http://iet.metastore.ingenta.com
1887

access icon openaccess Time-frequency BSS of biosignals

  • HTML
    161.6513671875Kb
  • PDF
    511.9326171875Kb
  • XML
    114.5595703125Kb
Loading full text...

Full text loading...

/deliver/fulltext/htl/5/6/HTL.2018.5029.html;jsessionid=gf30keo6ljeok.x-iet-live-01?itemId=%2fcontent%2fjournals%2f10.1049%2fhtl.2018.5029&mimeType=html&fmt=ahah

References

    1. 1)
      • 1. Cohen, L.: ‘Time–frequency analysis’ (Prentice-Hall, Englewood Cliffs, NJ, 1995).
    2. 2)
      • 2. Boashash, B.: ‘Time–frequency signal analysis and processing: a comprehensive reference’ (Elsevier, Oxford, 2003).
    3. 3)
    4. 4)
    5. 5)
    6. 6)
      • 6. Assous, S., Boashash, B.: ‘Evaluation of the modified S-transform for time–frequency synchrony analysis and source localization’, EURASIP J. Adv. Signal Process., 2012, 49.
    7. 7)
      • 7. Priestley, M.B.: ‘Spectral analysis and time series’ (Academic Press, San Diego, CA, 1981).
    8. 8)
    9. 9)
    10. 10)
      • 10. Suleesathira, R., Chaparro, L.F., Akan, A.: ‘Discrete evolutionary transform for time–frequency analysis’. Proc. Asilomar Conf. Signals, Systems and Computers, Pacific Grove, CA, USA, 1998, pp. 812816.
    11. 11)
    12. 12)
      • 12. Guo, Q., Ruan, G., Liao, Y.: ‘A time–frequency domain underdetermined blind source separation algorithm for MIMO radar signals’, Symmetry, 2017, 9, pp. 115.
    13. 13)
      • 13. Pal, M., Roy, R., Basu, J., et al: ‘Blind source separation: a review and analysis’. Asian Spoken Language Research and Evaluation Conf., Gurgaon, India, 2013, pp. 15.
    14. 14)
      • 14. Johnson, D.H., Dudgeon, D.E.: ‘Array signal processing: concepts and techniques’ (Prentice-Hall, Englewood Cliffs, NJ, 1993).
    15. 15)
      • 15. Makeig, S., Bell, A.J., Jun, T.P., et al: ‘Independent component analysis of EEG data’, J. Adv. Neural Inf. Process. Syst., 1996, 21, pp. 145151.
    16. 16)
    17. 17)
      • 17. Ma, L., Blu, T., Wang, W.: ‘An EEG blind source separation algorithm based on a weak exclusion principle’. 38th Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 16–20 August 2016, pp. 859862.
    18. 18)
    19. 19)
      • 19. Alvarez, L., Sarmiento, O., Gonzalez, A., et al: ‘Hybrid BSS techniques for fetal ECG extraction using a semi-synthetic database’. 20th IEEE Signal Processing, Images and Computer Vision (STSIVA) Symp., Bogota, Colombia, 2015.
    20. 20)
      • 20. Kam, A., Cohen, A.: ‘Separation of twins fetal ECG by means of blind source separation (BSS)’. 21st IEEE Convention, 0-7803-5842-2, Tel-Aviv, Israel, 2000, pp. 342345.
    21. 21)
      • 21. Delorme, A., Palme, J., Onton, J., et al: ‘Independent EEG sources are dipolar’, J. PLOS, 2012, 7, pp. 114.
    22. 22)
      • 22. Thuy-Duong, N.T., Linh-Trung, N., Tran-Duc, T., et al: ‘Separation of nonstationary EEG epileptic seizures using time–frequency-based blind signal processing techniques’. Fourth Int. Conf. Biomedical Engineering in Vietnam IFMBE Proc., Vietnam, 2013, vol. 49.
    23. 23)
      • 23. Zhang, X., Wang, W., Shen, C., et al: ‘Extraction of EEG components based on time–frequency blind source separation’, in Pan, J.S., Tsai, P.W., Watada, J., et al (Eds.): ‘Advances in intelligent information hiding and multimedia signal processing, smart innovation, systems and technologies’ (Springer, Shimane, Japan, 2018), vol. 82.
    24. 24)
    25. 25)
    26. 26)
    27. 27)
    28. 28)
    29. 29)
      • 29. Bohme, J.F.: ‘Array processing in semi-homogeneous random fields’. Proc. Septieme Colloque Sur le Traitment di Signal est Ses Applications, Nice, France, 1979, pp. 104/1104/4.
    30. 30)
    31. 31)
      • 31. Oh, J., Senay, S., Chaparro, L.F.: ‘Signal reconstruction from nonuniformly spaced samples using evolutionary Slepian transform-based POCS’, EURASIP Journal on Advances in Signal Processing, 2010, 2010, (9), pp. 112.
    32. 32)
      • 32. Senay, S.: ‘Nonstationary blind source separation using Slepian spectral estimator’, IARAS Int. J. Signal Process., 2017, 2, pp. 107114.
    33. 33)
    34. 34)
    35. 35)
      • 35. Moghtaderi, A., Takahara, G., Thomson, D.J.: ‘Evolutionary spectrum estimation for uniformly modulated processes with improved frequency resolution’. IEEE Workshop on Statistical Signal Processing, Cardiff, UK, 2009.
    36. 36)
    37. 37)
      • 37. Walter, G.G., Shen, X.: ‘Sampling with prolate spheroidal functions’, Am. Math. Soc. Abstr., 2003, 6, pp. 41227.
    38. 38)
      • 38. Woyczynski, W.A.: ‘Spectral representation of discrete-time stationary signals and their computer simulations’, inWoyczynski, W.A. (Ed.): ‘A first course in statistics for signal analysis’ (Birkhauser, Boston, 2010).
    39. 39)
      • 39. Tsiakoulis, P., Alexandros, P., Dimitrios, D.: ‘Instantaneous frequency and bandwidth estimation using filterbank arrays’. Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE Int. Conf., Vancouver, Canada, 2013.
    40. 40)
    41. 41)
      • 41. Marques, M., Neves, A., Marques, J.S., et al: ‘The Papoulis–Gerchberg algorithm with unknown signal bandwidth’. Int. Conf. Image Analysis and Recognition, Berlin, Heidelberg, 2006.
    42. 42)
    43. 43)
      • 43. Liebeherr, J., Markus, F., Shahrokh, V.: ‘A min-plus system interpretation of bandwidth estimation’. INFOCOM 26th IEEE Int. Conf. Computer Communications, Anchorage, AL, USA, 2007.
    44. 44)
    45. 45)
      • 45. Cardoso, J.F., Souloumiac, A.: ‘Blind beamforming for non-Gaussian signals’, Proc. Inst. Electr. Eng., 1993, 140, pp. 362370.
    46. 46)
    47. 47)
      • 47. Cichocki, A., Amari, S., Siwek, K., et al: ‘ICALAB toolboxes’. Available at http://www.bsp.brain.riken.jp/ICALAB, 2007, accessed 2018.
http://iet.metastore.ingenta.com/content/journals/10.1049/htl.2018.5029
Loading

Related content

content/journals/10.1049/htl.2018.5029
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address