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  2. Double-precision floating-point format - Wikipedia

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

    [citation needed] Before the widespread adoption of IEEE 754-1985, the representation and properties of floating-point data types depended on the computer manufacturer and computer model, and upon decisions made by programming-language implementers. E.g., GW-BASIC's double-precision data type was the 64-bit MBF floating-point format.

  3. Computer number format - Wikipedia

    en.wikipedia.org/wiki/Computer_number_format

    A 64-bit float is sometimes called a "real64" or a "double", meaning "double-precision floating-point value". The relation between numbers and bit patterns is chosen for convenience in computer manipulation; eight bytes stored in computer memory may represent a 64-bit real, two 32-bit reals, or four signed or unsigned integers, or some other ...

  4. IEEE 754-2008 revision - Wikipedia

    en.wikipedia.org/wiki/IEEE_754-2008_revision

    The binary interchange formats have the "half precision" (16-bit storage format) and "quad precision" (128-bit format) added, together with generalized formulae for some wider formats; the basic formats have 32-bit, 64-bit, and 128-bit encodings. Three new decimal formats are described, matching the lengths of the 32–128-bit binary formats.

  5. Complex data type - Wikipedia

    en.wikipedia.org/wiki/Complex_data_type

    The Go programming language has built-in types complex64 (each component is 32-bit float) and complex128 (each component is 64-bit float). Imaginary number literals can be specified by appending an "i". The Perl core module Math::Complex provides support for complex numbers. Python provides the built-in complex type. Imaginary number literals ...

  6. Minifloat - Wikipedia

    en.wikipedia.org/wiki/Minifloat

    The above describes an example 8-bit float with 1 sign bit, 4 exponent bits, and 3 significand bits, which is a nice balance. However, any bit allocation is possible. A format could choose to give more of the bits to the exponent if they need more dynamic range with less precision, or give more of the bits to the significand if they need more ...

  7. Bit numbering - Wikipedia

    en.wikipedia.org/wiki/Bit_numbering

    This table illustrates an example of an 8 bit signed decimal value using the two's complement method. The MSb most significant bit has a negative weight in signed integers, in this case -2 7 = -128. The other bits have positive weights. The lsb (least significant bit) has weight 2 0 =1. The signed value is in this case -128+2 = -126.

  8. decimal64 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Decimal64_floating-point...

    - Different understanding of significand as integer or fraction, and acc. different bias to apply for the exponent (for decimal64 what is stored in bits can be decoded as base to the power of 'stored value for the exponent minus bias of 383' times significand understood as d 0. d −1 d −2 d −3 d −4 d −5 d −6 d −7 d −8 d −9 d ...

  9. Extended precision - Wikipedia

    en.wikipedia.org/wiki/Extended_precision

    It was designed to support a 32-bit "single precision" format and a 64-bit "double-precision" format for encoding and interchanging floating-point numbers. The extended format was designed not to store data at higher precision, but rather to allow for the computation of temporary double results more reliably and accurately by minimising ...