摘要
研究一种基于人工神经网络的能区分故障的数字电路测试生成方法，该方法利用电路基本逻辑门的特性和神经网络模型的特点，首先建立测试生成的神经网络模型，然后通过求解网络能量函数的最小值点获得给定类型故障的测试矢量。
A distinguishable faults test generation method for digital circuits is presented.The features of basic gate circuits and neural networks are used to establish the test model, and to generate the test patterns for given faults.The fault model and constrained circuit are studied.Some strategies, e g,the reduction of the size of neural network, are proposed in order to accelerate test generation process.The experimental results demonstrate that the algorithm proposed in the paper is effective.
出处
《中山大学学报（自然科学版）》
CAS
CSCD
北大核心
1999年第3期21-24,共4页
Acta Scientiarum Naturalium Universitatis Sunyatseni
基金
广东省博士后基金
