Data Rep

Question 1

How does Twos Complement work?

Answer 1

Most significant bit is given a negative value

Question 2

Range of Twos Complement?

Answer 2

2^(n-1)-1 to -2^(n-1)

Question 3

Floating point - Binary to Decimal

Answer 3

Convert the exponent to decimal (x)
Place a point x+1 digits into binary number
Convert everything to decimal as you would normally

Question 4

Floating point - Decimal to Binary

Answer 4

First, find binary version normally
Add a zero to the leftmost side
Move the point to the left until in-between the 0 and 1, count how many movements
Convert number of movements to binary - that is the exponent. Mantissa is the OG binary conversion incl 0

Question 5

Absolute error method

Answer 5

Difference between actual and given decimal values.

Question 6

Relative error method

Answer 6

Abs error/Actual value
multiplied by 100

Question 7

Floating Point allows for…

Answer 7

Allows for larger range of numbers with a given number of bits as exponent can be negative or positive
Large Exponent and small mantissa allows a large range but little precision

Question 8

Normalisation Method

Answer 8

Split into mantissa and exponent
Shift x positions left or right to get 10 or 01 start
Take away x from decimal exponent value
Combine new mantissa and exponent

Question 9

Underflow Def

Answer 9

When very small numbers are being represented but there aren’t enough bits available.

Question 10

Analogue to Digital Conversion

Answer 10

ADC takes regular readings (samples) of analogue signal per second
Samples are quantised
Stored digitally as a bit pattern

Question 11

Storage formula for Bitmap image

Answer 11

Area*Bit Depth
Minimum value however, may also contain metadata eg height, width, date created and colour depth

Question 12

Vector Graphics

Answer 12

Geometric shapes stored in a list
List also stores colours, start positions, fill styles, dimensions

Question 13

Vector Graphics vs Bitmaps

Answer 13

Vector graphics use shapes not pixels hence can be scaled with our quality loss
VG well suited to logos etc but useless for photos
VG uses less storage space as info is stored for each shape instead of each pixel

Question 14

Sound size formula

Answer 14

Duration * Sample rate * Sample resolution
+ metadata

Question 15

Nyquist Theorem

Answer 15

Sampling rate must be double sound frequency to accurately represent sound

Question 16

MIDI

Answer 16

Musical Instrument Digital Interface
Stores event messages instead of sound
Event message contains volume of note, pitch, instrument used etc

Question 17

MIDI Pros and Cons

Answer 17

Easy manipulation of music without loss in quality
Smaller in size and lossless
HOWEVER produces less realistic sound and can’t be used for storing speech

Question 18

Lossy compression

Answer 18

Compression with loss of data

Question 19

Lossless compression

Answer 19

RLE - replaces everything with number of times it occurs in a row
If high level of unique values present then compression is ineffective

Dictionary - Each token is shown given a key, and data is replaced by keys. Dictionary appended to the file.

Question 20

How does the vernam cipher work

Answer 20

Aligns plaintext and the key
Converts each character into binary
Applies XOR to the two rows
Converts back into character

Question 21

4 error checking methods

Answer 21

Parity bit - Odd parity makes sure total number of 1s is odd
Majority Voting
Check digit
Checksum - data is modded and then appended to the packet. checked on the other side.