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Fault isolation in nonlinear analog circuits with tolerance using the neural network-based L/sub 1/-norm

机译:基于神经网络的L / sub 1 /范数具有容错能力的非线性模拟电路中的故障隔离

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This paper deals with fault isolation in nonlinear analog circuits with tolerance under an insufficient number of independent voltage measurements. A neural network-based L/sub 1/-norm optimization approach is proposed and utilized in locating the most likely faulty elements in nonlinear circuits. The validity of the proposed method is verified by both extensive computer simulations and practical examples. One simulation example is presented in the paper.
机译:本文研究了非线性模拟电路中的故障隔离,该电路具有足够的容限,无法进行足够数量的独立电压测量。提出了一种基于神经网络的L / sub 1 /范数优化方法,并将其用于定位非线性电路中最可能出现故障的元件。大量的计算机仿真和实例验证了该方法的有效性。本文提出了一个仿真示例。

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