System Identification Using Regular and Quantized Observations: Applications of Large Deviations Principles (SpringerBriefs in Mathematics)

by Qi He, Le Yi Wang, and George Yin

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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.
  • ISBN10 1461462924
  • ISBN13 9781461462927
  • Publish Date 7 July 2014
  • Publish Status Active
  • Publish Country US
  • Imprint Not Avail
  • Format eBook
  • Pages 99
  • Language English