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  2. Single-precision floating-point format - Wikipedia

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

    Thus only 23 fraction bits of the significand appear in the memory format, but the total precision is 24 bits (equivalent to log 10 (2 24) ≈ 7.225 decimal digits) for normal values; subnormals have gracefully degrading precision down to 1 bit for the smallest non-zero value. The bits are laid out as follows:

  3. Significand - Wikipedia

    en.wikipedia.org/wiki/Significand

    The significand [1] (also coefficient, [1] sometimes argument, [2] or more ambiguously mantissa, [3] fraction, [4] [5] [nb 1] or characteristic [6] [3]) is the first (left) part of a number in scientific notation or related concepts in floating-point representation, consisting of its significant digits. For negative numbers, it does not include ...

  4. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    The 24-bit significand will stop at position 23, ... As decimal fractions can often not be ... 3.141 8730499798241950 6 3.141 6627470548084133 3.141 ...

  5. Decimal floating point - Wikipedia

    en.wikipedia.org/wiki/Decimal_floating_point

    For example, a significand of 8 000 000 is encoded as binary 0111 1010000100 1000000000, with the leading 4 bits encoding 7; the first significand which requires a 24th bit (and thus the second encoding form) is 2 23 = 8 388 608. In the above cases, the value represented is: (−1) sign × 10 exponent−101 × significand

  6. decimal32 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Decimal32_floating-point...

    (−1) sign × 10 exponent−101 × significand, with the significand understood as positive integer. Alternatively it can be understood as (−1) sign × 10 exponent−95 × significand with the significand digits understood as d 0 . d −1 d −2 d −3 d −4 d −5 d −6, note the radix dot making it a fraction.

  7. Minifloat - Wikipedia

    en.wikipedia.org/wiki/Minifloat

    A minifloat in 1 byte (8 bit) with 1 sign bit, 4 exponent bits and 3 significand bits (in short, a 1.4.3 minifloat) is demonstrated here. The exponent bias is defined as 7 to center the values around 1 to match other IEEE 754 floats [3] [4] so (for most values) the actual multiplier for exponent x is 2 x−7. All IEEE 754 principles should be ...

  8. Half-precision floating-point format - Wikipedia

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

    Thus, only 10 bits of the significand appear in the memory format but the total precision is 11 bits. In IEEE 754 parlance, there are 10 bits of significand, but there are 11 bits of significand precision (log 10 (2 11) ≈ 3.311 decimal digits, or 4 digits ± slightly less than 5 units in the last place).

  9. 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.