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Izchak Lewkowicz

Publications and source records attributed to Izchak Lewkowicz.

28 records · Page 2Linked to original sources
arXiv2014

Characterizations of families of rectangular finite impulse response, para-unitary systems

We here study Finite Impulse Response (FIR) rectangular, not necessarily causal, systems which are (para)-unitary on the unit circle (=the class $\mathcal{U}$). First, we offer three characterizations of these systems. Then, introduce a %easy-to-use description of all FIRs in $\mathcal{U}$, as copies of a real polytope, parametrized by the dimensions and the McMillan degree of the FIRs. Finally, we present six simple ways (along with their combinations) to construct, from any FIR, a large family of FIRs, of various dimensions and McMillan degrees, so that whenever the original system is in $\mathcal{U}$, so is the whole family. A key role is played by Hankel matrices.

math.CV↗
arXiv2013

Minimal state space realization, static output feedback and matrix completion of families of systems

We here characterize the minimality of realization of arbitrary linear time-invariant dynamical systems through (i) intersection of the spectra of the realization matrix and of the corresponding state submatrix and (ii) moving the poles by applying static output feedback. In passing, we introduce, for a given square matrix A, a parameterization of all matrices B for which the pairs (A, B) are controllable. In particular, the minimal rank of such B turns to be equal to the smallest geometric multiplicity among the eigenvalues of A. Finally, we show that the use of a (not necessarily square) realization matrix L to examine minimality of realization, is equivalent to the study of a smaller dimensions, square realization matrix L_sq, which in turn is linked to realization matrices obtained as polynomials in L_sq. Namely a whole family of systems.

math.CV↗
arXiv2013

Easy-to-compute parameterizations of all wavelet filters: input-output and state-space

We here use notions from the theory linear shift-invariant dynamical systems to provide an easy-to-compute characterization of all rational wavelet filters. For a given N bigger or equql to 2, the number of inputs, the construction is based on a factorization to an elementary wavelet filter along with of m elementary unitary matrices. We shall call this m the index of the filter. It turns out that the resulting wavelet filter is of McMillan degree $N((N-1)/2+m). Rational wavelet filters bounded at infinity, admit state space realization. The above input-output parameterization is exploited for a step-by-step construction (where in each the index m is increased by one) of state space model of wavelet filters.

math.CV↗
arXiv2012

Interpolation by polynomials with symmetries on the imaginary axis

We here specialize the standard matrix-valued polynomial interpolation to the case where on the imaginary axis the interpolating polynomials admit various symmetries: Positive semidefinite, Skew-Hermitian, $J$-Hermitian, Hamiltonian and others. The procedure is comprized of three stages, illustrated through the case where on $i\R$ the interpolating polynomials are to be positive semidefinite. We first, on the expense of doubling the degree, obtain a minimal degree interpolating polynomial $P(s)$ which on $i\R$ is Hermitian. Then we find all polynomials $Ψ(s)$, vanishing at the interpolation points which are positive semidefinite on $i\R$. Finally, using the fact that the set of positive semidefinite matrices is a convex subcone of Hermitian matrices, one can compute the minimal scalar $\hatβ\geq 0$ so that $P(s)+βΨ(s)$ satisfies all interpolation constraints for all $β\geq\hatβ$. This approach is then adapted to cases when the family of interpolating polynomials is not convex. Whenever convex, we parameterize all minimal degree interpolating polynomials.

math.CV↗
arXiv2012

Convex Cones of Generalized Positive Rational Functions and Nevanlinna-Pick Interpolation

Scalar rational functions with a non-negative real part on the right half plane, called positive, are classical in the study of electrical networks, dissipative systems, Nevanlinna-Pick interpolation and other areas. We here study generalized positive functions, i.e with a non-negative real part on the imaginary axis. These functions form a Convex Invertible Cone, cic in short, and we explore two partitionings of this set: (i) into a pair of even and odd subcics and (ii) to (infinitely many non-invertible) convex cones of functions with prescribed poles and zeroes in the right half plane. It is then shown that a positive function can always be written as a sum of even and odd part, only over the larger set of generalized positive. It is well known that over positive functions Nevanlinna-Pick interpolation is not always feasible. Over generalized positive, there is no easy way to carry out this interpolation. The second partitioning is subsequently exploited to introduce a simple procedure for Nevanlinna-Pick interpolation. Finally we show that only some of these properties are carried over to generalized bounded functions, mapping the imaginary axis to the unit disk.

math.OC↗
arXiv2012

State space realization of even generalized positive and odd rational function. Applications to static output feedback

We here specialize the well known Positive Real Lemma (also known as the Kalman-Yakubovich-Popov Lemma) to complex matrix-valued rational functions, (i) generalized positive even and (ii) odd. On the way we characterize the (non) minimality of realization of arbitrary systems through (i) the corresponding state matrix and (ii) moving the poles by applying static output feedback. We then explore the application of static output feedback to both generalized positive even and to odd functions.

math.OC↗
arXiv2011

The positive real lemma and construction of all realizations of generalized positive rational functions

We here extend the well known Positive Real Lemma (also known as the Kalman-Yakubovich-Popov Lemma) to complex matrix-valued generalized positive rational function, when non-minimal realizations are considered. We then exploit this result to provide an easy construction procedure of all (not necessarily minimal) state space realizations of generalized positive functions. As a by-product, we partition all state space realizations into subsets: Each is identified with a set of matrices satisfying the same Lyapunov inclusion and thus form a convex invertible cone, cic in short. Moreover, this approach enables us to characterize systems which may be brought to be generalized positive through static output feedback. The formulation through Lyapunov inclusions suggests the introduction of an equivalence class of rational functions of various dimensions associated with the same system matrix.

math.OC↗
arXiv2011

Extending wavelet filters. Infinite dimensions, the non-rational case, and indefinite-inner product spaces

In this paper we are discussing various aspects of wavelet filters. While there are earlier studies of these filters as matrix valued functions in wavelets, in signal processing, and in systems, we here expand the framework. Motivated by applications, and by bringing to bear tools from reproducing kernel theory, we point out the role of non-positive definite Hermitian inner products (negative squares), for example Krein spaces, in the study of stability questions. We focus on the non-rational case, and establish new connections with the theory of generalized Schur functions and their associated reproducing kernel Pontryagin spaces, and the Cuntz relations.

math.CV↗
arXiv2011

Representation formulas for Hardy space functions through the Cuntz relations and new interpolation problems

We introduce connections between the Cuntz relations and the Hardy space H_2 of the open unit disk . We then use them to solve a new kind of multipoint interpolation problem in H_2, where for instance, only a linear combination of the values of a function at given points is preassigned, rather than the values at the points themselves. We also consider the case of de Branges-Rovnyak spaces.

math.FA↗