Signal-image translation method based on generative adversarial network
A generative and signal technology, applied in biological neural network models, image data processing, neural learning methods, etc., can solve the problems of noise interference, interference, radio signal information redundancy, etc., to improve anti-noise robustness, guarantee Security and concealment, the effect of ensuring diversity
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[0051] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be noted that the following embodiments are intended to facilitate the understanding of the present invention, but do not limit it in any way.
[0052] This embodiment provides a signal-image translation method based on a generative confrontation network, which uses a radio signal translation model to translate the original radio signal into a color signal image, through figure 1 The training method of the architecture shown, can obtain the radio signal translation model. The training method includes three modules: a radio signal translation model ST, a radio signal translation discrimination model SD, and a radio signal classification model SC.
[0053] The radio signal translation model ST can translate the original radio signal into a color signal image. The radio signal translation model ST is mainly composed of basic units such as ...
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