Memristive Circuit Design of Nonassociative Learning under Different Emotional Stimuli

被引:1
|
作者
Sun, Junwei [1 ]
Zhao, Linhao [1 ]
Wen, Shiping [2 ]
Wang, Yanfeng [1 ]
机构
[1] Zhengzhou Univ Light Ind, Sch Elect & Informat Engn, Zhengzhou 450002, Peoples R China
[2] Univ Technol Sydney, Australia AI Inst, Ultimo, NSW 2007, Australia
基金
中国国家自然科学基金;
关键词
memristor; nonassociative learning; habituation; sensitization; memristive circuit; NEURAL-NETWORK CIRCUIT; MEMORY; HABITUATION; MODEL;
D O I
10.3390/electronics11233851
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Most memristor-based circuits only consider the mechanism of nonassociative learning, and the effect of emotion on nonassociative learning is ignored. In this paper, a memristive circuit that can realize nonassociative learning under different emotional stimuli is designed. The designed circuit consists of stimulus judgment module, habituation module, sensitization module, emotion module. When different stimuli are applied, habituation or sensitisation is formed based on the intensity and nature of the stimuli. In addition, the influence of emotion on nonassociative is considered. Different emotional stimuli will affect the speed of habituation formation and strong negative stimuli will lead to sensitization. The simulation results on PSPICE show that the circuit can simulate the above complex biological mechanism. The memristive circuit of nonassociative learning under different emotional stimuli provides some references for brain-like systems.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] EMOTIONAL ASSESSMENT OF AUDITORY-STIMULI OF DIFFERENT INTENSITY
    RATANOVA, TA
    VOPROSY PSIKHOLOGII, 1986, (01) : 145 - 151
  • [32] OPPOSITE RESPONSES OF MUSCLE CIRCULATION TO DIFFERENT EMOTIONAL STIMULI
    BACCELLI, G
    ELLISON, GD
    MANCIA, G
    ZANCHETT.A
    EXPERIENTIA, 1971, 27 (10): : 1183 - &
  • [33] Memristive neural network circuit implementation of associative learning with overshadowing and blocking
    Jinying Liu
    Yue Zhou
    Shukai Duan
    Xiaofang Hu
    Cognitive Neurodynamics, 2023, 17 : 1029 - 1043
  • [34] Memristive self-learning logic circuit with application to encoder and decoder
    Qinghui Hong
    Zirui Shi
    Jingru Sun
    Sichun Du
    Neural Computing and Applications, 2021, 33 : 4901 - 4913
  • [35] Enhance controllability of a memristive neuron under magnetic field and circuit approach
    Yang, Feifei
    Han, Zhitang
    Ren, Guodong
    Guo, Qun
    Ma, Jun
    EUROPEAN PHYSICAL JOURNAL PLUS, 2024, 139 (06):
  • [36] Memristive Device Modeling and Circuit Design Exploration for Computation-in-Memory
    Siemon, Anne
    Wouters, Dirk
    Hamdioui, Said
    Menzel, Stephan
    2019 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2019,
  • [37] The Framework and Memristive Circuit Design for Multisensory Mutual Associative Memory Networks
    Zhang, Yutong
    Lv, Junting
    Zeng, Zhigang
    IEEE TRANSACTIONS ON CYBERNETICS, 2023, 53 (12) : 7844 - 7857
  • [38] Generalized Memristive Device SPICE Model and its Application in Circuit Design
    Yakopcic, Chris
    Taha, Tarek M.
    Subramanyam, Guru
    Pino, Robinson E.
    IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2013, 32 (08) : 1201 - 1214
  • [39] Memristive Threshold Logic Circuit Design of Fast Moving Object Detection
    Maan, Akshay Kumar
    Kumar, Dinesh Sasi
    Sugathan, Sherin
    James, Alex Pappachen
    IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2015, 23 (10) : 2337 - 2341
  • [40] Input design for controlling dynamics in a second-order memristive circuit
    Di Marco, Mauro
    Forti, Mauro
    Innocenti, Giacomo
    Tesi, Alberto
    24TH IEEE EUROPEAN CONFERENCE ON CIRCUIT THEORY AND DESIGN (ECCTD 2020), 2020,