@inproceedings{346eb1f4777f4468b3df47d33a23e462,
title = "Bio-inspired computing with resistive memories - Models, architectures and applications",
abstract = "The traditional Von Neumann architecture has constrained the potential for applying massively parallel architecture to embedded high performance computing where we must optimize the size, weight and power of the system. Inspired by highly parallel biological systems, such as the human brain, the neuromorphic architecture offers a promising novel computing paradigm for compact and energy efficient platforms. The discovery of memristor devices provided the element we need with unprecedented efficiency in realizing such a computing architecture. There are still many challenges left to meet our goal of a fully functional bio-inspired computer. Here we will discuss our research in memristor crossbar based architecture, adaptation of this architecture for cogent confabulation models, and potential applications of the bio-inspired computer.",
keywords = "architecture, bio-inspired, confabulation, memristor, neuromorphic",
author = "Qing Wu and Beiye Liu and Yiran Chen and Hai Li and Qiuwen Chen and Qinru Qiu",
year = "2014",
doi = "10.1109/ISCAS.2014.6865265",
language = "English (US)",
isbn = "9781479934324",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "834--837",
booktitle = "2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014",
note = "2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014 ; Conference date: 01-06-2014 Through 05-06-2014",
}