Energy‐Efficient Hardware Implementation of Spiking‐Restricted Boltzmann Machines Using Pseudo‐Synaptic Sampling

Energy‐Efficient Hardware Implementation of Spiking‐Restricted Boltzmann Machines Using Pseudo‐Synaptic Sampling

Stochastic sampling is performed to reduce hardware energy consumption and prevent overfitting by reducing parameters, because not all data are required for learning. In this study, a new approach, pseudo‐synaptic sampling (PS2) method, which approximates the conventional synaptic sampling machine (...

Full description

Saved in:
Bibliographic Details
Main Authors: Hyunwoo Kim, Suyeon Jang, Uicheol Shin, Masatoshi Ishii, Atsuya Okazaki, Megumi Ito, Akiyo Nomura, Kohji Hosokawa, Sungmin Lee, Matthew BrightSky, Sangbum Kim
Format: Article
Language:English
Published: Wiley 2025-05-01
Series:Advanced Intelligent Systems
Subjects:
energy‐efficiencies
in‐memory computings
neuromorphics
pseudo‐synaptic samplings
restricted Boltzmann machines
spiking neural networks
Online Access:https://doi.org/10.1002/aisy.202400557
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1002/aisy.202400557

Similar Items