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  2. Array slicing - Wikipedia

    en.wikipedia.org/wiki/Array_slicing

    Reducing the range of any index to a single value effectively eliminates that index. This feature can be used, for example, to extract one-dimensional slices (vectors: in 3D, rows, columns, and tubes [1]) or two-dimensional slices (rectangular matrices) from a three-dimensional array. However, since the range can be specified at run-time, type ...

  3. Row and column vectors - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_vectors

    The transpose (indicated by T) of any row vector is a column vector, and the transpose of any column vector is a row vector: […] = [] and [] = […]. The set of all row vectors with n entries in a given field (such as the real numbers ) forms an n -dimensional vector space ; similarly, the set of all column vectors with m entries forms an m ...

  4. Array programming - Wikipedia

    en.wikipedia.org/wiki/Array_programming

    The Nial example of the inner product of two arrays can be implemented using the native matrix multiplication operator. If a is a row vector of size [1 n] and b is a corresponding column vector of size [n 1]. a * b; By contrast, the entrywise product is implemented as: a .* b;

  5. Hamming code - Wikipedia

    en.wikipedia.org/wiki/Hamming_code

    The parity-check matrix of a Hamming code is constructed by listing all columns of length r that are non-zero, which means that the dual code of the Hamming code is the shortened Hadamard code, also known as a Simplex code. The parity-check matrix has the property that any two columns are pairwise linearly independent.

  6. Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Sorting_algorithm

    One implementation can be described as arranging the data sequence in a two-dimensional array and then sorting the columns of the array using insertion sort. The worst-case time complexity of Shellsort is an open problem and depends on the gap sequence used, with known complexities ranging from O ( n 2 ) to O ( n 4/3 ) and Θ( n log 2 n ).

  7. Longest increasing subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_increasing_subsequence

    It processes the sequence elements in order, maintaining the longest increasing subsequence found so far. Denote the sequence values as [], [], …, etc. Then, after processing [], the algorithm will have stored an integer and values in two arrays:

  8. Ackermann function - Wikipedia

    en.wikipedia.org/wiki/Ackermann_function

    First, place the natural numbers along the top row. To determine a number in the table, take the number immediately to the left. Then use that number to look up the required number in the column given by that number and one row up. If there is no number to its left, simply look at the column headed "1" in the previous row.

  9. Subsequence - Wikipedia

    en.wikipedia.org/wiki/Subsequence

    Every infinite sequence of real numbers has an infinite monotone subsequence (This is a lemma used in the proof of the Bolzano–Weierstrass theorem). Every infinite bounded sequence in R n {\displaystyle \mathbb {R} ^{n}} has a convergent subsequence (This is the Bolzano–Weierstrass theorem ).