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  2. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    Eigenvalues and eigenvectors. In linear algebra, an eigenvector (/ ˈaɪɡən -/ EYE-gən-) or characteristic vector is a vector that has its direction unchanged by a given linear transformation. More precisely, an eigenvector, , of a linear transformation, , is scaled by a constant factor, , when the linear transformation is applied to it: .

  3. Eigenfunction - Wikipedia

    en.wikipedia.org/wiki/Eigenfunction

    Eigenfunctions. In general, an eigenvector of a linear operator D defined on some vector space is a nonzero vector in the domain of D that, when D acts upon it, is simply scaled by some scalar value called an eigenvalue. In the special case where D is defined on a function space, the eigenvectors are referred to as eigenfunctions. That is, a ...

  4. Legendre polynomials - Wikipedia

    en.wikipedia.org/wiki/Legendre_polynomials

    In mathematics, Legendre polynomials, named after Adrien-Marie Legendre (1782), are a system of complete and orthogonal polynomials with a vast number of mathematical properties and numerous applications. They can be defined in many ways, and the various definitions highlight different aspects as well as suggest generalizations and connections ...

  5. Classical orthogonal polynomials - Wikipedia

    en.wikipedia.org/wiki/Classical_orthogonal...

    The classical orthogonal polynomials arise from a differential equation of the form. where Q is a given quadratic (at most) polynomial, and L is a given linear polynomial. The function f, and the constant λ, are to be found. (Note that it makes sense for such an equation to have a polynomial solution. Each term in the equation is a polynomial ...

  6. Jordan normal form - Wikipedia

    en.wikipedia.org/wiki/Jordan_normal_form

    The lambdas are the eigenvalues of the matrix; they need not be distinct. In linear algebra, a Jordan normal form, also known as a Jordan canonical form, [1][2] is an upper triangular matrix of a particular form called a Jordan matrix representing a linear operator on a finite-dimensional vector space with respect to some basis.

  7. Sturm's theorem - Wikipedia

    en.wikipedia.org/wiki/Sturm's_theorem

    Sturm's theorem. In mathematics, the Sturm sequence of a univariate polynomial p is a sequence of polynomials associated with p and its derivative by a variant of Euclid's algorithm for polynomials. Sturm's theorem expresses the number of distinct real roots of p located in an interval in terms of the number of changes of signs of the values of ...

  8. Hilbert–Schmidt theorem - Wikipedia

    en.wikipedia.org/wiki/Hilbert–Schmidt_theorem

    Hilbert–Schmidt theorem. In mathematical analysis, the Hilbert–Schmidt theorem, also known as the eigenfunction expansion theorem, is a fundamental result concerning compact, self-adjoint operators on Hilbert spaces. In the theory of partial differential equations, it is very useful in solving elliptic boundary value problems.

  9. Eigenvalues and eigenvectors - en.wikipedia.org

    en.wikipedia.org/.../Eigenvalues_and_eigenvectors

    In linear algebra, it is often important to know which vectors have their directions unchanged by a given linear transformation. An eigenvector (/ ˈ aɪ ɡ ən-/ EYE-gən-) or ch