System Identification Using Regular and Quantized Observations
Applications of Large Deviations Principles
Seiten
2013
Springer-Verlag New York Inc.
978-1-4614-6291-0 (ISBN)
Springer-Verlag New York Inc.
978-1-4614-6291-0 (ISBN)
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By considering both space complexity in terms of signal quantization and time complexity with respect to data window sizes, this study provides a perspective to understand the fundamental relationship between probabilistic errors and resources, which may represent data sizes in computer usage, and computational complexity in algorithms.
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.
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.
Introduction and Overview.- System Identification: Formulation.- Large Deviations: An Introduction.- LDP under I.I.D. Noises.- LDP under Mixing Noises.- Applications to Battery Diagnosis.- Applications to Medical Signal Processing.-Applications to Electric Machines.- Remarks and Conclusion.- References.- Index
| Erscheint lt. Verlag | 8.2.2013 |
|---|---|
| Reihe/Serie | SpringerBriefs in Mathematics |
| Zusatzinfo | 16 Illustrations, color; 1 Illustrations, black and white; XII, 95 p. 17 illus., 16 illus. in color. |
| Verlagsort | New York, NY |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
| Mathematik / Informatik ► Mathematik | |
| Technik ► Elektrotechnik / Energietechnik | |
| Schlagworte | binary observation • error estimate • large deviations • Parameter Estimation • quantized observation • System Identification |
| ISBN-10 | 1-4614-6291-6 / 1461462916 |
| ISBN-13 | 978-1-4614-6291-0 / 9781461462910 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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