Mercurial > hg > octave-lyh
view scripts/polynomial/polyeig.m @ 17181:3a23cbde59d5
interpft.m: Fix interpolation to preserve spectral symmetry (bug #39566)
* interpft.m: Fix interpolation to preserve spectral symmetry, be compatible
with Matlab. Add test cases.
author | Mike Miller <mtmiller@ieee.org> |
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date | Sun, 04 Aug 2013 17:27:40 -0400 |
parents | e39f00a32dc7 |
children | 1c89599167a6 |
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## Copyright (C) 2012 Fotios Kasolis ## ## This file is part of Octave. ## ## Octave is free software; you can redistribute it and/or modify it ## under the terms of the GNU General Public License as published by ## the Free Software Foundation; either version 3 of the License, or (at ## your option) any later version. ## ## Octave is distributed in the hope that it will be useful, but ## WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU ## General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with Octave; see the file COPYING. If not, see ## <http://www.gnu.org/licenses/>. ## -*- texinfo -*- ## @deftypefn {Function File} {@var{z} =} polyeig (@var{C0}, @var{C1}, @dots{}, @var{Cl}) ## @deftypefnx {Function File} {[@var{v}, @var{z}] =} polyeig (@var{C0}, @var{C1}, @dots{}, @var{Cl}) ## ## Solve the polynomial eigenvalue problem of degree @var{l}. ## ## Given an @var{n*n} matrix polynomial ## @code{@var{C}(s) = @var{C0} + @var{C1} s + @dots{} + @var{Cl} s^l} ## polyeig solves the eigenvalue problem ## @code{(@var{C0} + @var{C1} + @dots{} + @var{Cl})v = 0}. ## Note that the eigenvalues @var{z} are the zeros of the matrix polynomial. ## @var{z} is an @var{lxn} vector and @var{v} is an (@var{n} x @var{n})l matrix ## with columns that correspond to the eigenvectors. ## ## @seealso{eig, eigs, compan} ## @end deftypefn ## Author: Fotios Kasolis function [ z, varargout ] = polyeig (varargin) if ( nargout > 2 ) print_usage (); endif nin = numel (varargin); n = zeros (1, nin); for cnt = 1 : nin if (! issquare (varargin{cnt})) error ("polyeig: coefficients must be square matrices"); endif n(cnt) = size (varargin{cnt}, 1); endfor if (numel (unique (n)) > 1) error ("polyeig: coefficients must have the same dimensions"); endif n = unique (n); ## matrix polynomial degree l = nin - 1; ## form needed matrices C = [ zeros(n * (l - 1), n), eye(n * (l - 1)); -cell2mat(varargin(1 : end - 1)) ]; D = [ eye(n * (l - 1)), zeros(n * (l - 1), n); zeros(n, n * (l - 1)), varargin{end} ]; ## solve generalized eigenvalue problem if ( isequal (nargout, 1) ) z = eig (C, D); else [ z, v ] = eig (C, D); varargout{1} = v; ## return n-element eigenvectors normalized so ## that the infinity-norm = 1 z = z(1:n,:); ## max() takes the abs if complex: t = max (z); z /= diag (t); endif endfunction %!test %! C0 = [8, 0; 0, 4]; C1 = [1, 0; 0, 1]; %! [v,z] = polyeig (C0, C1); %! assert (isequal (z(1), -8), true); %! d = C0*v + C1*v*z; %! assert (isequal (norm(d), 0.0), true);