Computer Science & Information TechnologyComputer Organization and Architecture

Floating-Point Representation

  • Very large numbers cannot be represented using fixed-point notation, nor can very small fractions.
  • For decimal numbers, we get around this limitation by using scientific notation.

Example:
976000000000 can be represented as 9.76 × 1011.
0.00000000000976 can be represented as 9.76 × 10–12.

  • This same approach can be taken with binary numbers. We can represent a number in the form M × B±E
    where, M is mantissa, E is exponent

Floating Point Format

  • In order to simply operations, floating point numbers are normalized. A normalized number is one in which the most significant digit of mantissa is 1. Thus, a normalized non zero number is on in the form ± 1.bbb …. b × 2±E.

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