NeuroSOFM: A Neuromorphic Self-Organizing Feature Map Heterogeneously Integrating RRAM and FeFET
Many currently available hardware implementations of the unsupervised self-organizing feature map (SOFM) algorithm utilize complementary metal–oxide–semiconductor (CMOS)-only circuits that often compromise key behaviors of the SOFM algorithm due to complexity. We propose a neur...
Saved in:
Main Authors: | Siddharth Barve, Joshua Mayersky, Andrew J. Ford, Alexander Jones, Bayley King, Aaron Ruen, Rashmi Jha |
---|---|
Format: | article |
Language: | EN |
Published: |
IEEE
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/66f3762c4a0945d7a60e92ccad61c13f |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
ReSe2-Based RRAM and Circuit-Level Model for Neuromorphic Computing
by: Yifu Huang, et al.
Published: (2021) -
A Fully Integrated Reprogrammable CMOS-RRAM Compute-in-Memory Coprocessor for Neuromorphic Applications
by: Justin M. Correll, et al.
Published: (2020) -
Toward Learning in Neuromorphic Circuits Based on Quantum Phase Slip Junctions
by: Ran Cheng, et al.
Published: (2021) -
A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems
by: Yunpeng Guo, et al.
Published: (2021) -
Ternary Arithmetic Logic Unit Design Utilizing Carbon Nanotube Field Effect Transistor (CNTFET) and Resistive Random Access Memory (RRAM)
by: Furqan Zahoor, et al.
Published: (2021)