enow.com Web Search

Search results

1. Results from the WOW.Com Content Network

2. 2Sum - Wikipedia

   en.wikipedia.org/wiki/2Sum

   Fast2Sum is often used implicitly in other algorithms such as compensated summation algorithms; [1] Kahan's summation algorithm was published first in 1965, [3] and Fast2Sum was later factored out of it by Dekker in 1971 for double-double arithmetic algorithms. [4] The names 2Sum and Fast2Sum appear to have been applied retroactively by ...

3. Double-precision floating-point format - Wikipedia

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

   Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point. Double precision may be chosen when the range or precision of single precision would be insufficient.

4. Floating-point error mitigation - Wikipedia

   en.wikipedia.org/wiki/Floating-point_error...

   Extension of precision is using of larger representations of real values than the one initially considered. The IEEE 754 standard defines precision as the number of digits available to represent real numbers. A programming language can include single precision (32 bits), double precision (64 bits), and quadruple precision (128 bits). While ...

5. Floating-point arithmetic - Wikipedia

   en.wikipedia.org/wiki/Floating-point_arithmetic

   In the IEEE binary interchange formats the leading 1 bit of a normalized significand is not actually stored in the computer datum. It is called the "hidden" or "implicit" bit. Because of this, the single-precision format actually has a significand with 24 bits of precision, the double-precision format has 53, and quad has 113.

6. IEEE 754 - Wikipedia

   en.wikipedia.org/wiki/IEEE_754

   A property of the single- and double-precision formats is that their encoding allows one to easily sort them without using floating-point hardware, as if the bits represented sign-magnitude integers, although it is unclear whether this was a design consideration (it seems noteworthy that the earlier IBM hexadecimal floating-point representation ...

7. Kahan summation algorithm - Wikipedia

   en.wikipedia.org/wiki/Kahan_summation_algorithm

   For summing [, +,,] in double precision, Kahan's algorithm yields 0.0, whereas Neumaier's algorithm yields the correct value 2.0. Higher-order modifications of better accuracy are also possible. For example, a variant suggested by Klein, [ 12 ] which he called a second-order "iterative Kahan–Babuška algorithm".

8. Numeric precision in Microsoft Excel - Wikipedia

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

   Excel maintains 15 figures in its numbers, but they are not always accurate; mathematically, the bottom line should be the same as the top line, in 'fp-math' the step '1 + 1/9000' leads to a rounding up as the first bit of the 14 bit tail '10111000110010' of the mantissa falling off the table when adding 1 is a '1', this up-rounding is not undone when subtracting the 1 again, since there is no ...

9. Round-off error - Wikipedia

   en.wikipedia.org/wiki/Round-off_error

   The IEEE standard stores the sign, exponent, and significand in separate fields of a floating point word, each of which has a fixed width (number of bits). The two most commonly used levels of precision for floating-point numbers are single precision and double precision.