Source coding, large deviations, and approximate pattern matching

IEEE Transactions on Information Theory

Volumn 48, Issue 6, 2002, Pages 1590-1615

  Dembo, Amir ^b   Kontoyiannis, Ioannis ^a,c  

^a IEEE   (United States)

^b STANFORD UNIVERSITY   (United States)

^c Brown Univerity   (United States)

Author keywords

Data compression; Large deviations; Pattern matching; Rate distortion theory

Indexed keywords

SOURCE CODING;

ALGORITHMS; APPROXIMATION THEORY; CODES (SYMBOLS); DATA COMPRESSION; ENCODING (SYMBOLS); PATTERN MATCHING; PROBABILITY; REDUNDANCY; THEOREM PROVING;

INFORMATION THEORY;

EID: 0036611931     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIT.2002.1003841     Document Type: Article

References (100)

1. 2D-pattern matching image and video compression
2. The Erdös-Rényi law in distribution for coin tossing and sequence matching
3. The Erdös-Rényi strong law for pattern matching with a given proportion of mismatches
4. A phase transition for the score in matching random sequences allowing deletions
5. Pattern matching image compression: Algorithmic and empirical results
6. The strong ergodic theorem for densities: Generalized Shannon-McMillan-Breiman theorem
7. Game-theoretic optimal portfolios
8. Some communication problems of random fields
9. Strong invariance principles for mixing random fields
10. Basic properties of strong mixing conditions
11. The individual ergodic theorem for information theory
12. Correction to 'The individual ergodic theorem for information theory'
13. Large deviations and strong mixing
14. The source coding theorem via Sanov's theorem
15. A large deviation theory proof of the abstract alphabet source coding theorem
16. Relative entropy and identification of Gibbs measures in dynamical systems
17. The first-order asymptotics of waiting times with distortion between stationary processes
18. Stochastic sub-additivity approach to conditional large deviation principle
19. d
20. Large deviation estimates for a conditional probability distribution. Applications to random interaction Gibbs measures
21. Large deviations from the McKean-Vlasov limit for weakly interacting diffusions
22. The asymptotics of waiting times between stationary processes, allowing distortion
23. Critical behavior in lossy source coding
24. Universal codeword sets and representations of the integers
25. n
26. On entropy and information gain in random fields
27. Large deviations for the empirical field of a Gibbs measure
28. Some limit theorems for stationary processes
29. The redundancy of universal coding with a fidelity criterion
30. An almost sure recurrence theorem with distortion for stationary ergodic sources
31. On three topics for a course in information theory
32. Maximal length of common words among random letter sequences
33. A counterexample to Perez's generalization of the Shannon-McMillan theorem
34. Correction to: 'A counterexample to Perez's generalization of the Shannon-McMillan theorem'
35. Sample converses in source coding theory
36. On the asymptotic behaviors of the recurrence time with a fidelity criterion for discrete memoryless sources and memoryless Gaussian sources
37. Second-order noiseless source coding theorems
38. Asymptotic recurrence and waiting times for stationary processes
39. An implementable lossy version of the Lempel-Ziv algorithm-Part I: Optimality for memoryless sources
40. Pointwise redundancy in lossy data compression and universal lossy data compression
41. Sphere-covering, measure concentration, and source coding
42. Arbitrary source models and Bayesian codebooks in rate-distortion theory
43. On the role of mismatch in rate distortion theory
44. A suboptimal lossy data compression algorithm based on approximate pattern matching
45. Almost sure waiting time results for weak and very weak Bernoulli processes
46. The basic theorems of information theory
47. Large deviations for Gibbs random fields
48. The law of the iterated logarithm for stationary processes satisfying mixing conditions
49. Note on the law of the iterated logarithm for stationary processes satisfying mixing conditions
50. On the Shannon-Perez-Moy theorem
51. Large deviations in ergodic theory
52. The Shannon-McMillan-Breiman theorem for a class of amenable groups
53. Entropy and data compression schemes
54. Recent advances in the central limit theorem and its weak invariance principle for mixing sequences of random variables (a survey)
55. The rate distortion function for a class of sources
56. The rate of a class of random processes
57. A mathematical theory of communication
58. Coding theorems for a discrete source with a fidelity criterion
59. Waiting times: Positive and negative results on the Wyner-Ziv problem
60. An algorithm for source coding subject to a fidelity criterion, based upon string matching
61. Asymptotic properties of data compression and suffix trees
62. Convergence of sequences of convex sets, cones and functions
63. Universal data compression and repetition times
64. Bounds on the rate-distortion function for stationary sources with memory
65. Some asymptotic properties of the entropy of a stationary ergodic data source with applications to data compression
66. Fixed data base version of the Lempel-Ziv data compression algorithm
67. The sliding-window Lempel-Ziv algorithm is asymptotically optimal
68. On the role of pattern matching in information theory. (Information theory: 1948-1998)
69. On the performance of data compression algorithms based upon string matching
70. On the redundancy of lossy source coding with abstract alphabets
71. The shortest common superstring problem: Average case analysis for both exact and approximate matching
72. The redundancy of source coding with a fidelity criterion-Part II: Coding at a fixed rate level with unknown statistics
73. The index entropy of mismatched lossy source coding
74. A type generator model for adaptive lossy compression
75. Natural type selection in adaptive lossy compression
76. The redundancy of source coding with a fidelity criterion-Part I: Known statistics
77. A universal algorithm for sequential data compression
78. Compression of individual sequences by variable rate coding