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Wavelet domain natural gradient algorithm for blind source separation of non-stationary sources

Wavelet domain natural gradient algorithm for blind source separation of non-stationary sources

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A wavelet domain approach to blind source separation which avoids the permutation problem in transfer domain operation, and yields improved convergence rate for certain non-stationary signals, is introduced. The wavelet transform also facilitates noise reduction, further improving performance of the natural gradient algorithm.

Inspec keywords: signal sources; wavelet transforms; gradient methods

Other keywords: nonstationary signal; wavelet domain natural gradient algorithm; blind source separation

Subjects: Integral transforms; Signal processing and detection; Integral transforms; Signal processing theory

References

    1. 1)
      • S. Amari , T.-P. Chen , A. Cichocki . Stability analysis of adaptive blind source separation. Neural Netw. , 1345 - 1351
    2. 2)
      • Davies, M.: `Audio source separation', 5th IMA Int. Conf. on Mathematics in Signal Processing, 2000, Warwick, UK.
    3. 3)
      • Buccigrossi, R.W., Simoncelli, E.P.: `Image compression via joint statistical characterization in the wavelet domain', 414, Tech. Rep., 1997.
    4. 4)
      • S.C. Douglas , A. Cichocki . (1996) Convergence analysis of local algorithms for blind decorrelation, Advances in neural information processing systems.
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