Title :
Some results on adaptive statistics estimation for the reversible compression of sequences
Author :
Ramabadran, T.V.
Author_Institution :
Iowa State Univ., Ames, IA, USA
Abstract :
Extended summary form only given. This paper is concerned with statistics estimation methods and how they influence model performance. For simplicity, a memoryless model is assumed with a single context and binary alphabet. Nonadaptive estimation uses the relative frequency counts of the letters (0 and 1) in the entire sequence. Depletive adaptive estimation uses the relative frequency counts of the letters in the part of the sequence yet to be scanned. Cumulative adaptive estimation uses the relative frequency counts in the part of the sequence already scanned
Keywords :
binary sequences; data compression; estimation theory; binary alphabet; cumulative adaptive estimation; depletive adaptive estimation; memoryless model; model performance; nonadaptive estimation; relative frequency counts; reversible compression of sequences; statistics estimation methods; Adaptive estimation; Arithmetic; Binary sequences; Context modeling; Frequency estimation; Probability distribution; Statistical distributions; Statistics; Technological innovation;
Conference_Titel :
Data Compression Conference, 1991. DCC '91.
Conference_Location :
Snowbird, UT
Print_ISBN :
0-8186-9202-2
DOI :
10.1109/DCC.1991.213312