A neural network based identification system for VIRGO seismic noise

Author

Acernese, F. ; Barone, F. ; De Rosa, R. ; Eleuteri, A. ; Milano, L. ; Tagliaferri, R.

Author_Institution

Dipartimento di Sci. Fisiche, Naples Univ., Italy

Volume

1

fYear

2001

fDate

2001

Firstpage

252

Abstract

A neural network based approach is presented for the real time seismic noise identification of a GW laser interferometric antenna. The procedure allows the estimation of seismic events in a background noise. The recognition of such events is very important for the data quality of the interferometer output. The algorithm the authors propose is quite general and robust, taking into account that it does not require a-priori information on the data, nor precise model, and constitutes a powerful tool for quality data analysis

Keywords

astronomical instruments; astronomy computing; data analysis; gravitational wave detectors; light interferometers; neural nets; VIRGO; algorithm; astronomical instrument; astronomy; data analysis; gravitational radiation; gravitational wave detector; identification system; laser interferometric antenna; laser interferometry; light interferometer; measurement technique; neural net; neural network; real time; seismic event; seismic noise; Acceleration; Accelerometers; Background noise; Extraterrestrial measurements; Instruments; Laser noise; Mirrors; Neural networks; Optical interferometry; Optical sensors;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-7044-9

Type

conf

DOI

10.1109/IJCNN.2001.939026

Filename

939026