Divide-and-conquer methodology for modular supervised neural network design

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 1, Issue , 1994, Pages 119-124

  Chiang, Cheng Chin ^a   Fu, Hsin Chia ^a  

^a INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; ARTIFICIAL INTELLIGENCE; CORRELATION METHODS; ERRORS; LEARNING SYSTEMS; MATHEMATICAL MODELS; PATTERN RECOGNITION;

DIFFICULT TO LEARN PATTERNS; DIVIDE AND CONQUER METHODOLOGY; ERROR CORRELATION PARTITIONING; FUNCTION APPROXIMATION; LEARNING SPEED; MODULAR SUPERVISED NEURAL NETWORK; TRAINING ERROR; TRAINING PATTERNS;

NEURAL NETWORKS;

EID: 0028740629     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)