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  2. Generating function - Wikipedia

    en.wikipedia.org/wiki/Generating_function

    In mathematics, a generating function is a representation of an infinite sequence of numbers as the coefficients of a formal power series.Generating functions are often expressed in closed form (rather than as a series), by some expression involving operations on the formal series.

  3. Factorial - Wikipedia

    en.wikipedia.org/wiki/Factorial

    It separates out the sorted and reversed order of a set of items from the other ("mixed") orders, evaluating the number of mixed orders by subtracting two from the usual product formula for the factorial. The product rule for permutations was also described by 6th-century CE Jain monk Jinabhadra. [2]

  4. Memoization - Wikipedia

    en.wikipedia.org/wiki/Memoization

    function factorial (n is a non-negative integer) if n is 0 then return 1 [by the convention that 0! = 1] else if n is in lookup-table then return lookup-table-value-for-n else let x = factorial(n – 1) times n [recursively invoke factorial with the parameter 1 less than n] store x in lookup-table in the n th slot [remember the result of n! for ...

  5. Lazy evaluation - Wikipedia

    en.wikipedia.org/wiki/Lazy_evaluation

    In Python 3.x the range() function [28] returns a generator which computes elements of the list on demand. Elements are only generated when they are needed (e.g., when print(r[3]) is evaluated in the following example), so this is an example of lazy or deferred evaluation:

  6. Corecursion - Wikipedia

    en.wikipedia.org/wiki/Corecursion

    In computer science, corecursion is a type of operation that is dual to recursion.Whereas recursion works analytically, starting on data further from a base case and breaking it down into smaller data and repeating until one reaches a base case, corecursion works synthetically, starting from a base case and building it up, iteratively producing data further removed from a base case.

  7. Factorion - Wikipedia

    en.wikipedia.org/wiki/Factorion

    Let be a natural number. For a base >, we define the sum of the factorials of the digits [5] [6] of , :, to be the following: ⁡ = =!. where = ⌊ ⁡ ⌋ + is the number of digits in the number in base , ! is the factorial of and

  8. One-factor-at-a-time method - Wikipedia

    en.wikipedia.org/wiki/One-factor-at-a-time_method

    The latter is far from optimal, but the former, which changes only one variable at a time, is worse. See also the factorial experimental design methods pioneered by Sir Ronald A. Fisher. Reasons for disfavoring OFAT include: OFAT requires more runs for the same precision in effect estimation; OFAT cannot estimate interactions

  9. Horner's method - Wikipedia

    en.wikipedia.org/wiki/Horner's_method

    Horner's method is a fast, code-efficient method for multiplication and division of binary numbers on a microcontroller with no hardware multiplier. One of the binary numbers to be multiplied is represented as a trivial polynomial, where (using the above notation) a i = 1 {\displaystyle a_{i}=1} , and x = 2 {\displaystyle x=2} .