Abstract: Nonlinear models with a linear-in-coefficients property, i.e., the property that the model output is linear with respect to model coefficients, are highly valuable for behavioral modeling of ...

A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...

This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...

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 ...

Forbes contributors publish independent expert analyses and insights. Caroline Castrillon covers career, entrepreneurship and women at work. Non-linear careers represent a fundamental shift in how we ...

Elastic net is a form of penalized linear regression that performs feature selection by shrinking beta coefficients of predictor variables using a penalty term, the stength of which is determined ...

Forbes contributors publish independent expert analyses and insights. Kevin Kruse covers leadership development & emotional intelligence. For decades, leadership operated under the illusion that 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 ...