Implementation of Memristive Neural Network With Full-Function Pavlov Associative Memory

被引:94
|
作者
Liu, Xiaoyang [1 ]
Zeng, Zhigang [1 ,2 ]
Wen, Shiping [1 ,2 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Peoples R China
[2] Educ Minist China, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China
关键词
Associative memory; memristive neural network; memristor; SRDP; DESIGN; SYNAPSE; MODEL;
D O I
10.1109/TCSI.2016.2570819
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, implementation of memristive neural network with full-function Pavlov associative memory is designed based on a proposed associative memory rule. The designed neural network can well perform the Pavlov associative memory in the network with at least three interconnected neurons. This neural network and the associative memory rule that is partly based on spike-rate-dependent plasticity (SRDP) protocol are inspired by the famous Pavlov's dog-experiment that demonstrated the interrelation between the "sight of food" and the "ringing." Besides the learning activity, the proposed network can also perform two kinds of forgetting activities after the learning process is completed: on one hand, when the salivation neuron is stimulated by the food neuron alone, after a period of time, the ring neuron can no longer trigger the salivation neuron; on the other hand, when the salivation neuron is stimulated by the ring neuron alone, at first the salivation neuron can be triggered but after the salivation neuron realizes that the "ringing" is not associated with "food," the salivation neuron will not be triggered any longer. How to integrate the proposed network into large scale memristive neural network with multiple associations is also introduced. Simulations results demonstrate the correctness of the designs.
引用
收藏
页码:1454 / 1463
页数:10
相关论文
共 50 条
  • [31] ELECTRONIC IMPLEMENTATION OF ASSOCIATIVE MEMORY BASED ON NEURAL NETWORK MODELS
    MOOPENN, A
    LAMBE, J
    THAKOOR, AP
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1987, 17 (02): : 325 - 331
  • [32] Experimental demonstration of associative memory with memristive neural networks
    Pershin, Yuriy V.
    Di Ventra, Massimiliano
    NEURAL NETWORKS, 2010, 23 (07) : 881 - 886
  • [33] Bioinspired Memristive Neural Network Circuit Design of Cross-Modal Associative Memory
    Liu, Jinying
    Xiong, Feier
    Zhou, Yue
    Duan, Shukai
    Hu, Xiaofang
    IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2024, 16 (02) : 794 - 808
  • [34] CONNECTED ASSOCIATIVE MEMORY NEURAL NETWORK WITH DYNAMIC THRESHOLD FUNCTION
    HUANG, XM
    MIYAZAKI, Y
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 1992, E75D (01) : 170 - 179
  • [35] OPTICAL IMPLEMENTATION OF A NEURAL NETWORK ASSOCIATIVE MEMORY USING DIFFRACTION GRATINGS
    WEIBLE, KJ
    PEDRINI, G
    XUE, W
    THALMANN, R
    JAPANESE JOURNAL OF APPLIED PHYSICS PART 2-LETTERS & EXPRESS LETTERS, 1990, 29 (07): : L1301 - L1303
  • [36] Optical implementation of a neural network associative memory using diffraction gratings
    Weible, K.J.
    Pedrini, G.
    Xue, W.
    Thalmann, R.
    Japanese Journal of Applied Physics, Part 1: Regular Papers and Short Notes and Review Papers, 1990, 29 (07): : 1301 - 1303
  • [37] ELECTRONIC IMPLEMENTATION OF ASSOCIATIVE MEMORY BASED ON NEURAL NETWORK MODELS.
    Moopenn, A.
    Lambe, John
    Thakoor, A.P.
    1985, (SMC-17):
  • [38] Synchronization Control of Memristive Multidirectional Associative Memory Neural Networks and Applications in Network Security Communication
    Wang, Weiping
    Yu, Xin
    Luo, Xiong
    Kurths, Juergen
    IEEE ACCESS, 2018, 6 : 36002 - 36018
  • [39] A memristor-based circuit design and implementation for blocking on Pavlov associative memory
    Sichun Du
    Qing Deng
    Qinghui Hong
    Jun Li
    Haiyang Liu
    Chunhua Wang
    Neural Computing and Applications, 2022, 34 : 14745 - 14761
  • [40] A memristor-based circuit design and implementation for blocking on Pavlov associative memory
    Du, Sichun
    Deng, Qing
    Hong, Qinghui
    Li, Jun
    Liu, Haiyang
    Wang, Chunhua
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (17): : 14745 - 14761