基于改进的忆阻器在字符联想记忆中的应用  

Application of Improved Memristor in Character Associative Memory

作　　者：王雷敏 程佳俊 胡成[4] 周映江[5] 葛明峰 WANG Leimin;CHENG Jiajun;HU Cheng;ZHOU Yingjiang;GE Mingfeng(School of Automation,China University of Geosciences,Wuhan 430074,China;Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems,Wuhan 430074,China;Engineering Research Center of Intelligent Technology for Geo-Exploration,Ministry of Education,Wuhan 430074,China;School of Mathematics and Systems Science,Xinjiang University,Urumqi 830017,China;School of Automation,Nanjing University of Posts and Telecommunications,Nanjing 210003,China;School of Mechanical and Electronic Information,China University of Geosciences,Wuhan 430074,China)

机构地区：[1]中国地质大学(武汉)自动化学院,武汉430074 [2]复杂系统先进控制与智能自动化湖北省重点实验室,武汉430074 [3]地球探测智能化技术教育部工程研究中心,武汉430074 [4]新疆大学数学与系统科学学院,乌鲁木齐830017 [5]南京邮电大学自动化学院,南京210003 [6]中国地质大学(武汉)机械与电子信息学院,武汉430074

出　　处：《电子与信息学报》2023年第7期2667-2674,共8页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(62076229,61963033,62073301)。

摘　　要：忆阻因具有阻值可调、记忆特性以及纳米尺寸等特点,非常适合作为实现神经网络突触的电子元器件。为构建出更加符合真实物理忆阻器特性的忆阻器模型,该文在现有忆阻器模型的基础之上,克服了边界锁定、正负电压调整速率问题以及电路结构通用性问题,提出一种改进忆阻器模型。然后结合Pavlov联想记忆实验和Hopfield神经网络理论设计出了该文的字符联想记忆电路。电路结构主要有输入信号模块、突触阵列模块、激活函数模块以及反馈控制模块。该电路可以解决因传统阵列模块使用电阻作为突触模块的灵活性问题,而且还可以实现对3阶字符模糊图像的自联想功能。此外,该电路与深度学习相关的卷积计算模块原理类似,为实现基于忆阻的智能硬件奠定了理论基础。Memristor is a very suitable electronic component for synapse of neural network because of its adjustable resistance,memory property and nano size.In order to build a memristor model more consistent with the characteristics of real physical memristors,an improved memristor model is proposed based on existing ones to overcome the problems of boundary locking,positive and negative voltage rate adjustment and the universality of circuit structure.Then combining Pavlov associative memory experiment and Hopfield neural network theory,the character associative memory circuit is designed in this paper.The circuit structure includes mainly input signal module,synaptic array module,activation function module and feedback control module.This circuit can solve the flexibility problem of using resistors as synaptic modules in traditional array modules,and can also realize the self-association function of third-order character blurred images.In addition,the circuit is similar to the convolutional computation module related to deep learning,and provides a theoretical basis for realizing memristor-based intelligent hardware.

关 键 词：忆阻器 神经网络 电路设计 联想记忆 

分 类 号：TN601[电子电信—电路与系统]