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 ...

Conventional nanoscale electroplasmonic structures provide limited electrical tunability of nonlinear optical responses. Scientists at Japan's Institute for Molecular Science have demonstrated an ...

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 ...

Abstract: Lightning strikes have posed a severe threat to the operational safety of wind turbines. As an additional lightning-protection measure, metal meshes have been deployed on a number of ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict an employee's salary based on age, height, years of experience, and so on ...

Abstract: This paper presents a novel approach for the trajectory tracking control of a three wheeled mobile robot using neural network based nonlinear PID controller combined with the backstepping ...

ABSTRACT: Function-on-scalar regression is a type of function response regression used to analyze the relationship between function response and a set of scalar predictor factors. The variable ...

ABSTRACT: As extremely important methods, Lp regression methods have attracted the attention of either theoretical or empirical researchers all over the world. As special cases of that, quantile and ...