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  2. Single-precision floating-point format - Wikipedia

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

    Here we can show how to convert a base-10 real number into an IEEE 754 binary32 format using the following outline: Consider a real number with an integer and a fraction part such as 12.375; Convert and normalize the integer part into binary; Convert the fraction part using the following technique as shown here

  3. Decimal floating point - Wikipedia

    en.wikipedia.org/wiki/Decimal_floating_point

    One with a binary integer significand field encodes the significand as a large binary integer between 0 and 10 p −1. This is expected to be more convenient for software implementations using a binary ALU. Another with a densely packed decimal significand field encodes decimal digits more directly. This makes conversion to and from binary ...

  4. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    This means that numbers that appear to be short and exact when written in decimal format may need to be approximated when converted to binary floating-point. For example, the decimal number 0.1 is not representable in binary floating-point of any finite precision; the exact binary representation would have a "1100" sequence continuing endlessly:

  5. 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]

  6. Binary-coded decimal - Wikipedia

    en.wikipedia.org/wiki/Binary-coded_decimal

    If errors in representation and computation are more important than the speed of conversion to and from display, a scaled binary representation may be used, which stores a decimal number as a binary-encoded integer and a binary-encoded signed decimal exponent. For example, 0.2 can be represented as 2 × 10 −1.

  7. 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 ...

  8. Binary integer decimal - Wikipedia

    en.wikipedia.org/wiki/Binary_Integer_Decimal

    A decimal floating-point number can be encoded in several ways, the different ways represent different precisions, for example 100.0 is encoded as 1000×10 −1, while 100.00 is encoded as 10000×10 −2. The set of possible encodings of the same numerical value is called a cohort in the standard. If the result of a calculation is inexact the ...

  9. Computer number format - Wikipedia

    en.wikipedia.org/wiki/Computer_number_format

    In a hexadecimal system, there are 16 digits, 0 through 9 followed, by convention, with A through F. That is, a hexadecimal "10" is the same as a decimal "16" and a hexadecimal "20" is the same as a decimal "32". An example and comparison of numbers in different bases is described in the chart below.