  We propose a method for filling arbitrarily wide gaps in deterministic time
series. Crucial to the method is the ability to apply Takens' theorem in order
to reconstruct the dynamics underlying the time series. We introduce a
functional to evaluate how compatible is a filling sequence of data with the
reconstructed dynamics. An algorithm for minimizing the functional with a
reasonable computational effort is then discussed.
