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When designing a neural or fuzzy system, a careful preprocessing of the database is of utmost importance in order to produce a trustable system. In function approximation applications, when a functional relationship between input and output variables is supposed to exist, the presence of data where the similar set of input variables is associated to very different values of the output is not always...
In this paper, an online fault diagnosis scheme for nonlinear systems is derived from fuzzy rules extracted from the neurofuzzy network that models the residuals of the system. As the neurofuzzy network is updated online by the recursive least squares method, the proposed technique is able to diagnose faults online. To initiate the fault diagnosis scheme, a binary or real-valued fault database is...
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