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Towards Robustness in Neural Network Based Fault Diagnosis
2008
International Journal of Applied Mathematics and Computer Science
Towards Robustness in Neural Network Based Fault Diagnosis Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as neural networks become more and more popular in industrial applications of fault diagnosis. Taking into account the two crucial aspects, i.e., the nonlinear behaviour of the system being
doi:10.2478/v10006-008-0039-2
fatcat:l4xnrnjhsfavpjtkjee7gbdzzm