Zagreb Connection Numbers for Cellular Neural Networks
Joint Authors
Liu, Jia-Bao
Javaid, Muhammad
Raza, Zahid
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-23
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Neural networks in which communication works only among the neighboring units are called cellular neural networks (CNNs).
These are used in analyzing 3D surfaces, image processing, modeling biological vision, and reducing nonvisual problems of geometric maps and sensory-motor organs.
Topological indices (TIs) are mathematical models of the (molecular) networks or structures which are presented in the form of numerical values, constitutional formulas, or numerical functions.
These models predict the various chemical or structural properties of the under-study networks.
We now consider analogous graph invariants, based on the second connection number of vertices, called Zagreb connection indices.
The main objective of this paper is to compute these connection indices for the cellular neural networks (CNNs).
In order to find their efficiency, a comparison among the obtained indices of CNN is also performed in the form of numerical tables and 3D plots.
American Psychological Association (APA)
Liu, Jia-Bao& Raza, Zahid& Javaid, Muhammad. 2020. Zagreb Connection Numbers for Cellular Neural Networks. Discrete Dynamics in Nature and Society،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1153458
Modern Language Association (MLA)
Liu, Jia-Bao…[et al.]. Zagreb Connection Numbers for Cellular Neural Networks. Discrete Dynamics in Nature and Society No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1153458
American Medical Association (AMA)
Liu, Jia-Bao& Raza, Zahid& Javaid, Muhammad. Zagreb Connection Numbers for Cellular Neural Networks. Discrete Dynamics in Nature and Society. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1153458
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1153458