论文信息 - Fault Detection and Classification in Analogue Integrated Circuits using Robust Heteroscedastic Probabilistic Neural Networks - 字舞流文

Fault Detection and Classification in Analogue Integrated Circuits using Robust Heteroscedastic Probabilistic Neural Networks

A new neural network method has been used to distinguish faulty from fault-free circuit responses. This technique is significantly more accurate than other classification methods. A set of responses can be classified in the order of 1 second.

Mark Zwolinski | C. D. Chalk | Z. R. Yang | Z. R. Yang | Mark Zwolinski | C. Chalk

[1] B. W. Jervis,et al. Diagnosis of multifaults in analogue circuits using multilayer perceptrons , 1997 .

[2] D. F. Specht,et al. Probabilistic neural networks for classification, mapping, or associative memory , 1988, IEEE 1988 International Conference on Neural Networks.

[3] E. Parzen. On Estimation of a Probability Density Function and Mode , 1962 .

[4] Edgar Sanchez-Sinencio,et al. Analog fault diagnosis based on ramping power supply current signature clusters , 1996 .

[5] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[6] Christopher M. Bishop,et al. GTM: A Principled Alternative to the Self-Organizing Map , 1996, NIPS.

[7] Donald F. Specht,et al. Probabilistic neural networks , 1990, Neural Networks.

[8] Rupert G. Miller. The jackknife-a review , 1974 .

[9] Mark Zwolinski,et al. Generation and verification of tests for analogue circuits subject to process parameter deviations , 1997, 1997 IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems.

[10] Roy L. Streit,et al. Maximum likelihood training of probabilistic neural networks , 1994, IEEE Trans. Neural Networks.

[11] I. M. Bell,et al. Neural network approach to fault diagnosis in CMOS opamps with gate oxide short faults , 1994 .

[12] Teuvo Kohonen,et al. Self-Organization and Associative Memory , 1988 .