SVDS returns empty matrix.
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I have a 1000x1000 sparse matrix A. I am calling svds(A,10). I am getting an empty matrix as a result. I can't understand why am I getting this result. I visualized this matrix and found out that most of the non-zero elements appear to be along the diagonal. Is the result of svds an empty matrix because of the the placement of non-zero elements along the diagonal of the matrix?
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Walter Roberson
2015 年 11 月 29 日
"svds checks the accuracy of the computed singular vectors. If the vectors are not accurate enough, then svds returns fewer singular values than requested. To obtain the requested number of singular values, try decreasing the error tolerance in the options structure."
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