American Institute of Mathematical Sciences

Advanced
  • Previous Article
    Gevrey asymptotic theory for singular first order linear partial differential equations of nilpotent type — Part I —
  • CPAA Home
  • This Issue
  • Next Article
    Nonhomogeneous polyharmonic elliptic problems at critical growth with symmetric data
June  2003, 2(2): 187-209. doi: 10.3934/cpaa.2003.2.187

Attractors in continuous –time switching networks

Tomáš Gedeon 1,

1. 

Department of Mathematical Sciences, Montana State University, Bozeman, MT 59717, United States

Received  February 2002 Revised  January 2003 Published  March 2003

We consider a system of equations with discontinuous right hand side, which arise as models of gene and neural networks. We study attractors in $R^4$ which lie in a set of orthants in the form of figure eight. We find that if the attractor is symmetric with respect to these two loops, then the only possible attractor is a periodic orbit which traverses both loops once. We show that without the symmetry the set of admissible attractors include periodic orbits which follow one loop $k$ times and other loop once, for any $k$. However, we also show that no trajectory in an attractor can traverse both loops more then once in a row.
Keywords: additive neural networks., Attractors, continuous-time switching networks.
Mathematics Subject Classification: 34C25, 34D45, 92B2.
Citation: Tomáš Gedeon. Attractors in continuous –time switching networks. Communications on Pure and Applied Analysis, 2003, 2 (2) : 187-209. doi: 10.3934/cpaa.2003.2.187
[1]

Zhigang Zeng, Tingwen Huang. New passivity analysis of continuous-time recurrent neural networks with multiple discrete delays. Journal of Industrial and Management Optimization, 2011, 7 (2) : 283-289. doi: 10.3934/jimo.2011.7.283
[2]

Shui-Nee Chow, Xiaojing Ye, Hongyuan Zha, Haomin Zhou. Influence prediction for continuous-time information propagation on networks. Networks and Heterogeneous Media, 2018, 13 (4) : 567-583. doi: 10.3934/nhm.2018026
[3]

Fritz Colonius, Guilherme Mazanti. Decay rates for stabilization of linear continuous-time systems with random switching. Mathematical Control and Related Fields, 2019, 9 (1) : 39-58. doi: 10.3934/mcrf.2019002
[4]

Meiyu Sui, Yejuan Wang, Peter E. Kloeden. Pullback attractors for stochastic recurrent neural networks with discrete and distributed delays. Electronic Research Archive, 2021, 29 (2) : 2187-2221. doi: 10.3934/era.2020112
[5]

Simone Göttlich, Stephan Martin, Thorsten Sickenberger. Time-continuous production networks with random breakdowns. Networks and Heterogeneous Media, 2011, 6 (4) : 695-714. doi: 10.3934/nhm.2011.6.695
[6]

Ping Chen, Haixiang Yao. Continuous-time mean-variance portfolio selection with no-shorting constraints and regime-switching. Journal of Industrial and Management Optimization, 2020, 16 (2) : 531-551. doi: 10.3934/jimo.2018166
[7]

Ying Sue Huang. Resynchronization of delayed neural networks. Discrete and Continuous Dynamical Systems, 2001, 7 (2) : 397-401. doi: 10.3934/dcds.2001.7.397
[8]

Tingting Su, Xinsong Yang. Finite-time synchronization of competitive neural networks with mixed delays. Discrete and Continuous Dynamical Systems - B, 2016, 21 (10) : 3655-3667. doi: 10.3934/dcdsb.2016115
[9]

Cheng-Hsiung Hsu, Suh-Yuh Yang. Traveling wave solutions in cellular neural networks with multiple time delays. Conference Publications, 2005, 2005 (Special) : 410-419. doi: 10.3934/proc.2005.2005.410
[10]

Xiaochen Mao, Weijie Ding, Xiangyu Zhou, Song Wang, Xingyong Li. Complexity in time-delay networks of multiple interacting neural groups. Electronic Research Archive, 2021, 29 (5) : 2973-2985. doi: 10.3934/era.2021022
[11]

Joon Kwon, Panayotis Mertikopoulos. A continuous-time approach to online optimization. Journal of Dynamics and Games, 2017, 4 (2) : 125-148. doi: 10.3934/jdg.2017008
[12]

Hanqing Jin, Xun Yu Zhou. Continuous-time portfolio selection under ambiguity. Mathematical Control and Related Fields, 2015, 5 (3) : 475-488. doi: 10.3934/mcrf.2015.5.475
[13]

Tatyana S. Turova. Structural phase transitions in neural networks. Mathematical Biosciences & Engineering, 2014, 11 (1) : 139-148. doi: 10.3934/mbe.2014.11.139
[14]

Wenlian Lu, Fatihcan M. Atay, Jürgen Jost. Consensus and synchronization in discrete-time networks of multi-agents with stochastically switching topologies and time delays. Networks and Heterogeneous Media, 2011, 6 (2) : 329-349. doi: 10.3934/nhm.2011.6.329
[15]

Zengyun Wang, Jinde Cao, Zuowei Cai, Lihong Huang. Finite-time stability of impulsive differential inclusion: Applications to discontinuous impulsive neural networks. Discrete and Continuous Dynamical Systems - B, 2021, 26 (5) : 2677-2692. doi: 10.3934/dcdsb.2020200
[16]

Ruoxia Li, Huaiqin Wu, Xiaowei Zhang, Rong Yao. Adaptive projective synchronization of memristive neural networks with time-varying delays and stochastic perturbation. Mathematical Control and Related Fields, 2015, 5 (4) : 827-844. doi: 10.3934/mcrf.2015.5.827
[17]

Jianping Zhou, Yamin Liu, Ju H. Park, Qingkai Kong, Zhen Wang. Fault-tolerant anti-synchronization control for chaotic switched neural networks with time delay and reaction diffusion. Discrete and Continuous Dynamical Systems - S, 2021, 14 (4) : 1569-1589. doi: 10.3934/dcdss.2020357
[18]

Udhayakumar Kandasamy, Rakkiyappan Rajan. Hopf bifurcation of a fractional-order octonion-valued neural networks with time delays. Discrete and Continuous Dynamical Systems - S, 2020, 13 (9) : 2537-2559. doi: 10.3934/dcdss.2020137
[19]

Yong Zhao, Shanshan Ren. Synchronization for a class of complex-valued memristor-based competitive neural networks(CMCNNs) with different time scales. Electronic Research Archive, 2021, 29 (5) : 3323-3340. doi: 10.3934/era.2021041
[20]

Juan Cao, Fengli Ren, Dacheng Zhou. Asymptotic and finite-time cluster synchronization of neural networks via two different controllers. Discrete and Continuous Dynamical Systems - B, 2022  doi: 10.3934/dcdsb.2022005

2020 Impact Factor: 1.916

Tools

Metrics

  • PDF downloads (94)
  • HTML views (0)
  • Cited by (8)

Other articles
by authors

[Back to Top]

Copyright © 2022 American Institute of Mathematical Sciences | Privacy Policy