Isbn: 9786200324030 - fault tolerance for faults in artificial neural networks: robust fault tolerance for multinode faults in rbf neural networks (9 Ergebnisse)

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Taschenbuch. Zustand: Neu. Fault Tolerance for faults in Artificial Neural Networks | Robust Fault Tolerance for Multinode faults in RBF Neural Networks | Saritha V | Taschenbuch | 64 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200324030 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 64 pp. Englisch.…

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: V SarithaSaritha, presently works as Assistant Professor in VRSiddhartha Engineering College, Vijayawada. Shegraduated in E.C.E from Adams Engineering College in2002 and M.Tech in Digital Electronics andcommunication systems from JNT.…

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.…