Dve Laplasove energije i odnosi među njima

Ključne reči: Laplasov spektar (graf), Laplasova energija

Sažetak


Uvod/cilj: Laplasova energija (LE) jeste suma apsolutnih vrednosti pojmova μi-2m/n, gde su μi, i=1,2,...,n, sopstvene vrednosti Laplasove matrice grafa G sa n vrhova i m ivica. Godine 2006. uvedena je druga veličina Z, zasnovana na Laplasovim svojstvenim vrednostima, koja je takođe nazvana „Laplasova energija”. Z je suma kvadrata Laplasovih svojstvenih vrednosti. Cilj ovog rada je nalaženje odnosa između LE i Z.

Rezultati: Donja i gornja granica za LE određene su kao funkcije od Z.

Zaključak: Rad doprinosi Laplasovoj spektralnoj teoriji i teoriji energije grafova. Pokazano je da je, kao gruba aproksimacija, LE proporcionalna sa (Z-4m2/n)1/2.

Biografija autora

Ivan Gutman, Univerzitet u Kragujevcu, Prirodno-matematički fakultet, Kragujevac, Republika Srbija

videti na www.pmf.kg.ac.rs/gutman

Reference

Andriantiana, E.O.D. 2016. Laplacian energy. In: Gutman, I. & Li, X. (Eds.) Graph Energies - Theory and Applications. Kragujevac: University of Kragujevac, pp.49-80.

Bai, Y., Dong, L., Huang, X., Yang, W., & Liao, M. 2014. Hierarchial segmentation of polarimetric SAR image via non-parametric graph entropy. In: IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, Canada, July 13-18. Available at: https://doi.org/10.1109/IGARSS.2014.6947054.

Das, K.C., & Mojallal, S.A. 2014. On Laplacian energy of graphs. Discrete Mathematics, 325, pp.52-64. Available at: https://doi.org/10.1016/j.disc.2014.02.017.

Deepa, G., Praba, B. & Chandrasekaran, V.M. 2016. Spreading rate of virus on energy of Laplacian intuitionistic fuzzy graph. Research Journal on Pharmacy and Technology, 9(8), pp.1140-1144. Available at: https://doi.org/10.5958/0974-360X.2016.00217.1.

Grone, R., Merris, R., & Sunder, V.S. 1990. The Laplacian Spectrum of a Graph. SIAM Journal on Matrix Analysis and Applications, 11(2), pp.218-238. Available at: https://doi.org/10.1137/0611016.

Gutman, I. 2020. New bounds for Laplacian energy. Vojnotehnički glasnik/Military Technical Courier, 68(1), pp.1-7. Available at: https://doi.org/10.5937/vojtehg68-24257.

Gutman, I., & Furtula, B. 2019. Graph Energies: Survey, Census, Bibliography. Kragujevac: Centar SANU. Bibliography.

Gutman, I., & Zhou, B. 2006. Laplacian energy of a graph. Linear Algebra and its Applications, 414(1), pp.29-37. Available at: https://doi.org/10.1016/j.laa.2005.09.008.

Huigang, Z., Xiao, B., Huaxin, Z., Huijie, Z., Jun, Z., Jian, C., & Hanqing, L. 2013. Hierarchical remote sensing image analysis via graph Laplacian energy. IEEE Geoscience Remote Sensing Letters, 10(2), pp.396-400. Available at: https://doi.org/10.1109/LGRS.2012.2207087.

Lazić, M. 2006. On the Laplacian energy of a graph. Czechoslovak Mathematical Journal, 56(4), pp.1207-1213 [online]. Available at: http://cmj.math.cas.cz/cmj56-4/10.html [Accessed: 21 February 2020].

Li, X., Shi, Y., & Gutman, I. 2012. Introduction. In: Graph Energy. New York, NY: Springer Science and Business Media LLC., pp.1-9. Available at: https://doi.org/10.1007/978-1-4614-4220-2_1.

Luyuan, C., Meng, Z., Shang, L., Xiaoyan, M., & Xiao, B. 2010. Shape Decomposition for Graph Representation. In: Lee, R., Ma, J., Bacon, L., Du, W., & Petridis, M. (Eds.) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Studies in Computational Intelligence, 295. Berlin, Heidelberg: Springer, pp.1-10. Available at: https://doi.org/10.1007/978-3-642-13265-0_1.

Meng, Z. & Xiao, B. 2011. High-resolution satellite image classification and segmentation using Laplacian graph energy. In: IEEE Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada, July 24-29. Available at: https://doi.org/10.1109/IGARSS.2011.6049201.

Merris, R. 1994. Laplacian matrices of graphs: A survey. Linear Algebra and its Applications, 197-198, pp.143-176. Available at: https://doi.org/10.1016/0024-3795(94)90486-3.

Mohar, B. 1992. Laplace eigenvalues of graphs-a survey. Discrete Mathematics, 109(1-3), pp.171-183. Available at: https://doi.org/10.1016/0012-365X(92)90288-Q.

Nikiforov, V. 2007. The energy of graphs and matrices. Journal of Mathematical Analysis and Applications, 326(2), pp.1472-1475. Available at: https://doi.org/10.1016/j.jmaa.2006.03.072.

Pirzada, S., & Ganie, H.A. 2015. On the Laplacian eigenvalues of a graph and Laplacian energy. Linear Algebra and its Applications, 486, pp.454-468. Available at: https://doi.org/10.1016/j.laa.2015.08.032.

Pournami, P.N. & Govindan, V.K. 2017. Interest point detection based on Laplacian energy of local image network. In: International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, India, March 22-24. Available at: https://doi.org/10.1109/WiSPNET.2017.8299719.

Qi, X., Duval, R.D., Christensen, K., Fuller, E., Spahiu, A.,Wu, Q., Wu, Y., Tang, W., & Zhang, C. 2013. Terrorist networks, network energy and node removal: A new measure of centrality based on Laplacian energy. Social Networking, 2(1), pp.19-31. Available at: https://doi.org/10.4236/sn.2013.21003.

Qi, X., Fuller, E., Luo, R., Guo, G., & Zhang, C. 2015. Laplacian energy of digraphs and a minimum Laplacian energy algorithm. International Journal on the Foundation of Computer Science, 26(3), pp.367-380. Available at: https://doi.org/10.1142/S0129054115500203.

Qi, X., Fuller, E., Wu, Q., Wu, Y., & Zhang, C.Q. 2012. Laplacian centrality: A new centrality measure for weighted networks. Information Science, 194, pp.240-253. Available at: https://doi.org/10.1016/j.ins.2011.12.027.

Ramane, H.S. 2020. Energy of graphs. In: Pal, M., Samanta, S., & Pal, A. (Eds.) Handbook of Research on Advanced Applications of Graph Theory in Modern Society. Hershey, Pennsylvania, USA: IGI Global, pp.267-296.

Song, YZ., Arbelaez, P., Hall, P., Li, C., & Balikai, A. 2010. Finding semantic structures in image hierarchies using Laplacian graph energy. In: Daniilidis, K., Maragos, P. & Paragios N. (Eds.) Computer Vision – ECCV 2010. ECCV 2010. Lecture Notes in Computer Science, 6314. Berlin: Springer, pp.694-707. Available at: https://doi.org/10.1007/978-3-642-15561-1_50.

Xiao, B., Song, YZ., & Hall, P. 2011. Learning invariant for object identification by using graph methods. Computer Vision and Image Understanding, 115(7), pp.1023-1031. Available at: https://doi.org/10.1016/j.cviu.2010.12.016.

Zou, HL., Yu, ZG., Anh, V., & Ma, YL. 2018. From standard alpha-stable Lévy motions to horizontal visibility networks: dependence of multifractal and Laplacian spectrum. Journal of Statistical Mechanics Theory and Experiment, 2018(May) [online]. Available at: https://iopscience.iop.org/article/10.1088/1742-5468/aaac3d/pdf [Accessed: 21 February 2020].

Objavljeno
2020/04/16
Rubrika
Originalni naučni radovi