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  2. File:Jim Hefferon - Linear Algebra (4th Edition).pdf - Wikipedia

    en.wikipedia.org/wiki/File:Jim_Hefferon_-_Linear...

    English: Linear Algebra by Jim Hefferon, along with its answers to exercises, is a text for a first undergraduate course. It is Free. Use it as the main book, as a supplement, or for independent study.

  3. File:A First Course in Linear Algebra for print.pdf - Wikipedia

    en.wikipedia.org/wiki/File:A_First_Course_in...

    Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.

  4. Linear algebra - Wikipedia

    en.wikipedia.org/wiki/Linear_algebra

    With respect to general linear maps, linear endomorphisms and square matrices have some specific properties that make their study an important part of linear algebra, which is used in many parts of mathematics, including geometric transformations, coordinate changes, quadratic forms, and many other part of mathematics.

  5. File:Jim Hefferon, Linear algebra, third edition, book.pdf

    en.wikipedia.org/wiki/File:Jim_Hefferon,_Linear...

    Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.

  6. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    Eigenvalues and eigenvectors are often introduced to students in the context of linear algebra courses focused on matrices. [ 22 ] [ 23 ] Furthermore, linear transformations over a finite-dimensional vector space can be represented using matrices, [ 3 ] [ 4 ] which is especially common in numerical and computational applications.

  7. Schmidt decomposition - Wikipedia

    en.wikipedia.org/wiki/Schmidt_decomposition

    In linear algebra, the Schmidt decomposition (named after its originator Erhard Schmidt) refers to a particular way of expressing a vector in the tensor product of two inner product spaces. It has numerous applications in quantum information theory, for example in entanglement characterization and in state purification, and plasticity.

  8. File:Linear Algebra by Hussein Tevfik.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Linear_Algebra_by...

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Pages for logged out editors learn more

  9. Hessenberg matrix - Wikipedia

    en.wikipedia.org/wiki/Hessenberg_matrix

    In linear algebra, a Hessenberg matrix is a special kind of square matrix, one that is "almost" triangular. To be exact, an upper Hessenberg matrix has zero entries below the first subdiagonal, and a lower Hessenberg matrix has zero entries above the first superdiagonal. [1] They are named after Karl Hessenberg. [2]