1992
DOI: 10.1117/12.57079
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<title>Application of an adaptive fuzzy system to clustering and pattern recognition</title>

Abstract: This paper presents a modular, unsupervised neural network architecture which can be used for clustering and classification of complex data sets. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a conventional fuzzy K-means clustering algorithm as a learning rule embedded within a control structure similar to that found in the Adaptive Resonance Theory (ART-i) network. AFLC adaptively clusters analog … Show more

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