NDLI: A Repeated Significance Test With Applications To Sequential Detection In Sensor Networks

Content Provider	IEEE Xplore Digital Library
Author	Guerriero, M. Pozdnyakov, V. Glaz, J. Willett, P.
Copyright Year	1991
Abstract	In this paper we introduce a randomly truncated sequential hypothesis test. Using the framework of a repeated significance test (RST), we study a sequential test with truncation time based on a random stopping time. Using the functional central limit theorem (FCLT) for a sequence of statistics, we derive a general result that can be employed in developing a repeated significance test with random sample size. We present effective methods for evaluating accurate approximations for the probability of type I error and the power function. Numerical results are presented to evaluate the accuracy of these approximations. We apply the proposed test to a decentralized sequential detection problem in sensor networks (SNs) with communication constraints. Finally, a sequential detection problem with measurements at random times is investigated.
Sponsorship	IEEE Signal Processing Society
Starting Page	3426
Ending Page	3435
Page Count	10
File Size	660264
File Format	PDF
ISSN	1053587X
Volume Number	58
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sequential analysis Statistical analysis Tin Glazes Radar detection Sonar detection Bandwidth Costs Testing Probability truncated sequential test Decentralized detection repeated significance test sensor networks SPRT
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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