arXiv · 1810.11650
On the Equivalence of Convolutional and Hadamard Networks using DFT
Abstract
In this paper we introduce activation functions that move the entire computation of Convolutional Networks into the frequency domain, where they are actually Hadamard Networks. To achieve this result we employ the properties of Discrete Fourier Transform. We present some implementation details and experimental results, as well as some insights into why convolutional networks perform well in learning use cases.
Explore related subjects
Keep this discovery
Marcel Crasmaru. 2018-10-27. On the Equivalence of Convolutional and Hadamard Networks using DFT. https://arxiv.org/abs/1810.11650
Cite the original work for its findings. Save a collection to share your selection of sources.