Spectral variation of normalised laplacian for various network models

Many network models have been proposed to mimic real-world systems when they become too large and complex to be described explicitly. Since the models inherit similar structural properties to the real-world network, by studying their nodes and links, many network properties can be identified. While...

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Main Authors: Liang, Y.S.J., Chan, K.T., Shah, N.M.
Format: Article
Language:English
Published: Academy of Sciences Malaysia 2024
Online Access:http://psasir.upm.edu.my/id/eprint/114342/
http://psasir.upm.edu.my/id/eprint/114342/1/114342.pdf
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author Liang, Y.S.J.
Chan, K.T.
Shah, N.M.
author_facet Liang, Y.S.J.
Chan, K.T.
Shah, N.M.
author_sort Liang, Y.S.J.
building UPM Institutional Repository
collection Online Access
description Many network models have been proposed to mimic real-world systems when they become too large and complex to be described explicitly. Since the models inherit similar structural properties to the real-world network, by studying their nodes and links, many network properties can be identified. While most of the tools used to study their structural properties are coming from graph theory, spectral analysis is another method that can be used to reveal the structural inheritance properties of a network. In this work, we performed spectral analysis on network models, namely Erdo-Renyi (ER), Watts-Strogatz (WS), Barabasi Albert (BA), grids and growing geometrical network (GGN) with the undirected and directed connection. The eigenvalue spectrum of the normalised Laplacian was computed for each model and used in spectral plots, Cheeger constant and energy measurement. Results from the spectral measures have revealed specific characteristics for different models, which in turn make them easier to be recognised.
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spelling upm-1143422025-01-14T04:51:19Z http://psasir.upm.edu.my/id/eprint/114342/ Spectral variation of normalised laplacian for various network models Liang, Y.S.J. Chan, K.T. Shah, N.M. Many network models have been proposed to mimic real-world systems when they become too large and complex to be described explicitly. Since the models inherit similar structural properties to the real-world network, by studying their nodes and links, many network properties can be identified. While most of the tools used to study their structural properties are coming from graph theory, spectral analysis is another method that can be used to reveal the structural inheritance properties of a network. In this work, we performed spectral analysis on network models, namely Erdo-Renyi (ER), Watts-Strogatz (WS), Barabasi Albert (BA), grids and growing geometrical network (GGN) with the undirected and directed connection. The eigenvalue spectrum of the normalised Laplacian was computed for each model and used in spectral plots, Cheeger constant and energy measurement. Results from the spectral measures have revealed specific characteristics for different models, which in turn make them easier to be recognised. Academy of Sciences Malaysia 2024-08-30 Article PeerReviewed text en cc_by_nc_4 http://psasir.upm.edu.my/id/eprint/114342/1/114342.pdf Liang, Y.S.J. and Chan, K.T. and Shah, N.M. (2024) Spectral variation of normalised laplacian for various network models. ASM Science Journal, 19. pp. 1-14. ISSN 1823-6782; eISSN: 2682-8901 https://www.akademisains.gov.my/asmsj/article/spectral-variation-of-normalised-laplacian-for-various-network-models/ 10.32802/ASMSCJ.2023.1518
spellingShingle Liang, Y.S.J.
Chan, K.T.
Shah, N.M.
Spectral variation of normalised laplacian for various network models
title Spectral variation of normalised laplacian for various network models
title_full Spectral variation of normalised laplacian for various network models
title_fullStr Spectral variation of normalised laplacian for various network models
title_full_unstemmed Spectral variation of normalised laplacian for various network models
title_short Spectral variation of normalised laplacian for various network models
title_sort spectral variation of normalised laplacian for various network models
url http://psasir.upm.edu.my/id/eprint/114342/
http://psasir.upm.edu.my/id/eprint/114342/
http://psasir.upm.edu.my/id/eprint/114342/
http://psasir.upm.edu.my/id/eprint/114342/1/114342.pdf