Vector-exponential time-series modeling for polynomial J-spectral factorization

An iterative algorithm to perform the J-spectral factorization of a para-Hermitian matrix is presented. The algorithm proceeds by computing a special kernel representation of an interpolant for a sequence of points and associated directions determined from the spectral zeroes of the to-be factored matrix

A behavioral view of Nevanlinna-Pick interpolation

The classical Nevanlinna-Pick (NP) interpolation problem is about finding a rational function that satisfies given interpolation conditions, along with a norm condition. In this paper we address the NP problem using concepts from behavioral systems theory and quadratic differential forms (QDFs). The NP problem is solved using a certain “dualization of data”. We address system theoretic motivations for this dualization and the advantages gained in this process. Finally, we address the problem of constructing interpolating functions that satisfy a “frequency dependent” norm condition

Interpolation with bilinear differential forms

We present a recursive algorithm for modeling with bilinear differential forms. We discuss applications of this algorithm for interpolation with symmetric bivariate polynomials, and for computing storage functions for autonomous systems

Dissipative Systems Synthesis:a Linear Algebraic Approach

In this paper we consider the problem of synthesis of dissipative systems for the case that first and higher order derivatives of the concerned variables also appear in the weighting function. The problem is formulated and solved using the behavioral approach to systems and control. It turns out that this problem can be reformulated analogously as a problem of finding a non-negative subspace (non-negative with respect to a given indefinite constant symmetric matrix) within a finite dimensional vector space satisfying certain inclusion and dimensionality constraints