A Fuzzy Model Of Nervous System

Abstract

Still there is no model of mathematics that is able to represent the true biological process, which can transform the signals, obtained from the nervous system to logical reasoning. However, some mathematical models may approximate to the process of logical reasoning. This paper assumes the set of inputs as fuzzy propositions and uses a LCA (locally compact abelian) group structure to characterize knowledges as Fourier series. The representation used in the study enables us to introduce the notions of logical bases and logical dependencies of knowledges. Also, this makes possible to compare the truthfulness of propositions and define maximal truthfulness that corresponds to the true value in the Boolean logic. Finally, the axiom False ⇒ True of the Boolean logic results

Keywords

• nervous system
• neurons
• fuzzy systems
• locally compact abelian group
• fourier series
• sinir sistemi
• nöronlar
• fuzzy sistemler
• lokal kompakt abel grubu
• fourier serileri