7 papers
Stability of input-output maps and their minimal realizations in state-linear, state-affine, LPV, and linear switched systems
Mihály Petreczky, Juan-Pablo Ortega, Florian Rossmannek +1
Stability is often assumed in learning and identification, yet it is rarely characterized directly from input--output data. We show that an input--output family admits a stable fin…
On the equivalence between functionally affine LPV state-space representations and LFT models
Mihály Petreczky, Ziad Alkhoury, Guillaume Mercère
We propose a transformation algorithm for a class of Linear Parameter-Varying (LPV) systems with functional affine dependence on parameters, where the system matrices depend affine…
Length independent generalization bounds for deep SSM architectures via Rademacher contraction and stability constraints
Dániel Rácz, Mihály Petreczky, Bálint Daróczy
Many state-of-the-art models trained on long-range sequences, for example S4, S5 or LRU, are made of sequential blocks combining State-Space Models (SSMs) with neural networks. In…
A finite-sample bound for identifying partially observed linear switched systems from a single trajectory
Daniel Racz, Mihaly Petreczky, Balint Daroczy
We derive a finite-sample probabilistic bound on the parameter estimation error of a system identification algorithm for Linear Switched Systems. The algorithm estimates Markov par…
Loewner functions for bilinear systems
Pauline Kergus, Ion Victor Gosea, Mihaly Petreczky
This work brings together the moment matching approach based on Loewner functions and the classical Loewner framework based on the Loewner pencil in the case of bilinear systems. N…
A four-bodies motorcycle dynamic model for observer design
Tychique Nzalalemba Kabwangala, Ziad Alkhoury, Jawwad Ahmed +3
Motivated by the need to predict dangerous scenarios, this article introduces a non-linear dynamic model for motorcycles consisting of four rigid bodies. Using Jourdain's principle…