Hardware Implementation for Spiking Neural Networks on Edge Devices

Thao Nguyen; Bharadwaj Veeravalli; Xuanyao Fong

doi:10.1007/978-3-031-18034-7_13

ScienceGate Book Chapters

BOOK-CHAPTER

Hardware Implementation for Spiking Neural Networks on Edge Devices

Thao Nguyen Bharadwaj Veeravalli Xuanyao Fong

Year: 2022 Pages: 227-248

DOI: 10.1007/978-3-031-18034-7_13

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Edge device Data processing Enhanced Data Rates for GSM Evolution Edge computing Cloud computing Artificial neural network Computer architecture Embedded system Computer hardware Distributed computing Artificial intelligence Database Operating system

Metrics

Cited By

2.48

FWCI (Field Weighted Citation Impact)

Refs

0.91

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Memory and Neural Computing

Physical Sciences → Engineering → Electrical and Electronic Engineering

Ferroelectric and Negative Capacitance Devices

Physical Sciences → Engineering → Electrical and Electronic Engineering

Neural dynamics and brain function

Life Sciences → Neuroscience → Cognitive Neuroscience

Hardware Implementation for Spiking Neural Networks on Edge Devices

Metrics

Citation History

Topics

Related Documents

Smart Hardware Implementation of Spiking Neural Networks

HARDWARE IMPLEMENTATION OF STOCHASTIC SPIKING NEURAL NETWORKS

Hardware implementation of spiking neural networks on FPGA

Capacitor-Based Synaptic Devices for Hardware Spiking Neural Networks

A temporal coding hardware implementation for spiking neural networks