Other
Scientific paper
Sep 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011head...12.0602p&link_type=abstract
American Astronomical Society, HEAD meeting #12, #6.02
Other
Scientific paper
Detection of periodicity and period estimation in non-uniformly sampled time series data is frequently a goal in Astronomical data analysis. There are various problems faced: Firstly, data is sampled non-uniformly which makes it difficult to use simple Fourier transform for performing spectral analysis. Secondly, there are large gaps in data which makes it difficult to interpolate the signal for re-sampling. Finally, in data sets with smaller time periods the non-uniformity in sampling and noise in data pose even greater problems because of the lesser number of samples per period.
In this talk we review existing methods and then we propose new approaches in determining periods. We first use correntropy (an alternative to autocorrelation) that encapsulates non-linear correlations using a spatio-temporal kernel to estimate accurately the time period of the data. The other uses periodic kernels in non-parametric Gaussian process. These new techniques are also used for identifying periodic signals.
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