The Fault Analysis of Analog Circuit Based on BP Neural Network
| Autor: | Lin Yun, Xiao Xuefang, Zhao Qinghao |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Artificial neural network
Analogue electronics Computer science Monte Carlo method Hardware_PERFORMANCEANDRELIABILITY Fault (power engineering) Fault detection and isolation Computer Science::Hardware Architecture Point (geometry) Fault analysis MATLAB computer Algorithm computer.programming_language |
| Zdroj: | 2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE). |
| DOI: | 10.1109/aemcse51986.2021.00034 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|