Pure python implementation of SNN

Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.

Offical implementation of "Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips" (ICLR2024)

RBM implemented with spiking neurons in Python. Contrastive Divergence used to train the network.

OpenN@S: Open-source software to NAS automatic VHDL code generation

Simulation of Advanced Neuromorphic Architectures for Fast Exploration

Brilliantly Radical Artificially Intelligent Neural Machine

NeMo - A hardware agnostic neuromorphic processor simulation model built on ROSS

A bespoke time‑first language + toolchain for hybrid Neuromorphic - classical systems

An Address Event Representation toolbox for loading and visualising event data files in Python

Neuromorphic architectures are hardware architectures that use the biologically inspired neural functions as the basis of operation. Information processing based on spiking neuron architectures have caught considerable attention in recent years due to its low power consumption compared to traditional artificial neural networks. In this project, …

Bio-inspired neuromorphic cerebellum

Neuromorphic Auditory Visualizer Tool

This repository aims to provide a curated collection of resources for researchers and practitioners interested in neuromorphic navigation, including datasets, hardware platforms, and software tools.

openFrameworks addon for interfacing to the Dynamic Vision Sensors. This addon is a basic logger and player for the DAVIS/DVS sensors family

A fast generative model for stochastic memory cells

This is a collection of papers I read on SNN accelerators.

Emerging Threats and Countermeasures in Neuromorphic Systems: A Survey. By designing and analyzing Memristor Devices for Neuromorphic Computing, Spiking Neural Networks (SNNs), Physically Unclonable Functions (PUFs), True Random Number Generators (TRNGs), we are investigating their hardware and software security (attacks and defenses).

E-prop on spinnaker 2: exploring online learning in spiking rnns on neuromorphic hardware