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Neural network prediction of HF ionospheric propagation loss

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2 Author(s)
Chu, A.M. ; Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada ; Conn, D.R.

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

Published in:

Electronics Letters  (Volume:35 ,  Issue: 20 )