Over the past decades, computer scientists have introduced numerous artificial intelligence (AI) systems designed to emulate the organization and functioning of networks of neurons in the brain.

Two methods are discussed which result in near minimax rational approximations to the exponential function and at the same time retain the desirable property that the approximation for negative values ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Abstract: This paper proposes a novel iterative gradient-based optimization approach aimed at achieving more precise and streamlined approximations for the Gaussian Q function—an essential element in ...

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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 ...

ABSTRACT: Continuous groundwater quality monitoring poses significant challenges affecting the environment and public health. Groundwater in Abidjan, specifically from the Continental Terminal (CT), ...

Abstract: Function approximation has experienced significant success in the field of reinforcement learning (RL). Despite a handful of progress on developing theory for nonstationary RL with function ...