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Information boundedness principle in fuzzy inference process
Kybernetika, Tome 38 (2002) no. 3, pp. 327-338 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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The information boundedness principle requires that the knowledge obtained as a result of an inference process should not have more information than that contained in the consequent of the rule. From this point of view relevancy transformation operators as a generalization of implications are investigated.
The information boundedness principle requires that the knowledge obtained as a result of an inference process should not have more information than that contained in the consequent of the rule. From this point of view relevancy transformation operators as a generalization of implications are investigated.
Classification : 03B52, 03E72, 68T37
Keywords: inference; fuzzy system modeling 
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Sarkoci, Peter; Šabo, Michal. Information boundedness principle in fuzzy inference process. Kybernetika, Tome 38 (2002) no. 3, pp. 327-338. http://geodesic.mathdoc.fr/item/KYB_2002_38_3_a8/

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