Ten lectures on wavelets
Kolmogorov's theorem and multilayer neural networks
Neural Networks
Neural networks for pattern recognition
Neural networks for pattern recognition
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
An Introduction to Neural Networks
An Introduction to Neural Networks
Approximate Dynamic Programming: Solving the Curses of Dimensionality (Wiley Series in Probability and Statistics)
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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Within the framework of aging materials inspection, one of the most important aspects regards defects detection in metal welded strips. In this context, it is important to plan a method able to distinguish the presence or absence of defects within welds as well as a robust procedure able to characterize the defect itself. In this paper an innovative solution that exploits a rotating magnetic field is presented. This approach has been carried out by a Finite Element Model. Within this framework, it is necessary to consider techniques able to offer advantages in terms of sensibility of analysis, strong reliability, speed of carrying out, low costs: its implementation can be a useful support for inspectors. To this aim, it is necessary to solve inverse problems which are mostly ill-posed: in this case, the main problems consist on both the accurate formulation of the direct problem and the correct regularization of the inverse electromagnetic problem. In the last decades, a useful and very performing way to regularize ill-posed inverse electromagnetic problems is based on the use of a Neural Network approach, the so called "learning by sample techniques".