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计算机工程

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基于忆容桥的突触电路研究

李超辈,李传东,张金铖   

  1. (重庆大学计算机学院,重庆 400030)
  • 收稿日期:2012-09-03 出版日期:2013-12-15 发布日期:2013-12-13
  • 作者简介:李超辈(1987-),男,硕士研究生,主研方向:人工神经网络;李传东,教授、博士生导师;张金铖,硕士研究生
  • 基金资助:
    国家自然科学基金资助项目(60974020);中央高校基本科研业务费专项基金资助项目(CDJZR10185501)

Synapses Circuit Research Based on Memcapacitor Bridge

LI Chao-bei, LI Chuan-dong, ZHANG Jin-cheng   

  1. (College of Computer Science, Chongqing University, Chongqing 400030, China)
  • Received:2012-09-03 Online:2013-12-15 Published:2013-12-13

摘要: 利用4个相同忆容器构建一个能实现零、正和负突触权重的忆容桥电路。在附加3个晶体三极管后,忆容桥权重电路能够实现神经细胞的突触操作。由于整个操作都是基于脉冲输入信号,因此整个电路是高效节能的。通过Matlab实现突触权重设计和突触权重乘法的模拟。仿真实验结果表明,基于线性忆容桥的突触电路在性能上与忆阻突触桥电路基本相当,优于传统突触乘法电路。

关键词: 忆容器, 忆阻器, 忆容桥突触, 突触权重, 脉冲输入

Abstract: Through using the mathematical model of the charge-controlled memcapacitor, a memcapacitor bridge circuit consisting of four identical memcapacatiors is proposed that is able to perform zero, negative, and positive synaptic weightings. And together with three additional transistors, the memcapacitor bridge weight circuit is able to perform synaptic operation for neural cells. It is power efficient, since the operation is based on pulsed input signals. Synaptic weight programming and synaptic weight multiplication processing is performed by using the Matlab. Simulation results show that the performance of synapses circuit based on linear-memcapacitor bridge is almost equal as the memristor bridge synapses circuit, and is better than the traditional multiplication circuit.

Key words: memcapacitor, memristor, memcapacitor bridge synapses, synapses weight, pulsed input

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