Frontiers

Neural Network Dynamics: Unraveling Spiking and Synaptic Plasticity in Learning and Memory

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

Using Radial Basis Function Neural Network With Weight Memory Mechanism: Nonlinear System Identification

Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...

Biology-inspired brain model matches animal learning and reveals overlooked neuron activity

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

Build a deep neural network from scratch in Python

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

Activation Functions in Non-Negative Neural Networks

Abstract: Optical neural networks (ONNs) have the potential to overcome scaling limitations of transistor-based systems due to their inherent low latency and large available bandwidth. However, ...
EurekAlert!

Photonic compute-in-wire: remotely driven photonic deep neural network with single nonlinear loop

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 ...