Modeling of linear fading memory systems

Motivated by questions of approximate modeling and identification, we consider various classes of linear time-varying bounded-input-bounded output (BIBO) stable fading memory systems and the characterizations are proved. These include fading memory systems in general, almost periodic systems, and asymptotically periodic systems. We also show that the norm and strong convergence coincide for BIBO stable causal fading memory system

Worst-case analysis of identification - BIBO robustness for closed loop data

This paper deals with the worst-case analysis of identification of linear shift-invariant (possibly) infinite-dimensional systems. A necessary and sufficient input richness condition for the existence of robustly convergent identification algorithms in l1 is given. A closed-loop identification setting is studied to cover both stable and unstable (but BIBO stabilizable) systems. Identification (or modeling) error is then measured by distance functions which lead to the weakest convergence notions for systems such that closed-loop stability, in the sense of BIBO stability, is a robust property. Worst-case modeling error bounds in several distance functions are include

Input-output stabilization of linear systems on Z

A formal framework is set up for the discussion of generalized autoregressive with external input models of the form Ay__Bu, where A and B are linear operators, with the main emphasis being on signal spaces consisting of bounded sequences parametrized by the integers. Different notions of stability are explored, and topological notions such as the idea of a closed system are linked with questions of stabilizability in this very general context. Various problems inherent in using Z as the time axis are analyzed in this operatorial framework

Common hypercyclic vectors for families of operators

We provide a criterion for the existence of a residual set of common hypercyclic vectors for an uncountable family of hypercyclic operators which is based on a previous one given by Costakis and Sambarino. As an application, we get common hypercyclic vectors for a particular family of hypercyclic scalar multiples of the adjoint of a multiplier in the Hardy space, generalizing recent results by Abakumov and Gordon and also Bayart. The criterion is applied to other specific families of operators

Approximation in reflexive Banach spaces and applications to the invariant subspace problem

We formulate a general approximation problem involving reflexive and smooth Banach spaces, and give its explicit solution. Two applications are presented— the first is to the Bounded Completion Problem involving approximation of Hardy class functions, while the second involves the construction of minimal vec- tors and hyperinvariant subspaces of linear operators, generalizing the Hilbert space technique of Ansari and Enflo

Approximation in reflexive Banach spaces and applications to the invariant subspace problem

We formulate a general approximation problem involving reflexive and smooth Banach spaces, and give its explicit solution. Two applications are presented— the first is to the Bounded Completion Problem involving approximation of Hardy class functions, while the second involves the construction of minimal vec- tors and hyperinvariant subspaces of linear operators, generalizing the Hilbert space technique of Ansari and Enflo

Digital phase-locked loops tracked by a relay sensor

An optimal algorithm is presented for tracking the phase of a slowly modulating signal by means of digital sampling of its sign. Error bounds and a numerical illustration are given

Robust identification from band-limited data

Consider the problem of identifying a scalar bounded-input/bounded-output stable transfer function from pointwise measurements at frequencies within a bandwidth. We propose an algorithm which consists of building a sequence of maps from data to models converging uniformly to the transfer function on the bandwidth when the number of measurements goes to infinity, the noise level to zero, and asymptotically meeting some gauge constraint outside. Error bounds are derived, and the procedure is illustrated by numerical experiment

Asymptotic estimates for interpolation and constrained approximation in H2 by diagonalization of Toeplitz operators

Sharp convergence rates are provided for interpolation and approximation schemes in the Hardy space H-2 that use band-limited data. By means of new explicit formulae for the spectral decomposition of certain Toeplitz operators, sharp estimates for Carleman and Krein-Nudel'man approximation schemes are derived. In addition, pointwise convergence results are obtained. An illustrative example based on experimental data from a hyperfrequency filter is provided

Approximate Carleman theorems and a Denjoy-Carleman maximum principle

We give an extension of the Denjoy-Carleman theorem, which leads to a generalization of Carleman's theorem on the unique determination of probability measures by their moments. We also give complex versions of Carleman's theorem extending Theorem 4.1 of [2]