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data representation


Cambridge Computer Studies Mind Map on data representation, created by Daniel Taylor on 06/14/2018.
Daniel Taylor
Mind Map by Daniel Taylor, updated more than 1 year ago
Daniel Taylor
Created by Daniel Taylor about 4 years ago

Resource summary

data representation
  1. binary
    1. a series of 1s and 0s which each represent a number
      1. 1 is on and 0 is off
      2. computers read everything in binary
        1. binary addition
          1. 0+0=0
            1. 1+1=0 but carry a 1 to the next column
              1. 1+0 or 0+1=1 with no carried numbers
              2. Binary to denary conversion
                1. every denary number has a binary equivalent
              3. denary
                1. everyday numbers from 1 - 9
                2. hexadecimal
                  1. normal numbers up to 9 then 10 to 15 are A, B, C, D, E, and F represent the numbers
                    1. e.g. FF = 255, 11 = 17, 5B = 91 and E8 = 232
                    2. easy to convert to and from binary
                      1. a 16 base system
                      2. images
                        1. pixel: smallest addressable area
                          1. every pixel has the same amount of memory attached to it, if it is 2 bits it can store 4 colours
                            1. 8 bits = 256 colours
                          2. resolution = number of pixels across by number of pixels down
                          3. sound
                            1. sampling rate: how frequently the sounds are sampled
                              1. original sound is analogue but computers use digital
                                1. bitrate: number of bits that can be put through the system in a second, measured in kilobytes per second
                                  1. bits per sample x samples per second x number of channels
                                  2. midi
                                  3. compression
                                    1. lossless compression
                                      1. lossless compression leaves out repeated data and instead makes a note of how many times it is repeated
                                      2. lossy compression
                                        1. lossy removes data to make it smaller but this cant be restored and the image may not have the same quality as before
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