A memristor-based associative memory neural network circuit with emotion effect

被引:16
|
作者
Wang, Chunhua [1 ]
Xu, Cong [1 ]
Sun, Jingru [1 ]
Deng, Quanli [1 ]
机构
[1] Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Peoples R China
来源
NEURAL COMPUTING & APPLICATIONS | 2023年 / 35卷 / 15期
基金
中国国家自然科学基金;
关键词
Memristor; Associative memory; Circuit implementation; Emotion; Mood congruency memory; Mood-dependent memory; DESIGN; MODEL; MOOD;
D O I
10.1007/s00521-023-08275-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Generally, people tend to learn or recall pleasant experiences during positive feelings. Similarly, people tend to learn or recall unpleasant things during negative feelings. The research in psychological field has demonstrated that human memory is closely related to emotion. On one hand, emotion helps store the memory that possesses the same emotion valence, which is known as the mood congruency memory (MCM). On the other hand, memory stored in a certain emotional state will be associated easily when the same emotion occurs, which is called mood-dependent memory (MDM). Inspired by the mechanisms of MCM and MDM, a memristor-based circuit of emotion-affected associative memory neural network is proposed in this work. The designed circuit mainly contains MCM module and MDM module. The functions, such as learning, forgetting, variable learning rate, MCM effect, MDM effect, and time interval, are implemented by the circuit. The simulation results in PSPICE show that the proposed memristive circuit can learn and associate the memory based on emotional effects like humans.
引用
收藏
页码:10929 / 10944
页数:16
相关论文
共 50 条
  • [41] A New Model of Associative Memory Neural Network Based on An Improved Memristor
    Wan, Geliang
    Wang, Leimin
    Zou, Huayu
    Jiang, Shan
    PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE, 2020, : 7589 - 7594
  • [42] A memristor-based long short term memory circuit
    Smagulova, Kamilya
    Krestinskaya, Olga
    James, Alex Pappachen
    ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING, 2018, 95 (03) : 467 - 472
  • [43] Chimera in a network of memristor-based Hopfield neural network
    Parastesh, Fatemeh
    Jafari, Sajad
    Azarnoush, Hamed
    Hatef, Boshra
    Namazi, Hamidreza
    Dudkowski, Dawid
    EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS, 2019, 228 (10): : 2023 - 2033
  • [44] Memristor-Based Circuit Design for Multilayer Neural Networks
    Zhang, Yang
    Wang, Xiaoping
    Friedman, Eby G.
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2018, 65 (02) : 677 - 686
  • [45] Chimera in a network of memristor-based Hopfield neural network
    Fatemeh Parastesh
    Sajad Jafari
    Hamed Azarnoush
    Boshra Hatef
    Hamidreza Namazi
    Dawid Dudkowski
    The European Physical Journal Special Topics, 2019, 228 : 2023 - 2033
  • [46] Memristor-based vector neural network architecture
    刘海军
    陈长林
    朱熙
    孙盛阳
    李清江
    李智炜
    Chinese Physics B, 2020, (02) : 535 - 539
  • [47] Dual functional states of working memory realized by memristor-based neural network
    Wang, Hongzhe
    Pan, Xinqiang
    Wang, Junjie
    Sun, Mingyuan
    Wu, Chuangui
    Yu, Qi
    Liu, Zhen
    Chen, Tupei
    Liu, Yang
    FRONTIERS IN NEUROSCIENCE, 2023, 17
  • [48] Development in memristor-based spiking neural network
    Abdi, Gisya
    Karacali, Ahmet
    Tanaka, Hirofumi
    IEICE NONLINEAR THEORY AND ITS APPLICATIONS, 2024, 15 (04): : 811 - 823
  • [49] Memristor-based vector neural network architecture
    Liu, Hai-Jun
    Chen, Chang-Lin
    Zhu, Xi
    Sun, Sheng-Yang
    Li, Qing-Jiang
    Li, Zhi-Wei
    CHINESE PHYSICS B, 2020, 29 (02)
  • [50] Memristor-based Deep Spiking Neural Network with a Computing-In-Memory Architecture
    Nowshin, Fabiha
    Yi, Yang
    PROCEEDINGS OF THE TWENTY THIRD INTERNATIONAL SYMPOSIUM ON QUALITY ELECTRONIC DESIGN (ISQED 2022), 2022, : 163 - 168