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The increase in signal switching speed and density of digital circuits leads to the crosstalk faults of interconnection lines,
which may cause undesirable effects and even logic errors in the circuit. A new test method based on the neural network
models of digital circuits is proposed in this paper for the crosstalk faults in digital circuits. The neural network
corresponding to digital circuit is built, and the test vectors of the crosstalk faults are generated by computing the
minimum energy states of neural network. A chaotic evolutionary strategies algorithm is designed to compute the
minimum energy states. The algorithm combines the features of chaotic systems and evolutionary strategies, and takes
full advantages of the stochastic properties and global search ability of the two techniques. Experimental results on a lot
of benchmark circuits show that the approach proposed in this paper can be used to get the test vectors of the crosstalk
faults if the crosstalk faults are testable.e
Zhongliang Pan,Ling Cheng, andGuangzhao Zhang
"Test method based on neural network for crosstalk faults in digital circuits", Proc. SPIE 7133, Fifth International Symposium on Instrumentation Science and Technology, 713306 (12 January 2009); https://doi.org/10.1117/12.810608
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Zhongliang Pan, Ling Cheng, Guangzhao Zhang, "Test method based on neural network for crosstalk faults in digital circuits," Proc. SPIE 7133, Fifth International Symposium on Instrumentation Science and Technology, 713306 (12 January 2009); https://doi.org/10.1117/12.810608