@conference {684, title = {A Diffusion-based distributed EM algorithm for density estimation in wireless sensor networks}, booktitle = {Int. Conf. Acoust., Speech, Signal Process. (ICASSP)}, year = {2013}, abstract = {
Distributed implementations of the Expectation-Maximization
(EM) algorithm reported in the literature have been proposed for
applications to solve specific problems. In general, a primary
requirement to derive a distributed solution is that the
structure of the centralized version enables the computation
involving global information in a distributed fashion. This
paper treats the problem of distributed estimation of Gaussian
densities by means of the EM algorithm in wireless sensor
networks using diffusion strategies, where the information
is gradually diffused across the network for the computation
of the global functions. The low-complexity implementation
presented here is based on a two time scale operation
for information averaging and diffusion. The convergence to
a fixed point of the centralized solution has been studied and
the appealing results motivates our choice for this model. Numerical
examples provided show that the performance of the
distributed EM is, in practice, equal to that of the centralized
scheme.
}, keywords = {dynacs, wsn}, doi = {10.1109/ICASSP.2013.6638501}, author = {Silvana Silva Pereira and Alba Pag{\`e}s-Zamora and R. L{\'o}pez-Valcarce} }