Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
A Mathematical Model for Integrated Diagnostics
IEEE Design & Test
Analog and Mixed-Signal Benchmark Circuits-First Release
Proceedings of the IEEE International Test Conference
ICCIMA '03 Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications
Classification of Defective Analog Integrated Circuits Using Artificial Neural Networks
Journal of Electronic Testing: Theory and Applications
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A novel fault diagnosis approach is presented for analog circuits where the accessible test points are limited and insensitive enough to some fault components. The wavelet analysis as a tool to extract the fault samples makes good use of the fault information from the test points. Applying immune algorithm to obtain the clustering center of corresponding fault mode is satisfactory on convergence and accuracy. A fuzzy approach localizes the fault component according to the membership degrees of the test sample to the clustering centers of the standard fault modes. The results of the simulation experiment show that the proposed approach is effective and practicable.