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  2. Exponent bias - Wikipedia

    en.wikipedia.org/wiki/Exponent_bias

    When interpreting the floating-point number, the bias is subtracted to retrieve the actual exponent. For a half-precision number, the exponent is stored in the range 1 .. 30 (0 and 31 have special meanings), and is interpreted by subtracting the bias for an 5-bit exponent (15) to get an exponent value in the range −14 .. +15.

  3. Half-precision floating-point format - Wikipedia

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

    In computing, half precision (sometimes called FP16 or float16) is a binary floating-point computer number format that occupies 16 bits (two bytes in modern computers) in computer memory. It is intended for storage of floating-point values in applications where higher precision is not essential, in particular image processing and neural networks .

  4. List of eponymous laws - Wikipedia

    en.wikipedia.org/wiki/List_of_eponymous_laws

    Dalton's law, in chemistry and physics, states that the total pressure exerted by a gaseous mixture is equal to the sum of the partial pressures of each individual component in a gas mixture. Also called Dalton's law of partial pressure, and related to the ideal gas laws, this empirical law was observed by John Dalton in 1801.

  5. Extended precision - Wikipedia

    en.wikipedia.org/wiki/Extended_precision

    The exponent field is biased by 16383, meaning that 16383 has to be subtracted from the value in the exponent field to compute the actual power of 2. [20] An exponent field value of 32767 (all fifteen bits 1 ) is reserved so as to enable the representation of special states such as infinity and Not a Number .

  6. IEEE 754-1985 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754-1985

    In single precision, the bias is 127, so in this example the biased exponent is 124; in double precision, the bias is 1023, so the biased exponent in this example is 1020. fraction = .01000… 2 . IEEE 754 adds a bias to the exponent so that numbers can in many cases be compared conveniently by the same hardware that compares signed 2's ...

  7. Signed number representations - Wikipedia

    en.wikipedia.org/wiki/Signed_number_representations

    Biased representations are now primarily used for the exponent of floating-point numbers. The IEEE 754 floating-point standard defines the exponent field of a single-precision (32-bit) number as an 8-bit excess-127 field. The double-precision (64-bit) exponent field is an 11-bit excess-1023 field; see exponent bias.

  8. Exponentiation - Wikipedia

    en.wikipedia.org/wiki/Exponentiation

    The exponent is usually shown as a superscript to the right of the base as b n or in computer code as b^n. This binary operation is often read as "b to the power n"; it may also be called "b raised to the nth power", "the nth power of b", [2] or most briefly "b to the n".

  9. Significand - Wikipedia

    en.wikipedia.org/wiki/Significand

    The number 123.45 can be represented as a decimal floating-point number with the integer 12345 as the significand and a 10 −2 power term, also called characteristics, [11] [12] [13] where −2 is the exponent (and 10 is the base). Its value is given by the following arithmetic: 123.45 = 12345 × 10 −2.