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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. Minifloat - Wikipedia

    en.wikipedia.org/wiki/Minifloat

    A 2-bit float with 1-bit exponent and 1-bit mantissa would only have 0, 1, Inf, NaN values. If the mantissa is allowed to be 0-bit, a 1-bit float format would have a 1-bit exponent, and the only two values would be 0 and Inf. The exponent must be at least 1 bit or else it no longer makes sense as a float (it would just be a signed number).

  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. Double-precision floating-point format - Wikipedia

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

    Exponent: 11 bits; Significand precision: 53 bits (52 explicitly stored) The sign bit determines the sign of the number (including when this number is zero, which is signed). The exponent field is an 11-bit unsigned integer from 0 to 2047, in biased form: an exponent value of 1023 represents the actual zero. Exponents range from −1022 to ...

  6. 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 ...

  7. 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.

  8. Numeric precision in Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Numeric_precision_in...

    The last two examples illustrate what happens if x is a rather small number. In the second from last example, x = 1.110111⋯111 × 2 −50 ; 15 bits altogether. The binary is replaced very crudely by a single power of 2 (in this example, 2 −49) and its decimal equivalent is used.

  9. Significand - Wikipedia

    en.wikipedia.org/wiki/Significand

    In 1946, Arthur Burks used the terms mantissa and characteristic to describe the two parts of a floating-point number (Burks [11] et al.) by analogy with the then-prevalent common logarithm tables: the characteristic is the integer part of the logarithm (i.e. the exponent), and the mantissa is the fractional part.

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