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  2. Comparison of data-serialization formats - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data...

    binary real values are represented in a binary format that includes the mantissa, the base (2, 8, or 16), and the exponent; the special values NaN, -INF, +INF , and negative zero are also supported Multiple valid types ( VisibleString, PrintableString, GeneralString, UniversalString, UTF8String )

  3. Microsoft Binary Format - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Binary_Format

    MBF numbers consist of an 8-bit base-2 exponent, a sign bit (positive mantissa: s = 0; negative mantissa: s = 1) and a 23-, [43] [8] 31-[8] or 55-bit [43] mantissa of the significand. There is always a 1-bit implied to the left of the explicit mantissa, and the radix point is located before this assumed bit.

  4. Subnormal number - Wikipedia

    en.wikipedia.org/wiki/Subnormal_number

    Notice that for a binary radix, the leading binary digit is always 1. In a subnormal number, since the exponent is the least that it can be, zero is the leading significant digit (0.m 1 m 2 m 3...m p−2 m p−1), allowing the representation of numbers closer to zero than the smallest normal number. A floating-point number may be recognized as ...

  5. Minifloat - Wikipedia

    en.wikipedia.org/wiki/Minifloat

    The above describes an example 8-bit float with 1 sign bit, 4 exponent bits, and 3 significand bits, which is a nice balance. However, any bit allocation is possible. A format could choose to give more of the bits to the exponent if they need more dynamic range with less precision, or give more of the bits to the significand if they need more ...

  6. File:Binary search vs Linear search example.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Binary_search_vs...

    Example comparing two search algorithms. To look for "Morin, Arthur" in some ficitious participant list, linear search needs 28 checks, while binary search needs 5. Svg version: File:Binary search vs Linear search example svg.svg.

  7. Half-precision floating-point format - Wikipedia

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

    The half-precision binary floating-point exponent is encoded using an offset-binary representation, with the zero offset being 15; also known as exponent bias in the IEEE 754 standard. [9] E min = 00001 2 − 01111 2 = −14; E max = 11110 2 − 01111 2 = 15; Exponent bias = 01111 2 = 15

  8. Extended precision - Wikipedia

    en.wikipedia.org/wiki/Extended_precision

    In the following table, "s" is the value of the sign bit (0 means positive, 1 means negative), "e" is the value of the exponent field interpreted as a positive integer, and "m" is the significand interpreted as a positive binary number, where the binary point is located between bits 63 and 62.

  9. IEEE 754-1985 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754-1985

    In single precision, the bias is 127, so in this example the biased exponent is 124; in double precision, the bias is 1023, so the biased exponent in this example is 1020. fraction = .01000… 2 . IEEE 754 adds a bias to the exponent so that numbers can in many cases be compared conveniently by the same hardware that compares signed 2's ...