U. Anders-&-o and . Korn, Model selection in neural networks, Neural Networks, vol.12, issue.2, pp.309-323, 1992.
DOI : 10.1016/S0893-6080(98)00117-8

A. Antoniadis, J. Berruyer-&-r, and . Carmona, Régression non linéaire et applications Paris : Economica, 1992 [Aro 94Micro 2x16 II Type "Bas-Plus" Logiciel 7B-8B" Notice d'utilisation, 1993.

J. Bahren, B. Cetin-&-j, and . Burdick, Overcoming Local Minima in Neural Learning, Proceedings de la 6 ème Conférence Internationale Neuro-Nîmes, 1993.

P. L. Barlett, For Valid Generalization, the Size of the Weights is more Important than the Size of the Network

D. M. Bates-&-d and . Watts, Nonlinear Regression Analysis and its Applications, Wiley Series in Probability and Mathematical Statistics, 1988.

C. M. Bishop, Curvature-driven smoothing: a learning algorithm for feedforward networks, IEEE Transactions on Neural Networks, vol.4, issue.5, pp.882-884, 1993.
DOI : 10.1109/72.248466

C. M. Bishop, Neural Networks for Pattern Recognition, 1997.

S. De, S. Methodes-neuronales, Y. Thiria, and . Lechevallier, La mise en oeuvre des idées de V.N. Vapnik" Chapitre 16, 1997.

L. Breiman, Heuristics of instability and stabilization in model selection, The Annals of Statistics, vol.24, issue.6, pp.2350-2383, 1996.
DOI : 10.1214/aos/1032181158

J. D. Brown, M. G. Rodd-&-n, and . Williams, Application of Artificial Intelligence to Resistance Spot Welding, Doc. No. III -1092, 1995.

M. H. Brugge, W. J. Jansen, J. A. Nijhuis, and &. L. Spaanenburg, Non-destructive Test of Spot Welds Using a Neural Network, Proceedings ICAN '95, 1993.

R. Cazes, Le soudage par résistance" Les techniques de l'ingénieur, novembre, 1993.

S. Chen, S. A. Billings-&-w, and . Luo, Orthogonal least squares methods and their application to non-linear system identification, International Journal of Control, vol.10, issue.5, pp.1873-1896, 1989.
DOI : 10.2307/2284566

G. Cybenko, Approximation by superpositions of a sigmoidal function, Mathematics of Control, Signals, and Systems, vol.27, issue.4, pp.303-314, 1989.
DOI : 10.1007/BF02551274

R. D. De-vaux, J. Schumi, J. H. Schweinsberg-&-l, and . Ungar, Prediction Intervals for Neural Networks via Nonlinear Regression, Technometrics, vol.40, issue.4, pp.273-282, 1998.
DOI : 10.2307/1270528

L. P. Devroye-&-t and . Wagner, Distribution-free performance bounds for potential function rules, IEEE Transactions on Information Theory, vol.25, issue.5, pp.601-604, 1979.
DOI : 10.1109/TIT.1979.1056087

U. Dilthey-&-j and . Dickersbach, Quality Assurance of Resistance Spot Welding by Employment of Neural Networks, Doc. No. III -1093, 1997.

G. Dreyfus, L. Personnaz-&-g, and . Toulouse, Perceptrons, Old and New, Enciclopedia Italiana

K. Funahashi, On the approximate realization of continuous mappings by neural networks, Neural Networks, vol.2, issue.3, pp.349-360, 1991.
DOI : 10.1016/0893-6080(89)90003-8

P. Gallinari-14-de, S. Et-methodes-neuronales, S. Thiria, and Y. Lechevallier, Heuristiques pour la généralisation, 1997.

S. Geman, E. Bienenstock-&-r, and . Doursat, Neural Networks and the Bias/Variance Dilemma, Neural Computation, vol.36, issue.1, pp.1-58, 1992.
DOI : 10.1162/neco.1990.2.1.1

P. Gobez, Soudage des tôles revêtues" Les Techniques de l'ingénieur, 1994.

L. K. Hansen-&-j and . Larsen, Linear unlearning for cross-validation, Advances in Computational Mathematics, vol.1, issue.3, pp.269-280, 1994.
DOI : 10.1007/BF02124747

K. Hornik, M. Stinchcombe, H. White-&-p, and . Auer, Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives, Neural Computation, vol.6, issue.6, pp.1262-1275, 1994.
DOI : 10.1016/0893-6080(94)90063-9

N. Ivezic, J. D. Allen-&-t, and . Zacharia, Neural network-based resistance spot welding control and quality prediction, Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IPMM'99 (Cat. No.99EX296), 1994.
DOI : 10.1109/IPMM.1999.791516

M. Jou, An Intelligent Control System for Resistance Spot Welding Using Fuzzy Logic and Neural Networks

M. Jou, R. W. Messler-&-c, and . Li, An Intelligent Control System for Resistance Spot Welding Using a Neural Network and Fuzzy Logic, IEEE Transaction, 1995.

M. Kearns and D. Ron, Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross Validation, to the Tenth Annual Conference on Computational Learning Theory

K. Levenberg, A method for the solution of certain non-linear problems in least squares, Quarterly of Applied Mathematics, vol.2, issue.2, pp.164-168, 1944.
DOI : 10.1090/qam/10666

D. J. Mackay, A Practical Bayesian Framework for Backpropagation Networks, Neural Computation, vol.4, issue.3, pp.448-472, 1992.
DOI : 10.1038/323533a0

D. W. Marquardt, An Algorithm for Least-Squares Estimation of Nonlinear Parameters, Journal of the Society for Industrial and Applied Mathematics, vol.11, issue.2, pp.431-441, 1963.
DOI : 10.1137/0111030

K. I. Matsuyama, Nugget Size Sensing of Spot Weld Based on Neural Network Learning, Doc. No. III -1081, 1997.

A. D. Mcquarrie-&-c and . Tsai, Regression and Time Series Model Selection, 1994.
DOI : 10.1142/3573

R. W. Messler, M. J. Jou-&-c, and . Li, A Fuzzy Logic Control System for Resistance Spot Welding Based on a Neural Network Model, Proceedings of Sheet Metal Welding Conference N° 6, AWS, 1994.

J. Moody, Prediction Risk and Neural Network Architecture Selection" From Statistics to Neural Networks : Theory and Pattern Recognition Applications, 1990.

J. C. Nash, Compact Numerical Methods for Computers : Linear Algebra and Function Minimisation, 1990.

M. C. Nelson-&-w and . Illingworth, A Practical Guide to Neural Nets, 1991.

K. A. Osman, A. M. Higginson, H. R. Kelly, C. J. Newton-&-d, and . Boomer, Monitoring of Resistance Spot-Welding Using Multi-Layer Perceptrons, Proceedings Autotech '95, 1995.

L. Oukhellou, P. Aknin, H. Stoppiglia-&-g, and . Dreyfus, A new Decision Criterion for Feature Selection : Application to the Classification of Non Destructive Testing Signature, European Signal Processing Conference (EUSIPCO'98), 1998.

Y. Oussar, Réseaux d'ondelettes et réseaux de neurones pour la modélisation statique et dynamique de processus, 1998.