Complementing data-driven models of dynamic systems with certificates of reliability and
safety is of critical importance in many applications, such as in the design of robust control …

Standard state estimation approaches do not provide guaranteed confidence regions for
finite data amounts. For some applications, in particular safety critical ones, this can be of …

Sign-Perturbed Sums (SPS) is a non-asymptotic system identification method that can
construct confidence regions for general linear systems. It works under mild statistical …

In this paper, the problem of constructing non-asymptotic confidence regions for Errors-In-
Variables (EIV) systems is considered. In EIV systems both the input and the output …

Sign-Perturbed Sums (SPS) is a recently developed non-asymptotic system identification
algorithm that constructs confidence regions for parameters of dynamical systems. It works …

Abstract Sign-Perturbed Sum (SPS) is a powerful finite-sample system identification
algorithm which can construct confidence regions for the true data generating system with …

Abstract Sign-Perturbed-Sums (SPS) is a system identification algorithm that, under mild
assumptions on the distribution of the noise, constructs confidence regions with finite …

Finite sample system identification (FSID) methods construct confidence regions for system
parameters with non-asymptotic guarantees under minimal assumptions on the noise …

Sign-Perturbed Sums (SPS) is a recently developed finite sample system identification
method that can build exact confidence regions for linear regression problems under mild …

Recently, a new finite-sample system identification algorithm, called Sign-Perturbed Sums
(SPS), was introduced in [2]. SPS constructs finite-sample confidence regions that are …