There are 2 eigenvectors corresponding to 1 eigenvalue (with multiplicity 4) for the following example. However, R returns 4 distinct eigenvectors. It looks like pairs of them are approximately the sa
Based on the documents http://www.gnu.org/software/gsl/manual/html_node/Householder-Transformations.html
Hi I\'ve been doing some research about matrix inversion (linear algeb开发者_如何学编程ra) and I wanted to use C++ template programming for the algorithm , what i found out is that there are number of
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Is there a way to calculate the determinant of a complex matrix? F4<-matrix(c(1,1,1,1,1,1i,-1,-1i,1,-1,1,-1,1,-1i,-1,1i),nrow=4)
In MATLAB, when I run the command [V,D] = eig(a) for a symmetric matrix, the largest eigenvalue (and its associated vector) is located in last column. However, when I run it with a non-symmetric matri
Method lu of package Matrix works fine for square matrices. However, I can\'t see why there is that square开发者_JS百科 restriction. How can I perform LU decomposition on a rectangular matrix?You can
I am trying to work out if I can parallelise the training aspect of a machine learning algorithm. The computationally expensive part of the training involves Cholesky decomposing a positive-definite m
I am currently working on a C++ sparse matrix/math/iterative solver library, for a simulation tool I manage.I would have preferred to use an existing package, however, after extensive investigation, n
I use numpy for numerical linear algebra. I suspect that I can get much better performance if I make small modifications in how I carry out certain computations so that they are more memory efficient,
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