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
discretetime signals and systems. The course content includes the
concept and the classification of discretetime 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 timeinvariant system, discrete convolution, ztransform,
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 ztransform; 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 
Deadline for
homework
submission 
1 
6/9 
Introduction

[Lecture01]

June 27 
2 
6/13 
Linear, timeinvariant systems  I

[Lecture02]

June 27 
3 
6/16 
Linear, timeinvariant systems  II

[Lecture03]

June 27 
4 
6/20 
Fourie Transform

[Lecture04]

July 4 
5 
6/23 
ztransform  I

[Lecture05]

July 4 
6 
6/27 
ztransform  II

[Lecture06]

July 4 
7 
6/30 
Midterm examination

 
 
8 
7/4 
Discrete Fourier transform (DFT)  I

[Lecture07]

July 21 
9 
7/7 
Discrete Fourier transform (DFT)  II

[Lecture08]

July 21 
10 
7/21 
Discrete Fourier transform (DFT)  III

[Lecture09]

July 25 
11 
7/25 
Structure of digital filters  I

[Lecture10]

July 28 
12 
7/28 
Structure of digital filters  II

[Lecture11]

Aug. 1 
13 
7/30 
Digital filter design  I

[Lecture12]

Aug. 1 
14 
8/1 
Digital filter design  II

[Lecture13]

Aug. 4 
15 
8/3 
Final Review

[Lecture14]

 
Textbook
 Digital Signal Processing with Matlab,
Tatsuo Higuchi, Masayuki Kawamata, Morikita, 2015, ISBN: 9784627792111 (in Japanese)
Prerequests
Student Evaluation
 Quizzes: 14
 Exercises: 26
 Examinations: 30+30
Further Recommended Reading
 Syllabus in Japanese
 Syllabus in English
 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: 0966017633. http://www.dspguide.com/pdfbook.htm (free online text in pdf format)
 Shouji Shimada et al., Fundamentals of Digital Signal Processing, Koronasha, 2006 (in Japanese)