The Mathematical Theory of Communication by Claude Shannon

Consequently, by calculating the parameters of the new prognostic model, we will be able to determine the magnitude of the chaotic factor, the degree of our knowledge, the complex probability, the self-information functions, the message entropies, and the channel capacities in the probability sets and and and which are all functions of the message real probability subject to chaos and random effects. Hence, my purpose here is to link my complex probability paradigm to Claude Shannon's information theory that was originally proposed in 1948. To make communication theory a scientific discipline, Shannon needed to provide a precise definition of information that transformed it into a physical. It is of great importance that stochastic systems become totally predictable since we will be perfectly knowledgeable to foretell the outcome of all random events that occur in nature. Therefore, adding to the real set of probabilities R the contributions of the imaginary set of probabilities M will make the event in C = R + M absolutely deterministic. The original idea in my complex probability paradigm is to add new imaginary dimensions to the experiment real dimensions which will make the work in the complex probability set totally predictable and with a probability permanently equal to one. Shannon was a research mathematician at the Bell Telephone Laboratories and Donner professor of science at the Massachusetts Institute of Technology.

Andrey Kolmogorov put forward in 1933 the five fundamental axioms of classical probability theory.

The Mathematical Theory of Communication by Claude Shannon