The square matrix A could be represented as A=Q·H·QT, where Q is an orthogonal matrix, and H is a matrix in upper Hessenberg form.
The matrix in upper Hessenberg form is as follows (non-zero elements are marked with an "X"):
Like other algorithms of orthogonal factorization (for example, QR and LQ decomposition algorithms), this algorithm uses a sequence of elementary reflections to transform the matrix A. The matrix is transformed from the left and from the right. The transformations gradually remove the elements.
As a result of subroutine RMatrixHessenberg, the matrix A is replaced with matrix H and a sequence of reflection transformations stored in compact form. The form in which the transformations are stored and the subroutine parameters are described in more details in the subroutine comments. The method is similar to QR decomposition which uses the lower part of matrix R to store matrix Q.
As with QR decomposition, the subroutines for "unpacking" matrices Q and H are presented: RMatrixHessenbergUnpackQ and RMatrixHessenbergUnpackH. The first subroutine allows to get matrix Q, the second subroutine allows to get matrix H.
This algorithm is transferred from the LAPACK library.
This article is licensed for personal use only.
ALGLIB Project offers you two editions of ALGLIB:
ALGLIB Free Edition:
+delivered for free
+offers full set of numerical functionality
+extensive algorithmic optimizations
-no multithreading
-non-commercial license
ALGLIB Commercial Edition:
+flexible pricing
+offers full set of numerical functionality
+extensive algorithmic optimizations
+high performance (SMP, SIMD)
+commercial license with support plan
Links to download sections for Free and Commercial editions can be found below: