Simulation-based methods for blind maximum-likelihood filter identification
暂无分享,去创建一个
Eric Moulines | Arnaud Doucet | Olivier Cappé | Marc Lavielle | O. Cappé | A. Doucet | É. Moulines | M. Lavielle
[1] É. Moulines,et al. Convergence of a stochastic approximation version of the EM algorithm , 1999 .
[2] A. Doucet,et al. Bayesian estimation of filtered point processes using Markov chain Monte Carlo methods , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).
[3] Eric Moulines,et al. Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[4] Simon J. Godsill,et al. Bayesian Enhancement of Speech and Audio Signals which can be Modelled as ARMA Processes , 1997 .
[5] Patrick Duvaut,et al. Bayesian estimation of state-space models applied to deconvolution of Bernoulli - Gaussian processes , 1997, Signal Process..
[6] Xiao-Li Meng,et al. The EM Algorithm—an Old Folk‐song Sung to a Fast New Tune , 1997 .
[7] José A. R. Fonollosa,et al. Blind channel estimation and data detection using hidden Markov models , 1997, IEEE Trans. Signal Process..
[8] G. Roberts,et al. Updating Schemes, Correlation Structure, Blocking and Parameterization for the Gibbs Sampler , 1997 .
[9] M. Pitt,et al. Analytic Convergence Rates and Parameterization Issues for the Gibbs Sampler Applied to State Space Models , 1999 .
[10] Yves Goussard,et al. Unsupervised deconvolution of sparse spike trains using stochastic approximation , 1996, IEEE Trans. Signal Process..
[11] R. Kohn,et al. Markov chain Monte Carlo in conditionally Gaussian state space models , 1996 .
[12] Robert Kohn,et al. Semiparametric Bayesian Inference for Time Series with Mixed Spectra , 1996 .
[13] J. Cadzow. Blind deconvolution via cumulant extrema , 1996, IEEE Signal Process. Mag..
[14] G. Casella,et al. Rao-Blackwellisation of sampling schemes , 1996 .
[15] Rong Chen,et al. Simultaneous wavelet estimation and deconvolution of reflection seismic signals , 1996, IEEE Trans. Geosci. Remote. Sens..
[16] Peter Green,et al. Markov chain Monte Carlo in Practice , 1996 .
[17] Edward H. Ip,et al. Stochastic EM: method and application , 1996 .
[18] M. Rosenblatt. The Likelihood of an Autoregressive Scheme , 1996 .
[19] A. Harvey,et al. 5 Stochastic volatility , 1996 .
[20] S. Chib,et al. Understanding the Metropolis-Hastings Algorithm , 1995 .
[21] Rong Chen,et al. Blind restoration of linearly degraded discrete signals by Gibbs sampling , 1995, IEEE Trans. Signal Process..
[22] Daniel Pierre Loti Viaud. Random perturbations of recursive sequences with an application to an epidemic model , 1995, Journal of Applied Probability.
[23] N. Shephard,et al. The simulation smoother for time series models , 1995 .
[24] J. Besag,et al. Bayesian Computation and Stochastic Systems , 1995 .
[25] N. Shephard,et al. Stochastic Volatility: Likelihood Inference And Comparison With Arch Models , 1996 .
[26] L. Tierney. Markov Chains for Exploring Posterior Distributions , 1994 .
[27] Y. Hua. Fast maximum likelihood for blind identification of multiple FIR channels , 1994, Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers.
[28] R. Kohn,et al. On Gibbs sampling for state space models , 1994 .
[29] Ghassan Kawas Kaleh,et al. Joint parameter estimation and symbol detection for linear or nonlinear unknown channels , 1994, IEEE Trans. Commun..
[30] Jean Claude Biscarat. Almost sure convergence of a class of stochastic algorithms , 1994 .
[31] Jun S. Liu,et al. Covariance structure of the Gibbs sampler with applications to the comparisons of estimators and augmentation schemes , 1994 .
[32] Jitendra K. Tugnait,et al. Blind estimation of digital communication channel impulse response , 1994, IEEE Trans. Commun..
[33] Nambi Seshadri,et al. Joint data and channel estimation using blind trellis search techniques , 1994, IEEE Trans. Commun..
[34] Hui Liu,et al. A deterministic approach to blind symbol estimation , 1994, IEEE Signal Processing Letters.
[35] Bernard Delyon,et al. Accelerated Stochastic Approximation , 1993, SIAM J. Optim..
[36] Marc Lavielle,et al. Bayesian deconvolution of Bernoulli-Gaussian processes , 1993, Signal Process..
[37] C. L. Nikias,et al. Signal processing with higher-order spectra , 1993, IEEE Signal Processing Magazine.
[38] Athina P. Petropulu,et al. Blind convolution using signal reconstruction from partial higher order cepstral information , 1993, IEEE Trans. Signal Process..
[39] S. Koopman,et al. Disturbance smoother for state space models , 1993 .
[40] Jitendra Tugnait. Blind equalization and estimation of digital communication FIR channels using cumulant matching , 1992, [1992] Conference Record of the Twenty-Sixth Asilomar Conference on Signals, Systems & Computers.
[41] Yves Goussard,et al. On simultaneous signal estimation and parameter identification using a generalized likelihood approach , 1992, IEEE Trans. Inf. Theory.
[42] M. Lavielle. 2-D Bayesian deconvolution , 1991 .
[43] G. C. Wei,et al. A Monte Carlo Implementation of the EM Algorithm and the Poor Man's Data Augmentation Algorithms , 1990 .
[44] Adrian F. M. Smith,et al. Sampling-Based Approaches to Calculating Marginal Densities , 1990 .
[45] Guy Demoment,et al. Image reconstruction and restoration: overview of common estimation structures and problems , 1989, IEEE Trans. Acoust. Speech Signal Process..
[46] Jerry M. Mendel,et al. Identification of nonminimum phase systems using higher order statistics , 1989, IEEE Trans. Acoust. Speech Signal Process..
[47] Spiridon D. Likothanassis,et al. Optimal seismic deconvolution , 1988 .
[48] Adrian F. M. Smith,et al. Bayesian computation via the gibbs sampler and related markov chain monte carlo methods (with discus , 1993 .
[49] A. F. Smith,et al. Statistical analysis of finite mixture distributions , 1986 .
[50] J. Besag. On the Statistical Analysis of Dirty Pictures , 1986 .
[51] Lawrence R. Rabiner,et al. A tutorial on Hidden Markov Models , 1986 .
[52] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[53] R. Redner,et al. Mixture densities, maximum likelihood, and the EM algorithm , 1984 .
[54] M. Rosenblatt,et al. Deconvolution and Estimation of Transfer Function Phase and Coefficients for NonGaussian Linear Processes. , 1982 .
[55] J. Mendel. White-noise estimators for seismic data processing in oil exploration , 1977 .
[56] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[57] Carlos S. Kubrusly,et al. Stochastic approximation algorithms and applications , 1973, CDC 1973.
[58] P. Graefe. Linear stochastic systems , 1966 .