  We present the application of a new method to compute the Wiener filter
solution of large and complex data sets. Contrary to the iterative solvers
usually employed in signal processing, our algorithm does not require the use
of preconditioners to be computationally efficient. The new scheme is
conceptually very simple and therefore easy to implement, numerically
absolutely stable, and guaranteed to converge. We introduce a messenger field
to mediate between the different preferred bases in which signal and noise
properties can be specified most conveniently, and rephrase the signal
reconstruction problem in terms of this auxiliary variable. We demonstrate the
capabilities of the algorithm by applying it to cosmic microwave background
(CMB) radiation data obtained by the WMAP satellite.
