Distributed maximum likelihood estimation for sensor networks
Blatt, D.; Hero, A.
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP apos;04). IEEE International Conference on
Volume 3, Issue , 17-21 May 2004 Page(s): iii - 929-32 vol.3
Digital Object Identifier   10.1109/ICASSP.2004.1326698
Summary: The problem of finding the maximum likelihood estimator of a commonly observed model, based on data collected by a sensor network under power and bandwidth constraints, is considered. In particular, a case where the sensors cannot fully share their data is treated. An iterative algorithm that relaxes the requirement of sharing all the data is given. The algorithm is based on a local Fisher scoring method and an iterative information sharing procedure. The case where the sensors share sub-optimal estimates is also analyzed. The asymptotic distribution of the estimates is derived and used to provide a means of discrimination between estimates that are associated with different local maxima of the log-likelihood function. The results are validated by a simulation.

» View citation and abstract

Log in by entering your IEEE Web Account Username and Password.

IEEE Communications Society members: If you subscribe to the IEEE Electronic Periodicals Package or IEEE Electronic Periodicals Package Plus, you must access your subscription at www.comsoc.org.

Check with your librarian, information professional, or system manager to determine if you need to log in. Please complete the online Technical Support Form if you need assistance.

Select the Purchase History link to access the document. You will have 5 Days after purchase to access the Full Text PDF. Please complete the online Technical Support Form if you need assistance.

• Search and access Abstract records free of charge
• Register for table of contents alerts
• Purchase Full Text PDF documents

» Learn more about subscription options or how to become an IEEE Member.