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  2. Double-precision floating-point format - Wikipedia

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

    For the next range, from 2 53 to 2 54, everything is multiplied by 2, so the representable numbers are the even ones, etc. Conversely, for the previous range from 2 51 to 2 52, the spacing is 0.5, etc. The spacing as a fraction of the numbers in the range from 2 n to 2 n+1 is 2 n−52.

  3. Decimal data type - Wikipedia

    en.wikipedia.org/wiki/Decimal_data_type

    [2] Ruby's standard library includes a BigDecimal class in the module bigdecimal. Java's standard library includes a java.math.BigDecimal class. In Objective-C, the Cocoa and GNUstep APIs provide an NSDecimalNumber class and an NSDecimal C data type for representing decimals whose mantissa is up to 38 digits long, and exponent is from −128 to ...

  4. Format (Common Lisp) - Wikipedia

    en.wikipedia.org/wiki/Format_(Common_Lisp)

    Format is a function in Common Lisp that can produce formatted text using a format string similar to the print format string.It provides more functionality than print, allowing the user to output numbers in various formats (including, for instance: hex, binary, octal, roman numerals, and English), apply certain format specifiers only under certain conditions, iterate over data structures ...

  5. Q (number format) - Wikipedia

    en.wikipedia.org/wiki/Q_(number_format)

    The Q notation is a way to specify the parameters of a binary fixed point number format. For example, in Q notation, the number format denoted by Q8.8 means that the fixed point numbers in this format have 8 bits for the integer part and 8 bits for the fraction part. A number of other notations have been used for the same purpose.

  6. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    For numbers with a base-2 exponent part of 0, i.e. numbers with an absolute value higher than or equal to 1 but lower than 2, an ULP is exactly 2 −23 or about 10 −7 in single precision, and exactly 2 −53 or about 10 −16 in double precision. The mandated behavior of IEEE-compliant hardware is that the result be within one-half of a ULP.

  7. Computer number format - Wikipedia

    en.wikipedia.org/wiki/Computer_number_format

    2.3434E−6 = 2.3434 × 10 −6 = 2.3434 × 0.000001 = 0.0000023434. The advantage of this scheme is that by using the exponent we can get a much wider range of numbers, even if the number of digits in the significand, or the "numeric precision", is much smaller than the range. Similar binary floating-point formats can be defined for computers.

  8. Extended precision - Wikipedia

    en.wikipedia.org/wiki/Extended_precision

    The 80-bit floating-point format has a range (including subnormals) from approximately 3.65 × 10 −4951 to 1.18 × 10 +4932. Although log 10 ( 2 64) ≈ 19.266, this format is usually described as giving approximately eighteen significant digits of precision (the floor of log 10 ( 2 63), the minimum guaranteed precision).

  9. Decimal floating point - Wikipedia

    en.wikipedia.org/wiki/Decimal_floating_point

    The otherwise binary Wang VS machine supported a 64-bit decimal floating-point format in 1977. [2] The Motorola 68881 supported a format with 17 digits of mantissa and 3 of exponent in 1984, with the floating-point support library for the Motorola 68040 processor providing a compatible 96-bit decimal floating-point storage format in 1990. [2]