Researchers at Skoltech have proposed a new approach to training neural networks for wave propagation in absorbing media. The ...

It’s one thing to be in the spotlight for leading the scoreboard at a PGA Tour event, and a whole other thing for an unwanted ...

A new study provides a rigorous theoretical and numerical analysis of the accuracy of the method of characteristics (MoC), a ...

Data is often referred to as the new oil of the digital economy, representing a highly valuable and untapped asset. To fully realize the potential of spatial data, various spatial data marketplace ...

Abstract: In this paper, a hypervolume contribution approximation method is proposed. The main idea is to find out all angular points in the hypervolume contribution region of the solution by ...

The numerical integration of stiff equations is a challenging problem that needs to be approached by specialized numerical methods. Exponential integrators form a popular class of such methods since ...

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 ...

This paper presents an analysis of properties of two hybrid discretisation methods for Gaussian derivatives, based on convolutions with either the normalised sampled Gaussian kernel or the integrated ...

1 College of Mathematics and Information Science, Nanchang Hangkong University, Nanchang, China. 2 School of Statistics and Data Science, Jiangxi University of Finance and Economics, Nanchang, China.

ABSTRACT: Accurately approximating higher order derivatives is an inherently difficult problem. It is shown that a random variable shape parameter strategy can improve the accuracy of approximating ...

Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. As soon as an appropriate mathematical model is developed, it can ...