Title :
Online Morse code automatic recognition with neural network system
Author :
Luo, Ching-Hsing ; Fuh, Duu-Tong
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
In this paper proposed a new mixture of expert algorithm to improve the recognition rate of online Morse code automatic recognition system. From three person tests, the neural network has the average recognition rate up to 94.4%. The mixture of experts neural network has successfully overcome the difficulty of analyzing severely unstable Morse code time series.
Keywords :
codes; neural nets; signal processing; time series; mixture of experts neural network; neural network system; online Morse code automatic recognition; recognition rate improvement; severely unstable Morse code time series analysis; three person tests; tone series; Code standards; Computer networks; Neural networks; Pattern recognition; Prediction algorithms; Signal processing; Signal processing algorithms; Switches; Testing; Time series analysis;
Conference_Titel :
Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
Print_ISBN :
0-7803-7211-5
DOI :
10.1109/IEMBS.2001.1019028
