Distributed estimation and quantization

An algorithm is developed for the design of a nonlinear, n-sensor, distributed estimation system subject to communication and computation constraints. The algorithm uses only bivariate probability distributions and yields locally optimal estimators that satisfy the required system constraints. It is...

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Bibliographic Details
Published inIEEE transactions on information theory Vol. 39; no. 4; pp. 1456 - 1459
Main Author Gubner, J.A.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.07.1993
Institute of Electrical and Electronics Engineers
Subjects
Algorithm design and analysis
Applied sciences
Communication channels
Detection, estimation, filtering, equalization, prediction
Drives
Exact sciences and technology
Feedback
Force sensors
Information theory
Information, signal and communications theory
Probability distribution
Quantization
Sensor fusion
Sensor systems
Signal and communications theory
Signal, noise
Telecommunications and information theory
Quantization
Non linear estimation
Probability law
Algorithm
Signal estimation
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ISSN0018-9448
DOI10.1109/18.243470

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Summary:An algorithm is developed for the design of a nonlinear, n-sensor, distributed estimation system subject to communication and computation constraints. The algorithm uses only bivariate probability distributions and yields locally optimal estimators that satisfy the required system constraints. It is shown that the algorithm is a generalization of the classical Lloyd-Max results.< >
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:0018-9448
DOI:10.1109/18.243470