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  2. Matrix representation - Wikipedia

    en.wikipedia.org/wiki/Matrix_representation

    Matrix representation is a method used by a computer language to store column-vector matrices of more than one dimension in memory. Fortran and C use different schemes for their native arrays. Fortran uses "Column Major" ( AoS ), in which all the elements for a given column are stored contiguously in memory.

  3. MATLAB - Wikipedia

    en.wikipedia.org/wiki/MATLAB

    MATLAB (an abbreviation of "MATrix LABoratory" [18]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.

  4. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    In Matlab/GNU Octave a matrix A can be vectorized by A(:). GNU Octave also allows vectorization and half-vectorization with vec(A) and vech(A) respectively. Julia has the vec(A) function as well. In Python NumPy arrays implement the flatten method, [note 1] while in R the desired effect can be achieved via the c() or as.vector() functions.

  5. Matrix Template Library - Wikipedia

    en.wikipedia.org/wiki/Matrix_Template_Library

    The Matrix Template Library (MTL) is a linear algebra library for C++ programs. The MTL uses template programming , which considerably reduces the code length. All matrices and vectors are available in all classical numerical formats: float , double , complex<float> or complex<double> .

  6. Circulant matrix - Wikipedia

    en.wikipedia.org/wiki/Circulant_matrix

    An circulant matrix takes the form = [] or the transpose of this form (by choice of notation). If each is a square matrix, then the matrix is called a block-circulant matrix.. A circulant matrix is fully specified by one vector, , which appears as the first column (or row) of .

  7. Computational complexity of matrix multiplication - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    In theoretical computer science, the computational complexity of matrix multiplication dictates how quickly the operation of matrix multiplication can be performed. Matrix multiplication algorithms are a central subroutine in theoretical and numerical algorithms for numerical linear algebra and optimization, so finding the fastest algorithm for matrix multiplication is of major practical ...

  8. C data types - Wikipedia

    en.wikipedia.org/wiki/C_data_types

    For every type T, except void and function types, there exist the types "array of N elements of type T". An array is a collection of values, all of the same type, stored contiguously in memory. An array of size N is indexed by integers from 0 up to and including N−1. Here is a brief example:

  9. Spark (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Spark_(mathematics)

    Equivalently, the spark of a matrix is the size of its smallest circuit (a subset of column indices such that = has a nonzero solution, but every subset of it does not [1]). If all the columns are linearly independent, s p a r k ( A ) {\displaystyle \mathrm {spark} (A)} is usually defined to be m + 1 {\displaystyle m+1} (if A {\displaystyle A ...