4 papers
Gaussian behaviors and stochastic data-driven control
András Sasfi, Alberto Padoan, Ivan Markovsky +1
We propose a stochastic behavioral modeling framework, termed Gaussian behaviors, which augments a deterministic linear time-invariant (LTI) behavior with a Gaussian noise componen…
From Time Series to Affine Systems
A. Padoan, J. Eising, I. Markovsky
The paper extends core results of behavioral systems theory from linear to affine time-invariant systems. We characterize the behavior of affine time-invariant systems via kernel,…
Gaussian behaviors: representations and data-driven control
András Sasfi, Ivan Markovsky, Alberto Padoan +1
We propose a modeling framework for stochastic systems, termed Gaussian behaviors, that describes finite-length trajectories of a system as a Gaussian process. The proposed model n…
GREAT: Grassmannian REcursive Algorithm for Tracking & Online System Identification
András Sasfi, Alberto Padoan, Ivan Markovsky +1
This paper introduces an online approach for identifying time-varying subspaces defined by linear dynamical systems. The approach of representing linear systems by non-parametric s…