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
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 4/2018

25.05.2016 | Original Article

Global Lagrange stability for neutral type neural networks with mixed time-varying delays

verfasst von: Zhengwen Tu, Liangwei Wang

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 4/2018

Einloggen

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

search-config
loading …

Abstract

In this paper, the global exponential stability in Lagrange sense for neutral type neural networks with mixed time-varying delays is studied. By constructing proper Lyapunov functions and using inequality techniques, new delay-dependent succinct criteria are derived to ensure the global exponential Lagrange stability for the aforementioned neural networks. Meanwhile, globally exponentially attractive sets are given out. The results obtained here are more general than some of existing results. Finally, two examples are presented and analyzed to validate our results.
Vorheriger Artikel Association rule mining using treap
Nächster Artikel On derivations of linguistic truth-valued lattice implication algebras

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
Weitere Produktempfehlungen anzeigen
Literatur
1.
Dhamala M, Jirsa V, Ding M (2004) Enhancement of neural synchrony by time delay. Physical Rev Lett 92(074104):1–4
2.
3.
Xu S, Lam J (2006) A new approach to exponential stability analysis of neural networks with time-varying delays. Neural Networks 19(1):76–83CrossRefMATH
4.
Cao J, Wang J (2005) Global asymptotic and robust stability of recurrent neural networks with time delays. IEEE Trans Circ Syst I: Regular Papers 52(2):417–426MathSciNetCrossRefMATH
5.
Zeng Z, Wang J, Liao X (2005) Global asymptotic stability and global exponential stability of neural networks with unbounded time-varying delays. IEEE Trans Circ Syst II Express Briefs 52(3):168–173CrossRef
6.
Song Q (2008) Exponential stability of recurrent neural networks with both time-varying delays and general activation functions via LMI approach. Neurocomputing 71:2823–2830CrossRef
7.
Hu J, Wang J (2012) Global stability of complex-valued recurrent neural networks with time-delays. IEEE Trans Neural Networks Learning Syst 23(6):853–865CrossRef
8.
Song Q, Zhao Z (2016) Stability criterion of complex-valued neural networks with both leakage delay and time-varying delays on time scales. Neurocomputing 171:179–184CrossRef
9.
Lu W, Chen T (2004) Synchronization of coupled connected neural networks with delays. IEEE Trans Circ Syst Part I: Regular Papers 52(12):2491–2503MathSciNetCrossRefMATH
10.
Nie X, Zheng W (2015) Multistability of neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays. Neural Networks 65:65–79CrossRef
11.
Li T, Luo Q, Sun C, Zhang B (2009) Exponential stability of recurrent neural networks with time-varying discrete and distributed delays. Nonlinear Anal Real World Appl 10:2581–2589MathSciNetCrossRefMATH
12.
Cao J, Yuan K, Ho DW, Lam J (2006) Global point dissipativity of neural networks with mixed time-varying delays. Chaos 16(013105):1–9MathSciNetMATH
13.
Lakshmanan S, Senthilkumar T, Balasubramaniam P (2011) Improved results on robust stability of neutral systems with mixed time-varying delays and nonlinear perturbations. Appl Math Model 35:5355–5368MathSciNetCrossRefMATH
14.
Samidurai R, Marshal S (2010) Anthon, K. Balachandran. Global exponential stability of neutral-type impulsive neural networks with discrete and distributed delays. Nonlinear Anal Hybrid Syst 4:103–112MathSciNetCrossRefMATH
15.
Song Q, Zhao Z, Liu Y (2015) Impulsive effects on stability of discrete-time complex-valued neural networks with both discrete and distributed time-varying delays. Neurocomputing 168:1044–1050CrossRef
16.
Kuang Y (1993) Delay differential equations with applications in population dynamics. Academic Press, BostonMATH
17.
Brayton R (1966) Bifurcation of periodic solutions in a nonlinear difference-differential equation of neutral type. Quarterly Appl Math 24:215–224MathSciNetCrossRefMATH
18.
Arik S (2014) An analysis of stability of neutral-type neural systems with constant time delays. J Franklin Inst 351:4949–4959MathSciNetCrossRefMATH
19.
Luo Q, Zeng Z, Liao X (2011) Global exponential stability in Lagrange sense for neutral type recurrent neural networks. Neurocomputing 74:638–645CrossRef
20.
Jian J, Wang B (2015) Stability analysis in Lagrange sense for a class of BAM neural networks of neutral type with multiple time-varying delays. Neurocomputing 149:930–939CrossRef
21.
Yi Z, Tan K (2004) Convergence analysis of recurrent neural networks. Kluwer Academic Publishers, DordrechtCrossRefMATH
22.
Liao X, Luo Q, Zeng Z (2008) Positive invariant and global exponential attractive sets of neural networks with time-varying delays. Neurocomputing 71:513–518CrossRef
23.
Liao X, Luo Q, Zeng Z, Guo Y (2008) Global exponential stability in Lagrange sense for recurrent neural networks with time delays. Nonlinear Anal Real World Appl 9:1535–1557MathSciNetCrossRefMATH
24.
Wu A, Zeng Z (2014) Lagrange stability of memristive neural networks with discrete and distributed delays. IEEE Trans Neural Networks Learning Syst 25(4):690–703CrossRef
25.
Wu A, Zeng Z (2014) Lagrange stability of neural networks with memristive synapses and multiple delays. Information Sci 280:135–151MathSciNetCrossRefMATH
26.
Zhang G, Shen Y, Xu C (2015) Global exponential stability in a Lagrange sense for memristive recurrent neural networks with time-varying delays. Neurocomputing 149:1330–1336CrossRef
27.
Li L, Jian J (2015) Exponential convergence and Lagrange stability for impulsive Cohen-Grossberg neural networks with time-varying delays. J Comput Appl Math 277:23–35MathSciNetCrossRefMATH
28.
Tu Z, Cao J, Tasawar H (2016) Global exponential stability in Lagrange sense for inertial neural networks with time-varying delays. Neurocomputing 171:524–531CrossRef
29.
Boyd S, Ghaoui L, Feron E, Balakrishnan V (1994) Linear matrix inequalities in system and control theory. Society for industrial and applied mathematics, PhiladelphiaCrossRefMATH
30.
Wang X (2015) Uncertainty in learning from big data-editorial. J Intell Fuzzy Syst 28(5):2329–2330CrossRef
31.
Lu S, Wang X, Zhang G, Zhou X (2015) Effective algorithms of the Moore-Penrose inverse matrices for extreme learning machine. Intell Data Anal 19(4):743–760CrossRef
32.
Wang X, Ashfaq R, Fu A (2015) Fuzziness based sample categorization for classifier performance improvement. J Intell Fuzzy Syst 29(3):1185–1196MathSciNetCrossRef
33.
34.
Metadaten
Titel
Global Lagrange stability for neutral type neural networks with mixed time-varying delays
verfasst von
Zhengwen Tu
Liangwei Wang
Publikationsdatum
25.05.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 4/2018
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-016-0547-6

Weitere Artikel der Ausgabe 4/2018

International Journal of Machine Learning and Cybernetics 4/2018 Zur Ausgabe

Original Article

A new fusion approach for content based image retrieval with color histogram and local directional pattern

Original Article

Dependence space of topology and its application to attribute reduction

Original Article

Uncertain programming model for multi-item solid transportation problem

Original Article

On derivations of linguistic truth-valued lattice implication algebras

Original Article

Cardiac arrhythmia classification using multi-granulation rough set approaches

Original Article

Association rule mining using treap

Neuer Inhalt

    Bildnachweise