The Communication Model Compatible with Popper's Theory of Science Evolution

  Figure 5 Illustration of  information  I(X; y_j)

 Abstract: A generalized  information theory is proposed  as a natural extension of Shannon's information theory. It  proposes that information comes from forecasts. The  more precise and the more unexpected a forecast is, the more information it conveys. If subjective forecast  always conforms with objective facts then the generalized information measure will be equivalent to Shannon's information measure. The generalized communication model is consistent with  K. R. Popper's model of knowledge evolution. The mathematical foundations of the new information theory, the generalized communication model ,   information measures for semantic information and sensory information, and the coding meanings of generalized entropy and generalized  mutual information are introduced. Assessments and optimizations of pattern recognition, predictions, and detection with the generalized information criterion are  discussed. For economization  of communication, a  revised version of rate-distortion theory: rate-of-keeping-precision theory, which is  a theory for datum  compression  and also a theory for matching an objective channels with the subjective understanding of information receivers, is proposed.  Applications include stock market forecasting and video image presentation.

 Key words: Shannon’s information theory, generalized information theory,  semantic information,   forecasts, pattern recognition, communication optimizations