TAO-robust backpropagation learning algorithm

Neural Networks

Volumn 18, Issue 2, 2005, Pages 191-204

  Pernía Espinoza, Alpha V ^a   Ordieres Meré, Joaquín B ^a   Martínez De Pisón, Francisco J ^a   González Marcos, Ana ^b  

^a UNIVERSITY OF LA RIOJA   (Spain)

^b UNIVERSITY OF LEÓN   (Spain)

Author keywords

Neural networks; Outliers; Robust learning algorithm; Robust modelling

Indexed keywords

APPROXIMATION THEORY; BACKPROPAGATION; DATA REDUCTION; FUNCTIONS; MATHEMATICAL MODELS; NEURAL NETWORKS; REGRESSION ANALYSIS; ROBUSTNESS (CONTROL SYSTEMS);

COST FUNCTIONS; INDUSTRIAL MODELING; MEAN SQUARED ERROR (MSE); TAO-ROBUST PROPAGATION;

LEARNING ALGORITHMS;

ALGORITHM; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; COST BENEFIT ANALYSIS; LEARNING; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; NONLINEAR SYSTEM; PRIORITY JOURNAL; REGRESSION ANALYSIS; TRAINING;

ALGORITHMS; ANIMALS; COMPUTER SIMULATION; HUMANS; LEARNING; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; ROBOTICS;

EID: 15944426684     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2004.11.007     Document Type: Article

References (17)

1. M. Ahmed, and A. Farag A neural approach to zoom-lens camera calibration from data with outliers Image and Vision Computing 20 2002 619 630
2. M. Castejón-Limas, J. Ordieres-Meré, F. Martínez de Pisón, and E. Vergara-González Outlier detection and data cleaning in multivariate non-normal samples: The PAELLA algorithm Data Mining and Knowledge Discovery 9 2003 171 187
3. D.S. Chen, and R.C. Jain A robust backpropagation learning algorithm for function approximation IEEE Transactions on Neural Network 5 1994 467 479
4. C.-C. Chuang, S.-F. Su, and C.-C. Hsiao The annealing robust backpropagation (ARBP) learning algorithm IEEE Transactions on Neural Networks 11 5 2000 1067 1077
5. J.T. Connor, R.D. Martin, and L.E. Atlas Recurrent neural networks and robust time series prediction IEEE Transaction on Neural Network 5 1994 240 254
6. Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., & Stahel, W. A. (1986). Robust statistics, the approach based of influence functions. New York: Wiley.
7. D.M. Hawkins Identification of outliers 1980 Chapman and Hall London
8. B.L. Huang, B.L. Zhang, and Q. Huang Robust interval regression analysis using neural network Fuzzy Sets Systems 1998 337 347
9. P.J. Huber Robust statistics 1981 Wiley New York
10. K. Liano Robust error measure for supervised neural network learning with outliers IEEE Transactions on Neural Networks 7 1 1996 246 250
11. Martín B. & Sanz A. (2001). Redes Neuronales y Sistemas Borrosos. Madrid, ra-ma.
12. McDowall, T. M., & Ham, F. M. (1997). Robust partial least-squares regression: A modular neural network approach. Proceedings: SPIE, 3077, 344-355.
13. P. Rousseeuw, and A. Leroy Robust regression and outlier detection 1987 Wiley New York
14. Rousseeuw, P. J., & Yohai, V. J. (1984). Robust regression by means of S-estimators. In J. Franke, W. Hardle, & R. D. Martin (Eds.), Robust and nonlinear time series. Lecture notes in statistics No. 26 (pp. 256-272). New York: Springer.
15. M.A. Tabatabai, and I.K. Argyros Robust estimation and testing for general nonlinear regression models Applied Mathematics and Computation 58 1993 85 101
16. B. Walczak Neural networks with robust backpropagation learning algorithm Analytica Chimica Acta 322 1996 21 29
17. V. Yohai, and R. Zamar High breakdown-point estimates of regression bye means of the minimization of an efficient scale Journal of the American Statistical Association 83 402 1988 406 413