Research on Conducted Immunity Quantification Model of Operational Amplifier Based on Neural Networks and Feature Extraction

The quantitative model presented in this study focuses on analyzing and predicting the output behavior of conducted immunity operational amplifiers. By testing conducted immunity on operational amplifiers, a conducted immunity model is established using the time-domain waveform feature extraction and neural network method. The results demonstrate that the quantized model exhibits an error accuracy within 2 dB when compared to test data. Furthermore, the quantized model accurately predicts time-domain waveform features with an error accuracy within 1.2 dB.