Recurrent Neural Networks for Narrowband Signal Detection in the Time-Frequency Domain

Brodrick, David, Taylor, Douglas and Diederich, Joachim (2004). Recurrent Neural Networks for Narrowband Signal Detection in the Time-Frequency Domain. In: R. P. Norris and F. H. Stootman, Bioastronomy 2002 : life among the stars : proceedings of the 213th Symposium of the International Astronomical Union. 213th Symposium of the International Astronomical Union, Hamilton Island, Great Barrier Reef, Australia, (483-486). 8-12 July 2002.


Author Brodrick, David
Taylor, Douglas
Diederich, Joachim
Title of paper Recurrent Neural Networks for Narrowband Signal Detection in the Time-Frequency Domain
Conference name 213th Symposium of the International Astronomical Union
Conference location Hamilton Island, Great Barrier Reef, Australia
Conference dates 8-12 July 2002
Proceedings title Bioastronomy 2002 : life among the stars : proceedings of the 213th Symposium of the International Astronomical Union
Journal name Bioastronomy 2002: Life Among the Stars
Place of Publication San Francisco, Calif.
Publisher Astronomical Society of the Pacific for the IAU
Publication Year 2004
Sub-type Fully published paper
ISBN 9781583811719
1-58381-171-0
ISSN 0074-1809
Editor R. P. Norris
F. H. Stootman
Volume 213
Issue 213
Start page 483
End page 486
Total pages 4
Language eng
Abstract/Summary A recurrent neural network was trained to detect the time-frequency domain signature of narrowband radio signals against a background of astronomical noise. The objective was to investigate the use of recurrent networks for signal detection in the Search for Extra-Terrestrial Intelligence, though the problem is closely analogous to the detection of some classes of Radio Frequency Interference in radio astronomy.
Subjects 080108 Neural, Evolutionary and Fuzzy Computation
0201 Astronomical and Space Sciences
0801 Artificial Intelligence and Image Processing
Q-Index Code E1
Additional Notes IAU Symposia Series; 213

 
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