Fundamentals of Data Representation Flashcards
Natural Numbers
The set of positive integers and 0. A subset of Integer Numbers.
Integer Numbers
The set of numbers with no fractional part.
Rational Numbers
The set of numbers that can be represented as the ratio of two integers.
Irrational numbers
The set of numbers which cannot be represented as a ratio of two integers.
Ordinal Numbers
Natural numbers used to describe numerical position or order of objects
Binary
A number system with base 2.
Decimal
A number system with base 10.
Hexadecimal
A number system with base 16
Number base
The number of unique digits used by a particular number system to represent numbers.
Bit
A binary digit used by computers as the fundamental unit of information. Either 1 or 0.
Byte
A group of 8 bits
Nibble
A group of 4 bits
Binary prefix
A prefix to a unit representing a power of 2. Kibi = power of 10, Mebi = 20, Gibi= 30, Tebi = 40
Decimal Prefix
A prefix to a unit representing a power of 10
Signed binary
A binary system capable of representing negative and positive numbers
Unsigned binary
A binary system that can only represent positive numbers.
Two’s complement
Coding scheme used to represent negative or positive number. If most significant bit is 1 = negative
Exponent
Stores number of positions to move the decimal point
Fixed point form
Decimal point is at a fixed position.
Floating point form
Radix point moved by exponant and uses normalisation. Number before and after decimal point have to be opposite. ie 1.0… or 0.1…
Mantissa
Component of floating point that stores the significant figures of the floating point
Absolute error
Difference between correct value and rounded value (ie stored in binary)
Relative error
The percentage difference between the exact value and rounded value
Underflow
The misrepresentation of a numeric value because it is too small to be represented by allocated exponent.
Overflow
Incapability to store a number in assigned bits because it is too large
Character code
A unique binary representation of a character
ASCII
character set used to represent alphanumerical values or symbols as a set of 8 bits (used to be 7)
Unicode
Superset of ASCII. Uses 16 or 32 bits instead of 8, where first 8 bits are the same symbols as in ASCII, 32 bits includes thigs such as chinese characters. Good for multilingual data. Needs much more storage space and higher transmission time than ASCII.
Check digit
Method of error checking during data transmission by adding an extra digit at the end calculated from digits in code itself, usually mod 10.
Check sum
Checks for transmission errors by calculating sum of transmitted digits
Majority voting
Sending each bit thrice and then taking majority as correct digit. Error checking and correction during transmission.
Parity bits
Most significant bit used to make number of 1’s sent in data packet either even or odd.
Bitmapped Graphics
Image composed of an array of pixels with allocated number of bits arranged to form an image.
Bitmap resolution/Size
Width in pixels * height in pixels
Bitmap storage requirements
Amount of storage required for image = bitmap resolution * colour depth
Colour depth
Number of bits per pixel where n bits can store 2^n colours
Metadata
Data related to image file itself ie pixel width, depth, location
Bitmap Density
Number of pixels per inch, used to describe computer screen
Vector image
stores image as drawing list instead of pixels, can be scaled up without loss of detail, needs less storage space unless many tiny details.
Image manipulation
You can change individual pixels easily in bitmap images and individual objects but not pixels in vector images
Sound conversion to digital
Continuous analogue data converted to discrete digital data format where sampling frequency is measured in Hertz
Sampling rate
The frequency at which you record the amplitude of the sound, higher sampling rate equals smoother sounding playback, however needs a lot of storage
Sample size
num of bits per sec * length of recording in sec * num of bits per sample
Analogue data
Analogue technology records wave in original format, for ex signal in microscope can be copied onto tape, read, amplified and sent to a speaker, quantities are measured
Digital signal
Digital technology samples analogue waveforms in intervals and stores it on a digital device, quantities rather counted than measured
Analogue to digital
Microphone turns sound energy into electrical energy, ADC samples data and turns it into binary
Digital to Analogue
DAC converts binary back into a sound wave which then gets amplified which is connected to a speaker
Interpreting frequency
Higher frequency means higher pitch and vise versa
Nyquist theorem
Sampling rate should be at least double of the maximum frequency in original analogue signal
Sound sampling
The process of converting analogue sound waves to a digital waveform
Midi controller
Musical digital Instrument interface is a protocol for ADC audio transmission to a digital interface used for the majority of electronical musical instruments and computers
Event messages
Bidary data transmitted between midi device and computer processor that carries properties controlling when and how sound is produced
lossy compression
Removes non-essential information, data loss is non-recoverable
lossless compression
records patterns of data instead of actual data, no data is lost
Run-Length encoding
A type of lossless compression where repeated occurrences of the same data re stored as single data values with their counts
Dictionary based encoding
Lossless compression where often reoccurring words are stored in dictionary and those words in the text replaced with the dictionary code
Encryption
process of converting original data (plaintext) into a form which cannot be understood by unauthorised users (ciphertext) using an encryption algorithm (cipher)
Caeser cipher
shifts alphabet and number shifted by is the key
Vernam Cipher
Chiper that uses a one time pad to convert each each character to cipher text, computationally secure, uses XOR
Brute force attack
Try until code has been deciphered
Cryptanalysis
Uses for example frequency analysis to decode a cipher
One time pad
A secret random key which is only used once
Computationally secure
When time needed to decipher a code is unreasonable for data encrypted
