An spiking neural network (SNN) classifier is an attractive option for ultra-low-power intelligent internet-of-things (IoT) devices.

Assistant Professor of Electrical and Computer Engineering Jason Eshraghian and two students recently released the open-sourced code for the largest language-generating spiking neural network ever, ...

It's possible to get pretty much any neural network to run as a spiking neural network, but there are some significant challenges, like converting the input into a series of spikes in the first place.

This particular type of neural network is called a Spiking Neural Network (SNN) which uses discrete events, called “spikes”, instead of continuous real-valued activations.

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

Researchers have created spiking neural nets with thousands of memristors (that mimic how neurons operate) by using atomically thin layer of material. Spiking neural networks should be better than ...

The hybrid optoelectronic architecture of convolutional spiking neural network was proposed, and the 2×2 spike-based matrix convolution was realized in the optical domain.

In addition, spiking neuromorphic devices fire spikes only rarely, so they shuffle around much less data than the electronics that typically run neural networks.

They found that when the spiking networks were trained on a new task, but with occasional off-line periods that mimicked sleep, catastrophic forgetting was mitigated.