Communication protocol signal identification method based on depth residual network
A communication protocol and signal identification technology, applied in modulation type identification, digital transmission systems, electrical components, etc., can solve problems such as subsequent processing of problems affecting classification, lack of probability information, and sensitivity to error boundaries, achieving strong practical application value, identification High accuracy and efficient operation
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[0038] The present invention will be further described in detail below in conjunction with the accompanying drawings and technical solutions, and the implementation of the present invention will be described in detail through preferred embodiments, but the implementation of the present invention is not limited thereto.
[0039] Deep Residual Network (ResNet) belongs to the category of Convolutional Neural Network (CNN). It has excellent performance in the field of image processing. When CNN is used, it can effectively overcome the shortcomings of traditional pattern recognition methods based on explicit features (texture direction, boundary line, contour, etc.), implicitly self-learn from training data, and select the best one that reflects the uniqueness of the sample or Exclusive features, strong adaptability and promotion ability. For this reason, embodiment of the present invention, see figure 1 As shown, a communication protocol signal recognition method based on a deep...
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