23 Apr 07 Combinatorial Information Theory: I. Philosophical Basis of Cross-Entropy and Entropy
Robert K. Niven
Abstract: This study critically analyses the information-theoretic, axiomatic and combinatorial philosophical bases of the entropy and cross-entropy concepts. The combinatorial basis is shown to be the most fundamental (most primitive) of these three bases, since it gives (i) a derivation for the Kullback-Leibler cross-entropy and Shannon entropy functions, as simplified forms of the multinomial distribution subject to the Stirling approximation; (ii) an explanation for the need to maximize entropy (or minimize cross-entropy) to find the most probable realization; and (iii) new, generalized definitions of entropy and cross-entropy - supersets of the Boltzmann principle - applicable to non-multinomial systems. The combinatorial basis is therefore of much broader scope, with far greater power of application, than the information-theoretic and axiomatic bases. The generalized definitions underpin a new discipline of it combinatorial information theory, for the analysis of probabilistic systems of any type. Jaynes’ generic formulation of statistical mechanics for multinomial systems is re-examined in light of the combinatorial approach.
Powered by ScribeFire.
