@inproceedings{6fa77338c4714650bfa894ba7f85c489,
title = "Current Mode Neuromorphic Implementation using Current Memory",
abstract = "Recently, neuromorphic research has been drawing attentions as there is a limitation of a serial processor with a Von Neumann architecture. In particular, spiking neural network (SNN) is one of the neuromorphic AI models that has been actively researched because it can be implemented with a low power consumption and a parallel signal processing system. Non-volatile semiconductors are currently used for SNN implementation, but they still have limitations due to problems with production cost and compatibility with silicon devices. Therefore, in this paper, a new SNN model using CMOS is proposed and proved through post simulation with cadence MMSIM.",
keywords = "current memory, current-mode, neuromorphic, SNN",
author = "Hyungmin Kim and Lee, \{Daniel Juhun\} and Soyoun Park and Taemin Nho and Shin, \{Young Chul\} and Seongkweon Kim and Shim, \{Dong Ha\}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 17th International System-on-Chip Design Conference, ISOCC 2020 ; Conference date: 21-10-2020 Through 24-10-2020",
year = "2020",
month = oct,
day = "21",
doi = "10.1109/ISOCC50952.2020.9332996",
language = "English",
series = "Proceedings - International SoC Design Conference, ISOCC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "248--249",
booktitle = "Proceedings - International SoC Design Conference, ISOCC 2020",
}