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Fig. 8 | EURASIP Journal on Wireless Communications and Networking

Fig. 8

From: A novel deep learning automatic modulation classifier with fusion of multichannel information using GRU

Fig. 8

The (top) input and (bottom) output of stacked GRU layers. This figure presents the input features and the output activation of stack GRU layers for a 16QAM modulated signal with 18 dB SNR. The top figure is the input of stacked GRU layers, including in-phase/quadrature (I/Q) data, amplitude/phase (A/P) data, and the bottom one is the output of the second GRU layer along time step (N = 128). This figure shows that activations of many time steps correspond to the amplitude and phase changes in the input waveform. The visualization techniques can help us to understand how stack GRU layers behave for multichannel inputs

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