Comparison of defect compensation methods for feedforward neural networks

Proceedings of IEEE Pacific Rim International Symposium on Dependable Computing, PRDC

Volumn 2002-January, Issue , 2002, Pages 293-300

  Takahashi, Kin'ya ^a   Horiguchi, Susumu ^b   Yamamori, Kunihito ^a   Yoshihara, Ikuo ^a  

^a UNIVERSITY OF MIYAZAKI   (Japan)

^b JAPAN ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY   (Japan)

Author keywords

Fault tolerance; Feedforward neural networks; Feedforward systems; Image recognition; Information science; Large scale integration; Neural network hardware; Neural networks; Neurons; Robustness

Indexed keywords

ALGORITHMS; BACKPROPAGATION ALGORITHMS; DEFECTS; FAULT TOLERANCE; HARDWARE; IMAGE RECOGNITION; INFORMATION SCIENCE; LSI CIRCUITS; NEURAL NETWORKS; NEURONS; ROBUSTNESS (CONTROL SYSTEMS); WORLD WIDE WEB;

COMPENSATION METHOD; DEFECT COMPENSATION; FACE IMAGE RECOGNITION; FEEDFORWARD SYSTEMS; GENERALIZATION ABILITY; HARDWARE DEVICES; NEURAL NETWORK HARDWARE; QUANTITATIVE COMPARISON;

FEEDFORWARD NEURAL NETWORKS;

EID: 84948773205     PISSN: 15410110     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PRDC.2002.1185649     Document Type: Conference Paper

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