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 ...

A pruning reservoir computing technique can mitigate noise and reconstruct nonlinear dynamics for potential engineering and ...

In multi-component mixtures of self-assembling molecules, small differences in association energy between components can be amplified by nonlinear effects. This theoretical investigation of self ...

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 ...

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

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 ...

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 ...

Gallium Semi has released a library of nonlinear models for all of its broadband dual flat no-lead (DFN) plastic and air cavity ceramic (ACC) packaged GaN transistors. The 22 models are designed and ...