Title :
Self-organization based on the second maximum entropy principle
Author_Institution :
Edvard Kardelj Univ., Ljubljana, Yugoslavia
Abstract :
The article formulates an optimal mapping from a continuous onto a discrete random variable by introducing the second maximum entropy principle, complementary to the Gibbsian one. The mapping corresponds to the self-organization of a community of formal neurons. The derived properties of the interaction between neurons are similar to those in biological neural networks
Keywords :
entropy; neural nets; optimisation; random processes; self-adjusting systems; maxent principle; optimal mapping; random variable; second maximum entropy principle; self-organization;
Conference_Titel :
Artificial Neural Networks, 1989., First IEE International Conference on (Conf. Publ. No. 313)
Conference_Location :
London
