NDLI: Sequential detection with limited memory

Content Provider	IEEE Xplore Digital Library
Author	Ertin, E. Potter, L.C.
Copyright Year	2003
Description	Author affiliation: Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA (Ertin, E.; Potter, L.C.)
Abstract	Sequential tests outperform fixed sample size tests by requiring fewer samples on average to achieve the same level of error performance. The sequential probability ratio test (SPRT) has been suggested by Wald (1947) for sequential binary hypothesis testing problems. SPRT recursively calculates the likelihood of an observed data stream and requires this likelihood to be stored in memory between samples. In this paper we study the design of sequential detection tests under memory constraints. We derive the optimal sequential test in the case where only a quantized version of the likelihood can be stored in memory. An application of the proposed techniques is large scale sensor networks where price and communication constraints dictate limited complexity devices, which store and transmit concise representations of the state of nature.
Sponsorship	IEEE Signal Processing Soc
Starting Page	585
Ending Page	588
File Size	243712
Page Count	4
File Format	PDF
ISBN	0780379977
DOI	10.1109/SSP.2003.1289542
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-09-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sequential analysis Memory management Detectors System testing Cost function Automata Quantization Statistical analysis Probability Large-scale systems
Content Type	Text
Resource Type	Article

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