Digital Signal Processing 2008 教育部双语教学示范课程 Prof. Pengyu Tel：15904510911 Email：pengyu@hit.edu.cn Office：Room 526, Bldg. 2A, Science Park Automatic Test and Control Institute （53专业） School of electrical engineering and automation Harbin Institute of Technology

Introduction 1 Basic Concepts about Signal Definition A Signal carries information and can be described as a function of independent variables in mathematics. Variable of Signals： Time/Distance/Temperature/Voltage One-dimensional Signals： Single variable y=x(t) Two-dimensional Signals： Two variables Three-dimensional Signals ：Three variables

Classification of Signal Continuous-time and discrete-time signal Analog and digital signal (time and amplitude) (1) Continuous-time signal： (2) Discrete-time signal：Discrete variableContinuous amplitude Time-domain discrete signals (3) Analog Signal: Continuous variableContinuous amplitude Speech, Television, Time-domain continuous signals (4) Digital Signal：Discrete variablesDiscrete amplitude Quantized discrete-time signals

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

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

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

Signals and Systems Basic model: Input: x Output: y System: h DSP、FPGA、SOPC、SOC、Algorithm Codes 2017/4/21

x y Three Problems h Given x and h, find y analysis Given h and y, find x control Given x and y, find h design or synthesis 2017/4/21

3 Processing of analog signal with digital methods (1) Digitalized process for analog signals Sample Quantizer Coder xa(t) x(n) (2) Digital processing method A/D DSP D/A xa(t) ya(t) Filter x(n) y(n)

4 Feature of Digital System Advantages (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 (7) Data logging (8) Adaptive capability

Complex: cost and speed Disadvantages Complex: cost and speed K Xa(t) Ya(t) Analog Signal Processing A/D DSP D/A xa(t) ya(t) Filter x(n) y(n) Digital Signal Processing

Environment monitoring System 5 Study Case Environment monitoring System current Signal Conditioning voltage freq temp humidity Analog Switches CPU A/D MEMO DISP PC Printer Electrical/non-electrical measurement Analog/Digital Circuits Automatic test system Digital Signal Processing

MORE APPLICATIONS 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.

A MP3 Player

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

7. Research objectives 1-dimentional DSP, multi-dimentional DSP and the realization of DSP system 1D DSP: 1D discrete-time signals and system multi-D DSP: 2D or 3D image processing, etc. 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.

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

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

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

11. Proposed syllabus for the course Total period: 46; Class: 40 Experiment: 6 Discrete-time signals and system Discrete Fourier transform FFT and its applications Design of IIR digital filters Design of FIR digital filters

How to Learn ? 2017/4/21

Curriculum in Signal Processing Mathematics Signals and Systems Signal processing theory and systems Communications theory and systems Control theory and systems Applications and research 2017/4/21

Mathematics for Signal Processing Algebra, calculus, differential equations Linear algebra, matrices, vector spaces, functional analysis Probability, statistics, random processes Computational mathematics, numerical analysis, algorithms Computer Science and Engineering Math now has an experimental laboratory 2017/4/21

Modern Engineering is Design Science studies and describes what nature created, what already exists Engineering creates and builds what society wants and needs, what does not already exist Engineering uses mathematics in a different way from science 2017/4/21

History of Teaching and Learning Engineering Engineering was first a trade which was learned through apprenticeship Next, it was a profession which was learned through training Now it is a discipline which is learned through education. Modern liberal arts 2017/4/21

Training vs. Education 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? 2017/4/21

Training vs. Education Old 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. Old: study, work, then retire. New: study and work and retire without boundary Transition from old to new system occurred around 50 years ago but education has not changed 2017/4/21

Research in the New World In 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 work Same true for “Design” 2017/4/21

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 2017/4/21

Technology for Education Matlab, Mathematica, Maple, LabView OCW, Connexions, Wikipedia, Google Desktop, laptop, hand-held, mobile phone plus Internet; social software systems 2017/4/21

Open Educational Resources The Open Educational Resource (OER) movement was inspired by the Open Source movement in software. Open Course Ware “OCW” (MIT) Connexions “Cnx” (Rice) Wikipedia (Wikibooks, etc.) Creative Commons “CC” (Stanford, Duke) Curriki, PLoS, EOL, Shuttleworth's Siyavula Project, CK-12 Project, OSI, etc. 2017/4/21

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Interactive, Dynamic Virtual Lab COMPANIES LIKE NATIONAL INSTRUMENTS ARE MIXING THEIR POWERFUL SIMULATION ENVIRONMENTS INTO SCIENCE AND ENGINEERING COURSES… 2017/4/21

Multimedia CREATING AN INTERACATVITY THAT IS IMPOSSIBLE WITH A STATIC PAPER TEXTBOOK 2017/4/21

That can be translated by both companies and by volunteers into chinese, japanese, and thai to enable true world wide use of the materials 2017/4/21

Matlab www.mathworks.com

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) 2017/4/21

Signal Processing Web Sites DSP an Rice: http://www-dsp.rice.edu/ DSP at MIT: http://www.rle.mit.edu/ Connexions at Rice: http://cnx.org/ OCW at MIT: Georgia Tech, Univ. of Illinois, University of Texas, Princeton, Stanford 2017/4/21

Curriculum schedule Class: 0601104，0601201，0601202；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 Attendance in classes is mandatory ! Scores Assignment + Experiment + Report: 10% 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 LOTS OF WORK PRESSURE METHODOLOGY PLAN EXECUTE TEAM WORK  HAVE TO SHARE NEW BEGINNING FOR YOURSELF ! FOR YOUR FUTURE LIFE!

HOW TO GET WHAT YOU WANT ? WANTED !

BE ACTIVE IN YOUR STUDY! Emule：电驴 P2P软件 http://www.emule.org.cn ICQ,AOL Instant Messenger,Yahoo Pager, MSN Messenger, Tencet QQ-most popular P2P. BE ACTIVE IN YOUR STUDY!

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. Proakis. ISTE Publishing Company, 2008 3 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