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Neurocomputations in relational systems

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1 Author(s)
Pedrycz, W. ; Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada

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

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:13 ,  Issue: 3 )