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Consider the set of source distributions within a fixed maximum relative entropy with respect to a given nominal distribution. Lossless source coding over this relative entropy ball can be approached in more than one way. A problem previously considered is finding a minimax average length source code. The minimizing players are the codeword lengths --- real numbers for arithmetic codes, integers for prefix codes --- while the maximizing players are the uncertain source distributions. Another traditional minimizing objective is the first one considered here, maximum (average) redundancy. This problem reduces to an extension of an exponential Huffman objective treated in the literature but heretofore without direct practical application. In addition to these, this paper examines the related problem of maximal minimax pointwise redundancy and the problem considered by Gawrychowski and Gagie, which, for a sufficiently small relative entropy ball, is equivalent to minimax redundancy. One can consider both Shannon-like coding based on optimal real number (ideal) codeword lengths and a Huffman-like optimal prefix coding.
Stopping sets play a crucial role in failure events of iterative decoders over a binary erasure channel (BEC). The $ell$-th stopping redundancy is the minimum number of rows in the parity-check matrix of a code, which contains no stopping sets of siz
We consider the problem of one-way communication when the recipient does not know exactly the distribution that the messages are drawn from, but has a prior distribution that is known to be close to the source distribution, a problem first considered
Distributed arithmetic coding (DAC) has been shown to be effective for Slepian-Wolf coding, especially for short data blocks. In this letter, we propose to use the DAC to compress momery-correlated sources. More specifically, the correlation between
A transmitter without channel state information (CSI) wishes to send a delay-limited Gaussian source over a slowly fading channel. The source is coded in superimposed layers, with each layer successively refining the description in the previous one.
An encoder, subject to a rate constraint, wishes to describe a Gaussian source under squared error distortion. The decoder, besides receiving the encoders description, also observes side information consisting of uncompressed source symbol subject to