Receptive field optimisation and supervision of a fuzzy spiking neural network

Neural Networks

Volumn 24, Issue 3, 2011, Pages 247-256

  Glackin, Cornelius ^a   Maguire, Liam ^a   McDaid, Liam ^a   Sayers, Heather ^a  

^a UNIVERSITY OF ULSTER   (United Kingdom)

Author keywords

Clustering methods; Evolutionary algorithms; Receptive fields; Spiking neural network; Supervised learning

Indexed keywords

BENCHMARK CLASSIFICATION; BREAST CANCER; CLUSTERING METHODS; COMPACT SOLUTIONS; FEATURE DATA; FIRING RATES; FUZZY C MEANS CLUSTERING; FUZZY MEMBERSHIP FUNCTION; FUZZY REASONING; FUZZY RULE BASE; NETWORK TOPOLOGY; OPTIMISATIONS; OUTPUT LAYER; RECEPTIVE FIELDS; SMALL DATA SET; SPIKE TRAIN; SPIKING NEURAL NETWORK; SPIKING NEURAL NETWORKS; SUPERVISED TRAINING ALGORITHM; THRESHOLDING; WISCONSIN;

CLUSTERING ALGORITHMS; ELECTRIC NETWORK TOPOLOGY; EVOLUTIONARY ALGORITHMS; FUZZY CLUSTERING; FUZZY RULES; FUZZY SYSTEMS; KNOWLEDGE BASED SYSTEMS; LAKES; LEARNING ALGORITHMS; MEMBERSHIP FUNCTIONS; SUPERVISED LEARNING;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; CLUSTER ANALYSIS; FUZZY SYSTEM; GENETIC ALGORITHM; LEARNING; NERVE CELL; PRIORITY JOURNAL; RECEPTIVE FIELD; SPIKE;

ACTION POTENTIALS; ANIMALS; ARTIFICIAL INTELLIGENCE; FEMALE; FUZZY LOGIC; HUMANS; NEURAL NETWORKS (COMPUTER); NEURONS;

EID: 79951514022     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2010.11.008     Document Type: Article

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