Stopjakova V, Malosek P, Micusik D, et al. Classification of defective analog integrated circuits using artificial neural networks[J]. Journal of Electronic Testing: Theory and Applications, 2004: 20(1): 25-37
[3]
Wang P, Yang S. A new diagnosis approach for handling tolerance in analog and mixed- signal circuits by using fuzzy math [J]. IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, 2005, 52(10): 2118-2127
Wang Anna, Qiu Zeng, Wu Jie, et al. SVM-based multi-classifying algorithm for soft fault diagnosis of analog circuits[J]. Journal of Northeastern University (Natural Science), 2008, 29(7): 924-927.
Aminian F, Aminian M. Neural-network based analog-circuit fault diagnosis using wavelet transform as preprocessor[J]. IEEE Transactions on Circuits and System II: Analog and Digital Signal Processing, 2000, 47(2): 151-156.
[12]
Alippi C, Catelani M, Fort A, et al. Automated selection of test frequencies for fault diagnosis in analog electronic circuits[J]. IEEE Transactions on Instrumentation and Measurement, 2005, 54(3): 1033- 1044.
[13]
Zhang Wei, Shen Shituan, Li Yihua. Output response- oriented fault detection and isolation under multifrequency test[J]. Journal of Telemetry Trackingm and Command, 2003, 24(6): 43-46.
Zhong Jianlin, He You, Wang Hongxing. Circuit fault diagnosis based on multi-frequency wavelet analysis and D-S reasoning[J]. Transactions of China Electrotechnical Society, 2010, 25 (8): 180-184.
Peng Minfang, He Yigang. A fuzzy soft fault dictionary method for diagnosis of analog circuits with tolerance[J]. Journal of Hunan University (Natural Sciences), 2005, 32(1): 25-28.
[19]
Ma Yanheng, Liu Lin. The study of waveform fuzzy identification based on VXIbus measurement[J]. Journal of University of Electronic Science and Techonogy of China, 2001, 30(16): 625-628.