A neural network approach for the noise identification and data quality of the VIRGO antenna

Details A neural network approach for the noise identification and data quality of the VIRGO antenna A neural network approach for the noise identification and data quality of the VIRGO antenna

Jun 2000

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000aipc..523..465b&link_type=abstract

GRAVITATIONAL WAVES: Third Edoardo Amaldi Conference. AIP Conference Proceedings, Volume 523, pp. 465-466 (2000).

Mathematics

Logic

Gravitational Radiation Detectors, Mass Spectrometers, And Other Instrumentation And Techniques, Neural Networks, Fuzzy Logic, Artificial Intelligence

Scientific paper

We are exploring the possibility of using neural networks for noise identification and extraction in connection with the environment monitoring and within the global architecture of Data Quality. We report here the very promising results of a test of real-time acoustic noise identification and extraction for a bench test Michelson interferometer. .

Affiliated with

Also associated with

No associations

Rating

A neural network approach for the noise identification and data quality of the VIRGO antenna 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 A neural network approach for the noise identification and data quality of the VIRGO antenna, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A neural network approach for the noise identification and data quality of the VIRGO antenna will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1391049