Bài giảng Xử lý tín hiệu số - Chapter 0: Introduction has contents: Signal and systems, classification of signal, basic elements of a DSP system, DSP applications - communications,... and other contents.
Trang 1Chapter 0
Introduction
p
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Ha Hoang Kha, Ph.D.
Ho Chi Minh City University of Technology
Email: hhkha@hcmut.edu.vn @
Trang 21 Signal and Systems
A signal is defined as any physical quantity that varies with time,
space or an other independent ariables
space, or any other independent variables
Speech, image, video and electrocardiogram signals are information-bearing signals g
Mathematically, we describe a signal as a function of one or more
independent variables.p
Examples: x t( ) =110 sin(2π ⋅50 )t
2
( , ) 3 2 10
I x y( , ) = 3x + 2xy + 10y
I x y x + xy + y
A system is defined as a physical device that performs any operation
on a signal.g
A filter is used to reduce noise and interference corrupting a desired
information-bearing signal.
Trang 31 Signal and Systems
Signal processing is to pass a signal
through a system
A digital system can be
implemented as a digital computer
or digital hardware (logic circuits)
Trang 42 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 m ltichannel signals
referred to as a multichannel signals
Ex: 3-lead and 12-lead electrocardiograms (ECG) are often used in practice, which results in 3-channel and 12-channel signals
which results in 3 channel and 12 channel signals
A signal is called M-dimensional if its value is a function of M
independent variable
Picture: the intensity or brightness I(x,y) at each point is a function of 2
independent variables independent variables
Color TV picture is 3-dimensional signals I(x,y,t)
Trang 52 Classification of Signal
Continous-time versus discrete-time signal
Signals can be classified into four different categories depending on the characteristics of the time variable and the values they take
Time Amplitue
Continuous Discrete
(t) ( )
x(t)
n x(n)
Analog signal Discrete time signal
Discrete
xQ(n) 101
110 111
xQ(t)
Discrete
Quantized signal Digital signal
n
000001010
011 100
101 t
Quantized signal Digital signal
Trang 63 Basic elements of a DSP system
Most of the signals encountered in science and engineering are
analog in nat re To perform the processing digitall there is a need
analog in nature To perform the processing digitally, there is a need for an interface between the analog signal and the digital processor
Fig: Analog signal processing
Fi Di i l i l i Fig: Digital signal processing
Trang 74 DSP applications-Communications
Telephony: transmission of information in
digital form via telephone lines, modem
technology, mobile phone
Encoding and decoding of the
information sent over physical
h nn l (t ptimiz
channels (to optimize
transmission, to detect or
correct errors in transmission)
co ect e o s t a s ss o )
Trang 84 DSP applications-Radar
Radar and sonar:
Target detection:
position and
position and velocity estimation
Tracking
Tracking
Trang 94 DSP applications-Biomedical
Analysis of biomedical signals, diagnosis, patient monotoring,
pre enti e health care artificial organs
preventive health care, artificial organs
Examples:
Electrocardiogram (ECG) signal provides information about the condition of the patient’s heart
patient s heart
Electroencephhalogram (EEG) signal
pro ides information abo t the
provides information about the
activity of the brain
Trang 104 DSP applications-Speech
Noise reduction: reducing
backgro nd noise in the seq ence
background noise in the sequence
produced by a sensing device (a
microphone).p )
Speech recognition: differentiating
between various speech sounds
Synthesis of artificial speech :
Synthesis of artificial speech :
text to speech systems
Trang 114 DSP applications-Image Processing
Content based image retrieval
-bro sing searching and retrie ing
browsing, searching and retrieving
images from database
Image enhancement
Compression: reducing the redundancy in the image data to y g optimize transmission/storage
Trang 124 DSP applications-Multimedia
Generation storage and transmission
of so nd still images motion
of sound, still images, motion
pictures
Digital TV
Video conference
Trang 13The Journey
“ Learning digital signal processing is not something
you accomplish; it’s a journey you take”.
R.G Lyons, Understanding Digital Signal Processing
Trang 145 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 signals are g g easily stored.y
DSP methods allow for implementation of more sophisticated signal processing algorithms
Li it ti P ti l li it ti f DSP th ti ti
Limitation: Practical limitations of DSP are the quantization errors
and the speed of A/D converters and digital signal processors -> not suitable for analog signals with large bandwidths
Trang 15Course overview
Introduction to Digital Signal Processing (3 periods)
Sampling and reconstruction, quantization (6 periods)
Analysis of linear time invariant systems (LTI)(3 periods)
Finite Impulse Response (FIR) of LTI systems (3 periods)
Z-transform and its applications to the analysis of linear systems (6
Mid-term Exam
periods)
Fourier transform & FFT Algorithm (9 periods)
Digital filter realization(3 periods)
FIR and IIR filter designs (9 periods)
Final Exam
Trang 16 T t b k
Text books:
[1] S. J. Orfanidis, Introduction to Signal Processing, Prentice –Hall
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.
Trang 17Learning outcomes
Understand how to convert the analog to digital signal
Have a thorough grasp of signal processing in linear time invariant
Have a thorough grasp of signal processing in linear time‐invariant systems
Understand the z‐transform and Fourier transforms in analyzing the signal and systems
the signal and systems
Be able to design and implement FIR and IIR filters
Trang 18 Mid‐term exam: 30%
Final exam: 70%
Bonus: 0.5 mark/solving a problem in the class