Zagreb Connection Numbers for Cellular Neural Networks. (23rd October 2020)
- Record Type:
- Journal Article
- Title:
- Zagreb Connection Numbers for Cellular Neural Networks. (23rd October 2020)
- Main Title:
- Zagreb Connection Numbers for Cellular Neural Networks
- Authors:
- Liu, Jia-Bao
Raza, Zahid
Javaid, Muhammad - Other Names:
- Ragusa Maria Alessandra Academic Editor.
- Abstract:
- Abstract : 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.
- Is Part Of:
- Discrete dynamics in nature and society. Volume 2020(2020)
- Journal:
- Discrete dynamics in nature and society
- Issue:
- Volume 2020(2020)
- Issue Display:
- Volume 2020, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 2020
- Issue:
- 2020
- Issue Sort Value:
- 2020-2020-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-10-23
- Subjects:
- System analysis -- Periodicals
Dynamics -- Periodicals
Chaotic behavior in systems -- Periodicals
Differentiable dynamical systems -- Periodicals
003.05 - Journal URLs:
- https://www.hindawi.com/journals/ddns/ ↗
- DOI:
- 10.1155/2020/8038304 ↗
- Languages:
- English
- ISSNs:
- 1026-0226
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 14982.xml