ScienceGate
Advanced Search
Author Search
Journal Finder
Blog
Sign in / Sign up
ScienceGate
Search
Author Search
Journal Finder
Blog
Sign in / Sign up
SSCS-Singapore Holds Distinguished Lecture on Enabling and Exploiting: Machine Learning in Ultra-Low-Power Devices by Prof. Naveen Verma [Chapters]
IEEE Solid-State Circuits Magazine
◽
10.1109/mssc.2017.2746170
◽
2017
◽
Vol 9
(4)
◽
pp. 112-113
Author(s):
Jiang Wenyu
Keyword(s):
Machine Learning
◽
Low Power
◽
Power Devices
◽
Ultra Low Power
◽
Ultra Low Power Devices
Download Full-text
Related Documents
Cited By
References
An RC4-based hash function for ultra-low power devices
2010 2nd International Conference on Computer Engineering and Technology
◽
10.1109/iccet.2010.5486127
◽
2010
◽
Cited By ~ 2
Author(s):
Qian Yu
◽
Chang N. Zhang
◽
Xun Huang
Keyword(s):
Low Power
◽
Hash Function
◽
Power Devices
◽
Ultra Low Power
◽
Ultra Low Power Devices
Download Full-text
An optimized junctionless GAA MOSFET design based on multi-objective computation for high-performance ultra-low power devices
Journal of Semiconductors
◽
10.1088/1674-4926/35/7/074002
◽
2014
◽
Vol 35
(7)
◽
pp. 074002
◽
Cited By ~ 3
Author(s):
T. Bendib
◽
F. Djeffal
◽
M. Meguellati
Keyword(s):
Low Power
◽
High Performance
◽
Power Devices
◽
Ultra Low Power
◽
Multi Objective
◽
Ultra Low Power Devices
Download Full-text
Efficient Scalable Digit-Serial Inverter Over GF( $2^{m}$ ) for Ultra-Low Power Devices
IEEE Access
◽
10.1109/access.2016.2639039
◽
2016
◽
Vol 4
◽
pp. 9758-9763
◽
Cited By ~ 3
Author(s):
Atef Ibrahim
◽
Turki F. Al-Somani
◽
Fayez Gebali
Keyword(s):
Low Power
◽
Power Devices
◽
Ultra Low Power
◽
Ultra Low Power Devices
Download Full-text
Ultra-Low Power Devices by Taking Advantages of Atom Switches with Polymer Solid-electrolyte
10.7567/ssdm.2012.b-4-1
◽
2012
◽
Author(s):
H. Hada
◽
T. Sakamoto
◽
M. Tada
◽
N. Banno
◽
M. Miyamura
◽
...
Keyword(s):
Low Power
◽
Solid Electrolyte
◽
Power Devices
◽
Ultra Low Power
◽
Ultra Low Power Devices
Download Full-text
Wireless powered wake-up receiver for ultra-low-power devices
2018 IEEE Wireless Communications and Networking Conference (WCNC)
◽
10.1109/wcnc.2018.8377436
◽
2018
◽
Cited By ~ 4
Author(s):
Soheil Rostami
◽
Kari Heiska
◽
Oleksandr Puchko
◽
Kari Leppanen
◽
Mikko Valkama
Keyword(s):
Low Power
◽
Power Devices
◽
Ultra Low Power
◽
Ultra Low Power Devices
Download Full-text
Energy vs. Reliability Trade-offs Exploration in Biomedical Ultra-Low Power Devices
Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition (DATE)
◽
10.3850/9783981537079_0053
◽
2016
◽
Author(s):
Loris Duch
◽
P. Garcia del Valle
◽
Shrikanth Ganapathy
◽
Andreas Burg
◽
David Atienza
Keyword(s):
Low Power
◽
Power Devices
◽
Ultra Low Power
◽
Trade Offs
◽
Ultra Low Power Devices
Download Full-text
Analysis of Higher Stable 9T SRAM Cell for Ultra Low Power Devices
10.1007/978-3-030-76736-5_47
◽
2021
◽
pp. 517-525
Author(s):
Harekrishna Kumar
◽
V. K. Tomar
Keyword(s):
Low Power
◽
Power Devices
◽
Ultra Low Power
◽
Sram Cell
◽
Ultra Low Power Devices
Download Full-text
Exploring of equivalent circuit model of piezoelectric energy harvesters for ultra low-power devices
2015 IEEE East-West Design & Test Symposium (EWDTS)
◽
10.1109/ewdts.2015.7493115
◽
2015
◽
Cited By ~ 1
Author(s):
A. V. Korshunov
◽
P. S. Volobuev
Keyword(s):
Low Power
◽
Equivalent Circuit
◽
Equivalent Circuit Model
◽
Circuit Model
◽
Power Devices
◽
Ultra Low Power
◽
Energy Harvesters
◽
Piezoelectric Energy
◽
Ultra Low Power Devices
Download Full-text
Machine Learning Oriented Resource Allocation to Achieve Ultra Low Power, Low Latency and High Reliability Vehicular Communication Networks
2020 IEEE 17th India Council International Conference (INDICON)
◽
10.1109/indicon49873.2020.9342584
◽
2020
◽
Author(s):
Sasweth C Rajanarayanan
◽
Rohit Misra
◽
Rahul Jashvantbhai Pandya
Keyword(s):
Machine Learning
◽
Resource Allocation
◽
Low Power
◽
Communication Networks
◽
High Reliability
◽
Low Latency
◽
Vehicular Communication
◽
Ultra Low Power
◽
Vehicular Communication Networks
Download Full-text
From algorithms to devices: Enabling machine learning through ultra-low-power VLSI mixed-signal array processing
2017 IEEE Custom Integrated Circuits Conference (CICC)
◽
10.1109/cicc.2017.7993650
◽
2017
◽
Cited By ~ 4
Author(s):
Siddharth Joshi
◽
Chul Kim
◽
Sohmyung Ha
◽
Gert Cauwenberghs
Keyword(s):
Machine Learning
◽
Low Power
◽
Array Processing
◽
Ultra Low Power
◽
Mixed Signal
Download Full-text
Sign in / Sign up
Close
Export Citation Format
Close
Share Document
Close