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access icon openaccess Discriminant feature level fusion based learning for automatic staging of EEG signals

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References

    1. 1)
    2. 2)
      • 2. Hazarika, A., Barthakur, M., Dutta, L., et al: ‘Two-fold feature extraction technique for biomedical signals classification’. IEEE Conf. on Inventive Computation Technologies, India, 2016.
    3. 3)
      • 3. Hazarika, A., Barthakur, M., Dutta, L., et al: ‘Fusion of projected feature for classification of EMG patterns’. IEEE Conf. on Recent Advances and Innovations in Engineering, India, 2016.
    4. 4)
    5. 5)
      • 5. Hazarika, A., Bhuyan, M.: ‘A twofold subspace learning-based feature fusion strategy for classification of EMG and EMG spectrogram images’. Biologically Rationalized Computing Techniques for Image Processing Applications, Cham, 2018, pp. 5784.
    6. 6)
    7. 7)
    8. 8)
    9. 9)
      • 9. Hazarika, A., Barthakur, M., Dutta, L., et al: ‘Multi-view learning for classification of EMG template’. IEEE Conf. on Signal Processing and Communication, India, 2017.
    10. 10)
      • 10. Xia, T., Tao, D., Mei, T., et al: ‘Multiview spectral embedding’, IEEE Trans. Syst. Man Cybern. B, Cybern., 2010, 40, pp. 14361446.
    11. 11)
      • 11. Dutta, L., Hazarika, A., Bhuyan, M.: ‘Comparison of direct interfacing and ADC based system for gas identification using E-nose’. IEEE Conf. on Inventive Computation Technologies, India, 2016.
    12. 12)
    13. 13)
    14. 14)
      • 14. Dutta, L., Hazarika, A., Bhuyan, M.: ‘Microcontroller based E-nose for gas classification without using ADC’, Sens. Transducers, 2016, 202, pp. 3845.
    15. 15)
    16. 16)
    17. 17)
    18. 18)
    19. 19)
    20. 20)
    21. 21)
    22. 22)
    23. 23)
    24. 24)
    25. 25)
    26. 26)
      • 26. Hassanpour, H., Mesbah, M., Boashash, B.: ‘Time-frequency feature extraction of newborn EEG seizure using SVD-based techniques’, EURASIP J. Appl. Signal Process., 2004, 2004, pp. 25442554.
    27. 27)
    28. 28)
    29. 29)
    30. 30)
    31. 31)
    32. 32)
    33. 33)
    34. 34)
    35. 35)
    36. 36)
    37. 37)
    38. 38)
    39. 39)
      • 39. Barthakur, M., Hazarika, A., Bhuyan, M.: ‘Rule based fuzzy approach for peripheral motor neuropathy (PMN) diagnosis based on NCS data’. Proc. IEEE int. Conf. Proc. Recent Advances and Innovations in Engineering, Jaipur, India, May 2014, pp. 19.
    40. 40)
      • 40. Barthakur, M., Hazarika, A., Bhuyan, M.: ‘Classification of peripheral neuropathy by using ANN based nerve conduction study (NCS) protocol’, ACEEE Int. J. Commun., 2014, 5, p. 31.
    41. 41)
      • 41. Barthakur, M., Hazarika, A., Bhuyan, M.: ‘A novel technique of neuropathy detection and classification by using artificial neural network (ANN)’. Proc ACEEE Int. Conf. Advance Signal Process Communication, 2013, pp. 706713.
    42. 42)
      • 42. Barthakur, M., Hazarika, A., Bhuyan, M.: ‘A computer-assisted technique for nerve conduction study in early detection of peripheral neuropathy using ANN’, Int. J. Electron. Commun. Eng. Tech., 2013, 4, pp. 4765.
    43. 43)
    44. 44)
    45. 45)
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