Distributed TLS estimation under random data faults
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessRestricted access - publisher's policy
This paper addresses the problem of distributed estimation of a parameter vector in the presence of noisy input and noisy output data, as well as data faults, performed by a wireless sensor network in which only local interactions among the nodes are allowed. In the presence of unreliable observations, standard estimators become biased and perform poorly in low signal-to-noise ratios. We propose therefore two different distributed approaches based on the Expectation-Maximization algorithm: in the first one the regressors are estimated at each iteration, whereas the second one does not require explicit regressor estimation. Numerical results show that the proposed methods approach the performance of a clairvoyant scheme with knowledge of the random data faults.
CitationSilva, S., Pages, A., López, R. Distributed TLS estimation under random data faults. A: IEEE International Conference on Acoustics, Speech, and Signal Processing. "2015 IEEE International Conference on Acoustics, Speech, and Signal Processing: proceedings: April 19–24, 2014: Brisbane Convention & Exhibition Centre Brisbane, Queensland, Australia". Brisbane: Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 2949-2953.