Top

Neural Processing Letters

Published in:

04-08-2023

Hybrid Impulsive Control Based Synchronization of Leakage and Multiple Delayed Fractional-Order Neural Networks with Parameter Mismatch

Authors: Xueqi Yao, Shouming Zhong, Yuanhua Du

Published in: Neural Processing Letters | Issue 8/2023

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

This paper studies synchronization problems for a kind of parameter mismatched fractional-order neural networks with leakage terms and multiple delays by utilizing a novel hybrid impulsive control mechanism. The hybrid controller combines time-triggered and event-triggered, and switching updates can be described by the behavior between positive auxiliary function and preset exponentially decreasing function. The impulsive controlled neural networks can be translated to the impulsive differential fractional-order systems by using fractional-order calculus and Laplace transform method. Some lemmas are derived for fractional-order inequality with time delays, which together with the hybrid controller are employed to establish some sufficient quasi-synchronization criteria. And the event-triggered mechanism is proved to have no Zeno behavior. Some numerical simulations are showed to illustrate the effectiveness of the results.

previous article Ehsinet: Efficient High-Order Spatial Interaction Multi-task Network for Adaptive Autonomous Driving Perception

next article Smaller World Models for Reinforcement Learning

Dont have a licence yet? Then find out more about our products and how to get one now:

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!

inform now

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!

inform now

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!

inform now

Cao Y, Wang S, Guo Z, Huang T, Wen S (2019) Synchronization of memristive neural networks with leakage delay and parameter mismatch via event-triggered control. Neural Netw 119:178–189MATH

Wu A, Chen Y, Zeng Z (2021) Multi-mode function synchronization of memristive neural networks with mixed delays and parameters mismatch via event-triggered control. Inf Sci 572:147–166MathSciNet

You X, Dian S, Guo R, Li S (2021) Exponential stability for discrete-time quaternion-valued neural networks with leakage delay and discrete time-varying delays. Neurocomputing 430:71–81

Hu M, Li H, Chen Y, Wu Q, Rose GS, Linderman RW (2014) Memristor crossbar-based neuromorphic computing system: a case study. IEEE Trans Neural Netw Learn Syst 25:1864–1878

Jo SH, Chang T, Ebong I, Bhadviya BB, Mazumder P, Lu W (2010) Nanoscale memristor device as synapse in neuromorphic systems. Nano Lett 10:1297–1301

Wang J, Liu F, Qin S (2019) Global exponential stability of uncertain memristor-based recurrent neural networks with mixed time delays. Int J Mach Learn Cybern 10:743–755

Zhang Z, Liu X, Lin C, Zhou S (2019) Exponential stability analysis for delayed complex-valued memristor-based recurrent neural networks. Neural Comput Appl 31:1893–1903

Zhang Y, Zhuang J, Xia Y, Bai Y, Cao J, Gu L (2019) Fixed-time synchronization of the impulsive memristor-based neural networks, Communications Nonlinear Sci Numerical. Simulation 77:40–53MATH

Wang S, Cao Y, Huang T, Wen S (2019) Passivity and passification of memristive neural networks with leakage term and time-varying delays. Appl Math Comput 361:294–310MathSciNetMATH

10.

Suntonsinsoungvon E, Udpin S (2020) Exponential stability of discrete-time uncertain neural networks with multiple time-varying leakage delays. Comput Simul 171:233–245MathSciNetMATH

11.

Li H, Jiang H, Cao J (2020) Global synchronization of fractional-order quaternion-valued neural networks with leakage and discrete delays. Neurocomputing 385:211–219

12.

Wan P, Jian J (2019) Impulsive stabilization and synchronization of fractional-order complex-valued neural network. Neural Process Lett 50:2201–2218

13.

Liu W, Jiang M, Yan M (2019) Stability analysis of memristor-based time-delay fractional-order neural networks. Neurocomputing 323:117–127

14.

Jia J, Huang X, Li Y, Cao J, Alsaedi A (2020) Global stabilization of fractional-order memristor-based neural networks with time delay. IEEE Trans Neural Netw Learn Syst 31:997–1009MathSciNet

15.

Yang S, Yu J, Hu C, Jiang H Finite-time synchronization of memristive neural networks with fractional-order. IEEE Trans Syst Man Cybernet Syst. https://doi.org/10.1109/TSMC.2019.2931046

16.

Ali MS, Hymavathi M, Senan S, Shekher V, Arik S (2019) Global asymptotic synchronization of impulsive fractional-order complex-valued memristor-based neural networks with time varying delays. Commun Nonlinear Sci Numer Simul 78:104869MathSciNetMATH

17.

Huang X, Fan Y, Jia J, Wang Z, Li Y (2017) Quasi-synchronization of fractional-order memristor-based neural networks with parameter mismatches. IET Control Theory Appl 11:2317–2327MathSciNet

18.

Yang X, Li C, Huang T, Song Q, Chen X (2017) Quasi-uniform synchronization of fractional-order memristor-based neural networks with delay. Neurocomputing 234:205–215

19.

Zhang L, Yang Y (2020) Optimal quasi-synchronization of fractional-order memristive neural networks with PSOA. Neural Comput Appl 32(13):9667–9682

20.

Kao Y, Li Y, Park JH, Chen X (2020) Mittag-Leffler synchronization of delayed fractional memristor neural networks via adaptive control. IEEE Trans Neural Netw Learn Syst 32(5):2279–2284MathSciNet

21.

Narayanan G, Muhiuddin G, Ali MS, Diab AAZ, Al-Amri JF, Abdul-Ghaffar HI (2022) Impulsive synchronization control mechanism for fractional-order complex-valued reaction-diffusion systems with sampled-data control: its application to image encryption. IEEE Access 10:83620–83635

22.

Zhang L, Yang Y (2021) Bipartite finite time synchronization for general Caputo fractional-order impulsive coupled networks. Neural Comput Appl 33:2459–2470

23.

Kan Y, Lu J, Qiu J, Kurths J (2019) Exponential synchronization of time-varying delayed complex-valued neural networks under hybrid impulsive controllers. Neural Netw 114:157–163MATH

24.

Sun B, Wang S, Cao Y, Guo Z, Huang T, Wen S (2020) Exponential synchronization of memristive neural networks with time-varying delays via quantized sliding-mode control. Neural Netw 126:163–169MATH

25.

Wang F, Yang Y, Hu A, Xu X (2015) Exponential synchronization of fractional-order complex networks via pinning impulsive control. Nonlinear Dyn 82:1979–1987MathSciNetMATH

26.

Wang F, Yang Y (2017) Leader-following exponential consensus of fractional order nonlinear multi-agents system with hybrid time-varying delay: A heterogeneous impulsive method. Phys A 482:158–172MathSciNetMATH

27.

Fan Y, Huang X, Wang Z, Li Y (2018) Improved quasi-synchronization criteria for delayed fractional-order memristor-based neural networks via linear feedback control. Neurocomputing 306:68–79

28.

Li X, Fang J, Li H (2017) Master-slave exponential synchronization of delayed complex-valued memristor-based neural networks via impulsive control. Neural Netw 93:165–175MATH

29.

Zhang B, Deng F, Xie S, Luo S (2018) Exponential synchronization of stochastic time-delayed memristor-based neural networks via distributed impulsive control. Neurocomputing 286:41–50

30.

Zhang L, Yang Y (2020) Impulsive effectis on bipartite quasi synchronization of extended Caputo fractional order coupled networks. J Franklin Inst 357:4328–4348MathSciNetMATH

31.

Li X, Zhang W, Fang J, Li H (2019) Event-triggered exponential synchronization for complex-valued memristive neural networks with time-varying delays. IEEE Trans Neural Learn Syst 31(10):4104–4116MathSciNet

32.

Hu C, Jiang H, Teng Z (2010) Impulsive control and synchronization for delayed neural networks with reaction diffusion terms. IEEE Trans Neural Netw 21:67–81

33.

Zhou Y, Zhang H, Zeng Z (2019) Quasi-synchronization of delayed memristive neural networks via a hybrid impulsive control. IEEE Trans Syst Syst Man Cybernet

34.

Yang S, Hu C, Yu J, Jiang H (2020) Exponential stability of fractional-order impulsive control systems with applications in synchronization. IEEE Trans Cybernet 50:3157–3168

35.

Stamova I, Henderson J (2016) Practical stability analysis of fractional-order impulsive control systems. ISA Trans 64:77–85

36.

Narayanan G, Ali MS, Alsulami H, Ahmad B, Trujillo JJ (2022) A hybrid impulsive and sampled-data control for fractional-order delayed reaction-diffusion system of mRNA and protein in regulatory mechanisms. Commun Nonlinear Sci Numer Simul 111:106374MathSciNetMATH

37.

Zhou Y, Zeng Z (2019) Event-triggered impulsive control on quasi-synchronization of memristive neural networks with time-varying delays. Neural Netw 110:55–65MATH

38.

Podlubny I (1999) Fractional differential equations. Academic Press, San DiegoMATH

39.

Girod B (1997) Signals and systems. Wiley, Chichester

40.

Zhu W, Wang D, Liu L, Feng G (2018) Event-based impulsive control of continuous-time dynamic systems and its application to synchronization of memristive neural networks. IEEE Trans Neural Netw Learn Syst 29:3599–3609MathSciNet

41.

Abdurahman A, Jiang H, Teng Z (2015) Finite-time synchronization for memristor-based neural networks with time-varying delays. Neural Netw 69:20–28MATH

42.

Xiao Q, Huang Z, Zeng Z (2019) Passivity analysis for memristor-based intertial neural networks with discrete and distributed delays. IEEE Trans Syst Man Cybernet Syst 49:375–385

43.

Yao X, Zhong S, Hu T, Cheng H, Zhang D (2019) Uniformly stable and attractive of fractional-order memristor-based neural networks with multiple delays. Appl Math Comput 347:392–403MathSciNetMATH

44.

Wang D, xiao A (2015) Dissipativity and contractivity for fractional-order systems. Nonlinear Dyn 80:287–294MathSciNetMATH

45.

Zhang S, Yang Y, Sui X, Xu X (2019) Finite-time synchronization of memristive neural networks with parameter uncertainties via aperiodically intermittent adjustment. Phys A 534:122258MathSciNetMATH

46.

Narayanan G, Syed Ali M, Hamed Alsulami, Gani Stamov, Ivanka Stamova, Bashir Ahmad (2022) Impulsive security control for fractional-order delayed multi-agent systems with uncertain parameters and switching topology under DoS attack. Inf Sci 618:169–190

47.

Yang X, Li C, Huang T, Song Q, Huang J (2018) Global Mittag–Leffler synchronization of fractional-order neural networks via impulsive control. Neural Process Lett 48:459–479

Title: Hybrid Impulsive Control Based Synchronization of Leakage and Multiple Delayed Fractional-Order Neural Networks with Parameter Mismatch
Authors: Xueqi Yao
Shouming Zhong
Yuanhua Du
Publication date: 04-08-2023
Publisher: Springer US
Published in: Neural Processing Letters / Issue 8/2023
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI: https://doi.org/10.1007/s11063-023-11380-4

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 8/2023

A Neurodynamic Approach for Solving Robust Linear Programming under the Polyhedral Uncertainty Set

Global Results on Exponential Stability of Neutral Cohen–Grossberg Neural Networks Involving Multiple Neutral and Discrete Time-Varying Delays: A Method Based on System Solutions

Window-Adjusted Common Spatial Pattern for Detecting Error-Related Potentials in P300 BCI

CAM R-CNN: End-to-End Object Detection with Class Activation Maps

General Decay Synchronization of Fuzzy Inertial Memristive Neural Networks with Discontinuous Activation Function

Supervised Learning Strategy for Spiking Neurons Based on Their Segmental Running Characteristics