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Blind deconvolution by spectral weighted least-squares technique

Blind deconvolution by spectral weighted least-squares technique

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A new algorithm is presented for blind deconvolution of non-minimum phase systems. It is based on the gradient minimisation of a criterion designed as the weighted square of the difference between two statistical spectra. Its main advantages are that it does not require signal preprocessing (such as spectral prewhitening) nor source information, except for statistics up to the fourth-order, and has a high convergence speed and fairly limited computational requirements.

Inspec keywords: deconvolution; convergence of numerical methods; least squares approximations

Other keywords: blind deconvolution; gradient minimisation; high convergence speed; statistical spectra; least-squares technique; spectral weighted LS technique; nonminimum phase systems

Subjects: Interpolation and function approximation (numerical analysis); Signal processing and detection; Signal processing theory; Interpolation and function approximation (numerical analysis)

References

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      • A. Benveniste , M. Goursat , G. Ruget . Robust identification of a nonminimum phase system: blind adjustmentof a linear equalizer in data communications. IEEE Trans. , 3 , 385 - 399
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