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Canonical forms for matrix triples $(A,G,\hat G)$, where
$A$ is arbitrary rectangular and $G$, $\hat G$ are either real symmetric
or skew symmetric, or complex Hermitian or skew Hermitian, are derived.
These forms generalize classical product Schur forms as well as
singular value decompositions.
An new proof for the complex case is given, where there is no need to
distinguish whether $G$ and $\hat G$ are Hermitian or skew Hermitian.
This proof is independent from the results in Bolschakov/Reichstein 1995, where
a similar canonical form has been obtained for the complex case,
and it allows generalization to the real case. Here,
the three cases, i.e., that
$G$ and $\hat G$ are both symmetric, both skew symmetric or one each,
are treated separately.
We introduce a transformation between the generalized symplectic
pencils and the skew-Hermitian/Hermitian pencils. Under the transformation
the regularity of the matrix pencils is preserved, and the
equivalence relations about their eigenvalues and deflating subspaces
are established. The eigenvalue problems of the generalized symplectic
pencils and skew-Hermitian/Hermitian pencils are strongly related to
the discrete-time and continuous-time robust control problems, respectively.
With the transformation a simple connection between these two
types of robust control problems is made. The connection may help
to develop unified methods for solving the robust control problems.
We present structure preserving algorithms for the numerical com-
putation of structured staircase forms of skew-symmetric/symmetric
matrix pencils along with the Kronecker indices of the associated skew-
symmetric/symmetric Kronecker-like canonical form. These methods
allow deflation of the singular structure and deflation of infinite eigenvalues with index greater than one. Two algorithms are proposed: one
for general skew-symmetric/symmetric pencils and one for pencils in
0
which the skew-symmetric matrix is a direct sum of 0 and J = −I I .
0
We show how to use the structured staircase form to solve boundary
value problems arising in control applications and present numerical
examples.
We discuss the eigenvalue problem for
general and structured matrix polynomials which may
be singular and may have eigenvalues at infinity.
We derive staircase
condensed forms that allow deflation of the infinite eigenvalue and
singular structure of the matrix polynomial.
The remaining reduced order staircase form leads to
new types of linearizations which determine the finite eigenvalues and
and corresponding eigenvectors. The new linearizations
also simplify the construction of structure preserving linearizations.
Perturbation of Purely Imaginary Eigenvalues of Hamiltonian Matrices under Structured Perturbations
(2007)
We discuss the perturbation theory for purely imaginary eigenvalues of Hamiltonian matrices under Hamiltonian and non-Hamiltonian perturbations. We
show that there is a substantial difference in the behavior under these perturbations. We also discuss the perturbation of real eigenvalues of real
skew-Hamiltonian matrices under structured perturbations and use these results to analyze the properties of the URV method of computing the
eigenvalues of Hamiltonian matrices.
The classical singular value decomposition for a matrix $A\in\Cmn$ is a
canonical form for $A$ that also displays the eigenvalues
of the Hermitian matrices $AA^\ast$ and $A^\ast A$. In this paper, we develop
a corresponding decomposition for $A$ that provides the Jordan canonical forms
for the complex symmetric matrices $AA^T$ and $A^TA$. More generally, we consider
the matrix triple $(A,G_1,G_2)$, where $G_1\in\CC{m}, G_2\in\CC{n}$
are invertible and either complex symmetric and complex skew-symmetric, and we
provide a canonical form under transformations of the form
$(A,G_1,G_2)\mapsto(X^T A Y, X^T G_1X, Y^T G_2Y)$, where $X,Y$ are nonsingular.
We derive formulas for the minimal positive solution of a
particular non-symmetric Riccati
equation arising in transport theory. The formulas are based
on the eigenvalues of an
associated matrix. We use the formulas to explore some new
properties of the minimal positive solution and to derive
fast and highly accurate numerical methods. Some numerical tests
demonstrate the properties of the new methods.
The long standing problem is discussed of how to deflate the part associated with the eigenvalue infinity in a structured matrix pencil using structure preserving unitary transformations. We derive such a deflation procedure and apply this new technique to symmetric, Hermitian or alternating pencils and in a modified form to (anti)-palindromic pencils. We present a detailed error and perturbation analysis of this and other deflation procedures and demonstrate the properties of the new algorithm with several numerical examples.