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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Adaptive Detection in Distributed Networks Using Maximum Likelihood Detector

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Author(s):
Feitosa, Allan E. [1] ; Nascimento, Vitor H. [1] ; Lopes, Cassio G. [1]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Dept Elect Syst Engn, BR-05508010 Sao Paulo - Brazil
Total Affiliations: 1
Document type: Journal article
Source: IEEE SIGNAL PROCESSING LETTERS; v. 25, n. 7, p. 974-978, JUL 2018.
Web of Science Citations: 1
Abstract

This letter describes a maximum likelihood distributed detector algorithm with a special initialization that yields an exponential decay rate on error probabilities in transient, using the adaptive diffusion least mean squares (LMS) algorithm in a distributed sensor network. The nodes that compose the network must decide between two concurrent hypotheses concerning the environment where they are inserted, using local measurements and shared estimates coming from their neighbors. It is shown analytically and by simulations that the exponential performance does not depend on the LMS step size, provided it is sufficiently small. (AU)

FAPESP's process: 16/06529-1 - Structural health monitoring in airplanes via sensor networks: damage classification
Grantee:Allan Eduardo Feitosa
Support Opportunities: Scholarships in Brazil - Master