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Page 1: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

Data Representation

國立清華大學資訊工程學系

CS1356 資訊工程導論

112/04/18

Page 2: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

2

Problem with Colors

• Which one is 桃紅色 ?

Why such difficulty?

Page 3: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

3

Continuous versus Discrete

• Which are “continuous”?– Color– Light– Cars– Sound– Height and weight– Electric current and voltage– English letters

Many natural phenomena are continuous

Page 4: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

4

Represent Continuous Things

• Analog signal: simulation of a continuous time varying quantity in another– Voltage or current is an "analog" of the sound

timetime

strength voltage

Page 5: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

5

Alternative: Digital/Discrete

• How many colors in a rainbow?

Seven only? discretizationSeven only? discretization

Page 6: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

6

Computers Work with Signals

• What are inside the “black box”? – Data representation– Data processing

ComputerAnalog/digital signals

Page 7: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

7

Two Different Worlds

What we see/hear Inside computers

Text a,b,c

Number 1,2,3

Sound

Image

Video

01100001,01100010,01100011

00000001,00000010,00000011

01001100010101000110100…

10001001010100000100111...

00110000001001101011001…

Discrete/digital and binary!Discrete/digital and binary!

Page 8: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

8

Binary System

• Computers use 0 and 1 to represent and store all kinds of data

• Why binary?– We need to find physical objects/phenomena

to store, transmit, and process data. Binary is the most straightforward representation.

對負 陽

勝偽

有 上

0

黑南無 下 白 真 負

北 正 錯 陰 關 1

Page 9: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

9

Some Jargons

• Bit: a binary digit (0 or 1)

• Byte: 8 bits– Basic storage unit in

computer system

• Hexadecimal notation:– Represents each 4 bits

by a single symbol– Example: A3 denotes

1010 0011

(Fig. 1.6)

Page 10: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

10

Hexadecimal Notation

• Internally, computers store and process 0 and 1 (bits)

• But, it is hard for humans to deal with writing, reading and remembering bits

• Hexadecimal notations help humans to communicate

Page 11: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

11

More Jargons

• Kilobyte: 210 bytes = 1024 bytes 103 bytes– Example: 3 KB 3 103 bytes

• Megabyte: 220 bytes 106 bytes– Example: 3 MB 3 106 bytes

• Gigabyte: 230 bytes 109 bytes– Example: 3 GB 3 109 bytes

• Terabyte: 240 bytes 1012 bytes– Example: 3 TB 3 1012 bytes

Page 12: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

12

Outline

• Data representation in bit patterns

• Binary operations and logic gates

• Data storage and transmission

• Data processing

Page 13: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

13

Data Representation in Bit Patterns

Text, number, image, and sound

Page 14: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

14

Binary Numeral System (Sec. 1.5)

• Uses bits to represent a number in base-2

• We put a subscript b to a number for binary, and a subscript d for decimal– 10d is number ten, and 10b is number two

(Fig. 1.15)

Page 15: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

15

4-bit Representation

http://www.swarthmore.edu/NatSci/echeeve1/Ref/BinaryMath/NumSys.html

Decimal Hexadecimal Binary

0 0 0000

1 1 0001

2 2 0010

3 3 0011

4 4 0100

5 5 0101

6 6 0110

7 7 0111

8 8 1000

9 9 1001

10 A 1010

11 B 1011

12 C 1100

13 D 1101

14 E 1110

15 F 1111

Page 16: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

16

Binary to Decimal

• What is the decimal number of 100101b?

20

21

22

23

24

25

(Fig. 1.16)

Page 17: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

17

Decimal to Binary

• What is the binary number of 13d?

– First, how many bits we need for 13?• Since 13<16=24, 4 bits can represent 13

– Second, decide b0 is 0 or 1

• Since 13 is odd, b0 must be 1

– Then? How to decide b1?

• You can do (13-b0)/2 = 6 = b34+b22+b11

• Since 6 is even, b1 must be 0

13 = = b38+b24+b12+ b01b3 b2 b1 b0

Page 18: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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– We can use the same way to decide b2 and b3

• (6-b1)/2 = 3= b32+b21 is odd, so b2 is 1

• (3-b2)/2 = 1= b31, b3 must be 1

– So, 13d = 1101b

• You have your first algorithm here

(Fig. 1.17)

Page 19: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

19

Running the Algorithm 6

Remainder =1

1

Remainder =0

3

0

1

Remainder =1

1

0

Remainder =1

1

Binary representation

(Fig. 1.18)

Page 20: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

20

Binary Number Calculations

• Binary number is easy for calculations

• For example, the one bit addition

• So, what is 5d+9d in binary number form?

0 1 0 1

1 0 0 15

914

+

1 1 1 0

Carry

(Fig. 1.19)

Page 21: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

21

Another Example

00111010 + 00011011

10

1

1

1

01

1

0

1

10

The binary addition facts

Carry

Page 22: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

22

Negative Numbers (Sec. 1.6)

• How to represent -1, -2, … on a computer?• Solution 1: use an extra bit to represent the

negative sign – It is called the sign bit, in front of numbers– Usually, 0 is for positives; 1 is for negatives– Example: 1 0001 is -1 and 0 0100 is +4

• Note: the sign bit does not carry value (it is not part of the value)

Page 23: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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4-bit Representation, AgainDecimal Hexadecimal Binary

+0 0 0 000

+1 1 0 001

+2 2 0 010

+3 3 0 011

+4 4 0 100

+5 5 0 101

+6 6 0 110

+7 7 0 111

-0 8 1 000

-1 9 1 001

-2 A 1 010

-3 B 1 011

-4 C 1 100

-5 D 1 101

-6 E 1 110

-7 F 1 111

Decimal Hexadecimal Binary

0 0 0000

1 1 0001

2 2 0010

3 3 0011

4 4 0100

5 5 0101

6 6 0110

7 7 0111

8 8 1000

9 9 1001

10 A 1010

11 B 1011

12 C 1100

13 D 1101

14 E 1110

15 F 1111

Page 24: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

24

Solution-1 Representation

• Example: 1 001 is -1 and 0 100 is +4

• How can we do the addition (-1) + (4) efficiently?

• Question: Can we use “addition” to do addition and subtraction? with and without signs

• Solution idea:Use a different representation!

Page 25: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Solution 2

• The negative sign “–” just means the “opposite” or the “inverse”– For example, the opposite of east is west.

(why is not south or north?)– For addition, the inverse of a number d,

denoted I(d), has the property: I(d)+d=0– We can use this to define negative numbers

Page 26: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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• If we use four bits to represent a number, zero is 0000, and one is 0001. What is -1?– Find b3, b2, b1, b0 such that

– The solution is 1111– You can use the same

method to find other numbers– Observe: the leading bit is 1

for negative values sign bit

b3 b2 b1 b0

+ 0 0 0 1

1 0 0 0 0

This 1 will be “dropped ” since it is a 4 bits numbering system.

(Fig. 1.21)

Page 27: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

27

Two’s Complement

• A simple algorithm to find the inverse1. Change each bit 0 to 1 and bit 1 to 0

2. Add 1

• This number representation is called the two’s complement

6d = 0110b

1001b

1001b

+ 0001b

1010b= – 6d

0110b ( 6)

+ 1010b (–6)

1 0000b (0)

truncated

Page 28: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

28

Exercises

• What are the decimal numbers for the following 2’s complement representations?

• Find the negative value represented in 2’s complement for each number

(a) 00000001 (b) 01010101 (c) 11111001

(d) 10101010 (e) 10000000 (f) 00110011

Page 29: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Calculation with 2’s Complement

• Calculation can be made easy for two’s complement representation– Example

• use addition only• same with and

without signs

(Fig. 1.22)

Page 30: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

30

Overflow

• Suppose computer only allow 4 bits

• What is 5+4?

• This is called overflow– Adding two positive (negative)

numbers results in a negative (positive) number

– A 4-bit 2’s complement system can only represent 7~ –8

5d+4d=0101b + 0100b =1001b

Page 31: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

31

Fractions (pp. 67)

• The binary representation of fractions– Problem: where to put the decimal point?

2-3

2-2

2-1

20

21

22

(Fig. 1.20)

Page 32: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

32

Floating Point (Sec. 1.7)

• To represent a wide range of numbers, we allow the decimal point to “float”40.1d = 4.01d101 = 401d10-1 = 0.401d102

– It is just like the scientific notation of numbers101.101b = +1.01101b 22d = +1.01101b 210b

• This is called the floating point representation offractions

Note: Exponent has a sign too!(Fig. 1.26)

Page 33: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

33

Coding the Value of 25/8

• Exponent uses excess notation

25/8

MantissaExponentSign

Binary representation 10.101

Normalization 0.10101× 22

1 0 1 0 truncated1100

“000” represents the smaller number

(Fig. 1.27) (Fig. 1.25)

Page 34: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

34

Truncation Error (pp. 78-79)

• Mantissa field is not large enough– 25/8 = 2.625

• Nonterminating representation– 0.1 = 1/16+1/32+1/256+1/512 + ...

– Change the unit of measure do not use fractions

• Order of computation:2.5 + 0.125 + 0.125

2.5 + round off error (0.125)

2.5 + 0 + 0

Page 35: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

35

Exercises

• What are the fractions for the following floating number representations? – Suppose 1 bit for sign, 3 bits for exponent

(using excess notation), 4 bits for mantissa

• If direct truncation is used, what are the ranges of their possible values?

(a) 01001010 (b) 01101101 (c) 11011100 (d) 10101011

Page 36: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

36

Text Data (Sec. 1.4)

• Each character is assigned a unique bit pattern

• ASCII code– American Standard Code for

Information Interchange– Uses 7 bits to represent most

symbols used in English text

(Fig. 1.13)

Page 37: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

37

Big5 Code

• For Chinese character encoding

• Uses 16 bits to represent a character– 1st byte: 0x81 (1000 0001) ~ 0xfe (1111

1110)– Second byte: 0x40 to 0x7e, 0xa1 to 0xfe– But does not use all (A140-F9FF)

• Example我 身 騎 白 馬A7DA A8AD C34D A5D5 B0A8

Page 38: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Unicode

• Uses 16 bits to represent the major symbols used in languages worldwide

Arabic char CJK char Latin char Indic char

Page 39: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Display Characters

• Computer doesn’t show the codes directly to us. It displays what we can read

• Those images for displaying characters are called fonts– We will talk about images later

Text code

A7DA

A8AD

C34D

Lookup tableImage files Display images

我 身 騎

Page 40: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

40

BCD Representation

• We can use 4 bits to represent decimal digits 0,1,2,3,4,5,6,7,8,9 – This is called “Binary-coded

decimal” (BCD) representation– Example: 317=0011 0001 0111

• Problems– We waste last 6 bit-patterns of 4 bits– Difficult to do calculation (+-*/)

BCD

0 0000

1 0001

2 0010

3 0011

4 0100

5 0101

6 0110

7 0111

8 1000

9 1001

Page 41: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

41

Example of Adding BCDs

• Using lookup table

• EX: 5+7

• In BCD:

0101

+0111

0001 0010

: : : :

0101 0110 0001 0001

0101 0111 0001 0010

0101 1000 0001 0011

0101 1001 0001 0100

: : : :

a b carry sum

Page 42: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

42

Images

• Image representation depends on what the output device can display– For example, an image on the seven

segment can be represented by 7 bits

No Img Repre.

0 1111110

1 0110000

2 1101101

3 1111001

4 0110011

5 1011011

6 1011111

7 1100000

8 1111111

9 1111011

A 1110111

Page 43: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

43

Common Output Devices

• The cathode ray tube (CRT) uses raster scan

• The liquid crystal display (LCD) is consisted of an array of crystal molecules

• Most printers use dots to compose images

Page 44: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Raster Image (bitmap)

• Represent an image by a rectangular grid of pixels (short for “picture element”)

• Each pixel is composedby three values: R, G, B.

(pp. 59)

Page 45: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

45

Vector Graph Image

• When scaled up, a bitmap image shows the zigzag effect

• Vector graph images store the mathematical formula for lines, shapes and colors of the objects in an image– Example: TrueType font

• Rasterisation: – A process converting

vector graph to raster imageAAAAAAAAAAAACourier New

Courier

Page 46: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

46

Sound (pp. 60-61)

• Sound is an acoustic wave– A simple wave can be characterized by

amplitude and frequency.• The larger amplitude the louder the sound• The higher frequency the higher pitch

– All sounds can be composed by simple waves.

• MIDI file– Represent sounds by the amplitude and

frequency of composed simple waves.

amplitude1/frequency

Page 47: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

47

Sampled Sound

• The sound composed by simple waves may not sound real

• Alternatively, sampling the real sound and record it

• Quality of sampled sound is measured by– Sampling rate: how often to do the sampling– Bit depth: bits used for one sample– CD music has sampling rate 44.1kHZ and

uses 16 bits for each sample

Page 48: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Video

• Digital video is composed by a sequence of “continuous” images and synchronized sound tracks– Each image is called a “frame”– Each frame is flashed on the screen for a

short time (1/24 seconds or 1/30 seconds)

Page 49: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Binary Operations and Logic Gates

Basic operations for binary data and the physical devices to

implement them

Page 50: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Electric Switch

• What are the inputs and outputs?

Page 51: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Switch in a Circuit

• How many inputs/outputs?

• How many “states”?

y = f(x1, x1, …, xn)?

ON, OFF

Page 52: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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How to Turn on a Switch?

• By hand

• By electricity?– Why do we want

to do that?

Let’s first study how to operate on ON/OFF

Page 53: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Binary and Logic (Sec. 1.1)

• Logic: concerns about true or false

• Logic operation: – If the room is dark and someone is in the

room, turn on the light.

• True/false can be represented by 0/1

Room is darkYes

No Someone in the room

Yes

No

Light is onYes

No

(1)

(0)

(1)

(0)(1)

(0)

Binary number system in computer logic

Page 54: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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The AND Function

• We can use the AND function to represent the statement

Room is dark

A

Someone in the room

B

Light is on

A .AND. B

0 0 0

0 1 0

1 0 0

1 1 1

Input Output

Page 55: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

55

Boolean Operators

• The AND function is a Boolean operator

• Boolean operator is an operation that manipulates one or more 0/1 values

• Other common Boolean operations OR XOR (exclusive or) NOTInput Output

0 0 0

0 1 1

1 0 1

1 1 1

Input Output

0 0 0

0 1 1

1 0 1

1 1 0

Input Output

0 1

1 0

(Fig. 1.2)

Page 56: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Logic Gate

• There are devices to implement Boolean operations gate

• Pictorial representation of gates

(Fig. 1.2)

Page 57: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

57

BIG Idea

• Computers store and process binary #

• Logic true and false can be used to represent binary 1 and 0

• Logic operations can be implemented by logic gates– and in turn by ON/OFF switches

• Computers can be implemented using logic gates for storing and processing

Page 58: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Example

• Almost all operations of computers can be carried out by logic gates– The textbook uses flip-flop as an example– We will use “one bit adder” as an example

• One bit adder has two inputs and two outputs (S: sum, C: carry)

A: input 1

B: input 2

S: output 1

C: output 2

Page 59: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

59

One Bit Adder

A B S C

0 0 0 0

0 1 1 0

1 0 1 0

1 1 0 1

• The truth table of anone-bit adder

• Compare it to the truth table of Boolean function AND, OR, XOR, NOT– S = A .XOR. B– C = A .AND. B

For “processing” data

Page 60: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

60

Flip-flops (pp. 40-42)

• Flip-flop: a circuit built from gates that can store one bit– One input line to set its stored value to 1– One input line to set its stored value to 0– While both input lines are 0, the most recently

stored value is preserved for “storing” data

Page 61: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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A Simple Flip-flop Circuit

(Fig. 1.3)

Page 62: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Setting Output to 1

1 or 0

(Fig. 1.4)

Page 63: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Setting Output to 1 (cont.)

(Fig. 1.4)

Page 64: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Setting Output to 1 (cont.)

A “1” is stored

(Fig. 1.4)

Page 65: Data Representation 國立清華大學資訊工程學系 CS1356 資訊工程導論 2015/6/2

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Another Way

(Fig. 1.5)

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How to Implement a Gate?

• LEGO’s “mechanical gates”– AND gate

1: pushing an axle in 0: pulling an axle out 

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Implement Gate with Switch

• Can we flip the switches without hands?

A B

AND gate

A

B

OR gate

A

NOT gate

A B

A B

XOR gate

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Electronic Switch

• The earliest one is the vacuum tube– 1884, Thomas Edison

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Transistor

• The problems of vacuum tubes are slow, large, expensive, easy to break

• Transistor can be faster, smaller, and more robust

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How Transistor Works (1/5)

• Transistors consist of three terminals: source, gate, and drain

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How Transistor Works (2/5)

• In the n-type transistor, both the source and the drain are negatively-charged and sit on a positively-charged well of p-silicon

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How Transistor Works (3/5)

• When positive voltage is applied to the gate, electrons in the p-silicon are attracted to the area under the gate forming an electron channel between the source and the drain

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How Transistor Works (4/5)

• When positive voltage is applied to the drain, the electrons are pulled from the source to the drain. In this state the transistor is on.

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How Transistor Works (5/5)

• If the voltage at the gate is removed, electrons are not attracted to the area between the source and drain. The pathway is broken and the transistor is turned off.

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Transistor as Switch

“gate” as the switch

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Transistor Abstraction

Hide the complexity of low-level circuits

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Transistors for Logic Gates

CMOS

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Integrated Circuit (IC)

• An electronic circuit consists of transistors and other components in the thin substrate of semiconductor material

• Also known as IC, microchip, or chip

• Invented by Jack Kilby and Robert Noyce– 2000 Nobel Prize in Physics

• VLSI: Very-Large-Scale IC– More than million transistors

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Exercises

• What input bit patterns will cause the following circuit to output 1? And output 0?

• What Boolean operation does the circuit compute?

output

input

input

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Data Storage and Transmission

Memory, RAM, address

CD/DVD, hard disk, flash memory

signal, communication media

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Storage Media

• Physical objects that can store bits and retrieve them can be a storage media

• Volatile (temporary) memory: – DRAM, SRAM, SDRAM

• Non-volatile storage (massive storage)– Optical systems: CD, DVD– Magnetic systems: hard disk, tape– Flash drives: iPod, cell phone, USB drivers…

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Memory (Sec. 1.2)

• Memory is used inside computers for temporary storages

• They are often called RAMs– Random Access Memory: data can be

accessed in any order– Dynamic RAM (DRAM): – Synchronous DRAM (SDRAM)  – Static RAM (SRAM)

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Data Storage Unit

• To efficiently access data, computers use 8 bits (a byte) as a smallest storage unit

• Some jargons for a byte– Most significant bit: at the high-order end– Least significant bit: at the low-order end

(Fig. 1.7)

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Memory Address

• Each storage unit in memory is numbered by an address so that data can be stored and loaded

– These numbers are assigned consecutively starting at zero

(Fig. 1.8)

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CD/DVD (pp. 52)

• CD: Compact Disk

• DVD: Digital Video Disk– Use bumps to represent 0/1

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Hard Disks (HDD)

• A hard platter holds the magnetic medium– Use magnetic field to represent 0/1

(pp. 49)

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Some Terms of Hard Disk

(Fig. 1.9)

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Flash Memory

• Use electrical charge to represent 0/1

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Files (pp. 54-55)

• File is the basic storage unit in massive storages that contain data – Text documents, photos, mp3,…

• A file is associated with many attributes– File name, file name extension – Size, modified date, read only, etc.

• It requires a system to store, retrieve, and organize files.* *We will study the operating system in chapter 3.

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Data Transfer

• Many media can transfer binary data – Voltage

– Voltage change

– Voice: telephone line (modem)– Electromagnetic wave: radio – Light: infrared, laser, fiber optics

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Data Communication Rates

• Measurement units– Bps: Bits per second– Kbps: Kilo-bps (1,000 bps)– Mbps: Mega-bps (1,000,000 bps)– Gbps: Giga-bps (1,000,000,000 bps)

• Multiplexing: make single communication path as multiple paths

• Bandwidth: maximum available rate

(pp. 127)

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Data Processing

Compression, error correction, encryption

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Have You Ever Thought …

( 靜宜大學機車停車場 )

Only if I can

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Data Compression (Sec. 1.8)

• Purpose: reduce the data size so that data can be stored and transmitted efficiently

• Example: what is the size of the video …

( 逢甲大學 GIS 中心 )

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Data Compression (Sec. 1.8)

• Purpose: reduce the data size so that data can be stored and transmitted efficiently

• Example: what is the size of the video …– 43 sec, 720x480, 29 frames/sec– 720x480x3x29x43 = 1,292,889,600 bytes– Use Windows Media (.wmv): 3,038,848 bytes

Compression!!!

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Data Compression (Sec. 1.8)

• For example: – 0000000000111111111 can be compressed

as (10,0,9,1)– 123456789 can be compressed as (1,1,9)– AABAAAABAAC can be compressed as

11011111011100, where A, B, C are encoded as 1, 01, and 00 respectively

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Many Compression Techniques

• Lossy versus lossless

• Run-length encoding

• Frequency-dependent encoding – Huffman codes

• Relative encoding/differential encoding

• Dictionary encoding (includes adaptive dictionary encoding such as LZW encoding)

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Different Data Has Different Compression Methods

• Image data– GIF: Good for cartoons– JPEG: Good for photographs– TIFF: Good for image archiving

• Video: MPEG– High definition television broadcast– Video conferencing

• Audio: MP3– Temporal masking, frequency masking

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Error Detection (Sec. 1.9)

• During transmission, error could happen – For example, bit 0 1 or bit 1 0

• How could we know there is an error?– Adding a parity bit (even versus odd)

(Fig. 1.28)

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Error Correction

• Can we find a way that not only detects an error, but also corrects errors?– Yes, by carefully designing the code– Suppose 010100 is received

(Fig. 1.30)

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Exercises

• Using the error correction code table to decode the following message

• The following bytes are encoded using odd parity. Which of them definitely has an error

001111 100100 001100 010001 000000 001011 011010 110110 100000 011100

(a) 10101101 (b) 10000001 (c) 11100000 (d) 11111111

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How to Share a Secrete?

lock unlock

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Data Encryption

• Suppose Alice wants to send a secret message, 10110101, to Bob– If they both know a key, 00111011, that no

one else knows– Alice can send the encrypted message to Bob

using XOR, and Bob can decrypt it the same way

10110101

XOR 00111011

10001110

10001110

XOR 00111011

10110101

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Secret Key Encryption

• This is called the secret key encryption

• If no one else knows the secret key and the key is generated randomly and used only once, this is a very good encryption algorithm

• Problems: – The key can be used only once– Alice and Bob both need to know the key

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Why Not Make It Public?

• Distribute the locks freely

• Keep the key to myself

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• Anything that is locked using my lock

• I can unlock it!

• And no one else can

With Public “Locks”

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Public Key Encryption

Asymmetric key

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Related Courses

• Data storage, representation, processing– 計算機結構– Data transfer 計算機網路概論

• Gates, transistors – 數位邏輯設計、電子電路、積體電路設計簡介

• Data compression, correction – 影像處理、資訊檢索、多媒體技術概論

• Data encryption– 離散數學、離散結構專題、密碼與網路安全概論