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Let be an
matrix with and full rank (viz. rank ). An orthogonal matrix triangularization (QR Decomposition) consists of determining an
orthogonal matrix such that
with the
upper triangular matrix . One only has then to solve the triangular system , where consists of the first rows of .
Householder transformations clear whole columns except for the first element of a vector. If one wants to clear parts of a matrix one element at a time, one can use Givens rotation, which is particularly practical for parallel implementation .
A matrix
with properly chosen
and
for some rotation angle can be used to zero the element . The elements can be zeroed column by column from the bottom up in the following order:
is then the product of
Givens matrices
.
To annihilate the bottom element of a
vector:
the conditions
and
give:
For “Fast Givens”, see [Golub89].
References
- Golub89
- Gene H. Golub and Charles F. van Loan: Matrix Computations, 2nd edn., The John Hopkins University Press, 1989.
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