Digital Signal Processing
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Transcript Digital Signal Processing
Digital Signal Processing
Shi Ping
School of Information Engineering
CUC
Copyright © 2005. Shi Ping CUC
Course outline
Text books :
《数字信号处理教程》
(第三版)
清华大学出版社,程佩青 2006年
Reference books:
<Digital Signal Processing Using MATLAB>
英文影印版 科学出版社
Vinay K. Ingle John G. Proakis 2003
Copyright © 2005. Shi Ping CUC
Course outline
Reference books:
王世一 《数字信号处理》北京理工大学出版
社,1997年
A.V.奥本海姆 R.W.谢弗 J.R.巴克 编著 刘树
堂 黄建国 译《离散时间信号处理》(第2版)
西安交通大学出版社 2001年
胡广书《数字信号处理-理论、算法与实现》
(第二版)清华大学出版社2003年
Copyright © 2005. Shi Ping CUC
Course outline
Relationship with other courses
About MATLAB Software
Requirements
Copyright © 2005. Shi Ping CUC
Chapter 1
Introduction to DSP
Content
Signal, System, Signal Processing
The Constitution of DSP System
How to implement the DSP
The Application of DSP
The advantages of DSP
Copyright © 2005. Shi Ping CUC
Signal, System, Signal Processing
Signal
A signal is a function of independent variables such as
time, distance, position, temperature and pressure
Signals play an important role in our daily life.
Most signals we encounter are generated naturally.
However, a signal can also be generated synthetically
or by a computer.
Depending on the nature of the independent variables
and the value of the function, we can classify the
signals as follows
Copyright © 2005. Shi Ping CUC
Signal, System, Signal Processing
● scalar signal
A signal generated by a single source
● vector signal (or multichannel signal)
A signal generated by multiple sources
● one dimensional (1-D) signal
A function of a single independent variable
● multidimensional (M-D) signal
A function of more than one independent variables
sound
Image
Video
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Signal, System, Signal Processing
● continuous-time signal
x(t )
see
The independent variable is continuous
● discrete-time signal (sequence)
x(n)
The independent variable is discrete
● analog signal
A continuous-time signal with a continuous amplitude
● quantized-boxcar signal
A continuous-time signal with a discrete-value amplitude
● digital signal
A discrete-time signal with a discrete-value amplitude
● Sampled-data signal
A discrete-time signal with a continuous amplitude
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Signal, System, Signal Processing
● deterministic signal
A signal that can be uniquely determined by a
well-defined process, such as a mathematical
expression or rule, or table look-up.
● random signal
A single that is generated in a random fashion
and cannot be predicted ahead of time.
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Signal, System, Signal Processing
● periodic signal
A signal that repeats itself in a periodic fashion from
negative to positive infinity.
x( t ) x( t kT )
x( n) x( n kN )
● aperiodic signal
A signal that extends to both positive and negative
infinity without repeating in a periodic pattern.
Copyright © 2005. Shi Ping CUC
Signal, System, Signal Processing
● power signal
An infinite energy signal with finite average power.
1
P lim
T T
T
0
2
x ( t ) dt
1
P lim
N N
N 1
x ( n)
2
n 0
● energy signal
An finite energy signal with zero average power.
E
2
x( t ) dt
E x ( n)
2
a periodic sequence — power signal
a finite-length sequence — energy signal
Copyright © 2005. Shi Ping CUC
Signal, System, Signal Processing
System
A system is any process that produces an output signal
in response to an input signal.
Depending on the types of the signal processed, we
can classify the systems as follows:
Copyright © 2005. Shi Ping CUC
Signal, System, Signal Processing
● analog system
input and output analog signals
● digital system
input and output digital signals
● continuous-time system
input and output continuous-time signals
● discrete-time system
input and output discrete-time signals
Copyright © 2005. Shi Ping CUC
Signal, System, Signal Processing
Signal Processing
A signal carries information !
The objective of signal processing:
To extract, enhance, store and transmit the useful
information carried by the signal.
Digital signal processing:
To implement the signal processing by a digital means.
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The Constitution of DSP System
Equivalent to an analog signal processor
analog
analog
PrF
ADC
DSP
DAC
PoF
waveform
PrF: antialiasing filtering
example
PoF: smooth out the staircase waveform
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How to Implement the DSP
To handle the DSP algorithms in a general-purpose
microprocessor by means of software programming
To handle the DSP algorithms in a specifically
designed Digital Signal Processors (DSPs)
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The Application of DSP
The main tasks of DSP
Signal Analysis
Measurement of signal properties
Spectrum (frequency/phase) analysis
Target detection, verification, recognition
Signal Filtering
Signal-in-signal-out, filter
Removal of noise/interference
Separation of frequency bands
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The Application of DSP
DSP application examples
Telecommunications
Multiplexing
Compression
Echo control
Audio Processing
Music
Speech generation
Speech recognition
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The Application of DSP
DSP application examples
Echo Location
Radar
Sonar
Reflection seismology
Image Processing
Medical
Space
Commercial Imaging Products
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The Application of DSP
Demonstration
FM synthesis of sound
chirp
clarinet
brass
bell
Digital image processing
Deblurring
Edge detection
Noise reduction
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The Advantages of DSP
Absence of drift in the filter characteristics
Improved quality level
Reproducibility
Ease of new function development
Multiplexing
Modularity
Total single chip implementation using VLSI technology
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The sound signal is an example of a 1-D signal
where the independent variable is time
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CUC
A black-and-white image signal is an example of a
2-D signal where the 2 independent variables are the
2 spatial variables.
I ( x, y)
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A color image signal is a 3-channel signal composed of three
2-D signals representing the three primary color: red, green
and blue (RGB)
I R ( x , y )
u( x , y ) I G ( x , y )
I G ( x , y )
return
Copyright © 2005. Shi Ping
CUC
A black-and-white video signal is an example of a 3-D signal
where the 3 independent variables are the 2 spatial variables
and the time variable.
I ( x, y, t )
Copyright © 2005. Shi Ping CUC
A color video signal is a 3-channel signal composed of three
3-D signals representing the three primary color: red, green
and blue (RGB)
I R ( x , y , t )
u( x , y , t ) I G ( x , y , t )
I B ( x , y , t )
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CUC
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