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  2. Petrick's method - Wikipedia

    en.wikipedia.org/wiki/Petrick's_method

    Referring to our example: KNP expands to A'B' + BC' + AC where K converts to A'B', N converts to BC', etc. LMQ expands to A'C' + B'C + AB Both products expand to six literals each, so either one can be used. In general, application of Petrick's method is tedious for large charts, but it is easy to implement on a computer. [7]

  3. And–or tree - Wikipedia

    en.wikipedia.org/wiki/And–or_tree

    Given an initial problem P 0 and set of problem solving methods of the form: P if P 1 and … and P n. the associated and–or tree is a set of labelled nodes such that: The root of the tree is a node labelled by P 0. For every node N labelled by a problem or sub-problem P and for every method of the form P if P 1 and ... and P n, there exists ...

  4. Flowchart - Wikipedia

    en.wikipedia.org/wiki/Flowchart

    A flowchart can also be defined as a diagrammatic representation of an algorithm, a step-by-step approach to solving a task. The flowchart shows the steps as boxes of various kinds, and their order by connecting the boxes with arrows. This diagrammatic representation illustrates a solution model to a given problem.

  5. Algorithm - Wikipedia

    en.wikipedia.org/wiki/Algorithm

    Flowchart of using successive subtractions to find the greatest common divisor of number r and s. In mathematics and computer science, an algorithm (/ ˈ æ l ɡ ə r ɪ ð əm / ⓘ) is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation. [1]

  6. P versus NP problem - Wikipedia

    en.wikipedia.org/wiki/P_versus_NP_problem

    In other words, any problem in EXPTIME is solvable by a deterministic Turing machine in O(2 p(n)) time, where p(n) is a polynomial function of n. A decision problem is EXPTIME-complete if it is in EXPTIME, and every problem in EXPTIME has a polynomial-time many-one reduction to it. A number of problems are known to be EXPTIME-complete.

  7. Pseudocode - Wikipedia

    en.wikipedia.org/wiki/Pseudocode

    algorithm ford-fulkerson is input: Graph G with flow capacity c, source node s, sink node t output: Flow f such that f is maximal from s to t (Note that f (u,v) is the flow from node u to node v, and c (u,v) is the flow capacity from node u to node v) for each edge (u, v) in G E do f (u, v) ← 0 f (v, u) ← 0 while there exists a path p from ...

  8. Quine–McCluskey algorithm - Wikipedia

    en.wikipedia.org/wiki/Quine–McCluskey_algorithm

    The Quine-McCluskey algorithm works as follows: Finding all prime implicants of the function. Use those prime implicants in a prime implicant chart to find the essential prime implicants of the function, as well as other prime implicants that are necessary to cover the function.

  9. Pollard's kangaroo algorithm - Wikipedia

    en.wikipedia.org/wiki/Pollard's_kangaroo_algorithm

    The algorithm was introduced in 1978 by the number theorist John M. Pollard, in the same paper as his better-known Pollard's rho algorithm for solving the same problem. [ 1 ] [ 2 ] Although Pollard described the application of his algorithm to the discrete logarithm problem in the multiplicative group of units modulo a prime p , it is in fact a ...