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Blind deconvolution of coloured signals based on higher-order cepstra and data fusion

Blind deconvolution of coloured signals based on higher-order cepstra and data fusion

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  • Author(s): A.P. Petropulu 1  and  C.L. Nikias 2
    • View affiliations
    • Affiliations: 1: Electrical and Computer Engineering Department, Drexel University, Philadelphia, USA
      2: Electrical Engineering-Systems Department, Signal and Image Processing Institute, University of Southern California, Los Angeles, USA
  • Source: Volume 140, Issue 6, December 1993, p. 356 – 361
    DOI:  10.1049/ip-f-2.1993.0053 , Print ISSN 0956-375X, Online ISSN 2053-9045
© The Institution of Electrical Engineers
Published

A new nonparametric blind deconvolution algorithm for coloured non-Gaussian signals is presented. The goal of blind deconvolution is the reconstruction of the input of an unknown linear time-invariant (LTI) mixed-phase system based only on the system output. The existing deconvolution schemes that require the least amount of knowledge about the input signal and the LTI system were developed for white input signals, or rely on parametric modelling of both the system and the input. To develop nonparametric algorithms for the deconvolution of coloured processes of unknown statistics, we are forced to consider a two-channel approach. The proposed algorithm utilises the data collected by two different receivers, each being the output of a different system due to the same input. The two systems are then reconstructed combining higherorder statistics of the measured signals and the theory of signal reconstruction from the higherorder spectral phase only.

Inspec keywords: linear systems; array signal processing; sensor fusion; statistical analysis; spectral analysis; signal synthesis

Other keywords: linear time-invariant system; white input signals; higher-order statistics; receivers; nonparametric blind deconvolution algorithm; higher-order cepstra; signal reconstruction theory; data fusion; measured signals; mixed-phase system; system output; coloured nonGaussian signals

Subjects: Signal processing and detection; Information theory

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