Towards Practical Minimum-Entropy Universal Decoding

Minimum-entropy decoding is a universal decoding algorithm used in decoding block compression of discrete memoryless sources as well as block transmission of information across discrete memoryless channels. Extensions can also be applied for multiterminal decoding problems, such as the Slepian-Wolf source coding problem. The `method of types' has been used to show that there exist linear codes for which minimum-entropy decoders achieve the same error exponent as maximum-likelihood decoders. Since minimum-entropy decoding is NP-hard in general, minimum-entropy decoders have existed primarily in the theory literature. We introduce practical approximation algorithms for minimum-entropy decoding. Our approach, which relies on ideas from linear programming, exploits two key observations. First, the `method of types' shows that that the number of distinct types grows polynomially in n. Second, recent results in the optimization literature have illustrated polytope projection algor...

• Type: Conference
• Year: 2005
• Where: DCC
• Authors: Todd P. Coleman, Muriel Médard, Michelle Effros
• Keywords: Computer Graphics, DCC 2005, Minimum-entropy Decoding, Multiterminal Decoding Problems, Universal Decoding Algorithm