Fine structure constant - A possibilistic approach

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The paper discusses some unusual interpretations of the fine structure constant (FSC) taking into account of our earlier results and the concept of "unde-tached observer" introduced by Pauli. A joint possibilistic-probabilistic approach and a two-fold "controlling-observing equations" are proposed for a new reinter-pretation of FSC using specific bivariate possibility distribution as a hypotheti-cally proper concept of FSC.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
Pages665-679
Number of pages15
Volume243
DOIs
Publication statusPublished - 2009

Publication series

NameStudies in Computational Intelligence
Volume243
ISSN (Print)1860949X

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Várlaki, P., Fullér, R., & Rudas, I. (2009). Fine structure constant - A possibilistic approach. In Studies in Computational Intelligence (Vol. 243, pp. 665-679). (Studies in Computational Intelligence; Vol. 243). https://doi.org/10.1007/978-3-642-03737-5_48

Fine structure constant - A possibilistic approach. / Várlaki, P.; Fullér, R.; Rudas, I.

Studies in Computational Intelligence. Vol. 243 2009. p. 665-679 (Studies in Computational Intelligence; Vol. 243).

Research output: Chapter in Book/Report/Conference proceedingChapter

Várlaki, P, Fullér, R & Rudas, I 2009, Fine structure constant - A possibilistic approach. in Studies in Computational Intelligence. vol. 243, Studies in Computational Intelligence, vol. 243, pp. 665-679. https://doi.org/10.1007/978-3-642-03737-5_48
Várlaki P, Fullér R, Rudas I. Fine structure constant - A possibilistic approach. In Studies in Computational Intelligence. Vol. 243. 2009. p. 665-679. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-642-03737-5_48
Várlaki, P. ; Fullér, R. ; Rudas, I. / Fine structure constant - A possibilistic approach. Studies in Computational Intelligence. Vol. 243 2009. pp. 665-679 (Studies in Computational Intelligence).
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