3 papers
cs.AR2026
Full Feature Spiking Neural Network Simulation on Micro-Controllers for Neuromorphic Applications at the Edge
L. Niedermeier, J. L. Krichmar
Microcontroller units (MCU), which have an order of magnitude lower Size, Weight and Power (SWaP) than standard computers, makes them suitable for applications at the edge. Neuromo…
cs.NE2025
A Multi-Threading Kernel for Enabling Neuromorphic Edge Applications
Lars Niedermeier, Vyom Shah, Jeffrey L. Krichmar
Spiking Neural Networks (SNNs) have sparse, event driven processing that can leverage neuromorphic applications. In this work, we introduce a multi-threading kernel that enables ne…
cs.NE2024
An Integrated Toolbox for Creating Neuromorphic Edge Applications
Lars Niedermeier, Jeffrey L. Krichmar
Spiking Neural Networks (SNNs) and neuromorphic models are more efficient and have more biological realism than the activation functions typically used in deep neural networks, tra…