RateDistortion: Routines for Solving Rate-Distortion Problems
An implementation of routines for solving rate-distortion problems. Rate-distortion theory is a field within information theory that examines optimal lossy compression. That is, given that some information must be lost, how can a communication channel be designed that minimizes the cost of communication error? Rate-distortion theory is concerned with the optimal (minimal cost) solution to such tradeoffs. An important tool for solving rate-distortion problems is the Blahut algorithm, developed by Richard Blahut and described in: . Blahut, R. E. (1972). Computation of channel capacity and rate-distortion functions. IEEE Transactions on Information Theory, IT-18(4), 460-473. . This package implements the basic Blahut algorithm, and additionally contains a number of `helper' functions, including a routine for searching for an information channel that minimizes cost subject to a constraint on information rate.
- Chris R. Sims
- Date of publication
- 2015-08-11 08:22:22
- Chris R. Sims <firstname.lastname@example.org>
- Implementation of the Blahut algorithm described in (Blahut,...
- Compute the channel distortion for a given channel and cost...
- Return the conditional output distribution for a given...
- Compute the difference distribution for a given channel.
- Find an optimal information channel for a given source, cost...
- Search for a channel that achieves a given level of...
- Compute the maximum cost for an information source and cost...
- Compute the mutual information for a given channel and source...
- Routines for Solving Rate-Distortion Problems
- Generate random samples from a channel distribution.
Files in this package