Learning of Linear Dynamical Systems as a Noncommutative Polynomial Optimization Problem

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00375698" target="_blank" >RIV/68407700:21230/24:00375698 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/TAC.2023.3313351" target="_blank" >https://doi.org/10.1109/TAC.2023.3313351</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TAC.2023.3313351" target="_blank" >10.1109/TAC.2023.3313351</a>

Result language
angličtina
Original language name
Learning of Linear Dynamical Systems as a Noncommutative Polynomial Optimization Problem
Original language description
There has been much recent progress in time series forecasting and estimation of system matrices of linear dynamical systems. We present an approach to both problems based on an asymptotically convergent hierarchy of convexifications of a certain nonconvex operator-valued problem, which is known as noncommutative polynomial optimization problem. We present promising computational results, including a comparison with methods implemented in MATLAB System Identification Toolbox.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/GA23-07947S" target="_blank" >GA23-07947S: Learning Models of Quantum Systems as a Non-Commutative Polynomial Optimization Problem</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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