A team of researchers at Kyoto University have demonstrated that the chaotic component of heartbeat variability is uniquely ...

In his doctoral thesis, Michael Roop develops numerical methods that allow finding physically reliable approximate solutions ...

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 ...

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 ...

Investigating task- and stimulus-dependent connectivity is key to understanding how the interactions between brain regions underpin complex cognitive processes. Yet ...

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: The ability to quickly synthesize an optimal control signal for a nonlinear system is critical for practical implementations. In previous work, we have introduced a computational procedure ...