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  2. Comparison of linear algebra libraries - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_linear...

    C++ template library; binds to optimized BLAS such as the Intel MKL; Includes matrix decompositions, non-linear solvers, and machine learning tooling Eigen: Benoît Jacob C++ 2008 3.4.0 / 08.2021 Free MPL2: Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms. Fastor [5]

  3. Armadillo (C++ library) - Wikipedia

    en.wikipedia.org/wiki/Armadillo_(C++_library)

    An interface to the Python language is available through the PyArmadillo package, [4] which facilitates prototyping of algorithms in Python followed by relatively straightforward conversion to C++. Armadillo is a core dependency of the mlpack machine learning library [5] and the ensmallen C++ library for numerical optimization. [6]

  4. SymbolicC++ - Wikipedia

    en.wikipedia.org/wiki/SymbolicC++

    SymbolicC++ is a general purpose computer algebra system written in the programming language C++. It is free software released under the terms of the GNU General Public License. SymbolicC++ is used by including a C++ header file or by linking against a library.

  5. Comparison of programming languages (array) - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_programming...

    Comparison of ALGOL 68 and C++; ALGOL 68: Comparisons with other languages; Compatibility of C and C++; Comparison of Pascal and Borland Delphi; Comparison of Object Pascal and C; Comparison of Pascal and C; Comparison of Java and C++; Comparison of C# and Java; Comparison of C# and Visual Basic .NET; Comparison of Visual Basic and Visual Basic ...

  6. Matrix multiplication algorithm - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication...

    The definition of matrix multiplication is that if C = AB for an n × m matrix A and an m × p matrix B, then C is an n × p matrix with entries = =. From this, a simple algorithm can be constructed which loops over the indices i from 1 through n and j from 1 through p, computing the above using a nested loop:

  7. Strassen algorithm - Wikipedia

    en.wikipedia.org/wiki/Strassen_algorithm

    This reduces the number of matrix additions and subtractions from 18 to 15. The number of matrix multiplications is still 7, and the asymptotic complexity is the same. [6] The algorithm was further optimised in 2017, [7] reducing the number of matrix additions per step to 12 while maintaining the number of matrix multiplications, and again in ...

  8. Crout matrix decomposition - Wikipedia

    en.wikipedia.org/wiki/Crout_matrix_decomposition

    The Crout matrix decomposition algorithm differs slightly from the Doolittle method. Doolittle's method returns a unit lower triangular matrix and an upper triangular matrix, while the Crout method returns a lower triangular matrix and a unit upper triangular matrix. So, if a matrix decomposition of a matrix A is such that: A = LDU

  9. Matrix polynomial - Wikipedia

    en.wikipedia.org/wiki/Matrix_polynomial

    A matrix polynomial identity is a matrix polynomial equation which holds for all matrices A in a specified matrix ring M n (R). Matrix polynomials are often demonstrated in undergraduate linear algebra classes due to their relevance in showcasing properties of linear transformations represented as matrices, most notably the Cayley–Hamilton ...