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  2. Fixed-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_arithmetic

    A fixed-point representation of a fractional number is essentially an integer that is to be implicitly multiplied by a fixed scaling factor. For example, the value 1.23 can be stored in a variable as the integer value 1230 with implicit scaling factor of 1/1000 (meaning that the last 3 decimal digits are implicitly assumed to be a decimal fraction), and the value 1 230 000 can be represented ...

  3. Q (number format) - Wikipedia

    en.wikipedia.org/wiki/Q_(number_format)

    Q numbers are a ratio of two integers: the numerator is kept in storage, the denominator is equal to 2 n. Consider the following example: The Q8 denominator equals 2 8 = 256; 1.5 equals 384/256; 384 is stored, 256 is inferred because it is a Q8 number.

  4. Arithmetic shift - Wikipedia

    en.wikipedia.org/wiki/Arithmetic_shift

    The formal definition of an arithmetic shift, from Federal Standard 1037C is that it is: . A shift, applied to the representation of a number in a fixed radix numeration system and in a fixed-point representation system, and in which only the characters representing the fixed-point part of the number are moved.

  5. List of binary codes - Wikipedia

    en.wikipedia.org/wiki/List_of_binary_codes

    This is a list of some binary codes that are (or have been) used to represent text as a sequence of binary digits "0" and "1". Fixed-width binary codes use a set number of bits to represent each character in the text, while in variable-width binary codes, the number of bits may vary from character to character.

  6. Fixed-point logic - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_logic

    For a relational signature X, FO[PFP](X) is the set of formulas formed from X using first-order connectives and predicates, second-order variables as well as a partial fixed point operator used to form formulas of the form [, ⁡], where is a second-order variable, a tuple of first-order variables, a tuple of terms and the lengths of and coincide with the arity of .

  7. Computer number format - Wikipedia

    en.wikipedia.org/wiki/Computer_number_format

    2.3434E−6 = 2.3434 × 10 −6 = 2.3434 × 0.000001 = 0.0000023434. The advantage of this scheme is that by using the exponent we can get a much wider range of numbers, even if the number of digits in the significand, or the "numeric precision", is much smaller than the range. Similar binary floating-point formats can be defined for computers.

  8. Kaprekar's routine - Wikipedia

    en.wikipedia.org/wiki/Kaprekar's_routine

    In number theory, Kaprekar's routine is an iterative algorithm named after its inventor, Indian mathematician D. R. Kaprekar. [1] [2] Each iteration starts with a number, sorts the digits into descending and ascending order, and calculates the difference between the two new numbers. As an example, starting with the number 8991 in base 10:

  9. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    So a fixed-point scheme might use a string of 8 decimal digits with the decimal point in the middle, whereby "00012345" would represent 0001.2345. In scientific notation, the given number is scaled by a power of 10, so that it lies within a specific range—typically between 1 and 10, with the radix point appearing immediately after the first ...