The University of Aizu

授業の概要

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 beautiful.
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.

授業の目的と到達目標

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 designing.
After this lecture, we should be able to understand how to analize a given signal or system using tools such as Fourier transform; what kind of characteristics should we analize 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 for a given problem.

授業スケジュール

(The schedule for the three classes are different. Shown here is just an example. For detailed information, please refer to the web page of each class):
- An introduction to signals and systems, and representation of signals in time domain
- Linear, time-invariant systems, impulse response and convolution sum
- Fourier transform, frequency response and sampling theorem
- The z-transform and its properties
- System function, system stability, and inverse z-transform
- Discrete Fourier transform (DFT)
- Demonstration of DSP techniques (by using MatLab)
- Foundamental structures of digital filters
- Digital filter design - I
- Digital filter design - II
- Review

授業で使う教科書

Introduction to Digital Signal Processing, Tatsuo Higuchi, Shoukoudou, 1986 (in Japanese)