Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Neural Processing Letters
Erschienen in: Neural Processing Letters 3/2022

22.01.2022

Synchronization and Quasi-Synchronization of Delayed Fractional Coupled Memristive Neural Networks

verfasst von: Fangyuan Ma, Xingbao Gao

Erschienen in: Neural Processing Letters | Ausgabe 3/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This paper investigates the synchronization and quasi-synchronization of delayed fractional coupled memristive neural networks (DFCMNNs) with parameter mismatch. A criterion is provided to guarantee the asymptotic synchronization of the master and slave systems by designing a discontinuous controller and using Lyapunov method. Meanwhile, a quasi-synchronization criterion for the underlying systems is also derived. The given conditions can be easily checked by solving linear matrix inequalities (LMIs), the correctness of the obtained results are demonstrated by two numerical examples.
Vorheriger Artikel Extended Dissipative Criteria for Generalized Markovian Jump Neural Networks Including Asynchronous Mode-Dependent Delayed States
Nächster Artikel Learning Enriched Global Context Information for Human Pose Estimation

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Chua L (1971) Memristor-the missing circuit element. IEEE Trans Circuit Theory 18:507–519CrossRef
2.
Strukov DB, Snider GS, Stewatr DR, Williams RS (2008) The missing memristor found. Nature 453:80–83CrossRef
3.
Zhao H, Li L, Peng H, Kurths J, Xiao J, Yang Y (2008) Finite-time robust synchronization of memrisive neural network with perturbation. Neural Process Lett 47:509–533CrossRef
4.
Zhang R, Zeng D, Park J, Zhong S, Yu Y (2018) Novel discontinuous control for exponential synchronization of memristive recurrent neural networks with heterogeneous time-varying delays. J Frankl Inst 355:2826–2848MathSciNetCrossRef
5.
Cheng H, Yu J, Jiang H (2014) Finite-time synchronization of delayed neural networks with Cohen-Grossberg type based on delayed feedback control. Neurocomputing 143:90–96CrossRef
6.
Yang X, Cao J, Liang J (2017) Exponential synchronization of memristive neural networks with delays: interval matrix method. IEEE Trans Neural Netw Learn Syst 28:1878–1888MathSciNetCrossRef
7.
Guo Z, Gong S, Huang T (2018) Finite-time synchronization of inertial memristive neural networks with time delay via delay-dependent control. Neurocomputing 293:100–107CrossRef
8.
Yang X, Ho DWC (2016) Synchronization of delayed memristive neural networks: robust analysis approach. IEEE Trans Cybern 46:3377–3387CrossRef
9.
Wang W, Li L, Peng H et al (2015) Anti-synchronization control of memristive neural networks with nultiple poportional delays. Neural Process Lett 43:269–283CrossRef
10.
11.
Yang L, Jiang J (2014) Adaptive synchronization of drive-response fractional-order complex dynamical networks with uncertain parameters. Commun Nonlinear Sci 19:1496–1506MathSciNetCrossRef
12.
Kuntanapreeda S (2012) Robust synchronization of fractional-order unified chaotic systems via linear control. Comput Math Appl 63:183–190MathSciNetCrossRef
13.
Chen J, Zeng Z, Jiang P (2014) Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks. Neural Netw 51:1–8CrossRef
14.
Bao H, Park JH, Cao J (2015) Adaptive synchronization of fractional-order memristor-based neural networks with time delay. Nonlinear Dyn 82:1343–1354MathSciNetCrossRef
15.
Li R, Gao X, Cao J (2019) Non-fragile state estimation for delayed fractional-order memristive neural networks. Appl Math Comput 340:221–233MathSciNetMATH
16.
Zhang L, Yang Y, Wang F et al (2018) Lag synchronization for fractional-order memristive neural networks with time delay via switching jumps mismatch. J Frankl Inst 355:1217–1240MathSciNetCrossRef
17.
Velmurugan G, Rakkiyappan R, Vembarasan V, Cao J, Alsaedi A (2017) Dissipativity and stability analysis of fractional-order complex-valued neural networks with time delay. Neural Netw 86:42–53CrossRef
18.
Wang J, Zhao L (2021) Pd and pi control for passivity and synchronization of coupled neural networks with multi-weights. IEEE Trans Netw Sci Eng 99:1–1MathSciNet
19.
Yang C, Liu Y, Li F, Li Y (2020) Finite-time synchronization of a class of coupled memristor-based recurrent neural networks: static state control and dynamic control approach. Int J Control Autom Syst 19:1–13
20.
Wang G, Shen Y, Yin Q (2013) Exponential synchronization of coupled memristive neural networks via pinning control. Chinese Phys B 22:203–212
21.
Zhao H, Zheng M (2019) Finite-time synchronization of coupled memrisive neural network via robust control. IEEE Access 7:31820–31831CrossRef
22.
Chen C, Li L, Haipeng P et al (2018) Synchronization control of coupled memristor-based neural networks with mixed delays and stochastic perturbations. Neural Process Lett 47:679–696
23.
Wang S, Huang Y, Ren S (2017) Synchronization and robust synchronization for fractional-order coupled neural networks. IEEE Access 5:12439–12448CrossRef
24.
Hai Z, Ye M, Ye R et al (2018) Synchronization stability of Riemann-Liouville fractional delay-coupled complex neural networks. Phys A 508:155–165MathSciNetCrossRef
25.
Bao H, Park J, Cao J (2020) Adaptive synchronization of fractional-order output-coupling neural networks via quantized output control. IEEE Trans Neural Netw Learn Syst 99:1–10
26.
Song X, Li X, Song S, Zhang Y, Ning Z (2021) Quasi-synchronization of coupled neural networks with reaction-diffusion terms driven by fractional brownian motion. J Frankl Inst 358:2482–2499MathSciNetCrossRef
27.
He W, Qian F, Han Q, Cao J (2011) Lag quasi-synchronization of coupled delayed systems with parameter mismatch. IEEE Trans Circuit Theory 58:1345–1357MathSciNetMATH
28.
Ruan X, Wu A (2017) Multi-quasi-synchronization of coupled fractional-order neural networks with delays via pinning impulsive control. Adv Differ Equ 2017:1–19MathSciNetCrossRef
29.
Zhou Y, Zhang H, Zeng Z (2019) Quasi-synchronization of delayed memristive neural networks via a hybrid impulsive control. IEEE Trans Syst Man and Cy-S 53:1–12
30.
Bernfeld S (1990) Differential equations with discontinuous righthand sides (A. F. Filippov). SIAM Rev 32:312–315CrossRef
Metadaten
Titel
Synchronization and Quasi-Synchronization of Delayed Fractional Coupled Memristive Neural Networks
verfasst von
Fangyuan Ma
Xingbao Gao
Publikationsdatum
22.01.2022
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 3/2022
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-021-10698-1

Weitere Artikel der Ausgabe 3/2022

Neural Processing Letters 3/2022 Zur Ausgabe

OriginalPaper

FSFADet: Arbitrary-Oriented Ship Detection for SAR Images Based on Feature Separation and Feature Alignment

ReviewPaper

Supervised Shallow Multi-task Learning: Analysis of Methods

OriginalPaper

Unsuitability of NOTEARS for Causal Graph Discovery when Dealing with Dimensional Quantities

OriginalPaper

A New Lyapunov Function Method to the Fixed-Time Cluster Synchronization of Directed Community Networks

OriginalPaper

A Sparse Online Approach for Streaming Data Classification via Prototype-Based Kernel Models

OriginalPaper

Transformer-Based Interactive Multi-Modal Attention Network for Video Sentiment Detection

Neuer Inhalt

    Bildnachweise