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 ...

This is a preview. Log in through your library . Abstract Multinomial logit models, especially those calibrated on scanner data, often use explanatory variables that are nonlinear functions of the ...

A standard digital camera used in a car for stuff like emergency braking has a perceptual latency of a hair above 20 milliseconds. That’s just the time needed for a camera to transform the photons ...

We leverage recent advancements in machine learning to develop an integrated method to solve globally and estimate models featuring agent heterogeneity, nonlinear constraints, and aggregate ...

Ryotatsu Yanagimoto, a scientist at NTT Research, led the research under the supervision of Peter L. McMahon, an associate ...

Given appropriate models for vacuum tubes, circuit simulators such as SPICE make analysis based on such nonlinear models a tractable effort. The Langmuir, Leach, and Koren models are discussed for the ...

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 ...

Highly reduced order models with nonlinear contact – extremely efficient computation. Modeled as linear components interconnected with highly reduced-order components. 1-linear reduced model, ...

Long-term weather forecasting is a difficult task, partly because weather systems are inherently chaotic. Though mathematical ...