Editorial for the Special Issue on the Progress of Emerging Hardware Development for Post-Moore’s Computing-Reference-Cited by-同舟云学术

Editorial for the Special Issue on the Progress of Emerging Hardware Development for Post-Moore’s Computing

Published:2023-01-12 Issue:1 Volume:14 Page:193
ISSN:2072-666X
Container-title:Micromachines
language:en
Short-container-title:Micromachines

Author:

Chang Yao-Feng^ORCID

Abstract

The potential of machine learning and novel computing architecture can be exploited in the immediate future if more efficient hardware is developed that meets the special requirements of bio-inspired computing or unconventional computing schemes [...]

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering

Link

https://www.mdpi.com/2072-666X/14/1/193/pdf

Reference9 articles.

1. H Hasan, M., Abbasalipour, A., Nikfarjam, H., Pourkamali, S., Emad-Ud-Din, M., Jafari, R., and Alsaleem, F. (2021). Exploiting Pull-In/Pull-Out Hysteresis in Electrostatic MEMS Sensor Networks to Realize a Novel Sensing Continuous-Time Recurrent Neural Network. Micromachines, 12.

2. Chen, Y.-C., Lin, C.-C., and Chang, Y.-F. (2021). Post-Moore Memory Technology: Sneak Path Current (SPC) Phenomena on RRAM Crossbar Array and Solutions. Micromachines, 12.

3. Choi, J., and Kim, S. (2020). Improved Stability and Controllability in ZrN-Based Resistive Memory Device by Inserting TiO2 Layer. Micromachines, 11.

4. Chen, Q., Han, T., Tang, M., Zhang, Z., Zheng, X., and Liu, G. (2020). Improving the Recognition Accuracy of Memristive Neural Networks via Homogenized Analog Type Conductance Quantization. Micromachines, 11.

5. Reuben, J. (2020). Binary Addition in Resistance Switching Memory Array by Sensing Majority. Micromachines, 11.