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 Computing and Applications
Erschienen in: Neural Computing and Applications 1/2017

22.06.2016 | Original Article

Finite-time stabilization of uncertain neural networks with distributed time-varying delays

verfasst von: Shiju Yang, Chuandong Li, Tingwen Huang

Erschienen in: Neural Computing and Applications | Sonderheft 1/2017

Einloggen

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

search-config
loading …

Abstract

In this paper, the problem of finite-time stabilization for a class of uncertain neural networks with distributed time-varying delays is investigated. Based on the Lyapunov stability theory and integral inequality technique, some sufficient LMI conditions are derived to ensure the finite-time stability of considered neural networks. In addition, the upper bound of the settling time for stabilization is estimated. Numerical simulations are carried out to demonstrate the effectiveness of the obtained results.
Vorheriger Artikel Support top irrelevant machine: learning similarity measures to maximize top precision for image retrieval
Nächster Artikel Adaptive fuzzy backstepping output constraint control of flexible manipulator with actuator saturation

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

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

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+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
Literatur
1.
Welstead ST (1994) Neural network and fuzzy logic applications in C–C++. Wiley, Hoboken
2.
Li CD, Liao XF, Zhang R (2004) Global robust asymptotical stability of multi-delayed interval neural networks: an LMI approach. Phys Lett A 328(6):452–462CrossRefMATH
3.
Li CD, Liao X (2006) Global robust stability criteria for interval delayed neural networks via an LMI approach. IEEE Trans Circuits Syst II Express Briefs 53(9):901–905CrossRef
4.
Cao JD, Liang J (2004) Boundedness and stability for Cohen–Grossberg neural network with time-varying delays. J Math Anal Appl 296(2):665–685MathSciNetCrossRefMATH
5.
Zeng ZG, Wang J (2008) Design and analysis of high-capacity associative memories based on a class of discrete-time recurrent neural networks. IEEE Trans Syst Man Cybern Part B Cybern 38(6):1525–1536CrossRef
6.
Zeng ZG, Zheng WX (2012) Multistability of neural networks with time-varying delays and concave-convex characteristics. IEEE Trans Neural Netw Learn Syst 23(2):293–305CrossRef
7.
Li XD, Song S (2013) Impulsive control for existence, uniqueness, and global stability of periodic solutions of recurrent neural networks with discrete and continuously distributed delays. IEEE Trans Neural Netw Learn Syst 24(6):868–877CrossRef
8.
Li XD, Song S (2014) Research on synchronization of chaotic delayed neural networks with stochastic perturbation using impulsive control method. Commun Nonlinear Sci Numer Simul 19(10):3892–3900MathSciNetCrossRef
9.
Zhang G, Shen Y (2013) New algebraic criteria for synchronization stability of chaotic memristive neural networks with time-varying delays. IEEE Trans Neural Netw Learn Syst 24(10):1701–1707CrossRef
10.
Zhang G, Shen Y (2015) Exponential stabilization of memristor-based chaotic neural networks with time-varying delays via intermittent control. IEEE Trans Neural Netw Learn Syst 26(7):1431–1441MathSciNetCrossRef
11.
Wang L, Shen Y, Yin Q et al (2015) Adaptive synchronization of memristor-based neural networks with time-varying delays. IEEE Trans Neural Netw Learn Syst 26(9):2033–2042MathSciNetCrossRef
12.
Li CJ, Yu WW, Huang TW (2014) Impulsive synchronization schemes of stochastic complex networks with switching topology: average time approach. Neural Netw 54:85–94CrossRefMATH
13.
Li CJ, Yu XH, Huang TW et al (2016) A generalized Hopfield network for nonsmooth constrained convex optimization: lie derivative approach. IEEE Trans Neural Netw Learn Syst 27(2):308–321MathSciNetCrossRef
14.
15.
16.
Li CD, Liao XF, Zhang R (2005) Delay-dependent exponential stability analysis of bi-directional associative memory neural networks with time delay: an LMI approach. Chaos, Solitons & Fractals 24(4):1119–1134MathSciNetCrossRefMATH
17.
Li CD, Liao X, Zhang R (2006) A global exponential robust stability criterion for interval delayed neural networks with variable delays. Neurocomputing 69(7):803–809CrossRef
18.
Li CD, Li C, Liao X et al (2011) Impulsive effects on stability of high-order BAM neural networks with time delays. Neurocomputing 74(10):1541–1550CrossRef
19.
Cao JD, Wang J (2005) Global exponential stability and periodicity of recurrent neural networks with time delays. IEEE Trans Circuits Syst I Regul Pap 52(5):920–931MathSciNetCrossRefMATH
20.
Cao JD, Wan Y (2014) Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays. Neural Netw 53:165–172CrossRefMATH
21.
Li T, Song A, Fei S et al (2010) Delay-derivative-dependent stability for delayed neural networks with unbound distributed delay. IEEE Trans Neural Netw 21(8):1365–1371CrossRef
22.
Yang X, Song Q, Liang J et al (2015) Finite-time synchronization of coupled discontinuous neural networks with mixed delays and nonidentical perturbations. J Frankl Inst 352(10):4382–4406MathSciNetCrossRef
23.
Syed Ali M, Saravanakumar R, Zhu Q (2015) Less conservative delay-dependent \(H^\infty\) control of uncertain neural networks with discrete interval and distributed time-varying delays. Neurocomputing 166(C):84–95CrossRef
24.
Kamenkov G (1953) On stability of motion over a finite interval of time. J Appl Math Mech 17:529–540MathSciNet
25.
Forti M, Nistri P, Papini D (2005) Global exponential stability and global convergence in finite time of delayed neural networks with infinite gain. IEEE Trans Neural Netw 16(6):1449–1463CrossRef
26.
Wang L, Xiao F (2010) Finite-time consensus problems for networks of dynamic agents. IEEE Trans Autom Control 55(4):950–955MathSciNetCrossRefMATH
27.
Zhang X, Feng G, Sun Y (2012) Finite-time stabilization by state feedback control for a class of time-varying nonlinear systems. Automatica 48(3):499–504MathSciNetCrossRefMATH
28.
Liu X, Park JH, Jiang N et al (2014) Nonsmooth finite-time stabilization of neural networks with discontinuous activations. Neural Netw 52:25–32CrossRefMATH
29.
Wang L, Shen Y (2015) Finite-time stabilizability and instabilizability of delayed memristive neural networks with nonlinear discontinuous controller. IEEE Trans Neural Netw Learn Syst 26(11):2914–2924MathSciNetCrossRef
30.
Ambrosino R, Calabrese F, Cosentino C et al (2009) Sufficient conditions for finite-time stability of impulsive dynamical systems. IEEE Trans Autom Control 54(4):861–865MathSciNetCrossRefMATH
31.
Lin X, Li S, Zou Y (2014) Finite-time stability of switched linear systems with subsystems which are not finite-time stable. IET Control Theory Appl 8(12):1137–1146MathSciNetCrossRef
32.
Li D, Cao JD (2015) Finite-time synchronization of coupled networks with one single time-varying delay coupling. Neurocomputing 166:265–270CrossRef
33.
Yan Z, Zhang W, Zhang G (2015) Finite-time stability and stabilization of \(It^o\) Stochastic systems with Markovian switching: mode-dependent parameter approach. IEEE Trans Autom Control 60(9):2428–2433CrossRefMATH
34.
Wang L, Shen Y, Ding Z (2015) Finite time stabilization of delayed neural networks. Neural Netw 70:74–80CrossRef
35.
Kwon OM, Park JH (2008) New delay-dependent robust stability criterion for uncertain neural networks with time-varying delays. Appl Math Comput 205(1):417–427MathSciNetMATH
36.
Niamsup P, Ratchagit K, Phat VN (2015) Novel criteria for finite-time stabilization and guaranteed cost control of delayed neural networks. Neurocomputing 160:281–286CrossRef
37.
Amato F, Ambrosino R, Ariola M et al (2009) Finite-time stability of linear time-varying systems with jumps. Automatica 45(5):1354–1358MathSciNetCrossRefMATH
38.
Huang J, Li C, Huang T et al (2014) Finite-time lag synchronization of delayed neural networks. Neurocomputing 139:145–149CrossRef
39.
Boyd S, El-Ghaoui L, Feron E et al (1997) Linear matrix inequalities in system and control theory. Proc IEEE 85(4):698–699CrossRef
40.
Gu K (2000) An integral inequality in the stability problem of time delay systems. In: Proceedings of the 39th IEEE conference on decision and control. Sydney, 280522810
Metadaten
Titel
Finite-time stabilization of uncertain neural networks with distributed time-varying delays
verfasst von
Shiju Yang
Chuandong Li
Tingwen Huang
Publikationsdatum
22.06.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe Sonderheft 1/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2421-6

Weitere Artikel der Sonderheft 1/2017

Neural Computing and Applications 1/2017 Zur Ausgabe

Original Article

Flow regime independent volume fraction estimation in three-phase flows using dual-energy broad beam technique and artificial neural network

Original Article

GRASP for connected dominating set problems

Original Article

Application of trembling-hand perfect equilibrium to Nash nonlinear Grey Bernoulli model: an example of BRIC’s GDP forecasting

Original Article

An effective combining classifier approach using tree algorithms for network intrusion detection

Original Article

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments

Original Article

Soret and MHD effects on bioconvection wall jet flow of nanofluid containing gyrotactic microorganisms