Research Article
Transferable Adversarial Attacks against Automatic Modulation Classifier in Wireless Communications
Input: A classifier truncated model ; original signal sample to be attacked ; target signal sample ; clean signal sample ; Loss Function . | Parameter: perturbation size =0.001, number of iterations T. | Output:the adversarial sample that satisfy | . | . | put into ,obtain feature ; | put into ,obtain feature ; | put into ,obtain feature ; | t=0 to T-1 | put into ,obtain feature | Obtain the gradient , | where ; | calculate the accumulated gradient,renew the : | | update the with gradient method | | end for | |
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