Abstract
Generalized information theory is viewed in this paper as an information theory that is liberated from the boundaries of probability theory. After overviewing classical (probabilistic) information theory, the paper examines recent developments regarding nonprobabilistic measures and principles of uncertainty-based information, which form a nucleus of the emerging generalized information theory.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
