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

Physics

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