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Fault Diagnosis of Tolerance Analog Circuit Based on Wavelet Neural Network with PSO Algorithm

机译:基于PSO算法的小波神经网络的容差模拟电路故障诊断

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For the Difficulties in fault diagnosis of tolerance analog circuit, a Wavelet Neural Network (WNN) diagnosis method based on Particle Swarm Optimization (PSO) algorithm is proposed. To overcome the deficiencies of the traditional BP algorithm using in WNN, PSO algorithm is introduced into the parameters optimization in WNN, and the velocity disturbance operator is embedded to ensure the particle out of the premature position for PSO algorithm performance. The simulation results show that the proposed method has the fast training rate, accurate diagnosis, without local convergence.
机译:对于公差模拟电路故障诊断的困难,提出了一种基于粒子群优化(PSO)算法的小波神经网络(WNN)诊断方法。为了克服在Wnn中使用的传统BP算法的缺陷,PSO算法被引入Wnn中的参数优化,嵌入速度干扰操作员以确保粒子从过早位置进行PSO算法性能。仿真结果表明,该方法具有快速训练率,准确诊断,无局部收敛。

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