DocumentCode
1282505
Title
Neural network prediction of HF ionospheric propagation loss
Author
Chu, A.M. ; Conn, D.R.
Author_Institution
Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada
Volume
35
Issue
20
fYear
1999
fDate
9/30/1999 12:00:00 AM
Firstpage
1774
Lastpage
1776
Abstract
A generalised regression neural network is used to predict losses inherent in ionospheric radiowave propagation. Network inputs consist of sun declination, time of day, radio flux, geomagnetic A-index and X-ray flux. Simulations for a 400 km path demonstrate a 2.5 dB error between network predictions and actual measured values, representing a 46% reduction in errors compared to the linear regression method
Keywords
HF radio propagation; ionospheric electromagnetic wave propagation; losses; neural nets; telecommunication computing; 400 km; HF ionospheric propagation loss; X-ray flux; generalised regression neural network; geomagnetic A-index; ionospheric radiowave propagation; neural network prediction; radio flux; sun declination; time of day;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19991206
Filename
811179
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