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  2. Decimal data type - Wikipedia

    en.wikipedia.org/wiki/Decimal_data_type

    In the floating-point case, a variable exponent would represent the power of ten to which the mantissa of the number is multiplied. Languages that support a rational data type usually allow the construction of such a value from two integers, instead of a base-2 floating-point number, due to the loss of exactness the latter would cause.

  3. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    For numbers with a base-2 exponent part of 0, i.e. numbers with an absolute value higher than or equal to 1 but lower than 2, an ULP is exactly 2 −23 or about 10 −7 in single precision, and exactly 2 −53 or about 10 −16 in double precision. The mandated behavior of IEEE-compliant hardware is that the result be within one-half of a ULP.

  4. Significand - Wikipedia

    en.wikipedia.org/wiki/Significand

    The same value can also be represented in scientific notation with the significand 1.2345 as a fractional coefficient, and +2 as the exponent (and 10 as the base): 123.45 = 1.2345 × 10 +2. Schmid, however, called this representation with a significand ranging between 1.0 and 10 a modified normalized form. [12] [13] For base 2, this 1.xxxx form ...

  5. Double-precision floating-point format - Wikipedia

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

    Given the hexadecimal representation 3FD5 5555 5555 5555 16, Sign = 0 Exponent = 3FD 16 = 1021 Exponent Bias = 1023 (constant value; see above) Fraction = 5 5555 5555 5555 16 Value = 2 (ExponentExponent Bias) × 1.Fraction – Note that Fraction must not be converted to decimal here = 22 × (15 5555 5555 5555 16 × 2 −52) = 2 −54 ...

  6. Decimal floating point - Wikipedia

    en.wikipedia.org/wiki/Decimal_floating_point

    e=5; s=1.234571 − e=5; s=1.234567 ----- e=5; s=0.000004 e=−1; s=4.000000 (after rounding and normalization) The floating-point difference is computed exactly because the numbers are close—the Sterbenz lemma guarantees this, even in case of underflow when gradual underflow is supported.

  7. Math library - Wikipedia

    en.wikipedia.org/wiki/Math_library

    Logarithm in base 2 is relatively straightforward, as the integer part k is already in the floating-point exponent; a preliminary range reduction is accordingly performed, yielding k. The mantissa x (where log2( x ) is between -1/2 and 1/2) is then compared to a table and intervals for further reduction into a z with known log2 and an in-range ...

  8. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    This alternative definition is significantly more widespread: machine epsilon is the difference between 1 and the next larger floating point number.This definition is used in language constants in Ada, C, C++, Fortran, MATLAB, Mathematica, Octave, Pascal, Python and Rust etc., and defined in textbooks like «Numerical Recipes» by Press et al.

  9. Mantissa - Wikipedia

    en.wikipedia.org/wiki/Mantissa

    Mantissa (/ m æ n ˈ t ɪ s ə /) may refer to: Mantissa (logarithm) , the fractional part of the common (base-10) logarithm Significand (also commonly called mantissa), the significant digits of a floating-point number or a number in scientific notation