A finite-sample bound for identifying partially observed linear switched systems from a single trajectory
Fuente:
arXiv
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866913840643440640 |
|---|---|
| author | Racz, Daniel Petreczky, Mihaly Daroczy, Balint |
| author_facet | Racz, Daniel Petreczky, Mihaly Daroczy, Balint |
| contents | 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 parameters from a single trajectory and applies a variant of the Ho-Kalman algorithm to recover the system matrices. Our bound guarantees statistical consistency under the assumption that the true system exhibits quadratic stability. The proof leverages the theory of weakly dependent processes. To the best of our knowledge, this is the first finite-sample bound for this algorithm in the single-trajectory setting. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_13766 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A finite-sample bound for identifying partially observed linear switched systems from a single trajectory Racz, Daniel Petreczky, Mihaly Daroczy, Balint Machine Learning Systems and Control 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 parameters from a single trajectory and applies a variant of the Ho-Kalman algorithm to recover the system matrices. Our bound guarantees statistical consistency under the assumption that the true system exhibits quadratic stability. The proof leverages the theory of weakly dependent processes. To the best of our knowledge, this is the first finite-sample bound for this algorithm in the single-trajectory setting. |
| title | A finite-sample bound for identifying partially observed linear switched systems from a single trajectory |
| topic | Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2503.13766 |