Bài giảng Digital signal processing - Chapter 0: Introduction

Chapter 0

Introduction

Nguyen Thanh Tuan,_CM_lic._kE_ton_eg_d._{it Master subtitle style}

Department of Telecommunications (113B3)

Ho Chi Minh City University of Technology

Email: [email protected]om

1. Signal and System

 A signal is defined as any physical quantity that varies with time,

space, or any other independent variable(s).

 Speech, image, video and electrocardiogram signals are information-bearing

signals.

 Mathematically, we describe a signal as a function of one or more

independent variables.

 Examples:

x(t) 110sin(2 50t)

I(x, y)  3x 2xy 10y²

 A system is defined as a physical device that performs any operation

on a signal.

 A filter is used to reduce noise and interference corrupting a desired

information-bearing signal.

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1. Signal and System

 Signal processing is to pass a signal through a system.

 A digital system can be implemented as a combination of

hardware and software (program, algorithm).

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2. Classification of Signals

Multichannel 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 signals

 Ex: 3-lead and 12-lead electrocardiograms (ECG) are often used in practice,

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

 TV picture is 3-dimensional signal I(x,y,t)

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2. Classification of Signals

Continuous-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

Amplitude

Continuous

Discrete

x(n)

x(t)

Continuous

t

n

Analog signal

Discrete signal

x_Q(t)

x_Q(n)

111

110

101

100

011

010

001

000

Discrete

t

n

Quantized 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 nature. To perform the processing digitally, there is a need

for an interface between the analog signal and the digital processor.

Fig 0.1: Analog signal processing

Xử lý số tín hiệu

Xử lý tín hiệu số

Fig 0.2: Digital signal processing

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4. 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

channels (to optimize

transmission, to detect or

correct errors in transmission)

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4. DSP applications-Radar and Sonar

 Target detection:

position and

velocity estimation

 Tracking

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4. DSP applications-Biomedical

 Analysis of biomedical signals, diagnosis, patient monitoring,

preventive health care, artificial organs.

 Examples:

 Electrocardiogram (ECG) signal provides

information about the condition of the

patient’s heart.

 Electroencephalogram (EEG) signal

provides information about the

activity of the brain.

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4. DSP applications-Speech

 Noise reduction: reducing

background noise in the

sequence produced by a sensing

device (a microphone).

 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 retrieval:

browsing, searching and retrieving

images from database.

 Image enhancement

 Compression: reducing the

redundancy in the image data to

optimize transmission/storage

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4. DSP applications-Multimedia

 Generation, storage and transmission

of sound, still images, motion

pictures.

 Digital TV

 Video conference

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The Journey

“Learning digital signal processing is not

something 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 signals are easily stored.

 DSP methods allow for implementation of more sophisticated

signal processing algorithms.

 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.

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Course overview

 Chapter 0: Introduction to Digital Signal Processing (3 periods)

 Chapter 1: Sampling and Reconstruction (6 periods)

 Chapter 2: Quantization (3 periods)

 Chapter 3: Analysis of linear time invariant systems (LTI) (6 periods)

 Chapter 4: Finite Impulse Response and convolution (3 periods)

 Chapter 5: Z-transform and its applications (6 periods)

 Chapter 6: Transfer function and filter realization (3 periods)

 Chapter 7: Fourier transform and FFT algorithm (6 periods)

 Chapter 8: FIR and IIR filter designs (6 periods)

 Review and mid-term exam: 3 periods

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References

 Text books:

[1] S. J. Orfanidis, Introduction to Signal Processing, Prentice-

Hall Publisher 2010.

[2] J. Proakis, D. Manolakis, Digital Signal Processing, Macmillan

Publishing Company, 1989.

 Reference books:

[3] V. K. Ingle, J. Proakis, Digital Signal Processing Using Matlab,

Cengage Learning, 3 Edt, 2011.

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Learning outcomes

 Understand how to convert the analog to digital signal

 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.

 Be able to design and implement FIR and IIR filters.

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Assessment

Test and

Homework exam

(40%) (60%)

7.5

Final

Mark

(100%)

 Mid-term test: 20%

 Homework: 20%

 Final exam: 60%

0.0

2.5

3.0

4.0

5.5

6.0

7.0

7.5

7.0

4.50

4.60

4.80

4.90

4.80

4.90

4.80

4.60

5.50

4.5

5.0

4.5

2.5

6.0

5.5

4.5

4.0

3.5

3.0

2.5

 Bonus: added to

Test and Homework

10.0

4.00Absent

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Assessment

Điểm ghi trên Bảng điểm kiểm tra, Bảng điểm

thi và Bảng điểm tổng kết được làm tròn đến

0,5. (từ 0 đến dưới 0,25 làm tròn thành 0; từ 0,25

đến dưới 0,75 làm tròn thành 0,5; từ 0,75 đến

dưới 1,0 làm tròn thành 1,0)

Nếu điểm thi nhỏ hơn 3 và nhỏ hơn điểm tổng

kết tính từ các điểm thành phẩn (kể cả điểm thi)

thì lấy điểm thi làm điểm tổng kết.

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Timetable

Time

Class

Monday

(T1-3)

DD13BK01-A02

314B1

Tuesday

(T7-9)

DD13KSTD

206B1

Wednesday

(T10-12)

DD13LT04-A04

303B1

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Introduction

Bài giảng Digital signal processing - Chapter 0: Introduction - Nguyễn Thanh Tuấn