Ask the Automation Pros: How Can You Ensure the Best Rate of Change in the PID Manipulated Variable?

What is the best strategy to get the best rate of change in the PID for a manipulated variable, or is there a more elegant ...
Semiconductor Engineering

Parallel Implementation Of Nonlinear Functions Using An Optical Processor (UCLA)

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 ...
IEEE

Fixed-Time Distributed Consensus Optimization Control of High-Order Nonlinear Multi-Agent Systems via a Penalty-Function-Based Method

Abstract: This paper studies the distributed optimization problem of high-order multi-agent systems with unknown nonlinear terms and input saturation. Unlike existing results, nonlinear functions in ...
Semiconductor Engineering

Implementing AI Activation Functions

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 ...
IEEE

Finite-Time Adaptive Control of Nonstrict-Feedback Nonlinear Systems With Time-Varying Full State Constraints

Abstract: This paper proposes a finite-time adaptive tracking fuzzy control approach for nonlinear nonstrict-feedback systems with unknown disturbances and time-varying full state constraints. The ...
Forbes

A New Way Of Computing – Breakthroughs In Photonic And Quantum Operations

Forbes contributors publish independent expert analyses and insights. I am an MIT Senior Fellow & Lecturer, 5x-founder & VC investing in AI Deep learning and artificial intelligence continue to push ...
Frontiers

A Free-Knot Spline Modeling Framework for Piecewise Linear Logistic Regression in Complex Samples with Body Mass Index and Mortality as an Example

This paper details the design, evaluation, and implementation of a framework for detecting and modeling non-linearity between a binary outcome and a continuous predictor variable adjusted for ...
Frontiers

Estimating neural response functions from fMRI

This paper proposes a methodology for estimating Neural Response Functions (NRFs) from fMRI data. These NRFs describe non-linear relationships between experimental stimuli and neuronal population ...