Neural nets for radio morse code recognizing

Hsin Chia Fu, Y. Y. Lin, Hsiao-Tien Pao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationAPPLICATIONS OF ARTIFICIAL NEURAL NETWORKS IV
PublisherSPIE-INT SOC OPTICAL ENGINEERING
Pages334-345
Number of pages12
Volume1965
ISBN (Print)0819412015
DOIs
StatePublished - 2 Sep 1993
EventApplications of Artificial Neural Networks IV 1993 - Orlando, United States
Duration: 11 Apr 199316 Apr 1993

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
PublisherSPIE
ISSN (Print)0277-786X

Conference

ConferenceApplications of Artificial Neural Networks IV 1993
CountryUnited States
CityOrlando
Period11/04/9316/04/93

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