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Issue No.03 - March (1991 vol.13)
pp: 289-297
ABSTRACT
<p>Strong analogies between relational structures involving some composition operators and a certain class of neural networks are described. The problem of learning the connections of the structure is addressed, and relevant learning procedures are proposed. An optimized performance index which has a strong logical flavor is proposed. Some significant implementation details are studied. Numerical examples illustrate various schemes of learning in relational structures of different levels of complexity.</p>
INDEX TERMS
neurocomputations; relational systems; composition operators; neural networks; learning procedures; optimized performance index; complexity; fuzzy set theory; learning systems; neural nets
CITATION
W. Pedrycz, "Neurocomputations in Relational Systems", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.13, no. 3, pp. 289-297, March 1991, doi:10.1109/34.75517
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