Semiparametric model and superefficiency in blind deconvolution

[1]  Jitendra Tugnait,et al.  Blind identifiability of FIR-MIMO systems with colored input using second order statistics , 2000, IEEE Signal Processing Letters.

[2]  Philippe Loubaton,et al.  Blind channel and carrier frequency offset estimation using periodic modulation precoders , 2000, IEEE Trans. Signal Process..

[3]  Jitendra K. Tugnait,et al.  Multistep linear predictors-based blind identification and equalization of multiple-input multiple-output channels , 2000, IEEE Trans. Signal Process..

[4]  Andrzej Cichocki,et al.  Multichannel blind deconvolution of non-minimum phase systems using information backpropagation , 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

[5]  Ali Mansour,et al.  Blind Separation of Sources , 1999 .

[6]  Liqing Zhang,et al.  Natural gradient algorithm for blind separation of overdetermined mixture with additive noise , 1999, IEEE Signal Processing Letters.

[7]  S. Amari,et al.  Geometrical structures of FIR manifold and their application to multichannel blind deconvolution , 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

[8]  Shun-ichi Amari,et al.  Superefficiency in blind source separation , 1999, IEEE Trans. Signal Process..

[9]  Philippe Loubaton,et al.  Blind identification of MIMO-FIR systems: A generalized linear prediction approach , 1999, Signal Process..

[10]  Erkki Oja,et al.  The nonlinear PCA criterion in blind source separation: Relations with other approaches , 1998, Neurocomputing.

[11]  L. Tong,et al.  Multichannel blind identification: from subspace to maximum likelihood methods , 1998, Proc. IEEE.

[12]  Shun-ichi Amari,et al.  Adaptive blind signal processing-neural network approaches , 1998, Proc. IEEE.

[13]  Shun-ichi Amari,et al.  Natural Gradient Works Efficiently in Learning , 1998, Neural Computation.

[14]  T. Ens,et al.  Blind signal separation : statistical principles , 1998 .

[15]  Shun-ichi Amari,et al.  Blind source separation-semiparametric statistical approach , 1997, IEEE Trans. Signal Process..

[16]  Andrzej Cichocki,et al.  Stability Analysis of Learning Algorithms for Blind Source Separation , 1997, Neural Networks.

[17]  Aapo Hyvärinen,et al.  A Fast Fixed-Point Algorithm for Independent Component Analysis , 1997, Neural Computation.

[18]  Jean-François Cardoso,et al.  Estimating equations for source separation , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[19]  S. Amari,et al.  Information geometry of estimating functions in semi-parametric statistical models , 1997 .

[20]  S. Amari,et al.  Estimating Functions in Semiparametric Statistical Models , 1997 .

[21]  Philippe Loubaton,et al.  On subspace methods for blind identification of single-input multiple-output FIR systems , 1997, IEEE Trans. Signal Process..

[22]  Shun-ichi Amari,et al.  Stability Analysis Of Adaptive Blind Source Separation , 1997 .

[23]  Jean-François Cardoso,et al.  Equivariant adaptive source separation , 1996, IEEE Trans. Signal Process..

[24]  Philippe Loubaton,et al.  Subspace methods for blind identification of SIMO-FIR systems , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[25]  J. Cadzow Blind deconvolution via cumulant extrema , 1996, IEEE Signal Process. Mag..

[26]  R. Lambert Multichannel blind deconvolution: FIR matrix algebra and separation of multipath mixtures , 1996 .

[27]  Andrzej Cichocki,et al.  A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.

[28]  P. Marriott DIFFERENTIAL GEOMETRY AND STATISTICS , 1995 .

[29]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[30]  Nathalie Delfosse,et al.  Adaptive blind separation of independent sources: A deflation approach , 1995, Signal Process..

[31]  K. Do,et al.  Efficient and Adaptive Estimation for Semiparametric Models. , 1994 .

[32]  Y. Hua Fast maximum likelihood for blind identification of multiple FIR channels , 1994, Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers.

[33]  Andrzej Cichocki,et al.  Robust learning algorithm for blind separation of signals , 1994 .

[34]  Eric Moulines,et al.  Subspace methods for the blind identification of multichannel FIR filters , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[35]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[36]  Lang Tong,et al.  Blind identification and equalization based on second-order statistics: a time domain approach , 1994, IEEE Trans. Inf. Theory.

[37]  P. Bickel Efficient and Adaptive Estimation for Semiparametric Models , 1993 .

[38]  Jitendra K. Tugnait,et al.  Comments on 'New criteria for blind deconvolution of nonminimum phase systems (channels)' , 1992, IEEE Trans. Inf. Theory.

[39]  Christian Jutten,et al.  Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..

[40]  Lang Tong,et al.  Indeterminacy and identifiability of blind identification , 1991 .

[41]  Charles R. Johnson,et al.  Topics in Matrix Analysis , 1991 .

[42]  S. Amari,et al.  Estimation in the Presence of Infinitely many Nuisance Parameters--Geometry of Estimating Functions , 1988 .

[43]  Shun-ichi Amari,et al.  Differential-geometrical methods in statistics , 1985 .

[44]  J. Treichler,et al.  A new approach to multipath correction of constant modulus signals , 1983 .

[45]  Y. Sato Two Extensional Applications of the Zero-Forcing Equalization Method , 1975, IEEE Trans. Commun..

[46]  W. Boothby An introduction to differentiable manifolds and Riemannian geometry , 1975 .

[47]  R. W. Lucky,et al.  Techniques for adaptive equalization of digital communication systems , 1966 .

[48]  S. Amari Natural Gradient Works Eciently in Learning , 2022 .