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  2. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    [3]: 19-- It does not require computing the topological degree; it only requires computing the signs of function values. The number of required evaluations is at least log 2 ⁡ ( D / ϵ ) {\displaystyle \log _{2}(D/\epsilon )} , where D is the length of the longest edge of the characteristic polyhedron.

  3. Subnormal number - Wikipedia

    en.wikipedia.org/wiki/Subnormal_number

    In a subnormal number, since the exponent is the least that it can be, zero is the leading significant digit (0.m 1 m 2 m 3...m p−2 m p−1), allowing the representation of numbers closer to zero than the smallest normal number. A floating-point number may be recognized as subnormal whenever its exponent has the least possible value.

  4. NaN - Wikipedia

    en.wikipedia.org/wiki/NaN

    In computing, NaN (/ n æ n /), standing for Not a Number, is a particular value of a numeric data type (often a floating-point number) which is undefined as a number, such as the result of 0/0. Systematic use of NaNs was introduced by the IEEE 754 floating-point standard in 1985, along with the representation of other non-finite quantities ...

  5. IEEE 754 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754

    IEEE 754 specifies a special value called "Not a Number" (NaN) to be returned as the result of certain "invalid" operations, such as 0/0, ∞×0, or sqrt(−1). In general, NaNs will be propagated, i.e. most operations involving a NaN will result in a NaN, although functions that would give some defined result for any given floating-point value ...

  6. Half-precision floating-point format - Wikipedia

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

    largest subnormal number 0 00001 0000000000: 0400: 2 −14 × (1 + ⁠ 0 / 1024 ⁠) ≈ 0.00006103515625: smallest positive normal number 0 01101 0101010101: 3555: 2 −2 × (1 + ⁠ 341 / 1024 ⁠) ≈ 0.33325195: nearest value to 1/3 0 01110 1111111111: 3bff: 2 −1 × (1 + ⁠ 1023 / 1024 ⁠) ≈ 0.99951172: largest number less than one 0 ...

  7. Single-precision floating-point format - Wikipedia

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

    All integers with seven or fewer decimal digits, and any 2 n for a whole number −149 ≤ n ≤ 127, can be converted exactly into an IEEE 754 single-precision floating-point value. 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 .

  8. Truth value - Wikipedia

    en.wikipedia.org/wiki/Truth_value

    In C, the number 0 or 0.0 is false, and all other values are treated as true. In JavaScript, the empty string (""), null, undefined, NaN, +0, −0 and false [3] are sometimes called falsy (of which the complement is truthy) to distinguish between strictly type-checked and coerced Booleans (see also: JavaScript syntax#Type conversion). [4]

  9. Logarithmic decrement - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_decrement

    The logarithmic decrement can be obtained e.g. as ln(x 1 /x 3).Logarithmic decrement, , is used to find the damping ratio of an underdamped system in the time domain.. The method of logarithmic decrement becomes less and less precise as the damping ratio increases past about 0.5; it does not apply at all for a damping ratio greater than 1.0 because the system is overdamped.