Neural networks and dynamical systems
International Journal of Approximate Reasoning - Special issue on fuzzy logic and neural networks for pattern recognition and control
Obtaining Fault Tolerant Multilayer Perceptrons Using an Explicit Regularization
Neural Processing Letters
IEEE Transactions on Neural Networks
The Impact of Arithmetic Representation on Implementing MLP-BP on FPGAs: A Study
IEEE Transactions on Neural Networks
A Fault-Tolerant Regularizer for RBF Networks
IEEE Transactions on Neural Networks
Complete and partial fault tolerance of feedforward neural nets
IEEE Transactions on Neural Networks
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This paper studies the performance of faulty RBF networks when stuck-at-zero node fault and stuck-at-one node fault happen. An objective function for training fault tolerant RBF networks for node fault is first derived. A training learning algorithm for faulty RBF networks is then presented. Finally, a mean prediction error formula which can estimate the test set error of faulty networks is derived. Simulation experiments are then performed to verify our theoretical result.