• DocumentCode
    2286272
  • Title

    A hierarchical neural network-based approach to VIRGO noise identification

  • Author

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

  • Author_Institution
    Fac. di Sci. MM. FF. NN., Salerno Univ., Italy
  • Volume
    6
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    253
  • Abstract
    In this paper a hierarchical neural network-based approach is presented to identify the noise in the VIRGO experiment to detect gravitational waves by means of a laser interferometer
  • Keywords
    gravitational waves; light interferometers; neural nets; pattern classification; physics computing; signal processing; VIRGO noise; gravitational waves; hierarchical neural network; laser interferometer; signal processing; Adaptive signal detection; Computer networks; Instruments; Laser noise; Neural networks; Noise figure; Nonlinear dynamical systems; Signal processing; Signal to noise ratio; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
  • Conference_Location
    Como
  • ISSN
    1098-7576
  • Print_ISBN
    0-7695-0619-4
  • Type

    conf

  • DOI
    10.1109/IJCNN.2000.859405
  • Filename
    859405
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2286272