Title :
Adaptive coding and prediction of sources with large and infinite alphabets
Author :
Ryabko, Boris ; Astola, Jaakko
Author_Institution :
Siberian State Univ. of Telecommun. & Comput. Sci., Tomsk, Russia
Abstract :
The problem of predicting a sequence generated by a discrete source with unknown statistics is considered. This problem is of great importance for data compression, because of its use to estimate probability distributions for PPM algorithms and other adaptive codes. This paper suggested a scheme of adaptive coding (and prediction) for a case where a source generates letters from an alphabet with unknown or infinite size. This scheme can be applied along with Laplace, Krichevsky and any other predictors. The general case of the prediction, which is based on such a grouping, is considered and the estimates of the redundancy are given.
Keywords :
adaptive codes; data compression; prediction theory; probability; redundancy; sequences; Laplace-Krichevsky predictors; adaptive coding; data compression; infinite alphabets; probability distributions; redundancy estimation; sequence; source prediction; Adaptive coding; Computer science; Data compression; Probability distribution; Statistical distributions;
Conference_Titel :
Data Compression Conference, 2004. Proceedings. DCC 2004
Print_ISBN :
0-7695-2082-0
DOI :
10.1109/DCC.2004.1281536