Abstract: In this paper, we present a novel convolution theorem which encompasses the well known convolution theorem in (graph) signal processing as well as the one related to time-varying filters.

Abstract: Several topological and analytical notions of continuity and fading memory for causal and time-invariant filters are introduced, and the relations between them are analyzed. A significant ...

We have defined convolution and seen that it generalizes difference equations, but it is not yet obvious that we have made progress toward our stated goal of sculpting content in the frequency domain.

This code example demonstrates the convolution theorem with the use of the Complex Fast Fourier Transform (FFT), complex-by-complex multiplication, and support functions, which are part of the ...

This is my coursework project for 2023 autumn semester at BSUIR. The project is to study the differences in speed of large convolutions with and without Fourier transform (based on the convolution ...

Convolution is the core computational operator in Convolutional Neural Networks (CNNs), typically accounting for over 80% of the total inference workload. As CNN backbones continue to scale in depth ...