FAYETTEVILLE, GA, UNITED STATES, December 31, 2025 /EINPresswire.com/ — Artificial intelligence (AI) is increasingly transforming computational mechanics, yet many AI-driven models remain limited by ...
From electronic health records and blood tests to the stream of data from wearable devices, the amount of health information people generate is accelerating rapidly. Yet, many users struggle to ...
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 ...
Abstract: Gaussian Mixture Function (GMF) is a widely utilized model for analyzing and elucidating experimental data in science and engineering, where the fitting of GMF with noisy observations is ...
Abstract: We propose and experimentally demonstrate a reconfigurable nonlinear activation function (NAF) unit based on add-drop resonator Mach-Zehnder interferometers (ADRMZIs) for photonic neural ...
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 ...
1 The Affiliated Guangzhou Hospital of TCM of Guangzhou University of Chinese Medicine, Guangzhou, China 2 Sleep Research Institute of Traditional Chinese Medicine, Guangzhou Medical University, ...
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 ...
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