Articles liés à System Identification Using Regular and Quantized Observatio...

System Identification Using Regular and Quantized Observations: Applications of Large Deviations Principles - Couverture souple

Livre 17 sur 155: SpringerBriefs in Mathematics

He, Qi; Wang, Le Yi; Yin, George G.

 
9781461462910: System Identification Using Regular and Quantized Observations: Applications of Large Deviations Principles

Synopsis

​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 perspective to understand the fundamental relationship between probabilistic errors and resources, which may represent data sizes in computer usage, computational complexity in algorithms, sample sizes in statistical analysis and channel bandwidths in communications.

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Présentation de l'éditeur

'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 perspective to understand the fundamental relationship between probabilistic errors and resources, which may represent data sizes in computer usage, computational complexity in algorithms, sample sizes in statistical analysis and channel bandwidths in communications.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.