Limits of information, Markov chains, and projection

IEEE International Symposium on Information Theory - Proceedings

Volumn , Issue , 2000, Pages 25-

  Barron, A R ^a  

^a YALE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CAUCHY SEQUENCES; CHAIN RULE; INFORMATION PROJECTION;

BOUNDARY CONDITIONS; CONVERGENCE OF NUMERICAL METHODS; MARKOV PROCESSES; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS; SET THEORY; STATE SPACE METHODS; THEOREM PROVING;

INFORMATION THEORY;

EID: 0034446846     PISSN: 21578095     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. The strong ergodic theorem for densities: Generalized Shannon-McMillan-Breiman theorem
2. Competitive optimality of logarithmic investment
3. Sanov property, generalized I-projection and a conditional limit theorem
4. An information-theoretical proof of limit theorems for reversible Markov processes
5. An almost sure convergence theorem for sequences of random variables selected from log-convex sets
6. Estimation of mixture models
7. Information theoretical optimization techniques