Publisher
Springer Science and Business Media LLC
Reference54 articles.
1. A. al-Qerem, F. Kharbat, S. Nashwan, S. Ashraf, K. Blaou, General model for best feature extraction of EEG using discrete wavelet transform wavelet family and differential evolution. Int. J. Distrib. Sens. Netw. 16, 1–21 (2020). https://doi.org/10.1177/1550147720911009
2. K. Alsharabi, Y.B. Salamah, A.M. Abdurraqeeb, M. Aljalal, F.A. Alturki, EEG signal processing for Alzheimer’s disorders using discrete wavelet transform and machine learning approaches. IEEE Access 10, 89781–89797 (2022). https://doi.org/10.1109/access.2022.3198988
3. J.J. Aucouturier, Sounds like teen spirit: Computational insights into the grounding of everyday musical terms, in Language, Evolution and the Brain, Book Chapter-2 (City University of Hong Kong Press, 2009), pp. 35–64
4. E. Benetos, S. Dixon, D. Giannoulis, H. Kirchhoff, A. Klapuri, Automatic music transcription: challenges and future directions. J. Intell. Inf. Syst. 41(3), 407–434 (2013). https://doi.org/10.1007/s10844-013-0258-3
5. J.J. Bosch, J. Janer, F. Fuhrmann, P. Herrera, A comparison of sound segregation techniques for predominant instrument recognition in musical audio signals, in Proceedings, International Society for Music Information Retrieval Conference (ISMIR 2012) (2012), pp. 559–564. https://doi.org/10.5281/zenodo.1416075