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The Fault Analysis of Analog Circuit Based on BP Neural Network

机译:基于BP神经网络的模拟电路故障分析

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This article studies the fault analysis of analog circuit based on BP neural network. The fault characteristics are obtained by Monte Carlo analysis of analog circuit. The BP neural network is constructed by MATLAB and applied to the fault diagnosis of circuit. The results show that BP neural network can quickly locate the fault point in the continuous training optimization because of its self-learning ability, which has higher detection quality and efficiency. And the BP neural network has a strong application in large-scale circuit system.
机译:本文研究了基于BP神经网络的模拟电路故障分析。 通过模拟电路的Monte Carlo分析获得故障特性。 BP神经网络由MATLAB构建,并应用于电路的故障诊断。 结果表明,由于自学习能力,BP神经网络可以在连续训练优化中快速定位故障点,具有更高的检测质量和效率。 而BP神经网络在大型电路系统中具有很强的应用。

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