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comparison scripts/sparse/svds.m @ 10846:a4f482e66b65

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Grammarcheck more of the documentation. Use @noindent macro appropriately. Limit line length to 80 characters.
author Rik <octave@nomad.inbox5.com>
date Sun, 01 Aug 2010 20:22:17 -0700
parents f5f9bc8e83fc
children 2c356a35d7f5
comparison
equal deleted inserted replaced
10845:c0ffe159ba1a 10846:a4f482e66b65
67 ## 67 ##
68 ## @example 68 ## @example
69 ## @var{a}_approx = @var{u}*@var{s}*@var{v}' 69 ## @var{a}_approx = @var{u}*@var{s}*@var{v}'
70 ## @end example 70 ## @end example
71 ## 71 ##
72 ## @noindent
72 ## where @var{a}_approx is a matrix of size @var{a} but only rank @var{k}. 73 ## where @var{a}_approx is a matrix of size @var{a} but only rank @var{k}.
73 ## 74 ##
74 ## @var{flag} returns 0 if the algorithm has succesfully converged, and 1 75 ## @var{flag} returns 0 if the algorithm has succesfully converged, and 1
75 ## otherwise. The test for convergence is 76 ## otherwise. The test for convergence is
76 ## 77 ##
78 ## @group 79 ## @group
79 ## norm (@var{a}*@var{v} - @var{u}*@var{s}, 1) <= @var{tol} * norm (@var{a}, 1) 80 ## norm (@var{a}*@var{v} - @var{u}*@var{s}, 1) <= @var{tol} * norm (@var{a}, 1)
80 ## @end group 81 ## @end group
81 ## @end example 82 ## @end example
82 ## 83 ##
83 ## @code{svds} is best for finding only a few singular values from a large sparse 84 ## @code{svds} is best for finding only a few singular values from a large
84 ## matrix. Otherwise, @code{svd (full(@var{a}))} will likely be more efficient. 85 ## sparse matrix. Otherwise, @code{svd (full(@var{a}))} will likely be more
86 ## efficient.
85 ## @end deftypefn 87 ## @end deftypefn
86 ## @seealso{svd, eigs} 88 ## @seealso{svd, eigs}
87 89
88 function [u, s, v, flag] = svds (a, k, sigma, opts) 90 function [u, s, v, flag] = svds (a, k, sigma, opts)
89 91