I am using OpenCL to calculate the eigenvectors of a matrix. AMD has an example of eigenvalue calculation so I decided to use inverse iteration to get the eigenvectors.
I am using LAPACK\'s ssteqr function to calculate eigenvalues/eigenvectors. The do开发者_开发知识库cumentation for ssteqr says that the eigenvalues are sorted \"in ascending order\". Is it reasonable
I have a symmetric matrix with the elements A=[8.8191,0,1.0261; 0,3,0; 1.0261,0,3.1809]; I used the eig(A) function in MATLAB , the eigenvalues and eigenvectors are given :
I\'m trying to convert a generalized eigenvalue problem into a normal eigenvalue calculation. I have this code:
I have N eigenvalues in column vector form. Thus there are N开发者_StackOverflow中文版 eigenvectors corresponding to these eigenvalues, forming an eigenvector matrix.
Basically I\'m trying to find the eigenvalues for matrix, and it takes about 12 hours. When it finishes, it says it couldn\'t find all the eigenvect开发者_开发百科ors (actually barely any), and I\'m s
I\'m working with eigenfaces for a facial recognition program I am writing. I have a couple questions about how eigenfaces are actually generated:
I\'m implementing the system described within this paper, and I\'m getting a little stuck. I only recently encountered tensors/eigenvalues etc so excuse me if this is a lit开发者_如何学运维tle simple!
How to convert the following MATLAB code to Python? Here is my solution, but it doesn\'t quite produce the same results. For example, f seems to be always positive in the MATLAB code, but in my Python
Ok guys, I am using the following library: http://www.codeproject.com/KB/recipes/AdvancedMatrixLibrary.aspx
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