  We undertake a preliminary numerical investigation to understand how the
addition of white and colored noise to a time series affects the topology and
structure of the underlying chaotic attractor. We use the methods and measures
of recurrence networks generated from the time series for this analysis. We
explicitly show that the addition of noise destroys the recurrence of
trajectory points in the phase space. By using the results obtained from this
analysis, we go on to analyse the light curves from a dominant black hole
system and show that the recurrence network measures are effective in the
analysis of real world data involving noise and are capable of identifying the
nature of noise contamination in a time series.
