Abstract: In this article, we propose a novel non-iterative method, viz., the subspace-Rytov approximation (SRA) method, to solve inverse scattering problems. This method improves the inversion ...

Abstract: The sigmoid function is a widely used nonlinear activation function in neural networks. In this article, we present a modular approximation methodology for efficient fixed-point hardware ...

University of World Economy and Diplomacy, Tashkent, Uzbekistan. There are various approximate analytical methods for solving differential equations. For example, in the works [1] [2] new approaches ...

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 ...

An important part of the marginal maximum likelihood method described previously is the computation of the integral over the random effects. The default method in PROC NLMIXED for computing this ...