Neuroscience continually strives to unravel the intricate relationship between neural network morphology, spiking dynamics, and their resulting functional ...

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...

The development of deep learning has motivated the advancement of unconventional computing that leverages analog physical systems such as analog electronics, spintronics, and photonics. These ...

Abstract: To achieve precise lateral dynamics control for electric and autonomous vehicles under system model uncertainties and unknown external disturbances, this article introduces a novel barrier ...

For decades, networks have been built on the same fundamental principle: dedicated hardware appliances for each network function. Need a firewall? Buy a box. Need load balancing? Purchase another ...

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python What the US ...

Greenlight Networks — a New York-based broadband service provider — completed its acquisition of Scranton-based Loop Internet and strives to bring affordable, high-speed fiber internet to more homes ...

Abstract: Learning is central to intelligent control, particularly in real-world scenarios with complex time-varying constraints. This paper proposes an adaptive neural network-based control method ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...