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
International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 10/2018

11.04.2017 | Original Article

Finite-time synchronization by switching state-feedback control for discontinuous Cohen–Grossberg neural networks with mixed delays

verfasst von: Zuo-Wei Cai, Li-Hong Huang

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 10/2018

Einloggen

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

search-config
loading …

Abstract

This paper studies the finite-time synchronization problem of Cohen–Grossberg neural networks (CGNNs) with discontinuous neuron activations and mixed time-delays. Under the extended differential inclusion framework, the famous finite-time stability theorem and generalized Lyapunov approach are used to realize the finite-time synchronization control of drive-response system. Different from the conventional controllers, we propose two classes of novel switching state-feedback controllers which include discontinuous factor sign (\(\cdot\)). By doing so, the synchronization error of CGNNs can be controlled to converge zero in a finite time. Moreover, we also provide an estimation of the upper bound of the settling time for synchronization. Finally, two examples and simulation experiment are given to demonstrate the validity of theoretical results.
Vorheriger Artikel New results on convergence of fuzzy cellular neural networks with multi-proportional delays
Nächster Artikel Prediction of the hot metal silicon content in blast furnace based on extreme learning machine

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.
Cohen M, Grossberg S (1983) Absolute stability and global pattern formation and parallel memory storage by competitive neural networks. IEEE Trans Syst Man Cybern 13:815–826MathSciNetCrossRefMATH
2.
Liao XF, Li CG, Wong KW (2004) Criteria for exponential stability of Cohen–Grossberg neural networks. Neural Netw 17:1401–1414CrossRefMATH
3.
Wang L, Zou XF (2002) Exponential stability of Cohen–Grossberg neural networks. Neural Netw 15:415–422CrossRef
4.
Zheng CD, Shan QH, Zhang HG, Wang ZS (2013) On stabilization of stochastic Cohen–Grossberg neural networks with mode-dependent mixed time-delays and Markovian switching. IEEE Trans Neural Netw Learn Syst 24:800–811CrossRef
5.
Zhu QX, Li XD (2012) Exponential and almost sure exponential stability of stochastic fuzzy delayed Cohen–Grossberg neural networks. Fuzzy Sets Syst 203:74–94MathSciNetCrossRefMATH
6.
Chong EKP, Hui S, Zak SH (1999) An analysis of a class of neural networks for solving linear programming problems. IEEE Trans Autom Control 44:1995–2006MathSciNetCrossRefMATH
7.
Forti M, Nistri P (2003) Global convergence of neural networks with discontinuous neuron activations. IEEE Trans Circuits Syst I. Fundam Theory Appl 50:1421–1435MathSciNetCrossRefMATH
8.
Kennedy MP, Chua LO (1988) Neural networks for nonlinear programming. IEEE Trans Circuits Syst I. Fundam Theory Appl 35:554–562MathSciNetCrossRef
9.
Wang DS, Huang LH, Cai ZW (2013) On the periodic dynamics of a general Cohen–Grossberg BAM neural networks via differential inclusions. Neurocomputing 118:203–214CrossRef
10.
Wang DS, Huang LH (2014) Periodicity and global exponential stability of generalized Cohen–Grossberg neural networks with discontinuous activations and mixed delays. Neural Netw 51:80–95CrossRefMATH
11.
Wang DS, Huang LH (2016) Periodicity and multi-periodicity of generalized Cohen–Grossberg neural networks via functional differential inclusions. Nonlinear Dyn 85:67–86MathSciNetCrossRefMATH
12.
Liu XY, Park JH, Jiang N, Cao JD (2014) Nonsmooth finite-time stabilization of neural networks with discontinuous activations. Neural Netw 52:25–32CrossRefMATH
13.
Liu XY, Chen TP, Cao JD, Lu WL (2011) Dissipativity and quasi-synchronization for neural networks with discontinuous activations and parameter mismatches. Neural Netw 24:1013–1021CrossRefMATH
14.
Yang XS, Cao JD (2013) Exponential synchronization of delayed neural networks with discontinuous activations. IEEE Trans Circuits Syst I. Fundam Theory Appl 60:2413–2439MathSciNet
15.
Cai ZW, Huang LH, Guo ZY, Zhang LL, Wan XT (2015) Periodic synchronization control of discontinuous delayed networks by using extended Filippov-framework. Neural Netw 68:96–110CrossRefMATH
16.
Liu XY, Yu WW, Cao JD, Alsaadi F (2015) Finite-time synchronisation control of complex networks via non-smooth analysis. IET Control Theory Appl 9:1245–1253MathSciNetCrossRef
17.
Filippov AF (1988) Differential equations with discontinuous right-hand side. Mathematics and its applications (Soviet series). Kluwer Academic, BostonCrossRef
18.
Aubin JP, Cellina A (1984) Differential inclusions, set-valued functions and viability theory. Springer, BerlinMATH
19.
Wang KN, Michel AN (1996) Stability analysis of differential inclusions in banach space with application to nonlinear systems with time delays. IEEE Trans Circuits Syst I. Fundam Theory Appl 43(8):617–626MathSciNetCrossRef
20.
Clarke FH (1983) Optimization and nonsmooth analysis. Wiley, New YorkMATH
21.
Forti M, Grazzini M, Nistri P, Pancioni L (2006) Generalized Lyapunov approach for convergence of neural networks with discontinuous or non-Lipschitz activations. Phys D Nonlinear Phenom 214(1):88–99MathSciNetCrossRefMATH
22.
23.
Aubin JP, Frankowska H (1990) Set-valued analysis. Birkhauser, BostonMATH
24.
Clarke FH, Ledyaev Y, Stern RJ, Wolenski PR (1998) Nonsmooth analysis and control theory. Springer, New YorkMATH
25.
Hardy GH, Littlewood JE, Polya G (1988) Inequalities. Cambridge University Press, LondonMATH
26.
Zhu QX, Cao JD (2010) Robust exponential stability of Markovian jump impulsive stochastic Cohen–Grossberg neural networks with mixed time delays. IEEE Trans Neural Netw 21:1314–1325CrossRef
27.
Zhu QX, Cao JD (2011) Exponential stability analysis of stochastic reaction–diffusion Cohen–Grossberg neural networks with mixed delays. Neurocomputing 74:3084–3091CrossRef
28.
Zhu QX, Li XD, Yang XS (2011) Exponential stability for stochastic reaction–diffusion BAM neural networks with time-varying and distributed delays. Appl Math Comput 217:6078–6091MathSciNetMATH
29.
Wu HQ (2009) Global stability analysis of a general class of discontinuous neural networks with linear growth activation functions. Inf Sci 179:3432–3441MathSciNetCrossRefMATH
30.
Wu HQ, Shan CH (2009) Stability analysis for periodic solution of BAM neural networks with discontinuous neuron activations and impulses. Appl Math Model 33:2564–2574MathSciNetCrossRefMATH
31.
Wu HQ, Wang LF, Wang Y, Niu PF, Fang BL (2016) Exponential state estimation for Markovian jumping neural networks with mixed time-varying delays and discontinuous activation functions. Int J Mach Learn Cybern 7:641–652CrossRef
32.
Wu HQ, Zhang XW, Li RX, Yao R (2015) Adaptive exponential synchronization of delayed Cohen–Grossberg neural networks with discontinuous activations. Int J Mach Learn Cybern 6:253–263CrossRef
33.
Wang H, Zhu QX (2015) Finite-time stabilization of high-order stochastic nonlinear systems in strict-feedback form. Automatica 54:284–291MathSciNetCrossRefMATH
34.
Rakkiyappan R, Dharani S, Zhu QX (2015) Synchronization of reaction–diffusion neural networks with time-varying delays via stochastic sampled-data controller. Nonlinear Dyn 79:485–500MathSciNetCrossRefMATH
35.
Zhu QX, Cao JD (2012) pth moment exponential synchronization for stochastic delayed Cohen–Grossberg neural networks with Markovian switching. Nonlinear Dyn 67:829–845CrossRefMATH
36.
Zhu QX, Cao JD (2011) Adaptive synchronization under almost every initial data for stochastic neural networks with time-varying delays and distributed delays. Commun Nonlinear Sci Numer Simul 16:2139–2159MathSciNetCrossRefMATH
37.
Zhu QX, Cao JD (2010) Adaptive synchronization of chaotic Cohen–Crossberg neural networks with mixed time delays. Nonlinear Dyn 61:517–534MathSciNetCrossRefMATH
38.
Cao JD, Alofi A, Al-Mazrooei A, Elaiw A (2013) Synchronization of switched interval networks and applications to chaotic neural networks. Abstract and applied analysis, Article ID 940573, 11 pages
39.
Yang XS, Cao JD, Ho DWC (2015) Exponential synchronization of discontinuous neural networks with time-varying mixed delays via state feedback and impulsive control. Cognit Neurodyn 9:113–128CrossRef
40.
Syed Ali M, Saravanan S, Cao JD (2017) Finite-time boundedness, \(L_{2}\)-gain analysis and control of Markovian jump switched neural networks with additive time-varying delays. Nonlinear Anal Hybrid Syst 23:27–43MathSciNetCrossRefMATH
41.
Rakkiyappan R, Dharani S, Zhu QX (2015) Stochastic sampled-data \(H_{\infty }\) synchronization of coupled neutral-type delay partial differential systems. J Franklin Inst 352:4480–4502MathSciNetCrossRefMATH
42.
Yang XS, Cao JD, Yang ZC (2013) Synchronization of coupled reaction–diffusion neural networks with time-varying delays via pinning-impulsive controller. SIAM J Control Optim 51:3486–3510MathSciNetCrossRefMATH
43.
Velmurugan G, Rakkiyappan R, Cao JD (2016) Finite-time synchronization of fractional-order memristor-based neural networks with time delays. Neural Netw 73:36–46CrossRefMATH
44.
Cao JD, Song QK (2006) Stability in Cohen–Grossberg-type bidirectional associative memory neural networks with time-varying delays. Nonlinearity 19:1601–1617MathSciNetCrossRefMATH
45.
Cao JD, Ho DWC, Huang X (2007) LMI-based criteria for global robust stability of bidirectional associative memory networks with time delay. Nonlinear Anal Theory Methods Appl 66:1558–1572MathSciNetCrossRefMATH
46.
Cao JD, Li LL (2009) Cluster synchronization in an array of hybrid coupled neural networks with delay. Neural Netw 22:335–342CrossRefMATH
47.
Wu YY, Cao JD, Alofi A, Al-Mazrooei A, Elaiw A (2015) Finite-time boundedness and stabilization of uncertain switched neural networks with time-varying delay. Neural Netw 69:135–143CrossRefMATH
48.
Cao JD, Rakkiyappan R, Maheswari K, Chandrasekar A (2016) Exponential \(H_{\infty }\) filtering analysis for discrete-time switched neural networks with random delays using sojourn probabilities. Sci China Technol Sci 59:387–402CrossRef
49.
Wu AL, Zeng ZG (2014) Passivity analysis of memristive neural networks with different memductance functions. Commun Nonlinear Sci Numer Simul 19:274–285MathSciNetCrossRefMATH
Metadaten
Titel
Finite-time synchronization by switching state-feedback control for discontinuous Cohen–Grossberg neural networks with mixed delays
verfasst von
Zuo-Wei Cai
Li-Hong Huang
Publikationsdatum
11.04.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 10/2018
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-017-0673-9

Weitere Artikel der Ausgabe 10/2018

International Journal of Machine Learning and Cybernetics 10/2018 Zur Ausgabe

Original Article

A heuristic procedure for the outbound container space assignment problem for small and midsize maritime terminals

Original Article

Finite-time synchronization of delayed competitive neural networks with discontinuous neuron activations

Original Article

Kernel learning and optimization with Hilbert–Schmidt independence criterion

Original Article

Fuzzy c-means clustering-based mating restriction for multiobjective optimization

Original Article

Locality similarity and dissimilarity preserving support vector machine

Original Article

Prediction of the hot metal silicon content in blast furnace based on extreme learning machine

Neuer Inhalt

    Bildnachweise