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System Identification Using Regular and Quantized Observations

Applications of Large Deviations Principles

Produktform: E-Buch Text Elektronisches Buch in proprietärem

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.weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Elektronisches Format: PDF

Sprache(n): Englisch

ISBN: 978-1-4614-6292-7 / 978-1461462927 / 9781461462927

Verlag: Springer US

Erscheinungsdatum: 11.02.2013

Seiten: 95

Autor(en): Le Yi Wang, Qi He, George G. Yin

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