Some practical universal noiseless coding techniques

Abstract

Some practical adaptive techniques for the efficient noiseless coding of a broad class of such data sources are developed and analyzed. Algorithms are designed for coding discrete memoryless sources which have a known symbol probability ordering but unknown probability values. A general applicability of these algorithms to solving practical problems is obtained because most real data sources can be simply transformed into this form by appropriate preprocessing. These algorithms have exhibited performance only slightly above all entropy values when applied to real data with stationary characteristics over the measurement span. Performance considerably under a measured average data entropy may be observed when data characteristics are changing over the measurement span.