Multichannel adaptive blind deconvolution using the complex cepstrum of higher order cross-spectra

An adaptive cross-spectral blind deconvolution method, cross-TEA, for the case in which data are available from several sensors, is described. Unlike ordinary cross-spectra, higher order cross-spectra are separable, and this fact is used to identify and deconvolve each system. Cross-TEA was tested on four-channel QAM (quadrature amplitude modulation) signals, and the results are compared to those for TEA, an autospectral method. >

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