Application of support vector regression to vulnerability assessment of electronic devices illuminated or injected by high power microwave

Aiming at the problems that the existing methods based on the probability statistical theory and the fuzzy neural network method must be built on the foundation of large quantities of statistical data, and the failure thresholds of electronic devices estimated by the fuzzy information diffusion could be higher than the actual ones, a new method is presented that the raw experimental data are processed by the fuzzy information processing technology to obtain the training samples, on the basis of which the damage probabilities of electronic devices illuminated or injected by the high power microwave are predicted by support vector regression. The simulation results show that the fuzzy neural network and the new method both achieve good prediction results. But the results of the latter are more accurate and it overcomes the defect that errors could occur in the results predicted by the fuzzy neural network under the condition of small samples.