【摘要】 为了改善组合电路测试生成效率,提出了一种有效的基于三值神经网络的组合电路测试生成算法。该算法不需要传播和回溯,而是使用三值神经网络把组合电路表示为双向神经元网络,并构建网络的能量函数,最后使用遗传算法求出全局最小值点作为电路的测试矢量,所以组合电路的测试生成问题转换为优化问题。在标准电路上的测试实验结果表明该算法具有较高的故障覆盖率和较短的测试生成时间。更多还原

【Abstract】 In order to improve the quality of combinational circuit test generation,an effective combinational circuits test generation algorithm based three-valued neural networks~[1]is proposed in this paper. This algorithm does not need propagation and backtracks,but represents the combinational circuits as a bidirectional network of neurons using the three-valued neural networks,and constructs the energy function for the network. A genetic algorithm was used to find the global minimal as the test vectors. The problem of the combinational test generation was formulated to an optimization problem. The experimental results on some standard circuits demonstrate that the proposed algorithm has high fault coverage and short test time.更多还原