论文信息 - The generalized maximum entropy principle

The generalized maximum entropy principle

Generalizations of the maximum entropy principle (MEP) of E.T. Jaynes (1957) and the minimum discrimination information principle (MDIP) of S. Kullback (1959) are described. The generalizations have been achieved by enunciating the entropy maximization postulate and examining its consequences. The inverse principles which are inherent in the MEP and MDIP are made quite explicit. Several examples are given to illustrate the power and scope of the generalized maximum entropy principle that follows from the entropy maximization postulate. >

H. K. Kesavan | Jagat Narain Kapur | J. N. Kapur | H. Kesavan

[1] C. Tsallis. Possible generalization of Boltzmann-Gibbs statistics , 1988 .

[2] E. Jaynes. Information Theory and Statistical Mechanics , 1957 .

[3] J. N. Kapur,et al. Measures of uncertainty mathematical programming and physics , 1970 .

[4] R. Fisher,et al. On the Mathematical Foundations of Theoretical Statistics , 1922 .

[5] H. K. Kesavan,et al. On the families of solutions to generalized maximum entropy and minimum cross-entropy problems , 1990 .

[6] R. A. Leibler,et al. On Information and Sufficiency , 1951 .

[7] J. Shore,et al. Which is the better entropy expression for speech processing: -S log S or log S? , 1984 .

[8] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.