| 神经网络和优化算法在数字系统测试中的应用 |
| |
| 引用本文： | 陆广平,王友仁. 神经网络和优化算法在数字系统测试中的应用[J]. 计算机测量与控制, 2006, 14(2): 164-165,174 |
| |
| 作者姓名： | 陆广平 王友仁 |
| |
| 作者单位： | 南京航空航天大学自动化学院,江苏,南京,210016;南京航空航天大学自动化学院,江苏,南京,210016 |
| |
| 摘 要： | 介绍了用Hopfield神经网络模型把组合电路测试转化为相应的能量函数，采用遗传算法、最速下降法结合模拟退火法的优化算法来求解给定故障的测试矢量；通过并行故障仿真检验测试矢量集的故障覆盖率，并压缩测试矢量集，然后将电路响应序列Q移入特征多项式求得特征R，由此建立故障字典。
|
| 关 键 词： | 神经网络 优化算法 测试矢量 特征序列 故障字典 |
| 文章编号： | 1671-4598（2006）02-0164-02 |
| 收稿时间： | 2005-06-11 |
| 修稿时间： | 2005-06-112005-07-28 |
Application of Neural Network and Optimization Algorithm in the Test of Digital System |
| |
| Lu Guangping,Wang Youren. Application of Neural Network and Optimization Algorithm in the Test of Digital System[J]. Computer Measurement & Control, 2006, 14(2): 164-165,174 |
| |
| Authors: | Lu Guangping Wang Youren |
| |
| Affiliation: | College of Automation Engineering , NUAA, Nanjing 210016 China |
| |
| Abstract: | Combinational circuits are converted into energy functions with Hopfield neural network models, optimization algorithm of genetic algorithm and fast descent annealing algorithm are used to obtain test vectors of stuck faults. Fault coverage of test vectors are detected through parallel fault simulation, test vectors are compacted, then character sequences are obtained through shifting response sequences to character multinomial, in conclusion fault dictionary is built. |
| |
| Keywords: | neural network optimization algorithm test vectors LFSR analysis fault dictionary |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
