introduction to programmingmlli/courses/ee3660_syllabus... · 2018. 2. 22. · l j. w. leis,...
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EE3660Introduction
to Digital Signal Processing
數位訊號處理概論
Meng-Lin Li (李夢麟), Ph. D.
Department of Electrical Engineering
National Tsing Hua University
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EE3660Introduction
to Discrete Time
Digital Signal Processing 數位訊號處理概論
Meng-Lin Li (李夢麟), Ph. D.
Department of Electrical Engineering
National Tsing Hua University
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What is “Analog”? and
What is “Digital”?
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Definition of Digital Signal Processing
l That discipline which has allowed us to replace a circuit previously composed of a capacitor and a resistor with two antialiasing filters, and A-to-D and a D-to-A converter, and a general purpose computer (or array processor) so long as the signal we are interested in does not vary too quickly.
Thomas P. Barnwell, 1974
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Cyborg Cockroach
(Image: Carlos Sanchez, Mechanical Engineering, Texas A&M University)
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Course Information
l Time: W5W6R8
l Place: Delta 217
l Prerequisites:
n EE3610 Signals and Systems 訊號與系統 (a MUST)
n EE2310 Introduction to Programming 計算機程式設計(a MUST)
n EE2030 Linear Algebra 線性代數 (Linear equations and fundamental matrix operation)
n (EE3060 Probability 機率)
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Course Description
l The concept and applications of discrete/digital signal processing (DSP) will be introduced.
l Aims to strengthen students’ engineer intuition on DSP and preparation for DSP lab
l “Learning by doing” style will be particularly emphasized
l Instead of detailed mathematical derivation, "concepts" and "implementation notice" will be emphasized in this course.
l Multimedia, biomedical, and other applications will be discussed whenever appropriate.
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Textbook
l D. G. Manolakis and V. K. Ingle, “Applied Digital Signal Processing,” Cambridge University Press, 2011. (東華書局/新月圖書代理, (02) 2311-4027, textbook last year, with MATLAB codes inside)
l Class notes and related materials will be announced on the “iLMS e-Learning System” – http://lms.nthu.edu.tw
(If you are not able to access the LMS, try to visit my web page http://www.ee.nthu.edu.tw/~mlli/courses/courses.html for the first two weeks)
l In fact, most DSP books, e.g., the textbook and the references below cover almost the same topics.
l Having any DSP book, instead of the textbook, should be alright for this course.
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References
l A. V. Oppenheim and R. W. Schafer, “Discrete-Time Signal Processing,” 3rd ed., Prentice Hall, 2009. (Classic textbook of EE5630)
l R. G. Lyons, “Understanding Digital Signal Processing,” 3rd ed., Prentice Hall, 2010.
l S. W. Smith, “The Scientist and Engineer’s Guide to Digital Signal Processing,” 2nd ed., California Technical Publishing, 1999. (downloadable from http://dspguide.com/, I personally love this book)
l J. W. Leis, “Digital signal processing using MATLAB for students and researchers”, 1st ed., Wiley, 2011. (MATLAB tutorial)
l B. Porat, "A Course in Digital Signal Processing," 1st ed., Wiley, 1996. (I love the order and logistics in which the author introduces each key DSP topic, will be my lecture order this semester)
l J. H. McClellan, R. W. Schafer, and M. A. Yoder, "DSP First", 2nd ed., Pearson, 2016
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Definition of Digital Signal Processing
l That discipline which has allowed us to replace a circuit previously composed of a capacitor and a resistor with two antialiasing filters, and A-to-D and a D-to-A converter, and a general purpose computer (or array processor) so long as the signal we are interested in does not vary too quickly.
Thomas P. Barnwell, 1974
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Syllabus
l Topic 0 Tutorial on MATLAB
l Topic 1 Introduction of DSP
n HW1 - Experiencing your own scratched/immature DSP?
l Topic 2 Review of frequency-domain analysis
n Discrete-time (DT) signals and systems
n Fourier representation of signals
l Topic 3 Sampling and reconstruction (1D & 2D, Practical issue)
n Aliasing
n DT processing of continuous-time (CT) signals
n Sampling rate conversion
l Topic 4 Discrete Fourier transform (DFT) and practical spectral analysis
n DFT
n Linear convolution using DFT
n Practical spectral analysis
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Syllabus
l Topic 5 Miscellaneous - More about Convolution, Filter Design, Matrix-based FFT and etc.
l Topic 6 Revisit of z-Transform
n Structures for discrete-time systems
n From analysis to system design (revisit of linear phase system, and how poles and zeros affect the frequency response)
l Topic 7 Design of FIR and IIR filters
n Filter design and implementation with linear phase
n FIR filter design
n IIR filter design (if we have time)
l Selected advanced topics (if we have time):
n Spectral analysis of random signals
n Adaptive filtering
n Biomedical imaging
n Compressive sensing
n Machine learning
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Grading
l 6 to 7 Homework: 50%
n Combination of theory-inclined exercises and computer-based assignments
n Language: MATLAB; however, if you’d like to use Scilab, Python, C/C++, and etc., it’s ok. Simply let me know so that I can prepare the data at the format you can read).
l 1 Midterm exam: 25%
l 1 Final exam: 25%
l Bonus of classroom participation: up 5%
n Based on your attendance, engagement in group discussion, and the instructor’s overall impression
l These weights are approximate; we reserve the right to change them later
l
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Delay Policy of Homework
l 40% deduction at most (i.e., *0.6) before the TAs announce the grading
l New grade = (original grade)x(0.9)(delivery date-due date)/2
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No copy cat is allowed!
If we catch your cheating, you will FAIL this course, for sure.
The software “TurnItIn” can check plagiarism.
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My Office Hour and TA Hours
l Instructor Office Hour
n Tuesday 10:00 – 12:00 or by appointment at Delta R827.
l TA Hours
n TAs, designated time slots and location will be announced on the course website as soon as possible
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The Two Most Important Things for Signal Processingare
Observation (Dig Out All the Details)
and Justification
(Your Point of View, Different Point of View,
e.g., Time Domain vs. Frequency Domain, Of Course in a Professional Way)
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About Computer and Report-Style Homework
l Generally, you’re going to have two weeks for one homework.
l Supposedly, you have plenty of time for try and error and to think thoroughly to write a report.
l Though try and error is time consuming, anyway implementation is always time-consuming and painful -no pain, no gain.
l 助教、Office hours、討論區很重要l 助教、Office hours、討論區很重要l 助教、Office hours、討論區很重要
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The Attitude:You Are a Engineer of (Digital) Signal Processing.
The Homework Is Your Baby/Product.
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你們同學、學長姐的意見
l 我覺得DSP這堂課給我的感覺是教得太繁雜了，沒有一個中心。
l 講義真的太令人難以學習，我不知道該怎麼說，但可以參考XX老師的教學PPT 老實講，如果講義能類似那樣，這門課我可以保證我僅用一天就可以把一次段考範圍念到懂，沒有誤解兩天就可以考出很高分的成績(以平常完全沒認真上課第一次打開講義開始看的情況下)
l 投影片有人抱怨說和書本順序不一樣，好像在亂跳，但是我認為那些人剛好都是不聽課那群相反的，仔細上課的話會發現編排甚至比書本還要更適合教學!!
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你們同學、學長姐的意見
l 投影片截圖課本算式，常常有模糊的現象發生投影片建議老師自己依照自己的需求實作，不然有時候一個簡單的概念會講很久，卻沒辦法很痛快地講到那個點上(很多同學都反應這發生過不少次) 這門課作業的設計非常棒，是我修到目前最優良的作業，缺點就是評分實在無法公平，有時候必須改出作業差異，就會開始要求一些很零碎或是雞毛蒜皮的東西。
l 作業題目寫的不清不楚，不懂老師在問什麼，文字敘述的模糊性太高助教改作業評分標準太死，比較合理卻不符合標準答案的就會扣分寫作業根本像是湊一大堆文字說明，看有沒有碰巧"match"助教要求，一切都是運氣整堂課幾乎是一言堂評分根本不公正
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你們同學、學長姐的意見
l 教授對於課程準備得很充分也有很多值得學習的"工程師直覺"，每個細節都講得很詳盡，但有時可能因為太詳盡所以有點抓不住教授的重點，另外教授每次上課中很常講"ok嗎""ok嗎""ok嗎"，雖然有點不習慣但後來發現教授是真的很關心學生的學習狀況，謝謝教授的用心。
l 老師上課很認真，講解也很清楚！可以學到很多實作上的技巧，還有應該注意的事項！上課聽不清楚可以再討論區直接發問，還有上課的影片可以複習，蠻受用的一堂課，作業出的也都很有巧思，寫完蠻有成就感，目前在清大修過最值得的課之一！
l 我女友說老師很像水果奶奶很有喜感，她很喜歡陪我上課，感謝老師讓我增加感情的溫度
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最後…
l 我覺得這一門課留給同學的不該只是上課講義
n 看課本很重要
n 看課本很重要
n 看課本很重要
l DSP每個人的見解不同，同學應該要習慣去思考，其實同一topic不同的課本往往切入點或見解不同，同學應該多去體會不同的見解
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最後
l 要提醒我準時下課
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I Need You to Ask MeQuestions After Class
More Interaction Helps Me to Review My Lectures
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Take Home Quizzes
l Why I arrange the topics in the order shown in the syllabus?
l Limitations and drawback of ANAGLOG signal processing (ASP)?
l Advantage of DSP over ASP?
l Limitations of DSP?
l How DSP affects circuit design or circuit structure nowadays?
l (see textbook Chap 1)
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Take Home Quizzes
l Think about how to write a program to perform continuous time Fourier transform (CTFT)
n Generate a cosine signal (as a function of time) with a designated frequency
n Test your CTFT codes with the cosine signal
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Welcome on Board ^_^
NTHU Campus-Wide Licensed MATLABhttp://learning.cc.nthu.edu.tw