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  2. Gilbert Strang - Wikipedia

    en.wikipedia.org/wiki/Gilbert_Strang

    William Gilbert Strang (born November 27, 1934 [1]) is an American mathematician known for his contributions to finite element theory, the calculus of variations, wavelet analysis and linear algebra. He has made many contributions to mathematics education, including publishing mathematics textbooks.

  3. Eigendecomposition of a matrix - Wikipedia

    en.wikipedia.org/wiki/Eigendecomposition_of_a_matrix

    Let A be a square n × n matrix with n linearly independent eigenvectors q i (where i = 1, ..., n).Then A can be factored as = where Q is the square n × n matrix whose i th column is the eigenvector q i of A, and Λ is the diagonal matrix whose diagonal elements are the corresponding eigenvalues, Λ ii = λ i.

  4. Joint spectral radius - Wikipedia

    en.wikipedia.org/wiki/Joint_Spectral_Radius

    The joint spectral radius was introduced in 1960 by Gian-Carlo Rota and Gilbert Strang, [1] two mathematicians from MIT, but started attracting attention with the work of Ingrid Daubechies and Jeffrey Lagarias. [2] They showed that the joint spectral radius can be used to describe smoothness properties of certain wavelet functions. [3]

  5. Linear algebra - Wikipedia

    en.wikipedia.org/wiki/Linear_algebra

    Download as PDF; Printable version; ... Linear algebra is the branch of mathematics concerning linear equations such as: ... Strang, Gilbert (2016), ...

  6. Rank–nullity theorem - Wikipedia

    en.wikipedia.org/wiki/Rank–nullity_theorem

    The rank–nullity theorem is a theorem in linear algebra, which asserts: the number of columns of a matrix M is the sum of the rank of M and the nullity of M ; and the dimension of the domain of a linear transformation f is the sum of the rank of f (the dimension of the image of f ) and the nullity of f (the dimension of the kernel of f ).

  7. Strang splitting - Wikipedia

    en.wikipedia.org/wiki/Strang_splitting

    In applied mathematics Strang splitting is a numerical method for solving differential equations that are decomposable into a sum of differential operators. It is named after Gilbert Strang .

  8. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix into a rotation, followed by a rescaling followed by another rotation. It generalizes the eigendecomposition of a square normal matrix with an orthonormal eigenbasis to any ⁠ m × n {\displaystyle m\times n} ⁠ matrix.

  9. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    In linear algebra, the column space (also called the range or image) of a matrix A is the span (set of all possible linear combinations) of its column vectors. The column space of a matrix is the image or range of the corresponding matrix transformation .

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