
Proceedings Paper
Simulation of concept acquisition according to Posner's theory using artificial neural networksFormat | Member Price | Non-Member Price |
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Paper Abstract
The prototype model of classification assumes that categories are stored in human mind as abstracted summary
representations formed in the process of experiencing specimens. Classification of new exemplars is based on their
similarity to the abstracted prototype. From studies using Michael Posner’s dot-pattern recognition paradigm, we
selected several empirical observations, like category size effect, category breadth effect or prototype-exemplar
similarity effect, and tested them on artificial neural networks. In this work we show that the properties of human
categorization process can be very well simulated and observed on artificial neural networks.
Paper Details
Date Published: 6 October 2011
PDF: 9 pages
Proc. SPIE 8008, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2011, 80080S (6 October 2011); doi: 10.1117/12.905429
Published in SPIE Proceedings Vol. 8008:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2011
Ryszard S. Romaniuk, Editor(s)
PDF: 9 pages
Proc. SPIE 8008, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2011, 80080S (6 October 2011); doi: 10.1117/12.905429
Show Author Affiliations
Dawid Grzegorczyk, Warsaw Univ. of Technology (Poland)
Marek Nieznański, Cardinal Stefan Wyszynski Univ. (Poland)
Marek Nieznański, Cardinal Stefan Wyszynski Univ. (Poland)
Jan J. Mulawka, Warsaw Univ. of Technology (Poland)
Published in SPIE Proceedings Vol. 8008:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2011
Ryszard S. Romaniuk, Editor(s)
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