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System Identification Using Regular and Quantized Observations

Qi He · 2013

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About the book

​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 details

Year
2013
Language
English
Series
SpringerBriefs in Mathematics
Publisher
Springer New York
Editions
4
Pages
95
ISBN
9781461462927

Data source: Wikidata

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