System identification using regular and quantized observations : applications of large deviations principles
This brief presents characterizations of identification errors under a probabilistic framework when output sensors are binary, quantized, or regular. By considering both space complexity in terms of signal quantization and time complexity with respect to data window sizes, this study provides a new...
Gardado en:
| Auteurs principaux: | , , |
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| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado: |
New York, NY :
Springer New York
2013.
Cham : Springer Nature |
| Series: | SpringerBriefs in Mathematics
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| Acceso en liña: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • System Identification Using Regular and Quantized Observations, Texte imprimé, 9781461462934 • System identification using regular and quantized observations, applications of large deviations principles, by Qi He, Le Yi Wang, G. George Yin., New York, NY, Springer, 2013, SpringerBriefs in Mathematics, 978-1-4614-6291-0 |