Permutation vector permB if sparse B is really chol(B(permB,permB)). Note: p must satisfy k < p <= n for real symmetric, k+1 < p <= n otherwise.ġ if B is really its Cholesky factor chol(B), 0 otherwise. Default values are shown in brackets ( ).ġ if A or A- sigma *B represented by Afun is symmetric, 0 otherwise.ġ if A or A- sigma *B represented by Afun is real, 0 otherwise.Ĭonvergence: Ritz estimate residual = 2k ( p >= 2k+1 real nonsymmetric) advised. The MATLAB 5 value sigma = 'be' is obsolete for nonsymmetric and complex problems.Įigs(A,K, sigma,opts) and eigs(A,B,k, sigma,opts) Note, B need only be symmetric (Hermitian) positive semi-definite.įor real symmetric problems, the following are also options:īoth ends (one more from high end if k is odd)įor nonsymmetric and complex problems, the following are also options: If A is a function, Afun must return Y = A\x. Note, B need only be symmetric (Hermitian) positive semi-definite. If A is a function, Afun must return Y = (A- sigma *B)\x (i.e., Y = A\x when sigma = 0). Return k eigenvalues based on sigma, which can take any of the following values: Return the k largest magnitude eigenvalues. eigs(A.) indicates the standard eigenvalue problem A*V = V*D. B must be symmetric (or Hermitian) positive definite and the same size as A. Solves the generalized eigenvalue problem A*V = B*V*D.
If flag is 0 then all the eigenvalues converged otherwise not all converged. Returns a diagonal matrix D of A's six largest magnitude eigenvalues and a matrix V whose columns are the corresponding eigenvectors.Īlso returns a convergence flag. Returns a vector of A's six largest magnitude eigenvalues. Eigs (MATLAB Functions) MATLAB Function Referenceįind a few eigenvalues and eigenvectors of a square large sparse matrixĭ = eigs(Afun,n,k, sigma,options,p1,p2.)ĭ = eigs(Afun,n,B,k, sigma,options,p1,p2.)
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