
arXiv: 1102.2207
This paper presents prefix codes which minimize various criteria constructed as a convex combination of maximum codeword length and average codeword length or maximum redundancy and average redundancy, including a convex combination of the average of an exponential function of the codeword length and the average redundancy. This framework encompasses as a special case several criteria previously investigated in the literature, while relations to universal coding is discussed. The coding algorithm derived is parametric resulting in re-adjusting the initial source probabilities via a weighted probability vector according to a merging rule. The level of desirable merging has implication in applications where the maximum codeword length is bounded.
6 pages, 2 figures
FOS: Computer and information sciences, Information theory, Average codeword length, Coding algorithms, Convex combinations, Computer Science - Information Theory, Information Theory (cs.IT), Lossless coding, Universal coding, Codeword length, Weighting vector, Prefix codes, Exponential functions, Weighted probability, Algorithms
FOS: Computer and information sciences, Information theory, Average codeword length, Coding algorithms, Convex combinations, Computer Science - Information Theory, Information Theory (cs.IT), Lossless coding, Universal coding, Codeword length, Weighting vector, Prefix codes, Exponential functions, Weighted probability, Algorithms
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