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  2. Master theorem (analysis of algorithms) - Wikipedia

    en.wikipedia.org/wiki/Master_theorem_(analysis...

    The master theorem always yields asymptotically tight bounds to recurrences from divide and conquer algorithms that partition an input into smaller subproblems of equal sizes, solve the subproblems recursively, and then combine the subproblem solutions to give a solution to the original problem. The time for such an algorithm can be expressed ...

  3. Master theorem - Wikipedia

    en.wikipedia.org/wiki/Master_theorem

    In mathematics, a theorem that covers a variety of cases is sometimes called a master theorem. Some theorems called master theorems in their fields include: Master theorem (analysis of algorithms), analyzing the asymptotic behavior of divide-and-conquer algorithms; Ramanujan's master theorem, providing an analytic expression for the Mellin ...

  4. Ramanujan's master theorem - Wikipedia

    en.wikipedia.org/wiki/Ramanujan's_master_theorem

    The bracket integration method (method of brackets) applies Ramanujan's master theorem to a broad range of integrals. [7] The bracket integration method generates the integrand's series expansion , creates a bracket series, identifies the series coefficient and formula parameters and computes the integral.

  5. Analysis of algorithms - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_algorithms

    For looking up a given entry in a given ordered list, both the binary and the linear search algorithm (which ignores ordering) can be used. The analysis of the former and the latter algorithm shows that it takes at most log 2 n and n check steps, respectively, for a list of size n.

  6. Category : Theorems in computational complexity theory

    en.wikipedia.org/wiki/Category:Theorems_in...

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  7. Akra–Bazzi method - Wikipedia

    en.wikipedia.org/wiki/Akra–Bazzi_method

    In computer science, the Akra–Bazzi method, or Akra–Bazzi theorem, is used to analyze the asymptotic behavior of the mathematical recurrences that appear in the analysis of divide and conquer algorithms where the sub-problems have substantially different sizes.

  8. Quicksort - Wikipedia

    en.wikipedia.org/wiki/Quicksort

    The master theorem for divide-and-conquer recurrences tells us that T(n) = O(n log n). The outline of a formal proof of the O ( n log n ) expected time complexity follows. Assume that there are no duplicates as duplicates could be handled with linear time pre- and post-processing, or considered cases easier than the analyzed.

  9. Karatsuba algorithm - Wikipedia

    en.wikipedia.org/wiki/Karatsuba_algorithm

    For this recurrence relation, the master theorem for divide-and-conquer recurrences gives the asymptotic bound () = (⁡). It follows that, for sufficiently large n , Karatsuba's algorithm will perform fewer shifts and single-digit additions than longhand multiplication, even though its basic step uses more additions and shifts than the ...