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Rehman, N. U., Naveed, K., Ehsan, S. & McDonald-Maier, K. (2016). Multi-scale image denoising based on goodness of fit (GOF) tests. I 2016 24th European Signal Processing Conference (EUSIPCO) IEEE. https://doi.org/10.1109/eusipco.2016.7760508
Abdullah, S. M. U., Rehman, N. U., Khan, M. M. & Mandic, D. P. (2015). A Multivariate Empirical Mode DecompositionBased Approach to Pansharpening. IEEE Transactions on Geoscience and Remote Sensing, 53(7), 3974-3984. https://doi.org/10.1109/tgrs.2015.2388497
Hemakom, A., Ahrabian, A., Looney, D., Rehman, N. U. & Mandic, D. P. (2015). Nonuniformly sampled trivariate empirical mode decomposition. I 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) IEEE. https://doi.org/10.1109/icassp.2015.7178660
Rehman, N., Ehsan, S., Naveed, K., McDonald-Maier, K. D. & Safdar, M. W. (2015). Dynamically sampled multivariate empirical mode decomposition. Electronics Letters, 51(24), 2049-2051. https://doi.org/10.1049/el.2015.1176
ur Rehman, N., Ehsan, S., Abdullah, S. M. U., Akhtar, M. J., Mandic, D. P. & McDonald-Maier, K. D. (2015). Multi-Scale pixel-based image fusion using multivariate empirical mode decomposition. Sensors (Switzerland), 15(5), 10923-10947. https://doi.org/10.3390/s150510923
Rehman, N. U. & Mandic, D. P. (2014). Dynamically-Sampled Bivariate Empirical Mode Decomposition. IEEE Signal Processing Letters, 21(7), 857-861. https://doi.org/10.1109/lsp.2014.2317773
Rehman, N., Khan, M. M., Sohaib, M. I., Jehanzaib, M., Ehsan, S. & McDonald-Maier, K. (2014). Image fusion using multivariate and multidimensional EMD. I 2014 IEEE International Conference on Image Processing (ICIP) IEEE. https://doi.org/10.1109/icip.2014.7026035
Park, C., Looney, D., Rehman, N. U., Ahrabian, A. & Mandic, D. P. (2013). Classification of Motor Imagery BCI Using Multivariate Empirical Mode Decomposition. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 21(1), 10-22. https://doi.org/10.1109/tnsre.2012.2229296
Rehman, N. U., Park, C., Huang, N. E. & Mandic, D. P. (2013). Emd via memd: Multivariate noise-aided computation of standard emd. Advances in Adaptive Data Analysis, 05(02), 1350007. https://doi.org/10.1142/s1793536913500076
Ahmed, M. U., Rehman, N., Looney, D., Rutkowski, T. M., Kidmose, P. & Mandic, D. P. (2012). Multivariate entropy analysis with data-driven scales. I 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (s. 3901-3904). IEEE. https://doi.org/10.1109/icassp.2012.6288770, https://doi.org/10.1109/ICASSP.2012.6288770
Li, L., Looney, D., Park, C., Rehman, N. U. & Mandic, D. P. (2011). Power independent EMG based gesture recognition for robotics. I 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE. https://doi.org/10.1109/iembs.2011.6090036
Rehman, N. U. & Mandic, D. P. (2011). Filter Bank Property of Multivariate Empirical Mode Decomposition. IEEE Transactions on Signal Processing, 59(5), 2421-2426. https://doi.org/10.1109/tsp.2011.2106779
Rehman, N. U., Xia, Y. & Mandic, D. P. (2010). Application of multivariate empirical mode decomposition for seizure detection in EEG signals. I 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology IEEE. https://doi.org/10.1109/iembs.2010.5626665
Rehman, N. U. & Mandic, D. P. (2010). Quadrivariate Empirical Mode Decomposition. I The 2010 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/ijcnn.2010.5596768
Looney, D., Rehman, N. U., Mandic, D., Rutkowski, T. M., Heidenreich, A. & Beyer, D. (2009). Conditioning multimodal information for smart environments. I 2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) IEEE. https://doi.org/10.1109/icdsc.2009.5289373
Rehman, N., Looney, D., Rutkowski, T. M. & Mandic, D. P. (2009). Bivariate EMD-based image fusion. I 2009 IEEE/SP 15th Workshop on Statistical Signal Processing IEEE. https://doi.org/10.1109/ssp.2009.5278639
Rehman, N. U. & Mandic, D. P. (2009). Qualitative analysis of rotational modes within three dimensional empirical mode decomposition. I 2009 IEEE International Conference on Acoustics, Speech and Signal Processing IEEE. https://doi.org/10.1109/icassp.2009.4960367