Chapter
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Introduction
Ha Hoang Kha, Ph.D.Click to edit Master subtitle style
Ho Chi Minh City University of Technology
@
Email:

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1. Signal and Systems
™ A signal is defined as any physical quantity that varies with time,
space or an
space,
any other independent variables.
ariables
‰ Speech, image, video and electrocardiogram signals are information-bearing
signals.
g

™ Mathematically, we describe a signal as a function of one or more
independent
p
variables.
‰ Examples:

x(t ) = 110sin(2π ⋅ 50t )
I ( x, y ) = 3 x + 2 xy + 10 y 2


2. Classification of Signal
Multichannels and Multidimensional signals
™ Signals which are generated by multiple sources or multiple sensors
can be represented in a vector form. Such a vector of signals is
referred to as a multichannel
m ltichannel signals
‰ Ex: 3-lead and 12-lead electrocardiograms (ECG) are often used in practice,
which results in 33-channel
channel and 12-channel
12 channel signals
signals.

™ A signal is called M-dimensional if its value is a function of M
independent
d
d variable
b
‰ Picture: the intensity or brightness I(x,y) at each point is a function of 2
independent variables
‰ Color TV picture is 3-dimensional signals I(x,y,t)

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2. Classification of Signal

110
101
100
011
n
010
001
000
Digital signal
Digital signal 

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3. Basic elements of a DSP system
™ Most of the signals encountered in science and engineering are
analog in nat
nature.
re To perform the processing digitall
digitally, there is a need
for an interface between the analog signal and the digital processor

Fig: Analog signal processing

Fi Digital
Fig:
Di i l signal

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4. DSP applications-Radar
Radar and sonar:
™ Target detection:
position and
velocity estimation

™ Tracking

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4. DSP applications-Biomedical
™ Analysis of biomedical signals, diagnosis, patient monotoring,
pre enti e health care,
preventive
care artificial organs
organs.
™ Examples:
™ Electrocardiogram

microphone).
p
)

™ Speech recognition: differentiating
between various speech sounds
™ Synthesis of artificial speech :
text to speech systems

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4. DSP applications-Image Processing
™ Content based image retrievalbro sing searching and retrie
browsing,
retrieving
ing
images from database.
™ Image enhancement

™ Compression: reducing the
g data to
redundancyy in the image
optimize transmission/storage


i digital
di i l signal
i l processing
i is
i not something
hi
you accomplish; it’s a journey you take”.
R.G. Lyons, Understanding Digital Signal Processing

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5. Advantages of digital
over analog signal processing
™ A digital programmable system allows flexibility in reconfiguring the
DSP operations simply by changing the program.
™ A digital system provides much better control of accuracy
requirements.
™ Digital
g signals
g
are easilyy stored.
™ DSP methods allow for implementation of more sophisticated signal
processingg algorithms.
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References

™ Text
T t books:
b k
[1]  S. J. Orfanidis, Introduction to Signal Processing, Prentice –Hall 
Publisher 2010.
Publisher 2010.
[2]  J. Proakis, D. Manolakis, Introduction to Digital Signal 
Processing, Macmillan Publishing Company, 1989.
™ Reference books:
[3] V K Ingle J Proakis Digital Signal Processing Using Matlab
[3] V. K. Ingle, J. Proakis, Digital Signal Processing Using Matlab, 
Cengage Learning, 3 Edt, 2011. 

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