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  2. Characteristic polynomial - Wikipedia

    en.wikipedia.org/wiki/Characteristic_polynomial

    The characteristic polynomial of an endomorphism of a finite-dimensional vector space is the characteristic polynomial of the matrix of that endomorphism over any basis (that is, the characteristic polynomial does not depend on the choice of a basis).

  3. Faddeev–LeVerrier algorithm - Wikipedia

    en.wikipedia.org/wiki/Faddeev–LeVerrier_algorithm

    Urbain Le Verrier (1811–1877) The discoverer of Neptune.. In mathematics (linear algebra), the Faddeev–LeVerrier algorithm is a recursive method to calculate the coefficients of the characteristic polynomial = of a square matrix, A, named after Dmitry Konstantinovich Faddeev and Urbain Le Verrier.

  4. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    This polynomial is called the characteristic polynomial of A. Equation is called the characteristic equation or the secular equation of A. The fundamental theorem of algebra implies that the characteristic polynomial of an n-by-n matrix A, being a polynomial of degree n, can be factored into the product of n linear terms,

  5. Companion matrix - Wikipedia

    en.wikipedia.org/wiki/Companion_matrix

    The roots of the characteristic polynomial () are the eigenvalues of ().If there are n distinct eigenvalues , …,, then () is diagonalizable as () =, where D is the diagonal matrix and V is the Vandermonde matrix corresponding to the λ 's: = [], = [].

  6. Routh–Hurwitz stability criterion - Wikipedia

    en.wikipedia.org/wiki/Routh–Hurwitz_stability...

    A polynomial satisfying the Routh–Hurwitz criterion is called a Hurwitz polynomial. The importance of the criterion is that the roots p of the characteristic equation of a linear system with negative real parts represent solutions e pt of the system that are stable .

  7. Determinant - Wikipedia

    en.wikipedia.org/wiki/Determinant

    Determinants are used for defining the characteristic polynomial of a square matrix, whose roots are the eigenvalues. In geometry , the signed n -dimensional volume of a n -dimensional parallelepiped is expressed by a determinant, and the determinant of a linear endomorphism determines how the orientation and the n -dimensional volume are ...

  8. Matrix similarity - Wikipedia

    en.wikipedia.org/wiki/Matrix_similarity

    Characteristic polynomial, and attributes that can be derived from it: Determinant; Trace; Eigenvalues, and their algebraic multiplicities; Geometric multiplicities of eigenvalues (but not the eigenspaces, which are transformed according to the base change matrix P used). Minimal polynomial; Frobenius normal form

  9. Eigendecomposition of a matrix - Wikipedia

    en.wikipedia.org/wiki/Eigendecomposition_of_a_matrix

    We call p(λ) the characteristic polynomial, and the equation, called the characteristic equation, is an N th-order polynomial equation in the unknown λ. This equation will have N λ distinct solutions, where 1 ≤ N λ ≤ N. The set of solutions, that is, the eigenvalues, is called the spectrum of A. [1] [2] [3]