Title :
Generalized Tunstall codes for sources with memory
Author :
Savari, Serap A. ; Gallager, Robert G.
Author_Institution :
Bell Labs., Lucent Technol., Murray Hill, NJ, USA
fDate :
3/1/1997 12:00:00 AM
Abstract :
Tunstall codes are variable-to-fixed length codes that maximize the expected number of source letters per dictionary string for discrete, memoryless sources. We analyze a generalization of Tunstall coding to sources with memory and demonstrate that as the dictionary size increases, the number of code letters per source symbol comes arbitrarily close to the minimum among all variable-to-fixed length codes of the same size. We also find the asymptotic relationship between the dictionary size and the average length of a dictionary entry
Keywords :
Markov processes; probability; source coding; variable length codes; Markov sources; asymptotic relationship; code letters per source symbol; dictionary string; discrete memoryless sources; generalized Tunstall codes; sources with memory; variable-to-fixed length codes; Code standards; Data compression; Dictionaries; Encoding; Entropy; Helium; Information theory; Laboratories; Probability; Steady-state;
Journal_Title :
Information Theory, IEEE Transactions on