Premium
A neural network to identify stray signals in ionograms
Author(s) -
Koschmieder T. H.
Publication year - 1994
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1029/94rs01922
Subject(s) - ionosonde , ionogram , artificial neural network , computer science , high frequency , remote sensing , ionosphere , geology , artificial intelligence , physics , geophysics , electron density , plasma , quantum mechanics
A neural network will be used to identify stray signals in ionograms. The signals to be identified come from high‐frequency (HF, 2–30 MHz) transmitters that emit during the collection of the ionosonde data for the ionogram. Unfortunately, the ionosonde accepts the HF signals as valid and records them as data. The developed neural network correctly identifies 85% of the stray HF signals.