We present two synthetic datasets on classification of Morse code symbols for supervised machine learning problems, in particular, neural networks. The linked Github page has algorithms for generating a family of such datasets of varying difficulty. The datasets are spatially one-dimensional and have a small number of input features, leading to high density of input information content. This makes them particularly challenging when implementing network complexity reduction methods.

Dataset Files

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[1] Sourya Dey, "Morse Code Symbol Classification", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/wbhw-py68. Accessed: Feb. 04, 2023.
doi = {10.21227/wbhw-py68},
url = {http://dx.doi.org/10.21227/wbhw-py68},
author = {Sourya Dey },
publisher = {IEEE Dataport},
title = {Morse Code Symbol Classification},
year = {2019} }
T1 - Morse Code Symbol Classification
AU - Sourya Dey
PY - 2019
PB - IEEE Dataport
UR - 10.21227/wbhw-py68
ER -
Sourya Dey. (2019). Morse Code Symbol Classification. IEEE Dataport. http://dx.doi.org/10.21227/wbhw-py68
Sourya Dey, 2019. Morse Code Symbol Classification. Available at: http://dx.doi.org/10.21227/wbhw-py68.
Sourya Dey. (2019). "Morse Code Symbol Classification." Web.
1. Sourya Dey. Morse Code Symbol Classification [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/wbhw-py68
Sourya Dey. "Morse Code Symbol Classification." doi: 10.21227/wbhw-py68