2 September 1993 Neural nets for radio Morse code recognizing
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Abstract
This paper proposes a neural network recognition system for hand keying Radio Morse codes. The system has been trained and tested on real world data recorded from amateur radio Morse codes. The overall recognizing process can be partitioned into 3 major parts, the preprocessing, the feature extracting, and the character decoding. The whole operation is able to be performed in real-time on a PC/486 system. Self-Organizing Maps are used intensively in the recognition system to adaptively learn the variation of the Morse code signal. The average performance of the recognition system has been achieved about 96.4% with a rejection rate of 6.5%. It is hoped that many of the techniques would be applicable to a wide range of DSP and recognition tasks.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hsin-Chia Fu, Y. Y. Lin, Hsiao-Tien Pao, "Neural nets for radio Morse code recognizing", Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); doi: 10.1117/12.152533; https://doi.org/10.1117/12.152533
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