Abstract: Reinforcement Learning is a branch of machine learning to learn control strategies that achieve a given objective through trial-and-error in the environment ...

A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...

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 ...

This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

Forbes contributors publish independent expert analyses and insights. Caroline Castrillon covers career, entrepreneurship and women at work. Non-linear careers represent a fundamental shift in how we ...

Dom O'Leary is a contirbutor on Game Rant. He has over 6 years of experience in writing, covering everything from games news and reviews to commercial writing and editing. He's been a lover of games ...

A standard digital camera used in a car for stuff like emergency braking has a perceptual latency of a hair above 20 milliseconds. That’s just the time needed for a camera to transform the photons ...

The last time I went to the doctor, I lived in a different zip code, belonged to a different body-weight category, and was rounding out a different decade. I never consciously swore off health care, ...

Abstract: The article studies an adaptive practical fixed-time tracking control problem of nonlinear system using the funnel control method and the dynamic event-triggered control mechanism. First, an ...