Electromagnetic red information detection method based on cepstrum and convolutional neural network
A convolutional neural network and information detection technology, which is applied in the detection field of electromagnetic leakage red information, can solve the problems that the characteristics of electromagnetic red information cannot be extracted and expressed, the signal-to-noise ratio of electromagnetic red information is low, and the strength of characteristic signals is weak, etc., to achieve Effects of expanding dynamic range, high sensitivity, and suppressing overfitting problems
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[0099] Embodiment 1 (using the above-mentioned electromagnetic red information detection method based on cepstrum and convolutional neural network)
[0100] 1. Use the signal receiving equipment to collect m electromagnetic leakage signal samples:
[0101] S i (t), i=1, 2, 3... m
[0102] Its time-domain samples are as image 3 shown.
[0103] 2. Perform down-sampling processing on the electromagnetic leakage signal sample, and set L m 16000 sampling points, S m For 2MS / s, the time series of the standardized electromagnetic leakage signal is obtained:
[0104] S i (n), i=1, 2, 3... m
[0105] Wherein, the length of each sample sequence is 16000, that is, 0<n<16000.
[0106] 3. Perform cepstrum analysis on the down-sampled electromagnetic leakage signal sample to form a cepstrum-based electromagnetic red information feature representation. The process is as follows:
[0107] (1) to S i (n) Carry out Fourier transform, obtain the frequency spectrum of electromagnetic l...
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