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CompSci > 3.5 Fundamentals of data representation > Flashcards

3.5 Fundamentals of data representation Flashcards

1
Q

Natural numbers (symbol, what they are)

A

N, positive integers including 0

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2
Q

Integers (symbol, what they are)

A

Z, positive and negative whole numbers including 0

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3
Q

Real numbers (symbol, what they are)

A

R, any positive or negative number and includes both irrational and rational numbers

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4
Q

Rational numbers (symbol, what they are)

A

Q, ratio between two integers

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5
Q

Irrational numbers (what they are, example)

A

can not be represented as a fraction, pi

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6
Q

Ordinal numbers (what they are)

A

a natural number that describes the numerical position of a value

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7
Q

denary (base-10) numbers

A

using 0-9 to represent a number, power of 10

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8
Q

binary (base-2) numbers

A

using 0 or 1 to represent a number, power of 2

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9
Q

most significant and least significant bit

A

most significant is leftmost and least significant is rightmost

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10
Q

hexadecimal (base-16) numbers

A

0-9 then A-F, power of 16

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11
Q

why is hexadecimal used as a shorthand for binary?

A

long sequences of binary are hard to read and understand for humans

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12
Q

how many different values can be represented with n bits?

A

2^n

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13
Q

kilobytes

A

1000 bytes, 10^3

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14
Q

megabyte

A

1 million bytes, 10^6

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15
Q

gigabyte

A

1 billion bytes, 10^9

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16
Q

terabyte

A

1 trillion bytes, 10^12

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17
Q

kibibyte

A

1024 bytes, 2^10

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18
Q

mebibyte

A

2^20 bytes

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19
Q

gibibyte

A

2^30 bytes

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20
Q

tebibyte

A

2^40

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21
Q

ascii

A

used 7 bits to represent characters, common language for computers

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22
Q

extended ascii

A

8 bit character set containing 256 characters

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23
Q

unicode

A

supports languages that use a different language, uses up to 32 bits to represent a character

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24
Q

what is a parity bit?

A

extra bit added depending on the total number of 1s

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25
why are parity bits used?
to allow the receiving end to detect errors in data transmission
26
even parity
number of 1s add up to an even number
27
odd parity
number of 1s add up to an odd number
28
parity bit disadvantage
multiple errors wont show
29
majority voting
every bit is replicated an odd number of times, does not require a person to check
30
majority voting disadvantages
if two bits are transmitted incorrectly it will take the error as being correct, data is sent multiple times slowing down transmission time
31
analogue data
continuous data, needs to be converted into an electrical analogue signal
32
digital data
discrete data
33
digital signal
discrete values over time
34
analogue to digital conversion
continuous signal needs to be converted into discrete binary values through an ADC
35
how does an ADC work?
converts analogue electrical signals into digital data that can be stored
36
digital to analogue DAC
converts digital data stored on a computer into analogue electrical signals
37
bitmap image is made of
grid of pixels
38
colour depth
bit per pixel, 2^number
39
image resolution
clarity of an image, size of image
40
calculating image resolution
width in pixels x height in pixels
41
calculating bitmap file size
width in pixels x height in pixels x colour depth
42
reducing colour depth and effect on image quality
poorer quality as humans can see so many colours it doesn't look realistic
43
reducing colour depth and effect on file size
file size also reduces, less bits used saves more storage, quicker download time
44
metadata
data about image that is not included in the image
45
examples of metadata
location of creation, camera settings, date and time of creation, file format
46
how are bitmapped graphics created?
image will be stored as a grid of pixels, where each one represents a colour
47
sound processing
sound waves picked up by microphone, signals processed by ADC converting electrical signals into digital values (sampling), assigned a binary pattern
48
sampling (sound)
taking measurements of the levels of the analogue signal at regular intervals
49
playing a digital audio file
DAC to convert digital values into analogue electrical signals, signals are passed onto a speaker, vibrating the speaker cone making sound waves
50
sampling rate
number of samples taken per second, measured in hertz
51
sample resolution
number of bits used to represent a sample
52
nyquist theorem
in order to have an accurate representation of a signal, the sampling rate has to be at least twice the highest frequency present
53
calculating sound file size (in bits)
sampling rate x seconds x sample resolution
54
stereo sound files
multiply sound file size by two, left and right side
55
MIDI
does not store a digital representation of an analogue, hold signals to produce sound
56
MIDI advantages
uses less storage space, performance can be manipulated
57
MIDI disadvantages
does not sound as realistic
58
compression does not
change the fundamental properties of the file, e.g. music will still last the same amount of time
59
lossy compression
data is permanently removed, approximation of the original, might remove unnecessary data
60
lossy compression can not be applied to
word files
61
lossless compression
no data is lost, get back exactly what you started with when you decompress, RLE or dictionary based
62
RLE (run length encoding)
finds runs of repeated binary patterns and replaces them with a single instance of a pattern
63
dictionary based encoding
finds common strings and assigns that a code which is stored instead
64
plaintext
message that has not been encrypted
65
symmetric methods
same key is used to encrypt and decrypt
66
asymmetric methods
sender and recipient use a key pair
67
caesar cipher
shifts each letter of the plaintext by a number specified by the key
68
vernam cipher encrypting
a message is encrypted using a key of the same length, binary ascii for each letter of plaintext and key, XOR corresponding pair of bits
69
vernam cipher decryption
binary code for each character of the cipher text and key, XOR
70
XOR operations
0 + 0 = 0, 0 + 1 = 1, 1 + 0 = 1, 1 +1 = 0
71
analogue to digital conversion 2
analogue recorded via amplifier, each sample is quantised into integer, integer into binary

CompSci (8 decks)

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