- Tytuł:
- Analog Circuit Fault Classification Using Improved One-Against-One Support Vector Machines
- Autorzy:
-
Cui, J.
Wang, Y. - Powiązania:
- https://bibliotekanauki.pl/articles/220569.pdf
- Data publikacji:
- 2011
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
analog circuit
fault classification
Support Vector Machines Classifier
fault dictionary
kernel parameter - Opis:
- 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 radial-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.
- Źródło:
-
Metrology and Measurement Systems; 2011, 18, 4; 569-582
0860-8229 - Pojawia się w:
- Metrology and Measurement Systems
- Dostawca treści:
- Biblioteka Nauki
Artykuł