Granular neural networks and their development through context-based clustering and adjustable dimensionality of receptive fields

IEEE Transactions on Neural Networks

Volumn 20, Issue 10, 2009, Pages 1604-1616

  Park, Ho Sung ^a   Pedrycz, Witold ^b,c   Oh, Sung Kwun ^a  

^a Suwon University   (South Korea)

^b UNIVERSITY OF ALBERTA   (Canada)

^c SYSTEMS RESEARCH INSTITUTE   (Poland)

Author keywords

Context based fuzzy clustering; Genetic algorithm (GA); Information granules; Proximity; Radial basis function neural network (RBFNN)

Indexed keywords

CLUSTERING TECHNIQUES; COMPARATIVE ANALYSIS; COMPREHENSIVE DESIGNS; CONTEXT-BASED; CONTEXT-BASED FUZZY CLUSTERING; DYNAMIC REDUCTION; FUZZY C MEAN; GENETIC OPTIMIZATION; INFORMATION GRANULES; INPUT SPACE; INPUT VARIABLES; K-MEANS CLUSTERING; MACHINE LEARNING REPOSITORY; PROXIMITY; RADIAL BASIS FUNCTION NEURAL NETWORK (RBFNN); RADIAL BASIS FUNCTION NEURAL NETWORKS; RECEPTIVE FIELDS; STANDARD ARCHITECTURE; SYNTHETIC DATA; TRAINING DATA; UNIVERSITY OF CALIFORNIA;

ADAPTIVE FILTERING; ATTITUDE CONTROL; CLUSTER ANALYSIS; COMBINATORIAL MATHEMATICS; FUZZY CLUSTERING; FUZZY SYSTEMS; GENETIC ALGORITHMS; GRANULATION; LEARNING ALGORITHMS; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS;

CLUSTERING ALGORITHMS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; BIOMIMETICS; COMPUTER SIMULATION; METHODOLOGY; THEORETICAL MODEL;

BIOMIMETICS; COMPUTER SIMULATION; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 70350272885     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2009.2027319     Document Type: Article

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