Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields
In this paper, we consider the problem of predicting a large scale spatial field using successive noisy measurements obtained by mobile sensing agents. The physical spatial field of interest is discretized and modeled by a Gaussian Markov random field (GMRF) with uncertain hyperparameters. From a Ba...
| Main Authors: | Xu, Y., Choi, J., Dass, S., Maiti, T. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.32959 / |
| Published: |
2013
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887966966&doi=10.1016%2fj.automatica.2013.09.008&partnerID=40&md5=0759fe9c10f9c894698afc0e8fb83cb4 http://eprints.utp.edu.my/32959/ |
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