Integrated synapse devices for fluxon neural networks

用于 Fluxon 神经网络的集成突触设备

基本信息

  • 批准号:
    05650322
  • 负责人:
  • 金额:
    $ 1.54万
  • 依托单位:
  • 依托单位国家:
    日本
  • 项目类别:
    Grant-in-Aid for General Scientific Research (C)
  • 财政年份:
    1993
  • 资助国家:
    日本
  • 起止时间:
    1993 至 1994
  • 项目状态:
    已结题

项目摘要

Novel superconducting circuits for a neuron and two types of variable synapses, which are based on SQUIDs, are presented. Josephson circuits seem to be superior for VLSI of the neural networks because of the high-speed operation under very low power dissipation. A neuron circuit with good input-output isolation and steep threshold characteristics is accomplished using a combination of a single-junction SQUID coupled to a double-junction SQUID.The quantum state of the single-junction SQUID represents the neuron state, and output voltage of the double-junction SQUID,which is operated under a nonlatching mode with shunt resistors, is a sigmoid-shaped function. One of the variable synapse circuits changes its conductance value digitally. Another variable synapse circuit is a variable current source in which the output current can change digitally. Both synapse circuits consist of multiple shunted double-junction SQUIDs. Besides numerical simulations of the circuit characteristics, we have fabricated superconducting neural chips using a Nb/AIOx/Nb Josephson junction technology. The fundamental operation of each element and 3-bit A/D converter are successfully demonstrated. This A/D converter was operated with analog input frequency as high as 100kHz, limited by our high-gain measurement equipment. Simulation shows that this network responds to analog input at over 100MHz. Testing the network at such high speeds is one of our challenges in the future. A learning system based on Hebb's rule with variable-current-source type of synapse is also discussed.
提出了一种基于SQUID的神经元和两种可变突触的新型超导电路。约瑟夫森电路以其极低的功耗实现高速运算,在神经网络的超大规模集成电路中具有上级优势。利用单结SQUID和双结SQUID的组合实现了具有良好输入输出隔离度和陡峭阈值特性的神经元电路,单结SQUID的量子态代表神经元的状态,双结SQUID的输出电压是S形函数,工作在带分流电阻的非锁存模式下.可变突触电路之一以数字方式改变其电导值。另一可变突触电路是可变电流源,其中输出电流可以数字地改变。两个突触回路都由多个分流的双结SQUID组成。除了电路特性的数值模拟,我们已经制作了超导神经芯片使用Nb/AlOx/Nb约瑟夫森结技术。成功地演示了每个元件和3位A/D转换器的基本操作。该A/D转换器的模拟输入频率高达100 kHz,受到我们高增益测量设备的限制。仿真结果表明,该网络对100 MHz以上的模拟输入有响应。以如此高的速度测试网络是我们未来的挑战之一。本文还讨论了一个基于Hebb规则的变电流源型突触学习系统。

项目成果

期刊论文数量(48)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Y. Mizugaki: "Linearization analysis of threshold characteristics for some applications of mutually coupled SQUIDs" IECE Trans. Electron.E76-C. 1291-1297 (1993)
Y. Mizugaki:“互耦合 SQUID 某些应用的阈值特性的线性化分析”IECE Trans。
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
Y.Mizugaki: "Implementation of superconducting synapse into a neuro-based analog-to-digital converter" Appl.Phys.Lett.65. 1712-1713 (1994)
Y.Mizugaki:“将超导突触实现到基于神经的模数转换器”Appl.Phys.Lett.65。
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
S.Sato: "LSI Neural Chip of Pulse-Output Network with Programmable Synapse" IEICE Trans.ELECTRON.E78-C. 94-100 (1995)
S.Sato:“具有可编程突触的脉冲输出网络LSI神经芯片”IEICE Trans.ELECTRON.E78-C。
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
K. Nakajima: "Correct reaction neural network" Neural Networks. 6. 217-222 (1993)
K. Nakajima:“正确反应神经网络”神经网络。
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
Y.Mizugaki: "New Approach Implementation of Neural Circuits Using Superconductive Devices" Extended Abstracts of the 1994 Int.Conf.on SSDM. 364-366 (1994)
Y.Mizugaki:“使用超导器件实现神经电路的新方法”1994 年 Int.Conf.on SSDM 的扩展摘要。
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

NAKAJIMA Koji其他文献

NAKAJIMA Koji的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('NAKAJIMA Koji', 18)}}的其他基金

A Study of developing a framework for motivating university faculty for implementing e-learning by designing with ID models
通过 ID 模型设计开发激励大学教师实施电子学习的框架的研究
  • 批准号:
    24501225
  • 财政年份:
    2012
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
High speed logic and memory system based on pair-creation and -annihilation of shingle flux quanta
基于叠瓦通量量子配对生成和湮灭的高速逻辑和存储系统
  • 批准号:
    24656221
  • 财政年份:
    2012
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Challenging Exploratory Research
Elucidation of keratinocyte differentiation and proliferation by splicing of transcritption factor.
通过转录因子的剪接阐明角质形成细胞的分化和增殖。
  • 批准号:
    23791247
  • 财政年份:
    2011
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Young Scientists (B)
Expression regulation of basement membrane proteins by transcription factor of epithelial to mesenchymal transition
上皮间质转化转录因子对基底膜蛋白表达的调控
  • 批准号:
    21791055
  • 财政年份:
    2009
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Young Scientists (B)
Artificial Brain Construction based on a Massive Connection of Higher-order and Active Silicon Neurons
基于高阶活性硅神经元大规模连接的人工大脑构建
  • 批准号:
    18360159
  • 财政年份:
    2006
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
SFQ Fast Fourier Transform Circuit Using Localized SignalTransmission
使用局部信号传输的 SFQ 快速傅立叶变换电路
  • 批准号:
    18080001
  • 财政年份:
    2006
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Scientific Research on Priority Areas
The architectonic Study of information processing system based on fabricating an active artificial brain
基于主动人工脑的信息处理系统体系结构研究
  • 批准号:
    14350175
  • 财政年份:
    2002
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Constitution of Neuro-based Dynamic Memory
基于神经的动态记忆的构成
  • 批准号:
    09450135
  • 财政年份:
    1997
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Study on an associative memory system with a new analog memory device
新型模拟存储器件联想存储系统的研究
  • 批准号:
    09555106
  • 财政年份:
    1997
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
INTEGRATION OF NEURAL NETWORKS USING SUPERCONDUCTIVE DEVICES
使用超导器件集成神经网络
  • 批准号:
    06555112
  • 财政年份:
    1994
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Developmental Scientific Research (B)

相似海外基金

IC neuro chip with analog synapses for a correct reaction neural network
具有模拟突触的 IC 神经芯片,可实现神经网络的正确反应
  • 批准号:
    05555105
  • 财政年份:
    1993
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for Developmental Scientific Research (B)
Study on the Development of Neuro-Chip for the Quality Evaluation of Brown Rice
糙米品质评价神经芯片的研制
  • 批准号:
    03806038
  • 财政年份:
    1991
  • 资助金额:
    $ 1.54万
  • 项目类别:
    Grant-in-Aid for General Scientific Research (C)
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了