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  2. Offset binary - Wikipedia

    en.wikipedia.org/wiki/Offset_binary

    Offset binary, [1] also referred to as excess-K, [1] excess-N, excess-e, [2] [3] excess code or biased representation, is a method for signed number representation where a signed number n is represented by the bit pattern corresponding to the unsigned number n+K, K being the biasing value or offset.

  3. Signed number representations - Wikipedia

    en.wikipedia.org/wiki/Signed_number_representations

    In the offset binary representation, also called excess-K or biased, a signed number is represented by the bit pattern corresponding to the unsigned number plus K, with K being the biasing value or offset. Thus 0 is represented by K, and −K is represented by an all-zero bit pattern.

  4. 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 .

  5. Exponent bias - Wikipedia

    en.wikipedia.org/wiki/Exponent_bias

    In IEEE 754 floating-point numbers, the exponent is biased in the engineering sense of the word – the value stored is offset from the actual value by the exponent bias, also called a biased exponent. [1]

  6. List of file signatures - Wikipedia

    en.wikipedia.org/wiki/List_of_file_signatures

    In the table below, the column "ISO 8859-1" shows how the file signature appears when interpreted as text in the common ISO 8859-1 encoding, with unprintable characters represented as the control code abbreviation or symbol, or codepage 1252 character where available, or a box otherwise. In some cases the space character is shown as ␠.

  7. Quadruple-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Quadruple-precision...

    The quadruple-precision binary floating-point exponent is encoded using an offset binary representation, with the zero offset being 16383; this is also known as exponent bias in the IEEE 754 standard. E min = 0001 16 − 3FFF 16 = −16382; E max = 7FFE 16 − 3FFF 16 = 16383; Exponent bias = 3FFF 16 = 16383

  8. Ethan Slater's Ex-Wife Lilly Jay Breaks Silence on 'Public ...

    www.aol.com/ethan-slaters-ex-wife-lilly...

    Related: Ariana Grande and Ethan Slater's Relationship Timeline Jay wrote that "people from [her] past have reached out to say they saw my face in a tabloid," in relation to the controversy. But ...

  9. bfloat16 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Bfloat16_floating-point_format

    Thus, in order to get the true exponent as defined by the offset-binary representation, the offset of 127 has to be subtracted from the value of the exponent field. The minimum and maximum values of the exponent field (00 H and FF H ) are interpreted specially, like in the IEEE 754 standard formats.