Hello all
I have to solve for X in AX=B where  A, X and B are matrices.
Unfortunately A is a ``fat" matrix i.e. more number of columns than
rows. The help page for SVD
http://www.gnu.org/software/gsl/manual/html_node/Singular-Value-Decomposition.html
states that the code only solves systems for systems that have more
rows than columns. Please advise as to what can be done about it.

I am trying to solve for the weights of a radial basis function
network designed for interpolation problems i.e. as many hidden
neurons as there are training patterns.

Are there plans of including neural network and genetic algorithms in GSL?

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