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  2. Double-precision floating-point format - Wikipedia

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

    The exponents 000 16 and 7ff 16 have a special meaning: 00000000000 2 =000 16 is used to represent a signed zero (if F = 0) and subnormal numbers (if F ≠ 0); and; 11111111111 2 =7ff 16 is used to represent ∞ (if F = 0) and NaNs (if F ≠ 0), where F is the fractional part of the significand. All bit patterns are valid encoding.

  3. Half-precision floating-point format - Wikipedia

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

    The advantage over 8-bit or 16-bit integers is that the increased dynamic range allows for more detail to be preserved in highlights and shadows for images, and avoids gamma correction. The advantage over 32-bit single-precision floating point is that it requires half the storage and bandwidth (at the expense of precision and range). [5]

  4. 16-bit computing - Wikipedia

    en.wikipedia.org/wiki/16-bit_computing

    In computer architecture, 16-bit integers, memory addresses, or other data units are those that are 16 bits (2 octets) wide.Also, 16-bit central processing unit (CPU) and arithmetic logic unit (ALU) architectures are those that are based on registers, address buses, or data buses of that size. 16-bit microcomputers are microcomputers that use 16-bit microprocessors.

  5. Extended precision - Wikipedia

    en.wikipedia.org/wiki/Extended_precision

    The Motorola 6888x math coprocessors and the Motorola 68040 and 68060 processors also support a 64-bit significand extended-precision format (similar to the Intel format, although padded to a 96-bit format with 16 unused bits inserted between the exponent and significand fields, and values with exponent zero and bit 63 one are normalized values ...

  6. IEEE 754 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754

    The existing 64- and 128-bit formats follow this rule, but the 16- and 32-bit formats have more exponent bits (5 and 8 respectively) than this formula would provide (3 and 7 respectively). As with IEEE 754-1985, the biased-exponent field is filled with all 1 bits to indicate either infinity (trailing significand field = 0) or a NaN (trailing ...

  7. IBM hexadecimal floating-point - Wikipedia

    en.wikipedia.org/wiki/IBM_hexadecimal_floating-point

    Zero (0.0) is represented in normalized form as all zero bits, which is arithmetically the value +0.0 16 × 16 0 − 64 = +0 × 16 −64 ≈ +0.000000 × 10 −79 = 0. Given a fraction of all-bits zero, any combination of positive or negative sign bit and a non-zero biased exponent will yield a value arithmetically equal to zero.

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    The search engine that helps you find exactly what you're looking for. Find the most relevant information, video, images, and answers from all across the Web.

  9. Single-precision floating-point format - Wikipedia

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

    In the IEEE 754 standard, the 32-bit base-2 format is officially referred to as binary32; it was called single in IEEE 754-1985. IEEE 754 specifies additional floating-point types, such as 64-bit base-2 double precision and, more recently, base-10 representations.