The study introduces a new class of fuzzy neurons and fuzzy neural networks exploiting a model of a generalized multivalued exclusive-OR (XOR) operation. The proposed neural architecture is useful in an algebraic representation (description) of fuzzy functions regarded as mappings between unit hypercubes, say [0,1]n [0,1]m. Some underlying properties of the fXOR neurons are discussed and a detailed learning algorithm is given along with a number of illustrative numeric examples.

Pedrycz W, Succi G (2002). fXOR fuzzy logic networks. SOFT COMPUTING, 7(2), 115-120.

fXOR fuzzy logic networks

Succi G
2002

Abstract

The study introduces a new class of fuzzy neurons and fuzzy neural networks exploiting a model of a generalized multivalued exclusive-OR (XOR) operation. The proposed neural architecture is useful in an algebraic representation (description) of fuzzy functions regarded as mappings between unit hypercubes, say [0,1]n [0,1]m. Some underlying properties of the fXOR neurons are discussed and a detailed learning algorithm is given along with a number of illustrative numeric examples.
2002
Pedrycz W, Succi G (2002). fXOR fuzzy logic networks. SOFT COMPUTING, 7(2), 115-120.
Pedrycz W; Succi G
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/895680
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