TL;DR: The estimation and universal compression of discrete sources are considered, and a sequential algorithm for the universal coding of finite memory sources, attaining asymptotically minimum redundancy, is presented.
Abstract: The estimation and universal compression of discrete sources are considered, and a sequential algorithm for the universal coding of finite memory sources, attaining asymptotically minimum redundancy, is presented. The algorithm performs an online estimation of the source states and uses an arithmetic code. >
TL;DR: Using the results, including some new constructions, upper bounds for covering codes are improved and it is shown how simulated annealing can be used to find acceptable partitions for codes.
Abstract: The concept of (k, t)-subnormal covering codes, is discussed generalizing some of the earlier results. In a similar way, (k, t)-normal covering codes are defined. Using the results, including some new constructions, upper bounds for covering codes are improved. It is shown how simulated annealing can be used to find acceptable partitions for codes. >
TL;DR: A depth-first algorithm is presented for the construction of a binary minimum-redundancy variable length code with limited word length and heuristic information on the mean word length is used for efficient searching.
Abstract: A depth-first algorithm is presented for the construction of a binary minimum-redundancy variable length code with limited word length. In this algorithm, heuristic information on the mean word length is used for efficient searching. The extension to Q -ary codes is also discussed.
TL;DR: The known optimal lower bound for binary Huffman codes is generalized to arbitrary code alphabets and some upper bounds for D-ary Huffman code, 2 or=1/2 are generalized.
Abstract: A method for deriving optimal upper bounds on the redundancy of binary Huffman codes in terms of the probability p/sub 1/ of the most likely source letter is presented. This method will be used to compute bounds for all p/sub 1/>or=1/127, which were previously known only for a few special cases. Furthermore, the known optimal lower bound for binary Huffman codes is generalized to arbitrary code alphabets and some upper bounds for D-ary Huffman codes, 2 or=1/2. >