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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qing Wu Beiye Liu Yiran Chen Hai Li Qiuwen Chen Qinru Qiu |
| Copyright Year | 2014 |
| Description | Author affiliation: Elec. & Comp. Eng., Univ. of Pittsburgh, Pittsburgh, PA, USA (Beiye Liu; Yiran Chen; Hai Li) || Inf. Directorate, Air Force Res. Lab., Rome, NY, USA (Qing Wu) || Elec. Eng. & Comp. Sci, Syracuse Univ., Syracuse, NY, USA (Qiuwen Chen; Qinru Qiu) |
| 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. |
| Sponsorship | IEEE Circuits Syst. Soc. |
| Starting Page | 834 |
| Ending Page | 837 |
| File Size | 889294 |
| Page Count | 4 |
| File Format | |
| e-ISBN | 9781479934324 |
| DOI | 10.1109/ISCAS.2014.6865265 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-01 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Memristors Neuromorphics Computational modeling Arrays Biological system modeling Hardware confabulation neuromorphic architecture memristor bio-inspired |
| Content Type | Text |
| Resource Type | Article |
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