Operation and modeling of the MOS transistor
Operation and modeling of the MOS transistor
Advances in neural information processing systems 2
Regularization theory and neural networks architectures
Neural Computation
Handbook of mathematics (3rd ed.)
Handbook of mathematics (3rd ed.)
Computer organization and design (2nd ed.): the hardware/software interface
Computer organization and design (2nd ed.): the hardware/software interface
di/dt Noise in CMOS Integrated Circuits
Analog Integrated Circuits and Signal Processing - Special issue: analog design issues in digital VSLI circuits and systems
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Structured Computer Organization
Structured Computer Organization
The Handbook of Brain Theory and Neural Networks
The Handbook of Brain Theory and Neural Networks
Feature selection with neural networks
Pattern Recognition Letters
Sensitive Analysis of Radial Basis Function Networks for Fault Tolerance Purposes
IWANN '99 Proceedings of the International Work-Conference on Artificial and Natural Neural Networks: Foundations and Tools for Neural Modeling
TAO-robust backpropagation learning algorithm
Neural Networks
Neural Computation
Perfect Fault Tolerance of the n-k-n Network
Neural Computation
Investigating the Fault Tolerance of Neural Networks
Neural Computation
Design of Analog CMOS Integrated Circuits
Design of Analog CMOS Integrated Circuits
Tolerance of radial basis functions against stuck-at-faults
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Feedforward sigmoidal networks - equicontinuity and fault-tolerance properties
IEEE Transactions on Neural Networks
A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation
IEEE Transactions on Neural Networks
Encoding strategy for maximum noise tolerance bidirectional associative memory
IEEE Transactions on Neural Networks
Sensitivity to noise in bidirectional associative memory (BAM)
IEEE Transactions on Neural Networks
A constructive method for multivariate function approximation by multilayer perceptrons
IEEE Transactions on Neural Networks
Complete and partial fault tolerance of feedforward neural nets
IEEE Transactions on Neural Networks
Beyond Travel & Tourism competitiveness ranking using DEA, GST, ANN and Borda count
Expert Systems with Applications: An International Journal
Pareto-optimal noise and approximation properties of RBF networks
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
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Neural networks are intended to be used in future nanoelectronic technology since these architectures seem to be robust to malfunctioning elements and noise in its inputs and parameters. In this work, the robustness of radial basis function networks is analyzed in order to operate in noisy and unreliable environment. Furthermore, upper bounds on the mean square error under noise contaminated parameters and inputs are determined if the network parameters are constrained. To achieve robuster neural network architectures fundamental methods are introduced to identify sensitive parameters and neurons.