Possibilistic Kohonen maps

Authors:
Anas Dahabiah;John Puentes;Basel Solaiman
Affiliations:
TELECOM Bretagne, Département Image et Traitement de l'Information, Brest, France and Ministries of High Education and Health, Damascus, Syria;TELECOM Bretagne, Département Image et Traitement de l'Information, Brest, France and Ministries of High Education and Health, Damascus, Syria;TELECOM Bretagne, Département Image et Traitement de l'Information, Brest, France and Ministries of High Education and Health, Damascus, Syria
Venue:
AIKED'10 Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Year:
2010

Citing 4
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Abstract

A Possibilistic Kohonen network based essentially on two fuzzy measures (the possibility and the necessity degrees) is proposed in this paper. This type of network can take into account the imperfection of the information elements in the objects of the training set (the imprecision, the uncertainty, and the missing values) when processing the signals. A concrete numeric example is given to clarify and to easily explain the proposed algorithm.