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Fault Tolerance for faults in Artificial Neural Networks (in English)
Saritha V
(Author)
·
LAP Lambert Academic Publishing
· Paperback
Fault Tolerance for faults in Artificial Neural Networks (in English) - V, Saritha
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Synopsis "Fault Tolerance for faults in Artificial Neural Networks (in English)"
This bookk addresses the fault tolerance of RBF networks where all hidden nodes have the same fault rate and their fault probabilities are independent. Assuming that there is a Gaussian distributed noise in the output data, we have derived an objective function for robustly training an RBF network based on the Kullback-Leibler divergence. We also find that for a fault-tolerance regularizer some eigenvalues of the regularization matrix should be negative. For the Tipping's regularizer and the OLS regularizer, the regularization matrices are positive or semipositive definite. Hence, they cannot efficiently handle the multinode open fault.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
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