On 27.03.2012 20:22, Sahil Singla wrote:
> I am a second year undergraduate ,doing my major in Computer Sciences.
> I have done a course in Numerical Linear Algebra and Scientific Computing
> and it is by far the most interesting topic I have encountered in my life.
> 
> I want to improve the code of QR factorization used in sympy by using
> Householder reflections to find the QR of a matrix. Ideally the naiive
> algorithm in sympy has complexity of O(m*n*n). Using householder
> transformation method, this can be made much faster.
> 
> Apart from it, I intend to implement the method for finding the eigenvalues
> of a real matrix using a different algorithm. The present algorithm which
> computes the eigenvalues of a matrix by finding the roots of the
> characteristic polynomial is highly unstable and has a very high condition
> number. The condition number for calculating an eigenvalue of a matrix(say
> e) when the i'th coefficient in the matrix (say a(i)) is perturbed is
> (a(i)*(e^(i-1)))/(p'(e)) where p'(e) is the derivative of the
> characteristic polynomial at e. Seeing the amount of rounding errors that
> will be involved in calculation of a particular coefficient, the resulting
> error in the computation of the eigenvalue will be huge!
> 
> The method by which it can be simplified is the power iteration method. The
> program will have to be a combination of many different methods so that
> eigenvalues for different matrices . In particular, the method will sort
> out the issue 3189.
> 

It will be good!
But I have to note, that the main task of the issue 3189 to give a
chance to obtain the eigenvectors (not values) in several cases, when
the nullspace algorithm failed.

-
Alexey Gudchenko

> The method I intend to use is  QR Algorithm for real matrices. After
> applying finite preliminary reductions, the matrix can be converted into
> its hessenberg form so that the work per iteration (step: A=R*Q) is reduced
> to O(n^2) from O(n^3).
> 
> 
> Regards,
> Sahil Singla
> Sophomore,
> Computer Sciences,
> IIT Delhi
> 

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