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 2/2020

18.11.2019

Synchronization Control of Quaternion-Valued Neural Networks with Parameter Uncertainties

verfasst von: Hongzhi Wei, Baowei Wu, Ruoxia Li

Erschienen in: Neural Processing Letters | Ausgabe 2/2020

Einloggen

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

search-config
loading …

Abstract

In this paper, by starting from basic quaternion algebra properties and algorithms, we develop a comprehensive set of properties to ensure the uncertain quaternion-valued neural networks can receive synchronization and quasi-synchronization goals. By endowing the classic Lyapunov technique, several sufficient criteria for the synchronization and quasi-synchronization analysis of the addressed model are proposed by means of two simple and rigorous control strategies. Particularly, lexicographical ordering approach is proposed in this paper, which can be employed to determine the “magnitude” of two different quaternion-valued. Finally, we have numerical evidences that the mathematical model and the conclusions presented are validate.
Vorheriger Artikel Semi-supervised Fuzzy Min–Max Neural Network for Data Classification
Nächster Artikel Finite-Time Mittag-Leffler Stability of Fractional-Order Quaternion-Valued Memristive Neural Networks with Impulses

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.
Hamilton W (1853) Lectures on quaternions. Hodges and Smith, Dublin
2.
Kou K, Liu W, Xia Y (2019) Solve the linear quaternion-valued differential equations having multiple eigenvalues. J Math Phys 60:023510MathSciNetMATH
3.
Choe S, Faraway J (2004) Modeling head and hand orientation during motion using quaternions. J Aerosp 113:186–192
4.
Kou KI, Xia Y (2018) Linear quaternion differential equations: basic theory and fundamental results. Stud Appl Math 141:3–45MathSciNetCrossRef
5.
Chou J (1992) Quaternions kinematic and dynamic differential equations. IEEE Trans Robot Autom 8:53–64CrossRef
6.
Chen D, Kou KI, Xia Y (2018) Linear quaternion-valued dynamic equations on time scales. J Appl Anal Comput 8:172–201MathSciNet
7.
Isokawa T, Matsui N, Nishimura H (2009) Quaternionic neural networks: fundamental properties and applications. In: IGI global, Pennsylvania, pp 411–439
8.
Matsui N, Isokawa T, Kusamichi H, Peper F, Nishimura H (2004) Quaternion neural network with geometrical operators. J Intell Fuzzy Syst Appl Eng Technol 15:149–164MATH
9.
Ujang B, Took C, Mandic D (2011) Quaternion-valued nonlinear adaptive filtering. IEEE Trans Neural Netw 22:1193–1206CrossRef
10.
Tu Z, Cao J, Alsaedi A, Hayat T (2017) Global dissipativity analysis for delayed quaternion-valued neural networks. Neural Netw 89:97–104CrossRef
11.
Liu Y, Zhang D, Lou J, Lu J, Cao J (2018) Stability analysis of quaternion-valued neural networks: decomposition and direct approaches. IEEE Trans Neural Netw Learn Syst 29:4201–4211CrossRef
12.
Chen X, Song Q, Li Z (2018) Design and analysis of quaternion-valued neural networks for associative memories. IEEE Trans Syst Man Cybern Syst 48:2305–2314CrossRef
13.
Song Q, Chen X (2018) Multistability analysis of quaternion-valued neural networks with time delays. IEEE Trans Neural Netw Learn Syst 29:5430–5440MathSciNetCrossRef
14.
Liu Y, Zhang D, Lu J, Cao J (2016) Global \(\mu \)-stability criteria for quaternion-valued neural networks with unbounded time-varying delays. Inf Sci 360:273–288CrossRef
15.
Chen X, Song Q, Li Z, Zhao Z, Liu Y (2018) Stability analysis of continuous-time and discrete-time quaternion-valued neural networks with linear threshold neurons. IEEE Trans Neural Netw Learn Syst 29:2769–2781MathSciNet
16.
Chen X, Li Z, Song Q, Hu J, Tan Y (2017) Robust stability analysis of quaternion-valued neural networks with time delays and parameter uncertainties. Neural Netw 91:55–65CrossRef
17.
Ding S, Wang Z (2015) Stochastic exponential synchronization control of memristive neural networks with multiple time-varying delays. Neurocomputing 162:16–25CrossRef
18.
Yang X, Cao J (2013) Exponential synchronization of delayed neural networks with discontinuous activations. IEEE Trans Circuits Syst I Regul Papers 60:2431–2439MathSciNetCrossRef
19.
Li R, Gao X, Cao J (2019) Exponential synchronization of stochastic memristive neural networks with time-varying delays. Neural Proces Lett 50(1):459–475CrossRef
20.
Zhu X, Yang X, Alsaadi F, Hayat T (2018) Fixed-time synchronization of coupled discontinuous neural networks with nonidentical perturbations. Neural Process Lett 48(2):1161–1174CrossRef
21.
Liu Y, Cao J, Sun L, Lu J (2016) Sampled-data state feedback stabilization of boolean control networks. Neural Comput 28:778–799MathSciNetCrossRef
22.
Zhou C, Zhang W, Yang X, Xu C, Feng J (2017) Finite-time synchronization of complex-valued neural networks with mixed delays and uncertain perturbations. Neural Process Lett 46:271–291CrossRef
23.
Yang X, Ho Daniel W C (2016) Synchronization of delayed memristive neural networks: robust analysis approach. IEEE Trans Cybern 46(12):3377–3387CrossRef
24.
Wan Y, Cao J, Wen G, Yu W (2016) Robust fixed-time synchronization of delayed Cohen–Grossberg neural networks. Neural Netw 73:86–94CrossRef
25.
Xiao X, Tang R, Yang X (2018) Finite-time synchronization of memristive neural networks with proportional delay. Neural Proces Lett 50(2):1139–1152
26.
Ding S, Wang Z, Huang Z, Zhang H (2017) Novel switching jumps dependent exponential synchronization criteria for memristor-based neural networks. Neural Process Lett 45:15–28CrossRef
27.
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
28.
29.
Li R, Wei H (2016) Synchronization of delayed Markovian jump memristive neural networks with reaction-diffusion terms via sampled data control. Int J Mach Learn Cybernet 7:157–169CrossRef
30.
Zhou X, Zhou W, Yang J, Hu X (2015) Stochastic synchronization of neural networks with multiple time-varying delays and Markovian jump. J Frankl Inst 352:1265–1283MathSciNetCrossRef
31.
Liu X, Chen T, Cao J, Lu W (2011) Dissipativity and quasi-synchronization for neural networks with discontinuous activations and parameter mismatches. Neural Netw 24:1013–1021CrossRef
32.
Ding S, Wang Z (2017) Lag quasi-synchronization for memristive neural networks with switching jumps mismatch. Neural Comput Appl 28:4011–4022CrossRef
33.
Li W (2002) Quaternion matrices. National University of Defence Technology Press, Changsha
34.
Huang T, Li C, Liao X (2007) Synchronization of a class of coupled chaotic delayed systems with parameter mismatch. Chaos 17:1–5MathSciNetMATH
Metadaten
Titel
Synchronization Control of Quaternion-Valued Neural Networks with Parameter Uncertainties
verfasst von
Hongzhi Wei
Baowei Wu
Ruoxia Li
Publikationsdatum
18.11.2019
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 2/2020
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-019-10153-2

Weitere Artikel der Ausgabe 2/2020

Neural Processing Letters 2/2020 Zur Ausgabe

BriefCommunication

DNN-Based Cross-Lingual Voice Conversion Using Bottleneck Features

OriginalPaper

Image Set-Oriented Dual Linear Discriminant Regression Classification and Its Kernel Extension

OriginalPaper

Multi-layer Adaptive Feature Fusion for Semantic Segmentation

OriginalPaper

Memristor Crossbar Array Based ACO For Image Edge Detection

OriginalPaper

A Novel Model Predictive Runge–Kutta Neural Network Controller for Nonlinear MIMO Systems

OriginalPaper

Quantitative Analysis in Delayed Fractional-Order Neural Networks

Neuer Inhalt

    Bildnachweise