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System Identification Using Regular and Quantized Observations

System Identification Using Regular and Quantized Observations Applications of Large Deviations Principles - SpringerBriefs in Mathematics

2013

Paperback (08 Feb 2013)

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Publisher's 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.

Book information

ISBN: 9781461462910
Publisher: Springer New York
Imprint: Springer
Pub date:
Edition: 2013
DEWEY: 003.1
DEWEY edition: 23
Language: English
Number of pages: 95
Weight: 177g
Height: 234mm
Width: 156mm
Spine width: 5mm