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 ...

Abstract: Nonlinear functions are widely involved in modern digital signal processing systems, which are usually calculated by polynomial approximation, CORDIC algorithm, or look-up tables. Due to the ...

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 ...

The solution of the nonlinear differential equation Y″ = F(x, Y, Y′) with two-point boundary conditions is approximated by a quintic or cubic spline function y(x ...

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 ...

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 ...

Advancements in neuroscience research have led to significant progress in understanding the complex dynamics of the brain. However, the nonlinear properties of brain function still present a challenge ...