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 ...

Computational methods for fitting nonlinear models have developed considerably in the last decade. Statistical use of these techniques has, as yet, lagged somewhat behind. The present paper gives a ...

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 ...

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 ...

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 ...

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

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 ...