Details

Title

A Novel Approach of Analog Fault Classification Using a Support Vector Machines Classifier

Journal title

Metrology and Measurement Systems

Yearbook

2010

Issue

No 4

Authors

Keywords

analog circuits ; fault classification ; Support Vector Machines Classifier ; Neural Networks ; wavelet packet decomposition

Divisions of PAS

Nauki Techniczne

Coverage

561-581

Publisher

Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation

Date

2010

Type

Artykuły / Articles

Identifier

DOI: 10.2478/v10178-010-0046-0 ; ISSN 2080-9050, e-ISSN 2300-1941

Source

Metrology and Measurement Systems; 2010; No 4; 561-581

References

Catelani M. (2002), A fuzzy approach for soft fault detection in analog circuits, Meas, 32, 73. ; Spina R. (1997), Linear circuit fault diagnosis using neuro-morphic analyzers, IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process, 44, 3, 188. ; Aminian F. (2001), Fault Diagnosis of Nonlinear Analog Circuits Using Neural Networks with Wavelet and Fourier Transforms as Preprocessors, J. Electron. Test.: Theory Appl, 17, 471. ; El-Gamal M. (1999), A Combined Clustering and Neural Network Approach for Analog Multiple Hard Fault Classification, J. Electron. Test.: Theory Appl, 14, 207. ; Yanghong T. (2008), A novel method for fault diagnosis of analog circuits based on WP and GPNN, Int. J. Electron, 95, 5, 431. ; Aminian M. (2007), A Modular Fault-Diagnostic System for Analog Electronic Circuits Using Neural Networks With Wavelet Transform as a Preprocessor, IEEE Trans. Instrum. Meas, 56, 5, 1546. ; Fanni A. (1999), A Neural Network diagnosis Approach for analog circuits, Appl. Intell, 11, 2, 169. ; Yigang H. (2004), Fault Diagnosis of Analog Circuits based on Wavelet Packets, null, 267. ; Catelani M. (2002), Soft Fault Detection and Isolation in Analog Circuits: Some Results and a Comparison between a Fuzzy Approach and Radial Basis Function Networks, IEEE Trans. Instrum. Meas, 51, 2, 196. ; Salat R. (2003), Analog Filter Diagnosis Using Support Vector Machine, null, 421. ; Siwek K. (2006), Support Vector Machine for Fault Diagnosis in Electrical Circuits, null, 342. ; Grzechca D. (2009), Fault Diagnosis in Analog Electronic Circuits - The SVM Approach, Metrol. Meas. Syst, 16, 4, 583. ; Vapnik V. (1998), Statistical Learning Theory. ; Hsu C. (2002), A Comparison of Methods for Multi-class Support Vector Machines, IEEE Trans. Neural Networks, 13, 2, 415. ; Chapelle O. (1999), Support Vector Machines for histogram-based image classification, IEEE Trans. Neural Networks, 10, 5, 1055. ; Takahashi F. (2002), Decision-Tree-Based Multi-Class Support Vector Machines, null, 1418. ; Burges C. (1998), A Tutorial on Support Vector Machines For Pattern Recognition, Data Min. Knowl. Disc, 2, 2, 121. ; <a target="_blank" href='http://www.princeton.edu/~kung/ele571/571-MatLab/571svm/'>http://www.princeton.edu/~kung/ele571/571-MatLab/571svm/</a>
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