Abstract
This paper points out the limitations of present probability theory that does not recognize characteristics of probability as follows. Firstly, division of prior probability and posterior probability is not absolute in that prior probability is conditional probability actually. Secondly, probability is not absolutely fixed, and it may be uncertain or even multiple uncertain. Thirdly, probability is evolving with the increase of the conditions. Meanwhile, information is expressed by a set with probability distribution in information theory. When probability is taken as a certain value, the freedom of information is limited. It is analyzed that how the relativity of probability influences information theory. The relativity and reliablity of information that is widely existed in the reality is neglected and that causes the limitation of information theory.
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References
Kolmogorov, A.N.: Grundbegriffe der Wahrsche-inlichkeitsrechnung. Springer, Berlin (1933)
Xiong, D.: The natural axiom system of probability theory- Mathematical model of the random universe. World Scientific Publishing Co., Singapore (2003)
Cheng, S.: Advanced probability theory. Peking University Press, Beijing (1996)
Wang, Y.: Analyses on Limitations of Information Theory. In: International Conference on Artificial Intelligence and Computational Intelligence (AICI 2009), vol. 1, pp. 85–87 (2009)
Wang, Y., Wang, H., Tang, X.: On the Reliability of Information. In: Chinese Control and Decision Conference (CCDC 2009), June 17-19, pp. 871–874. IEEE Press, Los Alamitos (2009)
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Wang, Y. (2011). On Relativity of Probability and Information. In: Lin, S., Huang, X. (eds) Advances in Computer Science, Environment, Ecoinformatics, and Education. CSEE 2011. Communications in Computer and Information Science, vol 216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23345-6_2
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DOI: https://doi.org/10.1007/978-3-642-23345-6_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23344-9
Online ISBN: 978-3-642-23345-6
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