A team of physicists has designed quantum algorithms that can model one of the most elusive behaviors in nature: a photon ...

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

Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This paper explores the use ...

Multi-step temporal-difference (TD) learning, where the update targets contain information from multiple time steps ahead, is one of the most popular forms of TD learning for linear function ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this work, we describe the development of a new algorithm for the computation of ...

Let $P(m, X, N)$ be an $m$-degree polynomial in $X\in\mathbb{R}$ having fixed non-negative integers $m$ and $N$. Essentially, the polynomial $P(m, X, N)$ is a result ...

SiC-based converters and inverters are the optimal choice for battery-operated vehicles (BEVs), renewables, and all other applications where maximum efficiency is required. Silicon Carbide (SiC) ...

A variety of linear models are available to represent common active electronic devices such as transistors and vacuum tubes. Devices operating under large-signal conditions often require nonlinear ...

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.