Markov Chain Hebbian Learning Algorithm With Ternary Synaptic Units

Markov Chain Hebbian Learning Algorithm With Ternary Synaptic Units

In spite of remarkable progress in machine learning techniques, the state-of-the-art machine learning algorithms often keep machines from real-time learning (online learning) due, in part, to computational complexity in parameter optimization. As an alternative, a learning algorithm to train a memor...

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Bibliographic Details
Main Authors: Guhyun Kim, Vladimir Kornijcuk, Dohun Kim, Inho Kim, Jaewook Kim, Hyo Cheon Woo, Jihun Kim, Cheol Seong Hwang, Doo Seok Jeong
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Greedy edge-wise training
Hebbian learning
Markov chain
mental arithmetic
prime factorization
supervised learning
Online Access:https://ieeexplore.ieee.org/document/8607972/

Internet

https://ieeexplore.ieee.org/document/8607972/

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