89 citations · 445 across the 19 of their papers we have counts for
19 papers
Unleashing the Potential of Spiking Neural Networks by Dynamic Confidence
Chen Li, Edward Jones, Steve Furber
This paper presents a new methodology to alleviate the fundamental trade-off between accuracy and latency in spiking neural networks (SNNs). The approach involves decoding confiden…
2022 Roadmap on Neuromorphic Computing and Engineering
Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco +56
Modern computation based on the von Neumann architecture is today a mature cutting-edge science. In the Von Neumann architecture, processing and memory units are implemented as sep…
The SpiNNaker 2 Processing Element Architecture for Hybrid Digital Neuromorphic Computing
Sebastian Höppner, Yexin Yan, Andreas Dixius +15
This paper introduces the processing element architecture of the second generation SpiNNaker chip, implemented in 22nm FDSOI. On circuit level, the chip features adaptive body bias…
An FPGA Implementation of Convolutional Spiking Neural Networks for Radioisotope Identification
Xiaoyu Huang, Edward Jones, Siru Zhang +7
This paper details the FPGA implementation methodology for Convolutional Spiking Neural Networks (CSNN) and applies this methodology to low-power radioisotope identification using…
Spiking Neural Network Based Low-Power Radioisotope Identification using FPGA
Xiaoyu Huang, Edward Jones, Siru Zhang +7
this paper presents a detailed methodology of a Spiking Neural Network (SNN) based low-power design for radioisotope identification. A low power cost of 72 mW has been achieved on…
A Nanoscale Room-Temperature Multilayer Skyrmionic Synapse for Deep Spiking Neural Networks
Runze Chen, Chen Li, Yu Li +5
Magnetic skyrmions have attracted considerable interest, especially after their recent experimental demonstration at room temperature in multilayers. The robustness, nanoscale size…