Analyses on Limitations of Information Theory
Yong Wang
Abstract
Yong Wang
Abstract
The paper analyzes the limitations from the angles of conditional entropy and the expression of information. It is pointed out Shannon's definition of information is not absolute and the probability in the expression of information maybe random variable in practice, but in information theory the probability is treated as a fixed value, then the application of Shannon's theory is limited. It is stated that people would select information that is more reliable but more uncertain than the reverse in practice. The signality of the reliability of information which is ignored in Shannon's information theory is indicated and the clew to measure the reliability of information is given to be the uncertainty of probability.
OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The paper analyzes the limitations from the angles of conditional entropy and the expression of information. It is pointed out Shannon's definition of information is not absolute and the probability in the expression of information maybe random variable in practice, but in information theory the probability is treated as a fixed value, then the application of Shannon's theory is limited. It is stated that people would select information that is more reliable but more uncertain than the reverse in practice. The signality of the reliability of information which is ignored in Shannon's information theory is indicated and the clew to measure the reliability of information is given to be the uncertainty of probability.
Key concepts: Information theory, Conditional mutual information, Random variable, Information diagram, Expression (computer science), Entropy (arrow of time), Conditional entropy, Computer science