Top

Cognitive Neurodynamics

Published in:

21-07-2021 | Research Article

Finite-/fixed-time synchronization for Cohen–Grossberg neural networks with discontinuous or continuous activations via periodically switching control

Authors: Hao Pu, Fengjun Li

Published in: Cognitive Neurodynamics | Issue 1/2022

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

search-config

AI-assisted search

Off

Abstract

This paper is concerned with finite-/fixed-time synchronization for a class of Cohen–Grossberg neural networks with discontinuous or continuous activations and mixed time delays. Based on the finite-time stability theory, Lyapunov stability theory, the concept of Filippov solution and the differential inclusion theory, some useful finite-/fixed-time synchronization sufficient conditions for the considered Cohen–Grossberg neural networks are established by designing two kinds of novel periodically switching controllers. Instead of using uninterrupted high control strength, the periodically switching controller in each period is used with high strength control in one stage and weak strength in the other. It can overcome the effects caused by the uncertainties of Filippov solution induced by discontinuous neuron activation functions and reduce the control cost. Besides, the period switching control rate is closely related to the settling time T. Finally, two numerical examples are given to demonstrate the effectiveness and feasibility of the obtained results.

previous article Astrocytic modulation on neuronal electric mode selection induced by magnetic field effect

next article Chimera states and cluster solutions in Hindmarsh-Rose neural networks with state resetting process

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

Abdujelil A, Haijun J (2016) New results on exponential synchronization of memristor-based neural networks with discontinuous neuron activations. Neural Netw 84:161–171CrossRef

Abdujelil A, Haijun J, Zhidong T (2016) Exponential lag synchronization for memristor-based neural networks with mixed time delays via hybrid switching control. J. Franklin Instit 353:2859–2880CrossRef

Abdujelil A, Haijun J, Cheng H (2017) General decay synchronization of memristor-based Cohen–Grossberg neural networks with mixed time-delays and discontinuous activations. J Franklin Instit 354:7028–7052CrossRef

Abdujelil A, Haijun J, Zhidong T (2017) Lag synchronization for Cohen-Grossberg neural networks with mixed time-delays via periodically intermittent control. Int J Comput Math 94:275–295CrossRef

Alimi AM, Aouiti C, Assali EA (2019) Finite-time and fixed-time synchronization of a class of inertial neural networks with multi-proportional delays and its application to secure communication. Neurocomputing 332:29–43CrossRef

Arjmandzadeh Z, Safi M, Nazemi A (2017) A new neural network model for solving random interval linear programming problems. Neural Netw 89:11–18PubMedCrossRef

Chao Y, Lihong H (2017) Finite-time synchronization of coupled time-delayed neural networks with discontinuous activations. Neurocomputing 249:64–71CrossRef

Chao Y, Lihong H, Zuowei C (2019) Fixed-time synchronization of coupled memristor-based neural networks with time-varying delays. Neural Netw 116:101–109CrossRef

Cheng H, Juan Yu, Haijun J (2014) Finite-time synchronization of delayed neural networks with Cohen–Grossberg type based on delayed feedback control. Neurocomputing 143:90–96CrossRef

Cheng H, Juan Yu, Zhanheng C, Haijun J, Tingwen H (2017) Fixed-time stability of dynamical systems and fixed-time synchronization of coupled discontinuous neural networks. Neural Netw 89:74–83CrossRef

Dongshu W, Lihong H, Longkun T, Jinsen Z (2018) Generalized pinning synchronization of delayed Cohen–Grossberg neural networks with discontinuous activations. Neural Netw 104:80–92CrossRef

Dongxue P, Jianxiang L, Wei X, Xiaodi L (2020) Finite-time synchronization of coupled Cohen–Grossberg neural networks with mixed time delays. J Franklin Instit 357:11349–11367CrossRef

Effati S, Baymani M (2005) A new nonlinear neural network for solving convex nonlinear programming problems. Appl Math Comput 168(2):1370–1379

Fanchao K, Quanxin Z, Rathinasamy S (2020) Finite-time and fixed-time synchronization control of fuzzy Cohen–Grossberg neural networks. Fuzzy Sets Syst 394:87–109CrossRef

Fangmin R, Minghui J, Hao X, Mengqin L (2020) Quasi fixed-time synchronization of memristive Cohen–Grossberg neural networks with reaction–diffusion. Neurocomputing 415:74–83CrossRef

Forti M, Nistri P (2003) Global convergence of neural networks with discontinuous neuron activations. IEEE Trans Circuits Syst I-regular Papers I(50):1421–1435CrossRef

Gaojian J, Cheng H, Juan Yu, Haijun J (2018) Finite-time and fixed-time synchronization of discontinuous complex networks: a unified control framework design. J Franklin Instit 355:4665–4685CrossRef

Hongzhi W, Chunrong C, Zhengwen T, Ning L (2018) New results on passivity analysis of memristive neural networks with time-varying delays and reaction–diffusion term. Neurocomputing 275:2080–2092CrossRef

Huaiqin W, Xiaowei Z, Li R (2015) Adaptive exponential synchronization of delayed Cohen–Grossberg neural networks with discontinuous activations. Int J Mach Learn Cybern 6(2):253–263CrossRef

Hui L, Wangli H, Qinglong H, Chen P (2018) Fixed-time synchronization for coupled delayed neural networks with discontinuous or continuous activations. Neurocomputing 314:143–153CrossRef

Hui L, Wangli H, Qinglong H, Chen P (2019) Fixed-time pinning-controlled synchronization for coupled delayed neural networks with discontinuous activations. Neural Netw 116:139–149CrossRef

Jiarong L, Haijun J, Cheng H, Zhiyong Yu (2018) Multiple types of synchronization analysis for discontinuous Cohen–Grossberg neural networks with time-varying delays. Neural Netw 99:101–113CrossRef

Jiarong L, Haijun J, Cheng H, Ahmed A (2019) Finite/fixed-time synchronization control of coupled memristive neural networks. J Franklin Instit 356:9928–9952CrossRef

Jun M, Minghui J, Xiaohong W, Jiali H, Shuangtao W (2014) Finite-time synchronization of drive-response systems via periodically intermittent adaptive control. J Franklin Instit 351:2691–2710CrossRef

Leimin W, Yi S, Guodong Z (2016) General decay synchronization stability for a class of delayed chaotic neural networks with discontinuous activations. Neurocomputing 179:169–175CrossRef

Leimin W, Zhigang Z, Junhao H, Xiaoping W (2017) Controller design for global fixed-time synchronization of delayed neural networks with discontinuous activations. Neural Netw 87:122–131CrossRef

Lian D, Hui W, Lihong H (2019) Finite-time synchronization of delayed fuzzy cellular neural networks with discontinuous activations. Fuzzy Sets Syst 361:56–70CrossRef

Lian D, Qian W, Hui W, Zengyun W (2020) Multi-type synchronization dynamics of delayed reaction–diffusion recurrent neural networks with discontinuous activations. Neurocomputing 401:182–192CrossRef

Liu XS, Michael HC, ZQ, (2016) A switching approach to designing finite-time synchronization controllers of coupled neural networks. IEEE Trans Neural Netw Learn Syst 2(27):471–482

Majid R, Chongqi Z, Yucheng C (2020) Adaptive model-free synchronization of different fractional-order neural networks with an application in cryptography. Nonlinear Dyn 100(4):3979–4001CrossRef

Mei L, Haijun J, Cheng H (2016) Finite-time synchronization of memristor-based Cohen–Grossberg neural networks with time-varying delays. Neurocomputing 194:1–9CrossRef

Mingwen Z, Lixiang L, Haipeng P, Jinghua X, Yixian Y, Yanping Z, Hui Z (2018) Fixed-time synchronization of memristor-based fuzzy cellular neural network with time-varying delay. J Franklin Instit 355:6780–6809CrossRef

Na S, Huina L (2019) Super resolution reconstruction of images based on interpolation and full convolutional neural network and application in medical fields. IEEE Access 7:186470–186479CrossRef

Ozlem F (2020) New criteria for global stability of neutral-type Cohen–Grossberg neural networks with multiple delays. Neural Netw 125:330–337CrossRef

Ozlem F (2020) An improved Lyapunov functional with application to stability of Cohen-Grossberg neural networks of neutral-type with multiple delays. Neural Netw 132:532–539CrossRef

Peng W, Dihua S, Min Z (2020) Finite-time and fixed-time anti-synchronization of Markovian neural networks with stochastic disturbances via switching control. Neural Netw 123:1–11CrossRef

Polyakov A (2012) Nonlinear feedback design for fixed-time stabilization of linear control systems. IEEE Trans Autom Control 57:2106–2110CrossRef

Pradeep C, Cao Y, Murugesu R, Rakkiyappan R (2019) An event-triggered synchronization of semi-Markov jump neural networks with time-varying delays based on generalized free-weighting-matrix approach. Math Comput Simul 155:41–56CrossRef

Prakash M, Balasubramaniam P, Lakshmanan S (2016) Synchronization of Markovian jumping inertial neural networks and its applications in image encryption. Neural Netw 83:86–93PubMedCrossRef

Qintao G, Feng X, Hui S (2019) Fixed-time outer synchronization of hybrid-coupled delayed complex networks via periodically semi-intermittent control. J Franklin Instit 356:6656–6677CrossRef

Qintao G, Feng X, Yan Q, Jing Y (2019) Fixed-Time cluster synchronization of discontinuous directed community networks via periodically or aperiodically switching control. IEEE Access 7:83306–83318CrossRef

Ruoxia L, Jinde C, Ahmad A, Fuad A (2017) Exponential and fixed-time synchronization of Cohen-Grossberg neural networks with time-varying delays. Appl Math Comput 313:37–51

Sabri A (2019) A modified Lyapunov functional with application to stability of neutral-type neural networks with time delays. J Franklin Instit 356(1):276–291CrossRef

Sabri A (2020) New criteria for stability of neutral-type neural networks with multiple time delays. IEEE Trans Neural Netw Learn Syst 31(5):1504–1513CrossRef

Toshiaki H, Kazuharu A, Tetsuya T, etc, (2018) Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images. Gastr Cancer 21(4):653–660CrossRef

Wang Z, Wang J, Wang Y (2018) An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition. Neurocomputing 310:213–222CrossRef

Wentao W (2018) Finite-time synchronization for a class of fuzzy cellular neural networks with time-varying coefficients and proportional delays. Fuzzy Sets Syst 338:40–49CrossRef

Xiaofang H, Gang F, Shukai Duan L, Liu. (2017) A memristive multilayer cellular neural network with applications to image processing. IEEE Trans Neural Netw Learn Syst 28(8):1889–1901CrossRef

Xiaoyang L, Tianping C, Jinde C, Wenlian L (2011) Dissipativity and quasi-synchronization for neural networks with discontinuous activations and parameter mismatches. Neural Netw 24:1013–1021CrossRef

Xiaoyang L, Ho Daniel WC, Qiang S, Jinde C (2017) Finite-/fixed-time robust stabilization of switched discontinuous systems with disturbances. Nonlinear Dyn 90:2057–2068CrossRef

Xinsong Y, Jinde C (2013) Exponential synchronization of delayed neural networks with discontinuous activations. IEEE Trans Circuits Syst 60(9):2431–2439CrossRef

Xinsong Y, Qiang S, Jinling L, Bin H (2015) Finite-time synchronization of coupled discontinuous neural networks with mixed delays and nonidentical perturbations. J Franklin Instit 352:4382–4406CrossRef

Xudong X, Shiping W, Zheng Y, Tingwen H, Yiran C (2020) Designing pulse-coupled neural networks with spike-synchronization-dependent plasticity rule: image segmentation and memristor circuit application. Neural Comput Appl 32:13441–13452CrossRef

Yang C, Samidurai R, Sriraman R (2019) Robust passivity analysis for uncertain neural networks with leakage delay and additive time-varying delays by using general activation function. 155:57-77

Yang C, Samidurai R, Sriraman R (2019) Stability and dissipativity analysis for neural type stochastic Markovian jump static neural networks with time delays. J Artif Intell Soft Comput Res 9(3):189–204CrossRef

Yang C, Sriraman R, Shyamsundarraj N, Samidurai R (2020) Robust stability of uncertain stochastic complex-valued neural networks with additive time-varying delays. Math Comput Simul 171:207–220CrossRef

Yi Z, Xinsong Y, Rongqiang T, Zunshui C (2020) Finite-time quantized synchronization of coupled discontinuous competitive neural networks with proportional delay and impulsive effects. J Franklin Instit 357:11136–11152CrossRef

Yueheng L, Biao L, Derong L, Zhanyu Y, Yunli Z (2020) Adaptive synchronization of memristor-based neural networks with discontinuous activations. Neurocomputing 381:196–206CrossRef

Zuowei C, Lihong H, Lingling Z (2015) New exponential synchronization criteria for time-varying delayed neural networks with discontinuous activations. Neural Netw 65:105–114CrossRef

Zuowei C, Lihong H, Lingling Z (2017) Improved switching controllers for finite-time synchronization of delayed neural networks with discontinuous activations. J Franklin Instit 354:6692–6723CrossRef

Zuowei C, Lihong H, Lingling Z (2017) Finite-time synchronization of master-slave neural networks with time-delays and discontinuous activations. Appl Math Modell 47:208–226CrossRef

Title: Finite-/fixed-time synchronization for Cohen–Grossberg neural networks with discontinuous or continuous activations via periodically switching control
Authors: Hao Pu
Fengjun Li
Publication date: 21-07-2021
Publisher: Springer Netherlands
Published in: Cognitive Neurodynamics / Issue 1/2022
Print ISSN: 1871-4080
Electronic ISSN: 1871-4099
DOI: https://doi.org/10.1007/s11571-021-09694-x

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 1/2022

A new biological central pattern generator model and its relationship with the motor units

How glutamatergic synapse loss affects the firing rhythm of DG-CA3 model related with Alzheimer’s disease

Hybrid classification model for eye state detection using electroencephalogram signals

Long-term predictions of current confirmed and dead cases of COVID-19 in China by the non-autonomous delayed epidemic models

A computational examination of the two-streams hypothesis: which pathway needs a longer memory?

A survey of brain network analysis by electroencephalographic signals