皮质神经元的模拟电路实现

Shivangi Sharma, J. Dhanoa
{"title":"皮质神经元的模拟电路实现","authors":"Shivangi Sharma, J. Dhanoa","doi":"10.1109/ICRAIE51050.2020.9358377","DOIUrl":null,"url":null,"abstract":"Cortical neurons play a predominant role in major functions like motor and sensory actions, cognition, perception, etc. The analysis, modeling of cortical neurons facilitates the implementation of faster and smarter neuromorphic architectures. This paper presents the implementation of an analog CMOS circuit that resembles the functionality of cortical neurons. This silicon neuron circuit comprises only 14 MOSFETS and is capable of providing various kinds of spiking patterns such as regular, fast-spiking, and bursting, just by varying bias voltages. This property enables the fabrication of many neurons onto a single chip and exhibits flexibility of emulating different neuronal behaviors with a little modification in bias voltages. This makes a circuit that can be used as a basic cell in the implementation of spiking neural networks, brain-inspired circuits, and cognitive robots, etc. The circuit is analyzed for its performance and the simulations are carried out using cadence virtuoso at 180nm technology node.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analog Circuit Implementation of a Cortical Neuron\",\"authors\":\"Shivangi Sharma, J. Dhanoa\",\"doi\":\"10.1109/ICRAIE51050.2020.9358377\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cortical neurons play a predominant role in major functions like motor and sensory actions, cognition, perception, etc. The analysis, modeling of cortical neurons facilitates the implementation of faster and smarter neuromorphic architectures. This paper presents the implementation of an analog CMOS circuit that resembles the functionality of cortical neurons. This silicon neuron circuit comprises only 14 MOSFETS and is capable of providing various kinds of spiking patterns such as regular, fast-spiking, and bursting, just by varying bias voltages. This property enables the fabrication of many neurons onto a single chip and exhibits flexibility of emulating different neuronal behaviors with a little modification in bias voltages. This makes a circuit that can be used as a basic cell in the implementation of spiking neural networks, brain-inspired circuits, and cognitive robots, etc. The circuit is analyzed for its performance and the simulations are carried out using cadence virtuoso at 180nm technology node.\",\"PeriodicalId\":149717,\"journal\":{\"name\":\"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRAIE51050.2020.9358377\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAIE51050.2020.9358377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

皮层神经元在运动和感觉动作、认知、知觉等主要功能中起主导作用。皮质神经元的分析、建模有助于实现更快、更智能的神经形态架构。本文提出了一个模拟CMOS电路的实现,类似于皮质神经元的功能。这种硅神经元电路仅包含14个mosfet,并且能够通过改变偏置电压提供各种类型的尖峰模式,例如规则,快速尖峰和爆发。这一特性使得在单个芯片上制造许多神经元成为可能,并且显示出只需稍微改变偏置电压即可模拟不同神经元行为的灵活性。这就形成了一个电路,它可以作为实现尖峰神经网络、大脑启发电路和认知机器人等的基本细胞。对该电路进行了性能分析,并利用cadence virtuoso在180nm技术节点上进行了仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Analog Circuit Implementation of a Cortical Neuron
Cortical neurons play a predominant role in major functions like motor and sensory actions, cognition, perception, etc. The analysis, modeling of cortical neurons facilitates the implementation of faster and smarter neuromorphic architectures. This paper presents the implementation of an analog CMOS circuit that resembles the functionality of cortical neurons. This silicon neuron circuit comprises only 14 MOSFETS and is capable of providing various kinds of spiking patterns such as regular, fast-spiking, and bursting, just by varying bias voltages. This property enables the fabrication of many neurons onto a single chip and exhibits flexibility of emulating different neuronal behaviors with a little modification in bias voltages. This makes a circuit that can be used as a basic cell in the implementation of spiking neural networks, brain-inspired circuits, and cognitive robots, etc. The circuit is analyzed for its performance and the simulations are carried out using cadence virtuoso at 180nm technology node.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
COVID19: Impact on Indian Power Sector Smart Logic Built in Self-Test in SOC 2020 5th IEEE International Conference (Virtual Mode) on Recent Advances and Innovations in Engineering (IEEE - ICRAIE-2020) Hybrid Ant Colony Optimization Algorithm for Multiple Knapsack Problem Outage Probability Evaluation for Relay-Based DF Cooperative Diversity Systems with Multipath Fading Channels and Non-Identical Interferers
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1