Mimicking Classical Conditioning Based on a Single Flexible Memristor-Reference-Cited by-同舟云学术

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Mimicking Classical Conditioning Based on a Single Flexible Memristor

Published:2016-12-20 Issue:10 Volume:29 Page:1602890
ISSN:0935-9648
Container-title:Advanced Materials
language:en
Short-container-title:Adv. Mater.

Author:

Wu Chaoxing¹,Kim Tae Whan¹,Guo Tailiang²,Li Fushan²,Lee Dea Uk¹,Yang J. Joshua³

Affiliation:

1. Department of Electronic and Computer Engineering; Hanyang University; Seoul 133-791 Korea

2. Institute of Optoelectronic Display; Fuzhou University; Fuzhou 350002 P. R. China

3. Department of Electrical and Computer Engineering; University of Massachusetts; Amherst MA 01003-9292 USA

Funder

Ministry of Education, Science and Technology

Ministry of Science, ICT and Future Planning

Publisher

Wiley

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Reference47 articles.

1. The Principles of Large-Scale Computing Machines

2. Distributed synaptic modification in neural networks induced by patterned stimulation

3. Training and operation of an integrated neuromorphic network based on metal-oxide memristors

4. Associative memory realized by a reconfigurable memristive Hopfield neural network

5. Synchrony Detection and Amplification by Silicon Neurons With STDP Synapses

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