Re: [eigen] Student contribution 
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Rather than making the SVD effort
direction dependent on generalizing the Bidagonalization class,
would it make sense to move in an orthogonal direction and focus
the effort on decomposing square or tall matrices, at least
initially? This should simplify the code, require only the
UpperBidiagonalization, and decrease the scope. This improves the
probability the students will get to a point of usefulness in a
limited time. It is trivial to wrap a "tall SVD" to make a
general purpose SVD: [u,s,v]=svd(A) <=> [v,s,u] = svd(A').
The resulting wrapper may have some inefficiencies on wide
matrices due to the initial transpose, but I'd be surprised if it
was much. If the students finish quickly, or if parallel
development is desired; the task of Bidiagonalization could also
be performed, but it would not need to be a prerequisite for the
rest of the SVD.
 Mark On 05/22/2013 06:13 AM, Benoit Jacob wrote:

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