基于量子神经网络的模拟电路的软故障诊断

Soft Fault Diagnosis of Analog Circuits Based on Quantum Neural Network

提出了基于小波与量子神经网络的容差模拟电路的软故障诊断方法,它能将故障的不确定性数据合理地分配到各类中,从而减少故障检测的不确定度,提高故障检测的诊断率,克服了BP在模糊分类方面的局限性。通过实验,采用QNN与自适应BP神经网络相比,故障诊断率可提高11.11%。

Based on wavelet amt muti-level transfer quantum neural network,a new soft fault diagnosis method for analog circuits with tolerance is proposed.It can assign the ambiguity data to the corresponding patterns reasonably ,thus reducing the uncertainty of pattern recognition and improving the veracity of pattern recognition ,Through experiments using QNN and adaptive BP neural network compared.fauh diagnosis can imprnve the rate of 11.11 percent.