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  2. IEEE 754 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754

    The original binary value will be preserved by converting to decimal and back again using: [58] 5 decimal digits for binary16, 9 decimal digits for binary32, 17 decimal digits for binary64, 36 decimal digits for binary128. For other binary formats, the required number of decimal digits is [h]

  3. Double dabble - Wikipedia

    en.wikipedia.org/wiki/Double_dabble

    In computer science, the double dabble algorithm is used to convert binary numbers into binary-coded decimal (BCD) notation. [ 1 ] [ 2 ] It is also known as the shift-and-add -3 algorithm , and can be implemented using a small number of gates in computer hardware, but at the expense of high latency .

  4. Quadruple-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Quadruple-precision...

    This gives from 33 to 36 significant decimal digits precision. If a decimal string with at most 33 significant digits is converted to the IEEE 754 quadruple-precision format, giving a normal number, and then converted back to a decimal string with the same number of digits, the final result should match the original string.

  5. Single-precision floating-point format - Wikipedia

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

    Convert and normalize the integer part into binary; Convert the fraction part using the following technique as shown here; Add the two results and adjust them to produce a proper final conversion; Conversion of the fractional part: Consider 0.375, the fractional part of 12.375. To convert it into a binary fraction, multiply the fraction by 2 ...

  6. Half-precision floating-point format - Wikipedia

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

    The half-precision binary floating-point exponent is encoded using an offset-binary representation, with the zero offset being 15; also known as exponent bias in the IEEE 754 standard. [9] E min = 00001 2 − 01111 2 = −14; E max = 11110 2 − 01111 2 = 15; Exponent bias = 01111 2 = 15

  7. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal to 0) is used. For IEEE standard where the base β {\displaystyle \beta } is 2 {\displaystyle 2} , this means when there is a tie it is rounded so that the last digit is equal to 0 {\displaystyle 0} .

  8. Fixed-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_arithmetic

    The most common variants are decimal (base 10) and binary (base 2). The latter is commonly known also as binary scaling. Thus, if n fraction digits are stored, the value will always be an integer multiple of b −n. Fixed-point representation can also be used to omit the low-order digits of integer values, e.g. when representing large dollar ...

  9. Binary number - Wikipedia

    en.wikipedia.org/wiki/Binary_number

    The base-2 numeral system is a positional notation with a radix of 2.Each digit is referred to as a bit, or binary digit.Because of its straightforward implementation in digital electronic circuitry using logic gates, the binary system is used by almost all modern computers and computer-based devices, as a preferred system of use, over various other human techniques of communication, because ...