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680
Blind Beamforming for Non Gaussian Signals
 IEE ProceedingsF
, 1993
"... This paper considers an application of blind identification to beamforming. The key point is to use estimates of directional vectors rather than resorting to their hypothesized value. By using estimates of the directional vectors obtained via blind identification i.e. without knowing the arrray mani ..."
Abstract

Cited by 719 (31 self)
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estimation of directional vectors, based on joint diagonalization of 4thorder cumulant matrices
Capacity of a Mobile MultipleAntenna Communication Link in Rayleigh Flat Fading
"... We analyze a mobile wireless link comprising M transmitter and N receiver antennas operating in a Rayleigh flatfading environment. The propagation coefficients between every pair of transmitter and receiver antennas are statistically independent and unknown; they remain constant for a coherence int ..."
Abstract

Cited by 495 (22 self)
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signals. We prove that there is no point in making the number of transmitter antennas greater than the length of the coherence interval: the capacity for M> Tis equal to the capacity for M = T. Capacity is achieved when the T M transmitted signal matrix is equal to the product of two statistically
Decimated Signal Diagonalization for Obtaining the Complete Eigenspectra of Large Matrices
, 1999
"... An alternative method for obtaining high and interior eigenvalues of a dense spectrum is presented. The method takes advantage of the accurate, welltested and fully understood algorithms for the fast Fourier transform to create, in a natural manner, a `window' containing only a small number of ..."
Abstract

Cited by 1 (1 self)
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An alternative method for obtaining high and interior eigenvalues of a dense spectrum is presented. The method takes advantage of the accurate, welltested and fully understood algorithms for the fast Fourier transform to create, in a natural manner, a `window' containing only a small number of eigenvalues of the spectrum. The method is easy to implement, stable, ecient and accurate.
Sparse Reconstruction by Separable Approximation
, 2007
"... Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least absolute shrinkage and selection operator (LASSO), waveletbased deconvolution and reconstruction, and compressed sensing ..."
Abstract

Cited by 373 (38 self)
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Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least absolute shrinkage and selection operator (LASSO), waveletbased deconvolution and reconstruction, and compressed sensing
A Blind Source Separation Technique Using Second Order Statistics
, 1997
"... Separation of sources consists in recovering a set of signals of which only instantaneous linear mixtures are observed. In many situations, no a priori information on the mixing matrix is available: the linear mixture should be `blindly' processed. This typically occurs in narrowband array pro ..."
Abstract

Cited by 336 (9 self)
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Separation of sources consists in recovering a set of signals of which only instantaneous linear mixtures are observed. In many situations, no a priori information on the mixing matrix is available: the linear mixture should be `blindly' processed. This typically occurs in narrowband array
Tensor diagonalization, a useful tool in signal processing
 IFAC SYMPOSIUM ON SYSTEM IDENTIFICATION
, 1994
"... Tensors appear more and more often in signal processing problems, and especially spatial processing, which typically involves multichannel modeling. Even if it is not always obvious that tensor algebra is the best framework to address a problem, there are cases where no choice is left. Blind identif ..."
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Cited by 17 (7 self)
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Tensors appear more and more often in signal processing problems, and especially spatial processing, which typically involves multichannel modeling. Even if it is not always obvious that tensor algebra is the best framework to address a problem, there are cases where no choice is left. Blind
On the diagonalization of the discrete Fourier transform
, 2009
"... Dedicated to William Kahan and Beresford Parlett on the occasion of their 75th birthday Abstract. The discrete Fourier transform (DFT) is an important operator which acts on the Hilbert space of complex valued functions on the ring Z/NZ. In the case where N = p is an odd prime number, we exhibit a c ..."
Abstract

Cited by 7 (4 self)
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) is probably one of the most important operators in modern science. It is omnipresent in various fields of discrete mathematics and engineering, including combinatorics, number theory, computer science and, last but probably not least, digital signal processing. Formally, the DFT is
Wavelet Diagonalization of Convolution Operators
"... It is well known that wavelets cannot be eigenfunctions of differential operators. We show that for homogeneous convolution operators, one can obtain a diagonal representation using two different biorthogonal wavelet bases, properly adapted to the operator at hand. We generalize this to include many ..."
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Cited by 1 (0 self)
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It is well known that wavelets cannot be eigenfunctions of differential operators. We show that for homogeneous convolution operators, one can obtain a diagonal representation using two different biorthogonal wavelet bases, properly adapted to the operator at hand. We generalize this to include
Results 1  10
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680