article

Memristor crossbar-based unsupervised image learning

Authors:

Xin WangAuthors Info & Claims

Neural Computing and Applications, Volume 25, Issue 2

Pages 393 - 400

https://doi.org/10.1007/s00521-013-1501-0

Published: 01 August 2014 Publication History

Abstract

This letter presents a new memristor crossbar array system and demonstrates its applications in image learning. The controlled pulse and image overlay technique are introduced for the programming of memristor crossbars and promising a better performance for noise reduction. The time-slot technique is helpful for improving the processing speed of image. Simulink and numerical simulations have been employed to demonstrate the useful applications of the proposed circuit structure in image learning.

References

[1]

Strukov DB, Snider GS, Stewart DR, Williams RS (2008) The missing memristor found. Nature 452(7191):80---83

Crossref

Google Scholar

[2]

Chua LO (1971) Memristor: the missing circuit element. IEEE Trans Circuit Theory 18(5):507---519

Crossref

Google Scholar

[3]

Bayat FM, Shouraki SB (2011) Programming of memristor crossbars by using genetic algorithm. Proc Comput Sci 3:232---237

Crossref

Google Scholar

[4]

Prodromakis T, Toumazou C (2010) A review on memristive devices and applications. In: 17th IEEE international conference on electronics, circuits, and systems, 2010, Athens, 12---15 Dec 2010, pp 934---937

Crossref

Google Scholar

[5]

Pershin YV, Ventra MD (2010) Experimental demonstration of associative memory with memristive neural networks. Neural Networks 23(7):881---886

Digital Library

Google Scholar

[6]

Pershin YV, Ventra MD Neuromorphic, digital and quantum computation with memory circuit elements. Quantum 1---9

Google Scholar

[7]

Hu XF, Duan SK, Wang LD, Liao XF (2012) Memristive crossbar array with applications in image processing. Sci China Inf Sci 55(2):461---472

Crossref

Google Scholar

[8]

Kim KH, Gaba S, Wheeler D, Cruz-Albrecht JM, Hussain T, Srinivasa N, Lu W (2011) A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications. Nano Lett 12(3):389---395

Google Scholar

[9]

Aafifi A, Ayatollahi A, Raissi F (2009) Implementation of biologically plausible spiking neural network models on the memristor crossbar-based CMOS/nano circuits. In: ECCTD. European, conference on circuit theory and design, pp 563---566

Google Scholar

[10]

Querlioz D, Bichler O, Gamrat C (2011) Simulation of a memristor-based spiking neural network immune to device variations. In: The international joint conference on neural networks, pp 1775---1781

Google Scholar

[11]

Bayat FM, Shouraki SB (2011) Memristive fuzzy edge detector. IET image processing, arXiv:1109.4609v1, pp 1---21

Google Scholar

[12]

Bayat FM, Shouraki SB, Rohani A (2011) Memristor crossbar-based hardware implementation of the IDS method. IEEE Trans Fuzzy Syst 19(6):1083---1096

Digital Library

Google Scholar

[13]

Jo SH, Kim KH, Lu W (2009) High-density crossbar arrays based on a Si memristive system. Nano Lett 9(2):870---874

Crossref

Google Scholar

[14]

Masquelier T, Thorpe SJ (2007) Unsupervised learning of visual features through spike timing dependent plasticity. PLoS Comput Biol 3(2):e31, 247---257

Google Scholar

Cited By

View all

Liao MWang CSun YLin HXu C(2022)Memristor-based affective associative memory neural network circuit with emotional gradual processesNeural Computing and Applications10.1007/s00521-022-07170-z34:16(13667-13682)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s00521-022-07170-z
Sayyaparaju SAdnan MAmer SRose G(2020)Device-aware Circuit Design for Robust Memristive Neuromorphic Systems with STDP-based LearningACM Journal on Emerging Technologies in Computing Systems10.1145/338096916:3(1-25)Online publication date: 22-May-2020
https://dl.acm.org/doi/10.1145/3380969
Hong QLi YWang X(2020)Memristive continuous Hopfield neural network circuit for image restorationNeural Computing and Applications10.1007/s00521-019-04305-732:12(8175-8185)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s00521-019-04305-7
Show More Cited By

Recommendations

Memristor Crossbar Array for Image Storing
Advances in Neural Networks – ISNN 2015
Abstract
This letter uses image overlay technique on memristor crossbar array (MCA) structure for image storing. Different programming circuits with time slot techniques are designed for the MCA consisting of the nonlinear HP memristor (HPMCA) and the MCA ...
Recent progress in digital image restoration techniques: A review
Abstract
Digital images are playing a progressively important role in almost all the fields such as computer science, medicine, communications, transmission, security, surveillance, and many more. Digital images are susceptible to a number of distortions ...
Unsupervised feature learning framework for no-reference image quality assessment
CVPR '12: Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to build a computational model to automatically predict human perceived image ...

Comments

Information & Contributors

Information

Published In

cover image Neural Computing and Applications

Neural Computing and Applications Volume 25, Issue 2

August 2014

233 pages

ISSN:0941-0643

EISSN:1433-3058

Issue’s Table of Contents

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 August 2014

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

12
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 09 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Liao MWang CSun YLin HXu C(2022)Memristor-based affective associative memory neural network circuit with emotional gradual processesNeural Computing and Applications10.1007/s00521-022-07170-z34:16(13667-13682)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s00521-022-07170-z
Sayyaparaju SAdnan MAmer SRose G(2020)Device-aware Circuit Design for Robust Memristive Neuromorphic Systems with STDP-based LearningACM Journal on Emerging Technologies in Computing Systems10.1145/338096916:3(1-25)Online publication date: 22-May-2020
https://dl.acm.org/doi/10.1145/3380969
Hong QLi YWang X(2020)Memristive continuous Hopfield neural network circuit for image restorationNeural Computing and Applications10.1007/s00521-019-04305-732:12(8175-8185)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s00521-019-04305-7
Jiang BYang JJiang NLv ZMeng Q(2018)RETRACTED ARTICLE: Quality assessment for virtual reality technology based on real sceneNeural Computing and Applications10.1007/s00521-016-2828-029:5(1199-1208)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1007/s00521-016-2828-0
Li TDuan SLiu JWang L(2018)An improved design of RBF neural network control algorithm based on spintronic memristor crossbar arrayNeural Computing and Applications10.1007/s00521-016-2715-830:6(1939-1946)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s00521-016-2715-8
Liu SRen AWang YVarshney P(2017)Ultra-fast robust compressive sensing based on memristor crossbars2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2017.7952333(1133-1137)Online publication date: 5-Mar-2017
https://dl.acm.org/doi/10.1109/ICASSP.2017.7952333
Zhang PLi CHuang TChen LChen Y(2017)Forgetting memristor based neuromorphic system for pattern training and recognitionNeurocomputing10.1016/j.neucom.2016.10.012222:C(47-53)Online publication date: 26-Jan-2017
https://dl.acm.org/doi/10.1016/j.neucom.2016.10.012
Cao YWen SHuang T(2017)New Criteria on Exponential Lag Synchronization of Switched Neural Networks with Time-Varying DelaysNeural Processing Letters10.1007/s11063-017-9599-146:2(451-466)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1007/s11063-017-9599-1
Wang QKim YLi P(2016)Neuromorphic Processors with Memristive SynapsesACM Journal on Emerging Technologies in Computing Systems10.1145/289475612:4(1-22)Online publication date: 12-May-2016
https://dl.acm.org/doi/10.1145/2894756
Xin YLi YCheng ZHuang X(2016)Global exponential stability for switched memristive neural networks with time-varying delaysNeural Networks10.1016/j.neunet.2016.04.00280:C(34-42)Online publication date: 1-Aug-2016
https://dl.acm.org/doi/10.1016/j.neunet.2016.04.002
Show More Cited By

Abstract

References

Cited By

Recommendations

Memristor Crossbar Array for Image Storing

Recent progress in digital image restoration techniques: A review

Unsupervised feature learning framework for no-reference image quality assessment

Comments

Information

Published In

Publisher

Publication History

Author Tags

Qualifiers

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

Share

Share this Publication link

Share on social media

Affiliations