2007/12/30 by Michael B. Baer, Baer, Michael B.
Computer Science · Engineering · Mathematics · #Advanced Wireless Communication Techniques #Algorithms and Data Compression #Data Structures and Algorithms (cs.DS) #E.4 #Error Correcting Code Techniques #F.2 #FOS: Computer and information sciences #G.2.2 #H.1.1 #Information Theory (cs.IT) #cs.DS #cs.IT #math.IT
paper · pdf · doi:10.48550/arxiv.0801.0102
5 pages, submitted to ISIT 2008
arxiv created 2007/12/30 · openalex publication_date 2007/12/30 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Huffman coding finds an optimal prefix code for a given probability mass function. Consider situations in which one wishes to find an optimal code with the restriction that all codewords have lengths that lie in a user-specified set of lengths (or, equivalently, no codewords have lengths that lie in a complementary set). This paper introduces a polynomial-time dynamic programming algorithm that finds optimal codes for this reserved-length prefix coding problem. This has applications to quickly encoding and decoding lossless codes. In addition, one modification of the approach solves any quasiarithmetic prefix coding problem, while another finds optimal codes restricted to the set of codes with g codeword lengths for user-specified g (e.g., g=2).