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  2. Linear algebra - Wikipedia

    en.wikipedia.org/wiki/Linear_algebra

    Linear algebra is thus a fundamental part of functional analysis and its applications, which include, in particular, quantum mechanics (wave functions) and Fourier analysis (orthogonal basis). Scientific computation

  3. Gilbert Strang - Wikipedia

    en.wikipedia.org/wiki/Gilbert_Strang

    Differential Equations and Linear Algebra (2014) Differential Equations and Linear Algebra - New Book Website; Essays in Linear Algebra (2012) Algorithms for Global Positioning, with Kai Borre (2012) An Analysis of the Finite Element Method, with George Fix (2008) Computational Science and Engineering (2007) Linear Algebra and Its Applications ...

  4. Linear Algebra and Its Applications - Wikipedia

    en.wikipedia.org/wiki/Linear_Algebra_and_Its...

    Linear Algebra and its Applications is a biweekly peer-reviewed mathematics journal published by Elsevier and covering matrix theory and finite-dimensional linear ...

  5. LU decomposition - Wikipedia

    en.wikipedia.org/wiki/LU_decomposition

    Toggle Applications subsection ... In numerical analysis and linear algebra, ... Steven R.; McDonald, Judi J. (2021), Linear Algebra and its Applications (Sixth ed ...

  6. System of linear equations - Wikipedia

    en.wikipedia.org/wiki/System_of_linear_equations

    Linear systems are a fundamental part of linear algebra, a subject used in most modern mathematics. Computational algorithms for finding the solutions are an important part of numerical linear algebra , and play a prominent role in engineering , physics , chemistry , computer science , and economics .

  7. Marvin Marcus - Wikipedia

    en.wikipedia.org/wiki/Marvin_Marcus

    With Robert Charles Thompson, he was the co-founder of the journal Linear and Multilinear Algebra, [2] whose first issue was published in 1973. [8] He was the section editor for linear algebra in Addison-Wesley's series Encyclopedia of mathematics and its applications. [9]

  8. Numerical linear algebra - Wikipedia

    en.wikipedia.org/wiki/Numerical_linear_algebra

    For many problems in applied linear algebra, it is useful to adopt the perspective of a matrix as being a concatenation of column vectors. For example, when solving the linear system =, rather than understanding x as the product of with b, it is helpful to think of x as the vector of coefficients in the linear expansion of b in the basis formed by the columns of A.

  9. Indeterminate system - Wikipedia

    en.wikipedia.org/wiki/Indeterminate_system

    In linear systems, indeterminacy occurs if and only if the number of independent equations (the rank of the augmented matrix of the system) is less than the number of unknowns and is the same as the rank of the coefficient matrix. For if there are at least as many independent equations as unknowns, that will eliminate any stretches of overlap ...

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