Knowledge extraction from evolving spiking neural networks with rank order population coding

International Journal of Neural Systems

Volumn 20, Issue 6, 2010, Pages 437-445

  Soltic, Snjezana ^a,b   Kasabov, Nikola ^b  

^a MANUKAU INSTITUTE OF TECHNOLOGY   (New Zealand)

^b AUCKLAND UNIVERSITY OF TECHNOLOGY   (New Zealand)

Author keywords

Evolving spiking neural networks; fuzzy rules; knowledge discovery; rank order population coding; SNN

Indexed keywords

ARTIFICIAL NEURAL NETWORK; END USERS; FUZZY IF-THEN RULES; FUZZY RULE EXTRACTION; HIGH LEVEL KNOWLEDGE; KNOWLEDGE DISCOVERY; KNOWLEDGE EXTRACTION; POPULATION CODING; RANK ORDER; SNN; SPIKING NETWORKS; SPIKING NEURAL NETWORKS; TAKAGI-SUGENO; THIRD GENERATION;

FUZZY RULES; INTELLIGENT AGENTS; INTELLIGENT SYSTEMS; KNOWLEDGE REPRESENTATION;

FUZZY NEURAL NETWORKS;

ACTION POTENTIAL; ALGORITHM; ANIMAL; ARTICLE; BIOLOGICAL MODEL; CYTOLOGY; FUZZY LOGIC; HUMAN; INFORMATION RETRIEVAL; KNOWLEDGE; NERVE CELL; NERVE CELL NETWORK; PHYSIOLOGY;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; FUZZY LOGIC; HUMANS; INFORMATION STORAGE AND RETRIEVAL; KNOWLEDGE; MODELS, NEUROLOGICAL; NERVE NET; NEURONS;

EID: 78649583381     PISSN: 01290657     EISSN: None     Source Type: Journal    
DOI: 10.1142/S012906571000253X     Document Type: Article

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