In this thesis the generalized eigenvalue problem is described.
The generalized eigenvalues are computed by QZ algorithm and
its corresponding generalized eigenvectors are computed by
method which is called inverse iteration. The QZ algorithm is
based on the QR algorithm. This QR algorithm solves numerical
eigenvalue problem - calculates eigenvalues. The corresponding
eigenvectors are computed by inverse iteration too. The QR
iteration is based on QR-decomposition of the matrix A so that
A = QR where Q is the orthogonal matrix and R is the upper
triangular matrix. The matrix A can be decomposed in several
ways. For example we can use the Householder matrix of
reflection or Givens matrix of plane rotation or Gram-Schmidt
algorithm for decomposition of the matrix A.