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Dominating Topological Analysis and Comparison of the Cellular Neural Network

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  • Farukh Ejaz
  • Muhammad Hussain
  • Hamad Almohamedh
  • Khalid M. Alhamed
  • Rana Alabdan
  • Sultan Almotairi

Abstract

Graph theory is a discrete branch of mathematics for designing and predicting a network. Some topological invariants are mathematical tools for the analysis of connection properties of a particular network. The Cellular Neural Network (CNN) is a computer paradigm in the field of machine learning and computer science. In this article we have given a close expression to dominating invariants computed by the dominating degree for a cellular neural network. Moreover, we have also presented a 3D comparison between dominating invariants and classical degree-based indices to show that, in some cases, dominating invariants give a better correlation on the cellular neural network as compared to classical indices.

Suggested Citation

  • Farukh Ejaz & Muhammad Hussain & Hamad Almohamedh & Khalid M. Alhamed & Rana Alabdan & Sultan Almotairi, 2021. "Dominating Topological Analysis and Comparison of the Cellular Neural Network," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-9, April.
    • Handle: RePEc:hin:jnlmpe:6613433
    DOI: 10.1155/2021/6613433
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