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Circuit Realization of a Neuromorphic Computing System with Memristor-Based Synapse Design.

机译：基于忆阻器的突触设计的神经形态计算系统的电路实现。

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Conventional CMOS technology is slowly approaching its physical limitations and researchers are increasingly utilizing nanotechnology to both extend CMOS capabilities and to explore potential replacements. Novel memristive systems continue to attract growing attention since their reported physical realization by HP in 2008. Unique characteristics like non-volatility, re-configurability, and analog storage properties make memristors a very promising candidate for the realization of artificial neural systems. In this work, we propose a memristor-based design of bidirectional transmission excitation/inhibition synapses and implement a neuromorphic computing system based on our proposed synapse designs. The robustness of our system is also evaluated by considering the actual manufacturing variability with emphasis on process variation.

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作者
Liu, B.; Chen, Y.; Wysocki, B.; Huang, T.;
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年度 2013
页码 1-10
总页数 10
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Analog systems; Circuits; Synapse; Nanotechnology; Pattern recognition; Physical properties; Transmittance; Ann(Analog neural networks); Bidirectional snapses; Hopfield networks; Memristors; Neuromorphic computing systems;

机译：模拟系统;电路;突触;纳米技术;模式识别;物理特性;透射率;安（模拟神经网络）;双向快照; Hopfield网络;忆阻器;神经形态计算系统;

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专利

1. Monolithic 3D neuromorphic computing system with hybrid CMOS and memristor-based synapses and neurons [J] . An Hongyu, Ehsan M. Amimul, Zhou Zhen, Integration . 2019,第MARa期

机译：具有混合CMOS和基于忆阻器的突触和神经元的单片3D神经形态计算系统
2. Monolithic 3D neuromorphic computing system with hybrid CMOS and memristor-based synapses and neurons [J] . An Hongyu, Ehsan M. Amimul, Zhou Zhen, Integration . 2019,第Mara期

机译：具有杂种CMOS和基于椎体突触和神经元的整体式3D神经形态计算系统
3. Reconfigurable Neuromorphic Computing System with Memristor-Based Synapse Design [J] . Liu Beiye, Chen Yiran, Wysocki Bryant, Neural processing letters . 2015,第2期

机译：基于忆阻器的突触设计的可重构神经形态计算系统
4. The Circuit Realization of a Neuromorphic Computing System with Memristor-Based Synapse Design [C] . Beiye Liu, Yiran Chen, Bryant Wysocki, International conference on neural information processing . 2012

机译：基于忆阻器突触设计的神经形态计算系统的电路实现
5. Efficient Neuromorphic Computing Enabled by Spin-Transfer Torque: Devices, Circuits and Systems [D] . Sengupta, Abhronil. 2018

机译：旋转传递扭矩实现的高效神经形态计算：设备，电路和系统
6. Neuromorphic log-domain silicon synapse circuits obey bernoulli dynamics: a unifying tutorial analysis [O] . Konstantinos I. Papadimitriou, Shih-Chii Liu, Giacomo Indiveri, 2014

机译：神经形态对数域硅突触电路服从伯努利动力学：统一的教程分析
7. A differential memristive synapse circuit for on-line learning in neuromorphic computing systems [O] . Manu V Nair, Lorenz K Muller, Giacomo Indiveri 2017

机译：神经形态计算系统在线学习的差分膜突触电路

Circuit Realization of a Neuromorphic Computing System with Memristor-Based Synapse Design.

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