Article Versions Notes

Njirjak M, Otović E, Jozinović D, Lerga J, Mauša G, Michelini A, Štajduhar I. The Choice of Time–Frequency Representations of Non-Stationary Signals Affects Machine Learning Model Accuracy: A Case Study on Earthquake Detection from LEN-DB Data. Mathematics. 2022; 10(6):965. https://doi.org/10.3390/math10060965

Njirjak, Marko, Erik Otović, Dario Jozinović, Jonatan Lerga, Goran Mauša, Alberto Michelini, and Ivan Štajduhar. 2022. "The Choice of Time–Frequency Representations of Non-Stationary Signals Affects Machine Learning Model Accuracy: A Case Study on Earthquake Detection from LEN-DB Data" Mathematics 10, no. 6: 965. https://doi.org/10.3390/math10060965

Njirjak, M., Otović, E., Jozinović, D., Lerga, J., Mauša, G., Michelini, A., & Štajduhar, I. (2022). The Choice of Time–Frequency Representations of Non-Stationary Signals Affects Machine Learning Model Accuracy: A Case Study on Earthquake Detection from LEN-DB Data. Mathematics, 10(6), 965. https://doi.org/10.3390/math10060965