Hidden Multistability in a Memristor-Based Cellular Neural Network
Joint Authors
Wang, Guangyi
Xu, Birong
Lin, Hairong
Source
Advances in Mathematical Physics
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-27
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In this paper, we report a novel memristor-based cellular neural network (CNN) without equilibrium points.
Dynamical behaviors of the memristor-based CNN are investigated by simulation analysis.
The results indicate that the system owns complicated nonlinear phenomena, such as hidden attractors, coexisting attractors, and initial boosting behaviors of position and amplitude.
Furthermore, both heterogeneous multistability and homogenous multistability are found in the CNN.
Finally, Multisim circuit simulations are performed to prove the chaotic characteristics and multistability of the system.
American Psychological Association (APA)
Xu, Birong& Lin, Hairong& Wang, Guangyi. 2020. Hidden Multistability in a Memristor-Based Cellular Neural Network. Advances in Mathematical Physics،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1127590
Modern Language Association (MLA)
Xu, Birong…[et al.]. Hidden Multistability in a Memristor-Based Cellular Neural Network. Advances in Mathematical Physics No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1127590
American Medical Association (AMA)
Xu, Birong& Lin, Hairong& Wang, Guangyi. Hidden Multistability in a Memristor-Based Cellular Neural Network. Advances in Mathematical Physics. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1127590
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1127590