Title :
Fault Diagnosis of Circuits with Tolerance Based on Support Vector Machines
Author :
Wang, Aiping ; Bumin, Liu ; Zeng, Qiu ; Hua, Li
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeast Univ., Shenyang
Abstract :
There are many difficulties in diagnosis of analog circuits with tolerance because of the uncertainty characteristic the circuits, it is proposed to construct fault classifiers using the support vector machines (SVMs) algorithm. The fault classifiers based on SVMs can realize precise fault diagnosis even when a few samples are gotten, they have better generality and practicality too. Experiment shows the diagnosis method based on SVMs technique for analog circuits with tolerance types can completely overcome the limitations from some conventional classification methods such as neural networks, achieve nonlinear partition and solve the essential recognition problem for analog circuits with tolerance fault types
Keywords :
analogue circuits; circuit reliability; fault diagnosis; fault tolerance; support vector machines; SVM classifier; analog circuit; fault diagnosis; fault tolerance; support vector machine; Analog circuits; Circuit faults; Circuit testing; Fault diagnosis; Information science; Neural networks; Pattern recognition; Risk management; Support vector machine classification; Support vector machines;
Conference_Titel :
Communications, Circuits and Systems Proceedings, 2006 International Conference on
Conference_Location :
Guilin
Print_ISBN :
0-7803-9584-0
Electronic_ISBN :
0-7803-9585-9
DOI :
10.1109/ICCCAS.2006.285122