Empirical Mode Decomposition, Multivariate EMD, Multivariate Synchrosqueezing, Matlab code and data

See below for our recent contributions in this field.

Legend: MATLAB code, PDF files, Supplements and data.

You can also download some EEG Data used in some of the simulations in the work below. The EEG data contain EOG and EMG artifacts coming from eye blinks, eyebrow raising and eye rolling, and are used in our BSE, BSS, and EMD algorithms. The recordings also contain a 50Hz power line noise. Enjoy!

You can download below some key papers on multivariate EMD (complex, bivariate, trivariate, quaternion, multichannel) and noise assisted EMD. In the subsequent list there are some application papers.

Below is some of our work on multivariate extensions of EMD

  1. A. Ahrabian, D. Looney, L. Stankovic, and D. P. Mandic, "Synchrosqueezing-Based Time-Frequency Analysis of Multivariate Data," Signal Processing, vol. 106, pp. 331-341, 2015. [pdf] [MATLAB code]
  2. M. S. Koh, D. P. Mandic and A. G. Constantinides, "Theory of digital filterbanks realized via multivariate empirical mode decomposition," Advances in Adaptive Data Analysis, vol. 6, no. 1, pp. 1–31, 2014. [pdf]
  3. N. Rehman, C. Park, N. E. Huang, and D. P. Mandic, "Dynamically-sampled bivariate empirical mode decomposition," IEEE Signal Processing Letters, vol. 21, no. 7, pp. 857-861, 2014. [pdf]
  4. I. Mostafanezhad, E. Yavari, O. Boric-Lubecke, V. Lubecke, and D. P. Mandic, "Cancellation of unwanted Doppler radar sensor motion using empirical mode decomposition," IEEE Sensors Journal, vol. 13, no. 5, pp. 1897–1904, 2013. [pdf]
  5. D. P. Mandic, N. Rehman, Z. Wu, and N. E. Huang, "Empirical mode decomposition based time-frequency analysis of multivariate signals," IEEE Signal Processing Magazine, vol. 30, no. 6, pp. 74–86, 2013. [pdf]
  6. C. Park, D. Looney, N. Rehman, A. Ahrabian and D. P. Mandic, "Classification of motor imagery BCI using multivariate empirical mode decomposition," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 21, no. 1, pp. 10–22, 2013. [pdf]
  7. N. Rehman, C. Park, N. E. Huang, and D. P. Mandic, "EMD via MEMD: Multivariate noise-aided computation of standard EMD," Advances in Adaptive Data Analysis, vol. 5, no. 2, pp. 1–25, 2013. [pdf]
  8. A. Ahrabian, N. Rehman, and D. P. Mandic, "Bivariate Empirical Mode Decomposition for Unbalanced Real-World Signals," IEEE Signal Processing Letters, vol. 20, no. 3, pp. 245-248, 2013. [pdf]
  9. M. Leo, D. Looney, T. D’Orazio, and D. P. Mandic, "Identification of defective areas in composite materials by bivariate EMD analysis of ultrasound," IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 1, pp. 221-232, 2012. [pdf]
  10. T. Rutkowski, T. Tanaka, A. Cichocki, D. Erickson, J. Cao, and D. P. Mandic, "Interactive components extraction from fEEG and fNIRS for affective brain machine interfaces," Computers in Human Behavior (invited paper), vol. 27, pp. 1512-1518, 2011. [pdf]
  11. C. Park, D. Looney, P. Kidmose, M. Ungstrup, and D. P. Mandic, "Time-frequency analysis of EEG asymmetry using bivariate empirical mode decomposition,", IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 19, no. 4, pp. 366–373, 2011. [pdf]
  12. N. Rehman and D. P. Mandic, "Filter Bank Property of Multivariate Empirical Mode Decomposition," IEEE Transactions on Signal Processing, vol. 59, no. 5, pp. 2421-2426, 2011. [pdf] [MATLAB code]
  13. N. Rehman and D. P. Mandic, "Multivariate Empirical Mode Decomposition," Proceedings of the Royal Society A, vol. 466, no. 2117, pp. 1291-1302, 2010. [pdf] [MATLAB code] [Zipped content]
  14. N. Rehman and D. P. Mandic, "Empirical Mode Decomposition for Trivariate Signals," IEEE Transactions on Signal Processing, vol. 58, no. 3, pp. 1059-1068, 2010. [pdf]
  15. N. U. Rehman and D. P. Mandic, "Quadrivariate Empirical Mode Decomposition," in Proceedings of IJCNN'10, pp. 2265-2270, 2009. [pdf]
  16. D. Looney and D. P. Mandic, "Multi-Scale Image Fusion using Complex Extensions of EMD," IEEE Transactions on Signal Processing, vol. 57, no. 4, pp. 1626-1630, 2009. [pdf]
  17. T. Tanaka and D. P. Mandic, "Complex Empirical Mode Decomposition," IEEE Signal Processing Letters, vol. 14, no. 2, pp. 101-104, 2007. [pdf]
  18. M. U. Bin Altaf, T. Gautama, T. Tanaka, and D. P. Mandic, "Rotation Invariant Complex Empirical Mode Decomposition," Proceedings of ICASSP 2007, pp. 1009-1012, 2007. [pdf]
  19. C. Park, D. Looney, M M. Van Hulle and D. P. Mandic, "The Complex Local Mean Decomposition," Neurocopomuting, vol. 74, pp. 867–875, 2011. [pdf]
  20. N. U. Rehman and D. P. Mandic, "Qualitative Analysis of Rotational Modes within Three-Dimensional Empirical Mode Decomposition," in Proceedings of ICASSP 2009, pp. 3449-3452, 2009. [pdf]
  21. D. Looney and D. P. Mandic, "A Machine Learning Enhanced Empirical Mode Decomposition," in Proceedings of ICASSP'08, pp. 1897-1900, 2008. [pdf]
  22. M. Chen, P. Kidmose, M. Ungstrup, and D. P. Mandic, "Qualitative Assessment of Intrinsic Mode Functions of Empirical Mode Decomposition," in Proceedings of ICASSP'06, pp. 1905-1908, 2008. [pdf]
  23. Y. Washizawa, T. Tanaka, D. P. Mandic, and A. Cichocki, "A Flexible Method for Envelope Estimation in Empirical Mode Decomposition," in Proceedings of the 10th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems, KES-06, pp. 1248-1255, 2006. [pdf]

Below is some of our work on the applications of multivariate EMD, mostly in auditory and motor imagery Brain Computer Interface (BCI), Human Computer Interface (HCI) and detection of anomalies in composite materials

  1. M. Leo, D. Looney, T. D'Orazio, and D. P. Mandic, "Identification of Defective Areas in Composite Materials by Bivariate EMD Analysis of Ultrasound," IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 1, pp. 221-232, 2012. [pdf]
  2. C. Park, D. Looney, P. Kidmose, M. Ungstrup, and D. P. Mandic, "Time-Frequency Analysis of EEG Asymmetry Using Bivariate Empirical Mode Decomposition," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 19, no. 4, pp. 366–373, 2011. [pdf]
  3. T. Rutkowski, T. Tanaka, A. Cichocki, D. Erickson, and D. P.Mandic, "Interactive component extraction from fEEG, fNIRS and peripheral biosignals for affective brain–machine interfacing paradigms," Computers in Human Behaviour, vol. 27, pp. 1512-1518, 2011. [pdf]
  4. T. Rutkowski, A. Cichocki, D. P.Mandic, and T. Nishida, "Emotional empathy transition patterns from human brain responses in interactive communication situations," AI & Society, vol. 26, pp. 301-315, 2011. [pdf]
  5. T. Rutkowski, D. P. Mandic, A. Cichocki, and A. Przybyszewski, "EMD Approach to Multichannel EEG Data Analysis - The Amplitude and Phase Components Clustering," Journal of Circuits, Systems, and Computers, vol. 19, no. 1, pp. 215-229, 2010. [pdf]
  6. D. Looney, C. Park, Y. Xia, P. Kidmose, M. Ungstrup and D. P. Mandic, "Towards Estimating Selective Auditory Attention From EEG Using A Novel Time-Frequency-Synchronisation Framework," in Proceedings of IJCNN, 2010. [pdf]
  7. D. Looney, T. Rutkowski, A. Heidenreich, N. Rehman, and D. P. Mandic, "Conditioning Multimodal Information for Smart Environments," in Proc of the IEEE Smart Camera Workshop, 2009. [pdf]
  8. N. Rehman, D. Looney, and D. P. Mandic, "Bivariate EMD-Based Image Fusion," in Proc of the IEEE DSP Workshop, pp. 57-60, 2009. [pdf]
  9. T. Rutkowski, J. Dauwels, F. Vialatte, A. Cichocki, and D. P.Mandic, "Time-frequency and synchrony analysis of responses to steady-state auditory and musical stimuli from multichannel EEG," in Proceedings of NIPS'07, 2007. [pdf]