1. Digital Signal Processing
Prof. Yeong-Ho Ha

2. Course Objective: To study the principles and applications
of digital signal processing.
Analyze, process, and apply signals from/to varying
physical phenomena in the time and spatial domain

3. Course Syllabus
1. Introduction 2. Analog Signals, Systems, and Transforms 3. Sampling 4. Discrete-time Signals and Transforms 5. z-transform 6. Discrete-time Systems 7. Finite Impulse Response (FIR) Filter Design 8. Infinite Impulse Response (IIR) Filter Design 9. Advanced Topics in DSP

4. Assignments, Grading Criteria, and Evaluation:
Three quizzes: each quiz has 30 points,
H/W and Programming Assignments (10 points)
Prerequisite: Basic knowledge to Signals and Systems
Skill in C++ programming language

5. Chapter 1 Introduction

6. Historic Background At the end of the 1940s
- Shannon, Bode and some researchers discussed the possibility of digital
concept (circuit elements)  But no appropriate H/W
During the middle of the 1950s
- Linville at MIT discussed digital filtering at graduate seminars
- Hurewicz partly established a discipline:
sampling and its spectral effects
At the middle of 1960s
- A formal theory of DSP began to emerge
Since then
- Kaiser at Bell Lab. : digital filter synthesis
- Cooley & Tukey : FFT (1965)

7. Instrumentation Control Bio and Medical Engineering
Signal processing
Analyzes, processes, and applies signals from/to varying physical phenomena in time and spatial domain
Appliances
Instrumentation Control
- Digital television - Digital camera - Digital fax - Internet phone - Internet video - Internet music - Cellular mobile phone - MP3
- Spectrum analysis - Noise reduction - Data compression - Position and rate control
Speech Processing
- Speech recognition/analysis - Digital audio - Voice mailing system
Image Processing
- Pattern recognition - Robot vision - Image compression/enhancement
Bio and Medical Engineering
- Biological signal processing - Medical image processing - MRI/CT - Embryonic monitoring system
Telecommunication
- Data communication - Adaptive equalization - Video conferencing - Spread spectrum
Other Areas
- Radar signal processing - Sonar signal processing - Seismic signal processing - GPS/GIS
Fig. 1-1.

8. Analog and digital signal processing systems
Continuous input signal for analog system
Discrete number sequence for digital system
Analog System
Digital System
Fig. 1-2.

9. Conversion between analog and digital signals
Analog-to-digital converter
Digital-to-analog converter
A/D Convertor
Digital System
D/A Convertor
Analog input signal
Analog output signal
Fig. 4-3.

10. Sampling

11. Advantages of digital signals
1. Digital signals can be reproduced exactly
2. Digital signals can be manipulated easily