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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: He, Qi (Συγγραφέας), Wang, Le Yi (Συγγραφέας), Yin, G. George (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2013.
Σειρά:SpringerBriefs in Mathematics,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a He, Qi.  |e author. 
245 1 0 |a System Identification Using Regular and Quantized Observations  |h [electronic resource] :  |b Applications of Large Deviations Principles /  |c by Qi He, Le Yi Wang, G. George Yin. 
264 1 |a New York, NY :  |b Springer New York :  |b Imprint: Springer,  |c 2013. 
300 |a XII, 95 p. 17 illus., 16 illus. in color.  |b online resource. 
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490 1 |a SpringerBriefs in Mathematics,  |x 2191-8198 
505 0 |a 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. 
520 |a 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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650 0 |a System theory. 
650 0 |a Probabilities. 
650 0 |a Control engineering. 
650 1 4 |a Mathematics. 
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650 2 4 |a Control. 
650 2 4 |a Probability Theory and Stochastic Processes. 
700 1 |a Wang, Le Yi.  |e author. 
700 1 |a Yin, G. George.  |e author. 
710 2 |a SpringerLink (Online service) 
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