A fast algorithm for optimal length-limited Huffman codes
Journal of the ACM (JACM)
Overview of the second text retrieval conference (TREC-2)
TREC-2 Proceedings of the second conference on Text retrieval conference
Adding compression to a full-text retrieval system
Software—Practice & Experience
Computing a minimum-weight k-link path in graphs with the concave Monge property
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Graph Algorithms
In-Place Calculation of Minimum-Redundancy Codes
WADS '95 Proceedings of the 4th International Workshop on Algorithms and Data Structures
A Fast and Space - Economical Algorithm for Length - Limited Coding
ISAAC '95 Proceedings of the 6th International Symposium on Algorithms and Computation
Two Space-Economical Algorithms for Calculating Minimum Redundancy Prefix Codes
DCC '99 Proceedings of the Conference on Data Compression
Efficient construction of minimum-redundancy codes for large alphabets
IEEE Transactions on Information Theory
Incremental Calculation of Minimum-Redundancy Length-Restricted Codes
DCC '02 Proceedings of the Data Compression Conference
Length-Restricted Coding in Static and Dynamic Frameworks
DCC '01 Proceedings of the Data Compression Conference
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Given an alphabet Σ = {a1, ..., an} with a corresponding list of positive weights {w1, ..., wn} and a length restriction L, the length-restricted prefix code problem is to find, a prefix code that minimizes Σni=1 wili, where li, the length of the codeword assigned to ai, cannot be greater than L, for i = 1, ..., n. In this paper, we present an efficient implementation of the WARM-UP algorithm, an approximative method for this problem. The worst-case time complexity of WARMUP is O(n log n + n log wn), where wn is the greatest weight. However, some experiments with a previous implementation of WARM-UP show that it runs in linear time for several practical cases, if the input weights are already sorted. In addition, it often produces optimal codes. The proposed implementation combines two new enhancements to reduce the space usage of WARM-UP and to improve its execution time. As a result, it is about ten times faster than the previous implementation of WARM-UP and overcomes the LRR Package Method, the faster known exact method.