An overview of Hierarchical Temporal Memory: A new neocortex algorithm
X Chen, W Wang, W Li - 2012 Proceedings of International …, 2012 - ieeexplore.ieee.org
The overview presents the development and application of Hierarchical Temporal Memory
(HTM). HTM is a new machine learning method which was proposed by Jeff Hawkins in …
(HTM). HTM is a new machine learning method which was proposed by Jeff Hawkins in …
Methods for reducing memristor crossbar simulation time
R Uppala, C Yakopcic, TM Taha - 2015 national aerospace and …, 2015 - ieeexplore.ieee.org
Memristor crossbars have the potential to perform parallel resistive computations in the
analog domain, and they can be used to develop high density neural network algorithms …
analog domain, and they can be used to develop high density neural network algorithms …
ASIPs for artificial neural networks
D Shapiro, J Parri, JM Desmarais… - 2011 6th IEEE …, 2011 - ieeexplore.ieee.org
Customized application-specific processors called ASIPs are becoming commonplace in
contemporary embedded system designs. Neural networks are an interesting application for …
contemporary embedded system designs. Neural networks are an interesting application for …
Simulating large scale memristor based crossbar for neuromorphic applications
R Uppala - 2015 - rave.ohiolink.edu
The memristor is a novel nano-scale device discovered in 2008. Memristors are basically
nonvolatile variable resistors. Various breakthroughs of memristive devices have shown the …
nonvolatile variable resistors. Various breakthroughs of memristive devices have shown the …
Parallelization implementation of Bayesian algorithms based on Spark platform
H Liu, H Guo, W Hu - 2019 IEEE International Conference on …, 2019 - ieeexplore.ieee.org
With the rapid development of Internet technology, all kinds of data are growing
exponentially. How to effectively manage and utilize these data has become the focus of …
exponentially. How to effectively manage and utilize these data has become the focus of …