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Fault characterization of a multilayered perceptron network
Chang H. Tan,
Ravishankar K Iyer
Electrical and Computer Engineering
National Center for Supercomputing Applications (NCSA)
Carl R. Woese Institute for Genomic Biology
Coordinated Science Lab
Information Trust Institute
Biomedical and Translational Sciences
Siebel School of Computing and Data Science
Center for Global Studies
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Keyphrases
Fault Characterization
100%
Misclassified
100%
Multilayered Perceptron Network
100%
Transient Fault
66%
Classification Network
66%
Simulation Experiment
33%
Three-layered
33%
Output Value
33%
Node Failure
33%
Misclassification
33%
Permanent Fault
33%
Hardware Redundancy
33%
Perception Model
33%
Link Faults
33%
Engineering
Transients
100%
Perceptron
100%
Classification Network
66%
Nodes
33%
Output Value
33%
Misclassification
33%
Simulation Experiment
33%
Perception Model
33%
Computer Science
Transient Fault
100%
Simulation Experiment
50%
Permanent Fault
50%
Hardware Redundancy
50%
Biochemistry, Genetics and Molecular Biology
Perceptron
100%
Learning
100%