Topological properties of cellular neural networks

Muhammad Imran, Muhammad Kamran Siddiqui, Abdul Qudair Baig, Waqas Khalid, Hani Shaker

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

Graph theory is a fundamental and energetic tool for designing and modeling a graph/network. There are certain topological indices based on degree, distance and eccentricity, etc. The topological indices essentially relate certain physio-concoction properties and bio-Activity to the corresponding synthetic and atomic structure. In this paper, our aim is to figure out degree-based topological indices mainly atom-bond connectivity (ABC), geometric-Arithmetic (GA), ABC4 and GA5 indices for cellular neural network (CNN) and give closed results of these indices for cellular neural network. Moreover, we also compute general Randi cindex R of CNN for = { 1 ,-1 , 1 2 ,-1 2 } only and give analytical closed form results. A 3D graph analysis for comparison of indices is also given.

Original languageEnglish
Pages (from-to)3605-3614
Number of pages10
JournalJournal of Intelligent and Fuzzy Systems
Volume37
Issue number3
DOIs
Publication statusPublished - 2019

Keywords

  • Molecular descriptor
  • atom bond connectivity index
  • cellular neural network
  • general Randić index
  • geometric arithmetic index

ASJC Scopus subject areas

  • Statistics and Probability
  • Engineering(all)
  • Artificial Intelligence

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