points Subject is assigned by teacher Discuss with instructor 3 days before presentation Criterion : Content, Clear and fluent, Team works

NEW STUFF LIMITED TIME LIMITED TIME LOTS OF WORK LOTS OF WORK PRESSURE PRESSURE METHODOLOGY METHODOLOGY PLAN PLAN EXECUTE EXECUTE TEAM WORK  HAVE TO SHARE NEW BEGINNING FOR YOURSELF ! NEW BEGINNING FOR YOURSELF ! FOR YOUR FUTURE LIFE! FOR YOUR FUTURE LIFE!

HOW TO GET WHAT YOU WANT ? WANTED !

Emule :电驴 P2P 软件 ICQ,AOL Instant Messenger,Yahoo Pager, MSN Messenger, Tencet QQ-most popular P2P.

REVIEW What is DSP ? Why DSP ? How to ? BRIEF INTRODUCTIONS

References 1 Discrete-time Signal Processing. A.V. Oppenheim, R.W.Schafer. Pearson Education , 2005,1 2 Digital Signals Processing——using MATLAB. Vinay K. Ingle,John G. ProakisISTE Publishing Company, Digital Signals Processing——using MATLAB. Vinay K. Ingle,John G. Proakis. ISTE Publishing Company, Real-time Digital Signal Processing – Implementation, Application and Experiments with the TMS320C55X. Sen M. Kuo, Bob H. Lee. WILEY, 2003,12 4 Introduction to Signal Processing. Sophocles J. Orfanidis. Prentice Hall, 1998,12 5 Fundamentals of Digital Signal Processing. Joyce Van de Vegte. Prentice Hall, 2003,1