Spectral Analysis of Stellar Light Curves by Means of Neural Networks

Details Spectral Analysis of Stellar Light Curves by Means of Neural Networks Spectral Analysis of Stellar Light Curves by Means of Neural Networks

1999-06-10

arxiv.org/abs/astro-ph/9906182v1

Astronomy and Astrophysics

Astrophysics

35 pages, aa.cls macro file, to appear in A&AS, Vol. 137, June 1999

Scientific paper

10.1051/aas:1999254

Periodicity analysis of unevenly collected data is a relevant issue in several scientific fields. In astrophysics, for example, we have to find the fundamental period of light or radial velocity curves which are unevenly sampled observations of stars. Classical spectral analysis methods are unsatisfactory to solve the problem. In this paper we present a neural network based estimator system which performs well the frequency extraction in unevenly sampled signals. It uses an unsupervised Hebbian nonlinear neural algorithm to extract, from the interpolated signal, the principal components which, in turn, are used by the MUSIC frequency estimator algorithm to extract the frequencies. The neural network is tolerant to noise and works well also with few points in the sequence. We benchmark the system on synthetic and real signals with the Periodogram and with the Cramer-Rao lower bound.

Affiliated with

Also associated with

No associations

Rating

Spectral Analysis of Stellar Light Curves by Means of Neural Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Spectral Analysis of Stellar Light Curves by Means of Neural Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Spectral Analysis of Stellar Light Curves by Means of Neural Networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-199164