enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Subnormal number - Wikipedia

    en.wikipedia.org/wiki/Subnormal_number

    The significand (or mantissa) of an IEEE floating-point number is the part of a floating-point number that represents the significant digits. For a positive normalised number, it can be represented as m 0 . m 1 m 2 m 3 ... m p −2 m p −1 (where m represents a significant digit, and p is the precision) with non-zero m 0 .

  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. In the IEEE ...

  4. Half-precision floating-point format - Wikipedia

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

    Swift introduced half-precision floating point numbers in Swift 5.3 with the Float16 type. [20] OpenCL also supports half-precision floating point numbers with the half datatype on IEEE 754-2008 half-precision storage format. [21] As of 2024, Rust is currently working on adding a new f16 type for IEEE half-precision 16-bit floats. [22]

  5. Primitive data type - Wikipedia

    en.wikipedia.org/wiki/Primitive_data_type

    In computer science, primitive data types are a set of basic data types from which all other data types are constructed. [1] Specifically it often refers to the limited set of data representations in use by a particular processor, which all compiled programs must use.

  6. Elliptic curve point multiplication - Wikipedia

    en.wikipedia.org/wiki/Elliptic_curve_point...

    Q ← 0 for i from m to 0 do Q ← point_double_repeat(Q, w) if d i > 0 then Q ← point_add(Q, d i P) # using pre-computed value of d i P return Q This algorithm has the same complexity as the double-and-add approach with the benefit of using fewer point additions (which in practice are slower than doubling).

  7. Single-precision floating-point format - Wikipedia

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

    Single precision is termed REAL in Fortran; [1] SINGLE-FLOAT in Common Lisp; [2] float in C, C++, C# and Java; [3] Float in Haskell [4] and Swift; [5] and Single in Object Pascal , Visual Basic, and MATLAB. However, float in Python, Ruby, PHP, and OCaml and single in versions of Octave before 3.2 refer to double-precision numbers.

  8. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    This alternative definition is significantly more widespread: machine epsilon is the difference between 1 and the next larger floating point number.This definition is used in language constants in Ada, C, C++, Fortran, MATLAB, Mathematica, Octave, Pascal, Python and Rust etc., and defined in textbooks like «Numerical Recipes» by Press et al.

  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.