PERTANIKA JOURNAL OF TROPICAL AGRICULTURAL SCIENCE

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• Abrard, F., & Deville, Y. (2005). A time–frequency blind signal separation method applicable to underdetermined mixtures of dependent sources. Signal Processing, 85(7), 1389-1403. https://doi.org/10.1016/j.sigpro.2005.02.010

• Hassan, N., & Ramli, D. A. (2018). A Comparative study of blind source separation for bioacoustics sounds based on FastICA, PCA and NMF. Procedia Computer Science, 126, 363-372. https://doi.org/10.1016/j.procS.2018.07.270

• Huang, C. J., Yang, Y. J., Yang, D. X., & Chen, Y. J. (2009). Frog classification using machine learning techniques. Expert Systems with Applications, 36(2), 3737-3743. https://doi.org/10.1016/j.eswa.2008.02.059

• Hyvarinen, A. (2012). Independent component analysis: Recent advances. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371(1984), 20110534-20110534. https://doi.org/10.1098/rsta.2011.0534

• Jourjine, A., Rickard, S., & Yilmaz, O. (2000, June 5-9). Blind separation of disjoint orthogonal signals Demixing n sources from 2 mixtures. [Paper presentation]. 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No. 00CH37100), Istanbul, Turkey. https://doi.org/10.1109/ICASSP.2000.861162

• Li, Y., Cichocki, A., & Amari, S. I. (2003, April 1-4). Sparse component analysis for blind source separation with less sensors than sources. [Paper presentation]. 4th Internation Symposium on Independent Component Analysis and Blind Signal Separation (ECA2003), Nara, Japan.

• Li, Y., Nie, W., Ye, F., & Lin, Y. (2016). A mixing matrix estimation algorithm for underdetermined blind source separation. Circuits, Systems, and Signal Processing, 35(9), 3367-3379. https://doi.org/10.1007/s00034-015-0198-y

• Linh-Trung, N., El Bey, A. A., Abed-Meraim, K., & Belouchrani, A. (2005, August 28-31). Underdetermined blind source separation of non-disjoint nonstationary sources in the time-frequency domain. [Paper presentation]. 8th International Symposium on Signal Processing and its Applications, (ISSPA), Sydney, Australia. https://doi.org/10.1109/ISSPA.2005.1580192

• Lu, J., Cheng, W., He, D., & Zi, Y. (2019). A novel underdetermined blind source separation method with noise and unknown source number. Journal of Sound and Vibration, 457, 67-91. https://doi.org/10.1016/j.jsv.2019.05.037

• Miao, F., Zhao, R., Jia, L., & Wang, X. (2021). Multisource fault signal separation of rotating machinery based on wavelet packet and fast independent component analysis. International Journal of Rotating Machinery, 2021, Article 9914724. https://doi.org/10.1155/2021/9914724

• Reju, V. G., Koh, S. N., & Soon, I. Y. (2009). An algorithm for mixing matrix estimation in instantaneous blind source separation. Signal Processing, 89(9), 1762-1773. https://doi.org/10.1016/j.sigpro.2009.03.017

• Sadhu, A., Hazra, B., Narasimhan, S., & Pandey, M. D. (2011). Decentralized modal identification using sparse blind source separation. Smart Materials and Structures, 20(12), Article 125009. https://doi.org/10.1088/0964-1726/20/12/125009

• Santamaria, I. (2013). Handbook of blind source separation: Independent component analysis and applications (Common, P. and Jutten, ; 2010 [Book Review]. IEEE Signal Processing Magazine, 30(2), 133-134. https://doi.org/10.1109/msp.2012.2230552

• Stevenson, B. C., Borchers, D. L., Altwegg, R., Swift, R. J., Gillespie, D. M., & Measey, G. J. (2015). A general framework for animal density estimation from acoustic detections across a fixed microphone array. Methods in Ecology and Evolution, 6(1), 38-48. https://doi.org/10.1111/2041-210X.12291

• Su, Q., Shen, Y., Wei, Y., & Deng, C. (2017). Underdetermined blind source separation by a novel time-frequency method. AEU - International Journal of Electronics and Communications, 77, 43-49. https://doi.org/10.1016/j.aeue.2017.04.025

• Vincent, E., Gribonval, R., & Févotte, C. (2006). Performance measurement in blind audio source separation. IEEE Transactions on Audio, Speech and Language Processing, 14(4), 1462-1469. https://doi.org/10.1109/TSA.2005.858005

• Winter, S., Sawada, H., & Makino, S. (2006). Geometrical interpretation of the PCA subspace approach for overdetermined blind source separation. Eurasip Journal on Applied Signal Processing, 2006, 1-11. https://doi.org/10.1155/ASP/2006/71632

• Zhen, L., Peng, D., Yi, Z., Xiang, Y., & Chen, P. (2017). Underdetermined blind source separation using sparse coding. IEEE Transactions on Neural Networks and Learning Systems, 28(12), 3102-3108. https://doi.org/10.1109/TNNLS.2016.2610960