This article reviews work on the planning of experiments with response functions nonlinear in some parameters. Apart from older work on dilution series experiments and quantal bioassays, this field is ...

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 ...

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 ...

This paper provides a selective overview of nonlinear exchange rate models recently proposed in the literature and assesses their contribution to understanding exchange rate behavior. Two key ...

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 ...