Information Theory: Coding Theorems for Discrete Memoryless Systems
Information Theory: Coding Theorems for Discrete Memoryless Systems
The capacity of channels with feedback
IEEE Transactions on Information Theory
Capacity results for the discrete memoryless network
IEEE Transactions on Information Theory
To code, or not to code: lossy source-channel communication revisited
IEEE Transactions on Information Theory
Duality between source coding and channel coding and its extension to the side information case
IEEE Transactions on Information Theory
On competitive prediction and its relation to rate-distortion theory
IEEE Transactions on Information Theory
Feedback capacity of the first-order moving average Gaussian channel
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Source Coding With Feed-Forward: Rate-Distortion Theorems and Error Exponents for a General Source
IEEE Transactions on Information Theory
A Coding Theorem for a Class of Stationary Channels With Feedback
IEEE Transactions on Information Theory
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The problem of computing the capacity-cost function of channels with feedback and the rate-distortion function of sources with feed-forward is considered. Sufficient conditions are derived on : a) the structure of the cost function for a chosen joint distribution to achieve the optimal feedback capacitycost function, b) the structure of the distortion function for a chosen joint distribution to achieve the optimal feed-forward rate-distortion function. These structural results are useful since it is infeasible in general to directly compute the optimizations. Examples are provided to show how the results can help compute the performance limits with feedback and feed-forward.