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  2. Computational complexity of mathematical operations - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    Graphs of functions commonly used in the analysis of algorithms, showing the number of operations versus input size for each function. The following tables list the computational complexity of various algorithms for common mathematical operations.

  3. List of mathematical constants - Wikipedia

    en.wikipedia.org/wiki/List_of_mathematical_constants

    A mathematical constant is a key number whose value is fixed by an unambiguous definition, often referred to by a symbol (e.g., an alphabet letter), or by mathematicians' names to facilitate using it across multiple mathematical problems. [1]

  4. C mathematical functions - Wikipedia

    en.wikipedia.org/wiki/C_mathematical_functions

    Most of the mathematical functions are defined in <math.h> (<cmath> header in C++). The functions that operate on integers, such as abs, labs, div, and ldiv, are instead defined in the <stdlib.h> header (<cstdlib> header in C++). Any functions that operate on angles use radians as the unit of angle. [1]

  5. Barrett reduction - Wikipedia

    en.wikipedia.org/wiki/Barrett_reduction

    The Barrett multiplication previously described requires a constant operand b to pre-compute [] ahead of time. Otherwise, the operation is not efficient. Otherwise, the operation is not efficient. It is common to use Montgomery multiplication when both operands are non-constant as it has better performance.

  6. Quaternion - Wikipedia

    en.wikipedia.org/wiki/Quaternion

    A quaternion of the form a + 0 i + 0 j + 0 k, where a is a real number, is called scalar, and a quaternion of the form 0 + b i + c j + d k, where b, c, and d are real numbers, and at least one of b, c, or d is nonzero, is called a vector quaternion. If a + b i + c j + d k is any quaternion, then a is called its scalar part and b i + c j + d k ...

  7. Persistence of a number - Wikipedia

    en.wikipedia.org/wiki/Persistence_of_a_number

    The additive persistence of a number is smaller than or equal to the number itself, with equality only when the number is zero. For base b {\displaystyle b} and natural numbers k {\displaystyle k} and n > 9 {\displaystyle n>9} the numbers n {\displaystyle n} and n ⋅ b k {\displaystyle n\cdot b^{k}} have the same additive persistence.

  8. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    For example, given a = f(x) = a 0 x 0 + a 1 x 1 + ··· and b = g(x) = b 0 x 0 + b 1 x 1 + ···, the product ab is a specific value of W(x) = f(x)g(x). One may easily find points along W(x) at small values of x, and interpolation based on those points will yield the terms of W(x) and the specific product ab. As fomulated in Karatsuba ...

  9. Scale factor (computer science) - Wikipedia

    en.wikipedia.org/wiki/Scale_factor_(computer...

    154/11 = 14 101/11 = 9.1818... 54/11 = 4.9090... 3/11 = 0.2727... 0/11 = 0 160/11 = 14.5454... Many of these values have been truncated because they contain repeating decimals, which follows from the chosen scale factor (elevenths do not terminate in decimal). When storing these in our fixed-point format, some precision will be lost (in ...