@conference{10902/3444,
year = {2003},
month = {9},
url = {http://hdl.handle.net/10902/3444},
abstract = {This paper presents an efficient algorithm for computing
the maximum a posteriori (MAP) estimate of a Bernouilli-
Gaussian sequence distorted by a linear filter and corrupted by
noise. The computational effort for the MAP estimator increases
exponentially with the number of samples and is generally
unfeasible. The approach used by Kormylo and Mendel in their
pioneering work on the Single Most-Likely Replacement algorithm
(SMLR) has been the sub-optimal reference to evaluate the
efficiency of this new estimation method in computational effort
and detection probability. This algorithm reduces drastically
the SMLR computational load and allows real-time processing,
because only few samples of the observation data are required
by employing a windowing strategy. An extensive Monte Carlo
analysis, using synthetic data, has been performed to compare
the behaviour of the proposed estimators.},
publisher = {URSI 2003, XVIII Simposium Nacional de la Unión Científica Internacional de Radio, La Coruña},
title = {Estimador competitivo de bajo coste computacional para deconvolución dispersa},
author = {Vía Rodríguez, Javier and Pérez Blanco, David José and Santamaría Caballero, Luis Ignacio and Pantaleón Prieto, Carlos J.},
}