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Adjacency Matrix of Product of Graphs

8 pagesPublished: June 12, 2017

Abstract

In graph theory, different types of matrices associated with graph, e.g. Adjacency matrix, Incidence matrix, Laplacian matrix etc. Among all adjacency matrix play an important role in graph theory. Many products of two graphs as well as its generalized form had been studied, e.g., cartesian product, 2−cartesian product, tensor product, 2−tensor product etc. In this paper, we discuss the adjacency matrix of two new product of graphs G H, where = ⊗2, ×2. Also, we obtain the spectrum of these products of graphs.

Keyphrases: 2-Cartesian product, 2-tensor product, adjacency matrix, spectrum

In: Rajkumar Buyya, Rajiv Ranjan, Sumantra Dutta Roy, Mehul Raval, Mukesh Zaveri, Hiren Patel, Amit Ganatra, Darshak G. Thakore, Trupti A. Desai, Zankhana H. Shah, Narendra M. Patel, Mukesh E. Shimpi, Rajiv B. Gandhi, Jagdish M. Rathod, Bhargav C. Goradiya, Mehfuza S. Holia and Dharita K. Patel (editors). ICRISET2017. International Conference on Research and Innovations in Science, Engineering and Technology. Selected Papers in Computing, vol 2, pages 158--165

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BibTeX entry
@inproceedings{ICRISET2017:Adjacency_Matrix_of_Product,
  author    = {Urvashi Acharya and Himali Mehta},
  title     = {Adjacency Matrix of Product of Graphs},
  booktitle = {ICRISET2017. International Conference on Research and Innovations in Science, Engineering and Technology. Selected Papers in Computing},
  editor    = {Rajkumar Buyya and Rajiv Ranjan and Sumantra Dutta Roy and Mehul Raval and Mukesh Zaveri and Hiren Patel and Amit Ganatra and Darshak G. Thakore and Trupti A. Desai and Zankhana H. Shah and Narendra M. Patel and Mukesh E. Shimpi and Rajiv B. Gandhi and Jagdish M. Rathod and Bhargav C. Goradiya and Mehfuza S. Holia and Dharita K. Patel},
  series    = {Kalpa Publications in Computing},
  volume    = {2},
  pages     = {158--165},
  year      = {2017},
  publisher = {EasyChair},
  bibsource = {EasyChair, http://www.easychair.org},
  issn      = {2515-1762},
  url       = {https://easychair.org/publications/paper/M6h},
  doi       = {10.29007/fqlw}}
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