Researchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural networks (RNNs) that ...

Neuromorphic computing, as a novel approach to processing information by mimicking biological neural networks, has gradually demonstrated significant ...

Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body's chemistry and each ...

BP neural network is used to establish the order quantity prediction model, and the neural network toolbox provided by MATLAB is used to program. Then take the different demand as the objective ...

In this paper, we focus on the long time behavior of the mild solution to delayed reaction-diffusion Hopfield neural networks (DRDHNNs) driven by infinite dimensional Wiener processes. We analyze the ...

How reliable is artificial intelligence, really? An interdisciplinary research team at TU Wien has developed a method that ...

The attentional blink selectively impairs one component of attention, and impacts both target detection and discrimination via separable neural signatures.

A new study has used large language models and neural networks to identify and predict the reactivity of over 14,000 potential cementitious materials, offering a scalable approach to discovering ...