Fault diagnosis in analog circuits using multiclass Relevance Vector Machine

In this paper the capability of Relevance Vector Machines to perform multiclass classification has been illustrated. It has been demonstrated how faults in an analog circuit can be diagnosed by analyzing these faults as a multiclass machine learning problem. A simple first order Op-amp RC circuit validates our methodology which can be further applied to more complex analog circuits employing a larger number of electronic components.