Possibilistic Kohonen maps

Anas Dahabiah (1, 2) , John Puentes (1, 2) , Basel Solaiman (1, 2)

1 ITI - Département Image et Traitement Information
2 LaTIM - Laboratoire de Traitement de l'Information Medicale

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.

Anas Dahabiah, John Puentes, Basel Solaiman. Possibilistic Kohonen maps. WSEAS 2010 : International Conference on Artificial intelligence, knowledge engineering and Data bases, Feb 2010, Cambridge, United Kingdom. pp.179-184. ⟨hal-00476132⟩