  The Laser Interferometer Space Antenna (LISA) is expected to detect
gravitational radiation from a large number of compact binary systems. We
present a method by which these signals can be identified and have their
parameters estimated. Our approach uses Bayesian inference, specifically the
application of a Markov chain Monte Carlo method. The simulation study that we
present here considers a large number of sinusoidal signals in noise, and our
method estimates the number of periodic signals present in the data, the
parameters for these signals and the noise level. The method is significantly
better than classical spectral techniques at performing these tasks and does
not use stopping criteria for estimating the number of signals present.
