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EURASIP Journal on Wireless Communications and Networking
Fig. 1 | EURASIP Journal on Wireless Communications and Networking

Fig. 1

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

Fig. 1

The structure of the proposed framework. This figure presents the architecture of the proposed framework. It consists of three functional parts: fusion of input features and temporal characteristics mapping, spatial features extraction, and fully connected classifier. Part-A is the stacked GRU layers, which includes two GRU layers. Part-B includes three CNN layers and two max-pooling layers, and the number and kernel size of convolutional filters are given. Part-C includes two fully connected (FC) layers, and the Softmax activation function is adopted at the last FC layer

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