Abstract: Spiking neural networks (SNNs) are the third generation of neural networks that offer the advantages of low computational requirements, fast inference speed, and strong biological ...

Forbes contributors publish independent expert analyses and insights. I am an MIT Senior Fellow & Lecturer, 5x-founder & VC investing in AI In many of the articles where I describe presentations by ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

This project implements a complete event-driven spiking neural network (SNN) accelerator on FPGA with seamless PyTorch integration for training and deployment. The design uses Accumulate-only (AC) ...

Introduction: Brain-computer interfaces (BCIs) leverage EEG signal processing to enable human-machine communication and have broad application potential. However, existing deep learning-based BCI ...

What’s the difference between analog and digital spiking neural networks (SNNs)? Why analog and digital SNNs are complementary. Details about Innatera’s Pulsar ...

Abstract: This study investigates the application of Spiking Neural Network (SNN) in seismic signal denoising by developing a Convolutional Neural Network (CNN) to SNN conversion framework. We focus ...

1 College of Electronic Science and Technology, National University of Defense Technology, Changsha, China 2 College of Electronics and Internet of Things, Chongqing Polytechnic University of ...

The business of college football is booming so far in 2025, at least according to the TV ratings through the opening weeks of the season. Front Office Sports reported that total college football ...