SpringerBriefs in Mathematics: Applications of Large Deviations Principles

He, Qi; Wang, Le Yi; Yin, George G.

​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.

Details

Published by: Springer

Publication Date: 2013-02-08

Format: Paperback

ISBN-13: 9781461462910

DOI: 10.1007/978-1-4614-6292-7

Dimensions: 235cm x155cm

Pages: 95