Abstract: Operator learning is a recent development in the simulation of partial differential equations by means of neural networks. The idea behind this approach is to learn the behavior of an ...

Analog-to-digital conversion methods abound, but we are going to take a look at a particular approach as shown in Figure 1. Figure 1 An analog-to-digital converter where an analog input signal is ...

Abstract: Matrix approximation methods have successfully produced efficient, low-complexity approximate transforms for the discrete cosine transforms and the discrete Fourier transforms. For the DFT ...

The method seems to provide much closer accuracy to the slow method, while maintaining the same time complexity (just scaled up by a constant). I suggest we parallellize the FFTs in the LRA optionally ...

In this tutorial, we will solve one of the exercises proposed in a previous issue. The solution lends itself to an interesting interpretation of the famous Gibbs-Wilbraham phenomenon. In this tutorial ...

Stencil computations are widely used to simulate the change of state of physical systems across a multidimensional grid over multiple timesteps. I will talk about our recent results on performing ...

ABSTRACT: In the author’s recent publications, a parametric system biorthogonal to the corresponding segment of the exponential Fourier system was unusually effective. On its basis, it was discovered ...

ABSTRACT: This paper covers the concept of Fourier series and its application for a periodic signal. A periodic signal is a signal that repeats its pattern over time at regular intervals. The idea ...

This application demonstrates the mathematical foundation of Fourier analysis by visualizing how complex waveforms (square waves) can be synthesized from a sum of simple sine waves. It implements the ...