Course Description
The signal for processing is mathematically modeled as a function or a
sequence of numbers that represent the state or behavior of a physical
system. The examples of the signals range from speech, audio, image
and video in multimedia systems, electrocardiograms in medical systems
(ECG/EKG), to electronic radar waveforms in military. Signal
processing is concerned with the representation, transformation, and
manipulation of signals and the information they contain. For example,
we may wish to remove the noise in speech to make it clear, or to
enhance an image to make it more natural. Signal processing is one of
the fundamental theories and techniques to construct modern
information systems. During the last half century, lots of theories
and methods have been proposed and widely studied in digital signal
processing. In this semester, we only study the fundamentals of
discrete-time signals and systems. The course content includes the
concept and the classification of discrete-time signal,
representations of signals in time, frequency, z- and discrete
frequency domains, representations and analyses of systems, and filter
designs.
The course is a prerequisite course for your further studying of other
multimedia related courses, such as speech processing, image
processing, audio and video data compressing, pattern recognition,
communication systems and so forth.
Course Objectives
In this course, we will mainly study the following topics: signal
representation in time domain, Fourier transform, sampling theorem,
linear time-invariant system, discrete convolution, z-transform,
discrete Fourier transform, and discrete filter design.
After this lecture, the students should be able to understand how to
analyze a given signal or system using tools such as Fourier transform
and z-transform; what kind of characteristics should we analyze to
know the property of a signal or system; how to process signals to
make them more useful; and how to design a signal processor (digital
filter) for a given problem.
Course Schedule and themes
|
| No. |
Date |
Contents |
Teaching Material |
| 1 |
4/8 |
Introduction
|
[Lecture01]
|
| 2 |
4/15 |
Linear, time-invariant systems - I
|
[Lecture02]
|
| 3 |
4/22 |
Linear, time-invariant systems - II
|
[Lecture03]
|
| 4 |
5/7 |
Fourie Transform
|
[Lecture04]
|
| 5 |
5/13 |
z-transform - I
|
[Lecture05]
|
| 6 |
5/20 |
z-transform - II
|
[Lecture06]
|
| 7 |
5/27 |
Mid-term examination
|
--- |
| 8 |
6/3 |
Discrete Fourier transform (DFT) - I
|
[Lecture07]
|
| 9 |
6/10 |
Discrete Fourier transform (DFT) - II
|
[Lecture08]
|
|
| 10 |
6/17 |
Discrete Fourier transform (DFT) - III
|
[Lecture09]
|
| 11 |
6/24 |
Structure of digital filters - I
|
[Lecture10]
|
| 12 |
7/1 |
Structure of digital filters - II
|
[Lecture11]
|
| 13 |
7/8 |
Digital filter design - I
|
[Lecture12]
|
| 14 |
7/22 |
Digital filter design - II
|
[Lecture13]
|
| 15 |
7/22 |
Final Review
|
[Lecture14]
|
Textbook
- Introduction to Digital Signal Processing,
Tatsuo Higuchi, Shoukoudou, 1986 (in Japanese)
Pre-requests
Student Evaluation
- Quizzes: 14
- Exercises: 26
- Examinations: 30+30
Further Recommended Reading
- Syllabus (Japanese)
- Syllabus (English)
- Digital signal processing with MatLab, Tatsuo Higuchi and Masayuki
Kawamata, Shoukoudou (in Japanese)
- Richard G. Lyons, Understanding Digital Signal Processing, Prentice
Hall, 1996. ISBN:0201634678.
- S. W. Smith, The Scientist and Engineer's and Guide to Digital
Signal Processing, California Technical Publishing, 1997. ISBN:
0-9660176-3-3. http://www.dspguide.com/pdfbook.htm (free on-line text
in pdf format)
- Shouji Shimada et al., Fundamentals of Digital Signal Processing,
Koronasha, 2006 (in Japanese)
