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  2. Minifloat - Wikipedia

    en.wikipedia.org/wiki/Minifloat

    Decimal floating-point ... is also available and is equal to ... = 1.875 × 2 3 = 15 (normalized number) 0 0010 000 = 1.000 2 × 2 2 - (-2) = 1.000 × 2 4 = 16 ...

  3. Decimal floating point - Wikipedia

    en.wikipedia.org/wiki/Decimal_floating_point

    For example, while a fixed-point representation that allocates 8 decimal digits and 2 decimal places can represent the numbers 123456.78, 8765.43, 123.00, and so on, a floating-point representation with 8 decimal digits could also represent 1.2345678, 1234567.8, 0.000012345678, 12345678000000000, and so on.

  4. Half-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Half-precision_floating...

    This can express values in the range ±65,504, with the minimum value above 1 being 1 + 1/1024. Depending on the computer, half-precision can be over an order of magnitude faster than double precision, e.g. 550 PFLOPS for half-precision vs 37 PFLOPS for double precision on one cloud provider.

  5. Orders of magnitude (data) - Wikipedia

    en.wikipedia.org/wiki/Orders_of_magnitude_(data)

    2 0: bit: 10 0: bit 1 bit – 0 or 1, false or true, Low or High (a.k.a. unibit) 1.442695 bits (log 2 e) – approximate size of a nat (a unit of information based on natural logarithms) 1.5849625 bits (log 2 3) – approximate size of a trit (a base-3 digit) 2 1: 2 bits – a crumb (a.k.a. dibit) enough to uniquely identify one base pair of DNA

  6. Computer number format - Wikipedia

    en.wikipedia.org/wiki/Computer_number_format

    That is, the value of an octal "10" is the same as a decimal "8", an octal "20" is a decimal "16", and so on. In a hexadecimal system, there are 16 digits, 0 through 9 followed, by convention, with A through F. That is, a hexadecimal "10" is the same as a decimal "16" and a hexadecimal "20" is the same as a decimal "32".

  7. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    By this definition, ε equals the value of the unit in the last place relative to 1, i.e. () (where b is the base of the floating point system and p is the precision) and the unit roundoff is u = ε / 2, assuming round-to-nearest mode, and u = ε, assuming round-by-chop.

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    mail.aol.com

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  9. 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 ...