Chap1-Introduction to DSP

Copyright © 2005. Shi Ping CUC

Shi Ping

School of Information Engineering

CUC

Digital Signal Processing


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

Course outline

Reference books ： <Digital Signal Processing Using MATLAB>英文影印版科学出版社Vinay K. Ingle John G. Proakis 2003


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

Course outline


Relationship with other courses

About MATLAB Software

Requirements

Course outline


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



Signal

A signal is a function of independent variables such as time, distance, position, temperature and pressure

Depending on the nature of the independent variables and the value of the function, we can classify the signals as follows

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.



● 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



● continuous-time signal The independent variable is continuous ● discrete-time signal (sequence) 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

see

)(nx

)(tx



● 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.



● periodic signal A signal that repeats itself in a periodic fashion from

negative to positive infinity.

● aperiodic signal A signal that extends to both positive and negative

infinity without repeating in a periodic pattern.

)()()()(

kNnxnxkTtxtx



● energy signal An finite energy signal with zero average power.

● power signal An infinite energy signal with finite average power.

22 )()( nxEdttxE

1

0

2

0

2 )(1lim)(1limN

nN

T

Tnx

NPdttx

TP

a periodic sequence — power signala finite-length sequence — energy signal



SystemA 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:



● 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



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

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waveform

ADC DACDSPPrF PoFanalog analog

Equivalent to an analog signal processor

PrF: antialiasing filtering PoF: smooth out the staircase waveform

example


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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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

The main tasks of DSP



DSP application examples

Telecommunications Multiplexing Compression Echo control

Audio Processing Music Speech generation Speech recognition



DSP application examples

Echo Location Radar Sonar Reflection seismology

Image Processing Medical Space Commercial Imaging Products



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Demonstration

bellclarinet brass

FM synthesis of sound

chirp

Digital image processing

Deblurring

Noise reduction

Edge detection


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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Copyright © 2005. Shi Ping CUCreturn

The sound signal is an example of a 1-D signal where the independent variable is time


A black-and-white image signal is an example of a 2-D signal where the 2 independent variables are the 2 spatial variables.

),( yxI


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)

),(),(),(

),(yxIyxIyxI

yxu

G

G

R


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.

),,( tyxI


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)

),,(),,(),,(

),,(tyxItyxItyxI

tyxu

B

G

R


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Chap1-Introduction to DSP

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