Multilayer feedforward networks are universal approximators
Neural Networks
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Neural network design
TAO-robust backpropagation learning algorithm
Neural Networks
Robust LTS backpropagation learning algorithm
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Robust error measure for supervised neural network learning with outliers
IEEE Transactions on Neural Networks
The annealing robust backpropagation (ARBP) learning algorithm
IEEE Transactions on Neural Networks
Fast robust learning algorithm dedicated to LMLS criterion
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Robust neural network for novelty detection on data streams
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Robust Learning Algorithm Based on Iterative Least Median of Squares
Neural Processing Letters
| Hi-index | 0.01 |
Training data containing outliers are often a problem for supervised neural networks learning methods that may not always come up with acceptable performance. In this paper a new, robust to outliers learning algorithm, employing the concept of initial data analysis by the MCD (minimum covariance determinant) estimator, is proposed. Results of implementation and simulation of nets trained with the new algorithm and the traditional backpropagation (BP) algorithm and robust Lmls are presented and compared. The better performance and robustness against outliers for the new method are demonstrated.