Circuit teaching simulation platform technology based on deep learning optimization

Like the existing software simulation experiment platform, the remote camera can also provide a realistic scene effect, giving the experiment user a sense of presence, thus greatly improving the quality and effectiveness of the experiment. It is verified and evaluated in the actual measurement environment that the research on the sampling method of the characteristic value samples is less involved. Thus, there is a certain gap between engineering practice and the application of instrument measurement. In order to solve the problems of less measurable nodes, less fault feature information and fault information from simulation in analog circuits, this paper chooses the low-frequency noise spectral density that can best reflect the fault feature information as the feature parameter through the study of circuit noise mechanism and noise superposition theorem. The paper also proposes an improved average period cross-spectrum method based on a low-frequency noise detection technology. With low-pass filter, low noise amplifier module, ADC sampling module and FPGA platform, the utilization rate of experimental facilities is high. Proved by experiments, the technology in this paper can reduce the number of facilities needed for the same experimental task, and reduce the cost of school laboratory construction and maintenance.