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We present data analysis methods used in detection and the estimation ofparameters of gravitational wave signals from the white dwarf binaries in themock LISA data challenge. Our main focus is on the analysis of challenge 3.1,where the gravitational wave signals from more than 50 mln. Galactic binarieswere added to the simulated Gaussian instrumental noise. Majority of thesignals at low frequencies are not resolved individually. The confusion betweenthe signals is strongly reduced at frequencies above 5 mHz. Our basic dataanalysis procedure is the maximum likelihood detection method. We filter thedata through the template bank at the first step of the search, then we refineparameters using the Nelder-Mead algorithm, we remove the strongest signalfound and we repeat the procedure. We detect reliably and estimate parametersaccurately of more than ten thousand signals from white dwarf binaries.

Mock LISA data challenge for the galactic white dwarf binaries