Convergence analyses and comparisons of Markov chain Monte Carlo algorithms in digital communications

IEEE Transactions on Signal Processing

Volumn 50, Issue 2, 2002, Pages 255-270

  Chen, Rong ^a,b   Liu, Jun S ^c   Wang, Xiaodong ^a,d  

^a IEEE   (United States)

^b UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

^c HARVARD UNIVERSITY   (United States)

^d Columbia University ^*  (United States)

Author keywords

Bayesian receiver; Duality; Eigenvalue; Forward backward algorithm; Gibbs sampler; Metropolis algorithm; Transition function

Indexed keywords

BAYESIAN RECEIVERS;

ALGORITHMS; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; DECODING; DIGITAL SIGNAL PROCESSING; ERROR ANALYSIS; ITERATIVE METHODS; MARKOV PROCESSES;

DIGITAL COMMUNICATION SYSTEMS;

EID: 0036475631     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/78.978381     Document Type: Article

References (23)

1. Bayesian deconvolution of noisy filtered point processes
2. Blind deconvolution of convolutive discrete source mixture
3. On Gibbs sampling for state space models
4. Blind restoration of linearly degraded discrete signals by Gibbs sampler
5. Bayesian blind deconvolution for mobile communications
6. Geometric bounds for eigenvalues for Markov chains
7. Fully Bayesian analysis of hidden Markov models
8. Convergence rates of the Gibbs sampler; The Metropolis algorithm and other single-site updating dynamics
9. Sequence estimation in the presence of random parameters via the EM algorithm
10. Approximating the permanent
11. Peskun's theorem and a modified discrete-state Gibbs sampler
12. Covariance structure of the Gibbs sampler with applications to the comparisons of estimators and augmentation schemes
13. Covariance structure and convergence rate of the Gibbs sampler with various scans
14. Markov-chain Monte Carlo: Some practical implications of theoretical results
15. Minorization conditions and convergence-rates for Markov-chain Monte-Carlo
16. Interference cancellation using the Gibbs sampler
17. Markov-chains for exploring posterior distributions
18. Adaptive Bayesian multiuser detection for synchronous CDMA in Gaussian and impulsive noise
19. Blind turbo equalization in Gaussian and impulsive noise