This page has been produced for providing students with general informations and guidelines on the course of Signals and Systems. If you have any questions after reading this page, send a mail to your professor.
You can download the following information written in Word format. Click SYLLABUS, print, and bring the hardcopy to the first class hour!!!
COURSE NAME
● Signals and Systems (Undergraduate EEE2008 Class)
LECTURER
● Professor Joong Kyu Kim(Rm#: 21225, Tel: 031-290-7122)
COURSE OBJECTIVE
● To learn basic techniques on how to analyze signals and systems in both time and frequency domains for continuous as well as discrete cases.
COURSE DESCRIPTION
● Fundamentals of the analysis and processing of continuous and discrete signals. Linear systems and filtering. Convolution, Fourier Series(FS), Fourier Transform(FT), Discrete Time Fourier Transform(DTFT), Discrete Fourier Transform(DFT), and Sampling Theorem are discussed in detail. Analog and digital communication system and Fast Fourier Transform(FFT) will also be briefly introduced. PC based simulation and data processing are used to demonstrate the above concepts.
TEXTBOOK
● There is no particular textbook for this class, but the Signals and Systems by Haykin & Van Veen (Wiley) will be used as the main reference.
REFERENCE
● Signals and Systems by Oppenheim and Willsky, Prentice Hall
● Signal, Systems and Tranforms by L.B. Jackson, Addison Wesley
● Signals and Linear System Analysis by G.E.Carlson, Houghton Mifflin
CLASSNOTE
● For your convenience, the classnote in PS form as well as in PDF form will be distributed via this web-site. Visit Classnotes section, and download or print the classnote!
Note:
Also, in order for you to read and/or print the classnotes in PS form, you must download the viewer program "Ghostview" in your computer. Visit first the download site, and be sure to download the program before you get the classnotes!!! You must acquire both of the "gsview 4.3" and "AFPL Ghostscript 8.00" or their higher versions!!!
GRADE POLICY
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Mid-term Exam |
30% |
|---|---|
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Final Exam |
40% |
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Attendance |
10% |
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Homework and Project |
20% |
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Total |
100% |
Note:
● All the exams are closed books, but you may bring one page of A4 size hand-written reference sheet to each examination. (Illegal sheets will be confiscated at the place!!!)
● Attendance will be checked 5 times during the semester without advanced notice.
● No grade change will be permitted at the end of the semester. (e.g. C or D to F)
● Homework and Programming project will be assigned several times during the semester.
TOPICS TO COVER
● Introduction to Signals and System
● LTI System and Convolution
● ourier Series and Fourier Transform
● Filtering and AM(Amplitude Modulation)
● Correlation and Power Spectrum
● Discrete Fourier Series (DFS)
● Discrete (Time) Fourier Transform (DFT and DTFT)
● Fast Fourier Transform (FFT)
● Transforms and Sampling Theory
● Efficient Algorithm to compute two DFT's simultaneously
WEEKLY SCHEDULE
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Week No. |
Detailed Topics |
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Introduction: definitions, mathematical representations and categorizations of signals and systems. |
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Continuous Linear Time Invariant(LTI) system, impulse response and convolution integral. |
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Trigonometric Fourier Series(FS) representation of continuous periodic signals, Gibb's phenomenon. |
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Complex representation of FS, and FS examples for typical periodic signals. |
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Fourier Transform(FT) of continuous non-periodic signals: definition and characteristics of FT. |
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Continue FT characteristics, singular functions and their FT, and typical examples of FT for some non-periodic signals. |
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Analysis of continuous LTI systems on frequency domain using FT, comparison to convolution in time domain, concept of filter. |
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Ideal Low Pass Filter(LPF) and Band Pass Filter(BPF), signal modulation and demodulation in AM(Amplitude Modulation) system, comparison between AM and FM(Frequency Modulation) systems. |
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Autocorrelation and crosscorrelation functions for continuous periodic signals: definition, examples, properties, and applications. |
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Autocorrelation and crosscorrelation functions for continuous non-periodic signals, power spectral density of periodic signals, energy spectral density of non-periodic signals, and Parseval's Theorem. |
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Discrete LTI system, convolution sum, Discrete Fourier Series(DFS), and comparison to continuous FS. |
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Discrete Time Fourier Transform(DTFT): definition, properties, and examples for typical discrete non-periodic signals. |
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Discrete Fourier Transform(DFT): definition, properties, and examples for typical discrete finite duration signals, summary of transforms. |
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Conversion of continuous signals to discrete signals: Nyquist Sampling Theorem: background, analysis, and theorem. Concept of signal interpolation both in time and frequency domains. |
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Efficient algorithm to compute two DFT's of real discrete signals simultaneously. Introduction to Fast Fourier Transform(FFT). |
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