Analog Circuit Fault Classification Using Improved One-Against-One Support Vector Machines

Jiang Cui, Youren Wang
2011 Metrology and Measurement Systems  
This paper presents a novel strategy of fault classification for the analog circuit under test (CUT). The proposed classification strategy is implemented with the one-against-one Support Vector Machines Classifier (SVC), which is improved by employing a fault dictionary to accelerate the testing procedure. In our investigations, the support vectors and other relevant parameters are obtained by training the standard binary support vector machines. In addition, a technique of
more » ... adial-basis-function (RBF) kernel parameter evaluation and selection is invented. This technique can find a good and proper kernel parameter for the SVC prior to the machine learning. Two typical analog circuits are demonstrated to validate the effectiveness of the proposed method.
doi:10.2478/v10178-011-0055-7 fatcat:ssif56csu5fnndjstaifcrd5vu