RALLIS C. PAPADEMETRIOU, THOMAS J. KETSEOGLOU and NICOLAOS S. TZANNES
Multiple Information Principle (MIP) is reviewed as a method of assigning a prior probability mass of density function to a random variable in the presence of some prior…
Abstract
Multiple Information Principle (MIP) is reviewed as a method of assigning a prior probability mass of density function to a random variable in the presence of some prior information. It is compared to the Maximum Information (MI) method and shown to be more general and inclusive of prior data available to the investigator. The image restoration problem is outlined as an inverse source problem with insufficient data for yielding a unique solution.
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The Rate Distortion Theory is a branch of the Information Theory applicable to the case when the entropy of the source exceeds the capacity of the Channel. A rate distortion…
Abstract
The Rate Distortion Theory is a branch of the Information Theory applicable to the case when the entropy of the source exceeds the capacity of the Channel. A rate distortion function R(D) is defined between the input and output alphabets X, Y of a channel. It can be shown that it is possible to design a communication system which achieves a fidelity D when the capacity of the channel C is greater than R(D). In this paper, the formulation of the Rate Distortion Theory is used for the problem of derived probability models. The variables X, Y and the Channel are given new interpretations, and the result is an ability to pick a derived probability model for Y when X is of a known probability structure. The fidelity criterion assumes the rle of an error function in this terminology. Two specific cases are discussed.