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Cited 2 time in webofscience Cited 2 time in scopus
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Demonstration of cognitive learning, associative learning, and multi-bit reservoir computing using TiOx/HfOx-based volatile memristor with low current

Authors
Jang, HeeseongJu, DongyeolKim, Sungjun
Issue Date
Feb-2025
Publisher
ELSEVIER SCIENCE SA
Keywords
Memristor; Resistive switching; Short-term memory; EPSC; Reservoir computing
Citation
Journal of Alloys and Compounds, v.1016, pp 1 - 11
Pages
11
Indexed
SCIE
SCOPUS
Journal Title
Journal of Alloys and Compounds
Volume
1016
Start Page
1
End Page
11
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/57865
DOI
10.1016/j.jallcom.2025.178897
ISSN
0925-8388
1873-4669
Abstract
In this study, the TiN/TiOx/HfOx/Pt memristor with short-term memory (STM) and self-rectifying properties is characterized for multiple computing functions. The STM properties of the devices are detected by the retention test. The emulation of synaptic memory and forgetfulness by STM effects is demonstrated using paired-pulse facilitation. We also emulate various synaptic behaviors such as several excitatory post-synaptic currents and Pavlovian associative learning. The TiN/TiOx/HfOx/Pt configuration of this device replicates key functions of biological nociceptors for sensory memory. Emulation includes important aspects such as threshold, relaxation, "Hyperalgesia" and "Allodynia." Finally, efficient training reservoir computing is demonstrated in artificial neural network simulations, composed of physical storage memristor devices with 16 and 128 states (4-bit and 7bit), and a readout layer, yielding respective pattern recognition accuracies of 97.73 % and 96.77 % for the dataset.
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