System Identification Using Regular and Quantized Observations (häftad)
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
95
Utgivningsdatum
2013-02-08
Upplaga
2013 ed.
Förlag
Springer-Verlag New York Inc.
Medarbetare
Wang, Le Yi / Yin, George G.
Illustrationer
16 Illustrations, color; 1 Illustrations, black and white; XII, 95 p. 17 illus., 16 illus. in color.
Dimensioner
234 x 158 x 6 mm
Vikt
158 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9781461462910
System Identification Using Regular and Quantized Observations (häftad)

System Identification Using Regular and Quantized Observations

Applications of Large Deviations Principles

Häftad Engelska, 2013-02-08
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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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Innehållsförteckning

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