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  2. Iliffe vector - Wikipedia

    en.wikipedia.org/wiki/Iliffe_vector

    In computer programming, an Iliffe vector, also known as a display, is a data structure used to implement multi-dimensional arrays. Data structure. An Iliffe vector for an n-dimensional array (where n ≥ 2) consists of a vector (or 1-dimensional array) of pointers to an (n − 1)-dimensional array. They are often used to avoid the need for ...

  3. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    Programming languages or their standard libraries that support multi-dimensional arrays typically have a native row-major or column-major storage order for these arrays. Row-major order is used in C / C++ / Objective-C (for C-style arrays), PL/I , [ 4 ] Pascal , [ 5 ] Speakeasy , [ citation needed ] and SAS .

  4. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    In this case, the array from which samples are taken is [2, 3, -1, -20, 5, 10]. In computer science, the maximum sum subarray problem, also known as the maximum segment sum problem, is the task of finding a contiguous subarray with the largest sum, within a given one-dimensional array A [1...n] of numbers. It can be solved in time and space.

  5. Array (data structure) - Wikipedia

    en.wikipedia.org/wiki/Array_(data_structure)

    A two-dimensional array stored as a one-dimensional array of one-dimensional arrays (rows). An Iliffe vector is an alternative to a multidimensional array structure. It uses a one-dimensional array of references to arrays of one dimension less. For two dimensions, in particular, this alternative structure would be a vector of pointers to ...

  6. Knapsack problem - Wikipedia

    en.wikipedia.org/wiki/Knapsack_problem

    Definition. The most common problem being solved is the 0-1 knapsack problem, which restricts the number of copies of each kind of item to zero or one. Given a set of items numbered from 1 up to , each with a weight and a value , along with a maximum weight capacity , subject to and . Here represents the number of instances of item to include ...

  7. Bin packing problem - Wikipedia

    en.wikipedia.org/wiki/Bin_packing_problem

    In the guillotine cutting problem, both the items and the "bins" are two-dimensional rectangles rather than one-dimensional numbers, and the items have to be cut from the bin using end-to-end cuts. In the selfish bin packing problem, each item is a player who wants to minimize its cost.

  8. Cutting stock problem - Wikipedia

    en.wikipedia.org/wiki/Cutting_stock_problem

    This was an open problem until 2007, when an efficient algorithm based on dynamic programming was published. [14] The minimum number of knife changes problem (for the one-dimensional problem): this is concerned with sequencing and permuting the patterns so as to minimise the number of times the slitting knives have to be moved.

  9. Nyquist–Shannon sampling theorem - Wikipedia

    en.wikipedia.org/wiki/Nyquist–Shannon_sampling...

    Nyquist–Shannon sampling theorem. The Nyquist–Shannon sampling theorem is an essential principle for digital signal processing linking the frequency range of a signal and the sample rate required to avoid a type of distortion called aliasing. The theorem states that the sample rate must be at least twice the bandwidth of the signal to avoid ...