![]() For example, splitting the real and imaginary parts into separate tensors, combining the real and imaginary parts in the dimension of the channel, adding a dimension for the real and imaginary parts, and so on.There are various implementations of complex convolution by real convolution in disarray, and they are not compatible with each other.Therefore, at present, complex convolution can only be realized by a combination of real convolutions. However, even though complex convolution is the most used of the complex networks, convolution functions are not yet supported for complex numbers (See the bottom for current issues). PyTorch has already been working on complex network implementation. ![]() Complex networks have received more attention since the paper " Deep complex networks" was published.
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