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  2. Rounding - Wikipedia

    en.wikipedia.org/wiki/Rounding

    3.125 RPSP to 1/4 ⇒ result is 3.25; 3.25 RPSP to 1/2 ⇒ result is 3.5; 3.5 round-half-to-even to 1 ⇒ result is 4 (wrong) If the erroneous middle step is removed, the final rounding to integer rounds 3.25 to the correct value of 3. RPSP is implemented in hardware in IBM zSeries and pSeries.

  3. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    Round-by-chop: The base-expansion of is truncated after the ()-th digit. This rounding rule is biased because it always moves the result toward zero. Round-to-nearest: () is set to the nearest floating-point number to . When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal ...

  4. Significant figures - Wikipedia

    en.wikipedia.org/wiki/Significant_figures

    If the n + 1 digit is greater than 5 or is 5 followed by other non-zero digits, add 1 to the n digit. For example, if we want to round 1.2459 to 3 significant figures, then this step results in 1.25. If the n + 1 digit is 5 not followed by other digits or followed by only zeros, then rounding requires a tie-breaking rule. For example, to round ...

  5. Talk:Rounding - Wikipedia

    en.wikipedia.org/wiki/Talk:Rounding

    If you want to round to whole values, you have 0 and 1 available. 0 covers -0.5 to 0.5, and 1 covers 0.5 to 1.5. 0.0 through 0.4 thus clearly convert to 0, and 0.6 through 1.0 clearly convert to 1. 0.5's range is perfectly divided in two by the ranges that 0 and 1 cover.

  6. Interval arithmetic - Wikipedia

    en.wikipedia.org/wiki/Interval_arithmetic

    The main objective of interval arithmetic is to provide a simple way of calculating upper and lower bounds of a function's range in one or more variables. These endpoints are not necessarily the true supremum or infimum of a range since the precise calculation of those values can be difficult or impossible; the bounds only need to contain the function's range as a subset.

  7. Unit in the last place - Wikipedia

    en.wikipedia.org/wiki/Unit_in_the_last_place

    In computer science and numerical analysis, unit in the last place or unit of least precision (ulp) is the spacing between two consecutive floating-point numbers, i.e., the value the least significant digit (rightmost digit) represents if it is 1. It is used as a measure of accuracy in numeric calculations. [1]

  8. Q (number format) - Wikipedia

    en.wikipedia.org/wiki/Q_(number_format)

    For example, a Q15.1 format number requires 15+1 = 16 bits, has resolution 2 −1 = 0.5, and the representable values range from −2 14 = −16384.0 to +2 14 − 2 −1 = +16383.5. In hexadecimal, the negative values range from 0x8000 to 0xFFFF followed by the non-negative ones from 0x0000 to 0x7FFF.

  9. Decimal floating point - Wikipedia

    en.wikipedia.org/wiki/Decimal_floating_point

    The leading digit is between 0 and 9 (3 or 4 binary bits), and the rest of the significand uses the densely packed decimal (DPD) encoding. The leading 2 bits of the exponent and the leading digit (3 or 4 bits) of the significand are combined into the five bits that follow the sign bit. This is followed by a fixed-offset exponent continuation field.