Complex data is commonly encountered in several domains of signal and image processing, where two important components, namely the magnitude and phase of the complex data, convey valuable information. This paper introduces novel complex convolution and activation functions aimed at enhancing the efficiency of the complex convolution network. The suggested complex convolution function incorporates complex weights and exhibits equivariance to complex multiplication. Furthermore, a novel activation function is introduced that shows equivariance to complex multiplication, hence enhancing the efficiency of the complex convolution network.
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Sabokpa et al. (2024) studied this question.
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