In this paper we present a powerful technique for the blind extraction of Direct-Sequence Code-Division Multiple Access (DS-CDMA) signals from convolutive mixtures received by an antenna array. The technique is based on a generalization of the Canonical or Parallel Factor Decomposition (CANDECOMP/PARAFAC) in multilinear algebra. We present a bound on the number of users under which blind separa...

The relative Newton algorithm, previously proposed for quasi maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind deconvolution of images. Smooth approximation of the absolute value is used in modelling the log probability density function, which is suitable for sparse sources. We propose a method of sparsification, which allows ...

This paper proposes an adaptive microphone array using blind deconvolution. The method realizes an signal enhancement based on the combination with beamforming using blind deconvolution, synchronized summation and DSA method. The proposed method improves a performance of estimation by the iterative operation of blind deconvolution using a cost-function base on the coherency function.

INFORMATION-THEORETIC APPROACH Anthony J. Bell and Terrence J. Sejnowski Computational Neurobiology Laboratory, The Salk Institute, 10010 N. Torrey Pines Road, La Jolla, California 92037

In this paper we present a new multichannel blind deconvolution method based on so-called subspace technique that was originally proposed by Harikumar and Bresler. When at least two differently degraded images (channels) of the original scene are provided, the method is better conditioned than classical single channel ones. In comparison with earlier multichannel blind deconvolution techniques ...

A blind deconvolution algorithm based on the Richardson–Lucy deconvolution algorithm is presented. Its performance in the presence of noise is found to be superior to that of other blind deconvolution algorithms. Results are presented and compared with results obtained from implementation of a Weiner filter blind deconvolution algorithm. The algorithm is developed further to incorporate functio...

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The blind estimation of the symbol period of an unknown linearly modulated signal is addressed. We propose an original methodology relying on the concept of blind deconvolution, which does not suffer from the drawbacks of the classical approaches relying upon the cyclostatinarity of the received signal. Under suitable technical conditions, we show that the optimization of certain cost functions...

This paper is devoted to blind deconvolution and blind separation problems. Blind deconvolution is the identiication of a point spread function and an input signal from an observation of their convolution. Blind source separation is the recovery of a vector of input signals from a vector of observed signals, which are mixed by a linear (unknown) operator. We show that both problems are paradigm...

This paper addresses the blind deconvolution of multi-input– multi-output (MIMO) FIR systems driven by white non-Gaussian source signals. First, we present a weaker condition on source signals than the so-called i.i.d. condition so that blind deconvolution is possible. Then, under this condition, we provide a necessary and sufficient condition for blind deconvolution of MIMO FIR systems. Finall...