| Title: | OS9-5 A Multistage Heuristic Tuning Algorithm for an Analog Silicon Neuron Circuit |
|---|---|
| Publication: | ICAROB2017 |
| Volume: | 22 |
| Pages: | 144-147 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2017.OS9-5 |
| Author(s): | Ethan Green, Takashi Kohno |
| Publication Date: | January 19, 2017 |
| Keywords: | neuromorphic engineering, analog VLSI, silicon neurons |
| Abstract: | This research looks at an ultra-low power subthreshold-operated silicon neuron circuit designed with qualitative neuronal modeling. One technical challenge to future implementation of such circuits is parameter tuning—a problem stemming from temperature sensitivity of subthreshold-operated MOSFETs and the uniqueness of individual circuits in a neuronal network due to transistor variation. This research proposes a fully automated parameter tuning algorithm that combines two heuristic approaches to search for appropriate circuit parameters over a range of temperatures. The algorithm can tune the circuit to behave as a Class I or Class II neuron. |
| PDF File: | https://alife-robotics.co.jp/members2017/icarob/data/html/data/OS_pdf/OS9/OS9-5.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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