Self-organization based on the second maximum entropy principle

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.<
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