The problem of multiple change point estimation is considered for sequences with
unknown number of change points. A consistency framework is suggested that
is suitable for highly dependent time-series, and an asymptotically consistent algorithm is proposed. In order for the consistency to be established the only assumption required is that the data is generated by stationary ergodic time-series
distributions. No modeling, independence or parametric assumptions are made;
the data are allowed to be dependent and the dependence can be of arbitrary form.
The theoretical results are complemented with experimental evaluations.