@inproceedings{69c633e897f346ff9f895f7f1eb51f40,
title = "Analog Unidirectional Memristive and Memcapacitive Device for Neuromorphic Computing",
abstract = "Intelligent and adaptable systems can greatly benefit from the capabilities of tunable electronics. Memristors and memcapacitors have undergone thorough investigation as compelling options for fulfilling the demand of various emerging applications, thanks to their attributes of low power consumption, high density, and rapid operation, enabling the provision of adjustable states. This work focused on the characteristics of analog unidirectional memristive and memcapacitive switching in ITO/ZnO/Yb2031 Au. The analog resistive memory device exhibited a gradual transformation in resistance and capacitance during repeated voltage sweeps. Simultaneously, the coexistent analog memristive and memcapacitive traits emulated the dynamics of biological synaptic strengthening and weakening, implying a potential application in neuromorphic devices to analyze long-term memory (L TM) or short-term memory (STM). The device's capacity for altering its weight was used for hardware implementation of neural networks, achieving an impressive accuracy rate of 93%.",
keywords = "analog, LTM, Memcapacitive, Memristive, STM",
author = "Khan, {Muhammad Umair} and Yawar Abbas and Baker Mohammad",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 18th International Workshop on Cellular Nanoscale Networks and their Applications, CNNA 2023 ; Conference date: 28-09-2023 Through 30-09-2023",
year = "2023",
doi = "10.1109/CNNA60945.2023.10652757",
language = "British English",
series = "International Workshop on Cellular Nanoscale Networks and their Applications",
publisher = "IEEE Computer Society",
booktitle = "2023 18th International Workshop on Cellular Nanoscale Networks and their Applications, CNNA 2023",
address = "United States",
}