We consider a nonlinear function-on-function additive regression model with multiple functional predictors. The forms of the nonlinear functions are unspecified, and offer great flexibility to model ...

Nonlinear mixed effects models (NLMMs) and self-modeling nonlinear regression (SEMOR) models are often used to fit repeated measures data. They use a common function shared by all subjects to model ...

Literature on Nonlinear Mixed Models Davidian and Giltinan (1995) and Vonesh and Chinchilli (1997) provide good overviews as well as general theoretical developments and examples of nonlinear mixed ...

Asymmetric interactions between different species of molecules have previously been demonstrated to result in self-organized ...

Author Dr. R. Russell Rhinehart discusses his new book, Nonlinear Model-Based Control: Using First-Principles Models in Process Control, and explains why nonlinear first-principles models should be ...

Getting an all-optical AI to handle non-linear math Instead of sensing photons and processing the results, why not process the photons?

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 ...