Test method based on neural network for crosstalk faults in digital circuits

摘要：

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.

关键词： Digital circuits crosstalk faults test generation fault detection neural networks

作者: Pan Zhongliang Chen Ling Zhang Guangzhao

作者单位: School of Physics and Telecommunications Engineering, South China Normal University,Guangzhou 510006 Department of Electronics and Communications, Sun Yat-sen University, Guangzhou 510275, China

会议类型: 国际会议

会议名称: 第五届仪器科学与技术国际学术会议(ISIST 2008)Fifth International Symposium on Instrmentation Science and Technology

会议地点: 沈阳

会议语种:英文

页码: 1-7

在线出版日期: 2008-09-15（万方平台首次上网日期，不代表论文的发表时间）