Introduction to
Digital Signal Processing
(Discrete-time Signal Processing)
Prof. Ja-Ling Wu
Dept. CSIE & GINM
National Taiwan University
Overview
Introduction
to DSP
Information
Theory and
Coding Tech.
C&C
Digital Speech Processing
Multi-D DSP
Digital Image Processing
Multi-rate DSP
VLSI DSP
Advanced topics in DSP
Data Compression
Error Control coding
Recognition
Understanding
DSP-processor
Application-specific
system
efficient communication
system
Digital Modulation
Information Security
Reliable communication
system
Multimedia Security
Secure communication
system
Introduction
DSP theory has been applied to a variety of problems such as:
•Biomedical data processing : EEG, ECG(EKG), CT…
•Digital Audio
: CE-Disk, Audio-CD
•Sonar and Radar processing
: homeland security, video surveillance,
military applications
•Speech processing
: recognition
•Data Communication
: ISDN, Digital Communications
•Reliable data storage of
computerized information
: digital storage with error correction
capability
•Seismic Signal Processing
: oil exploration, underwater mapping
•Image Processing and Vision : Data Compression, Computer Vision
•Error Control Coding
: Reliable communication
•Information Security
: steganograph / data hiding / watermarking
/ forensics
Signal Classification
Continuous time
Discrete time
x(t)
x(t)
Continuous
amplitude
Analog
t
x(t)
Discrete
t
Digital
t
x(t)
Discrete
amplitude
Sample-data
t
Block Diagram of digital processing
for analog waveforms
Band-limited
signal
Analog
Signal
input
Low-pass
filter
Analog / Digital Conversion
•Sampling
•Quantization
DSP double- period
sequence
Analog
Signal
output
Low-pass
filter
digital
Digital
Processes
Digital / Analog Conversion
•Sample-and-hold
digital
Digital Devices (VLSI)
Digital Computers
DSP
• Advantages of digital processing
– Reliable – easy to be stored and/or transmitted
– Flexible
– Accurate
– Faster
• Disadvantage: Easy to make
• Challenges
‒ Exact copy!!
– Optical processing
‒ Good forgery!!
– Bio-computing
Serious IPR threats
What does “digital” mean ?
Analog
Waveform
x(t)
△z
Quantization
step
Discrete in
amplitude
t
△t : Sampling period
Discrete in time
Remarks
1.
What is “DSP” ?
keep what we want and eliminate what don’t as ________ as
possible !
f(t)
trend prediction
– Much
– Precisely
?
– Soon
2. Δt (Sampling period)
Sampling Theorem
t
T T+n
– Fourier Analysis / Transform
video motion estimation
– Interpolation / Extrapolation
3. Δz (Quantization step)
Finite-Wordlength Effects
– Available Hardware Support
– Precision Requirement
uniform vs. non-uniform
scalar vs. vector quantization
4. What kind of signals can we really process ?
– Bandlimited
– finite-dynamic-range
– If the signal is stochastic, some statistic properties must be
known; say, mean, variance, acf, psd, …etc.
(random/stochastic process)
– long-duration signal (such as: voice/speech signal) short-time
analysis. (sliding window)
Course outline
1. Introduction
2. Signals and Systems
•
•
•
•
•
•
3.
Z-transform
System function
LTI-system
digital convolution
Sampling Theorem
System stability
Fourier Response of a System
•
•
•
•
Fourier Transform
DFT
Fast Fourier Transform
Convolution Theorem
4. Digital Filters
•
FIR filter
•
IIR filter
5. Quantization and Finite Wordlength Effects
6. Specific topics in DSP
References
1. Digital Signal Processing by Roberts & Mullis (Addison Wesley)
2. Discrete time Signal Processing by Oppenheim (Prentice-Hall)
3. Signal Processing First by James H. McClellan, Ronald W. Schafer,
Mark A. Yoder
Course Information
• Lecturer: Ja-Ling Wu (wjl@cmlab.csie.edu.tw)
• TA: Yin-Tzu Lin (known@cmlab.cie.ntu.edu.tw)
Yun-Chung Shen (cazindo@cmlab.csie.ntu.edu.tw)
• Lecture Notes
– http://www.cmlab.csie.ntu.edu.tw/~dsp/dsp2010
• Grades
–
–
–
–
40% Homework
15% Quiz 1 : in-class + take home(extra 15% of Quiz 1)
15% Quiz 2 : in-class + take home(extra 15% of Quiz 2)
30% Final
• Writtten Quiz (60% of final)
• Monograph (40% of final)
• MATLAB will be used in homework