OR/AND neurons and the development of interpretable logic models

In this paper, we are concerned with the concept of fuzzy logic networks and logic-based data analysis realized within this framework. The networks under discussion are homogeneous architectures comprising of OR/AND neurons originally introduced by Hirota and Pedrycz. Being treated here as generic p...

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Bibliographic Details
Published in:	IEEE transactions on neural networks Vol. 17; no. 3; pp. 636 - 658
Main Authors:	Pedrycz, W., Reformat, M., Li, K.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.05.2006 Institute of Electrical and Electronics Engineers
Subjects:	Algorithms AND logic operations Applied sciences Artificial Intelligence Boolean functions Computer science; control theory; systems Connectionism. Neural networks Data analysis Digital systems Exact sciences and technology function decomposition Fuzzy Logic fuzzy logic network fuzzy neurons genetic algorithms Genetics Hypercubes Information Storage and Retrieval - methods Input variables Instruments interactive network design interpretation Logistic Models Multidimensional systems Neural Networks (Computer) Neurons OR/AND fuzzy neuron Pattern Recognition, Automated - methods pruning Signal Processing, Computer-Assisted Systems Theory pruning Data analysis Multivalued function OR Parametric programming fuzzy neurons Logical programming Neural network genetic algorithms Fuzzy neural nets Function decomposition Fuzzy logic interactive network design Genetic algorithm fuzzy logic network interpretation OR/AND fuzzy neuron AND logic operations
ISSN:	1045-9227, 1941-0093
Online Access:	Get full text
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