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Al-Bahir Journal for Engineering and Pure Sciences

Abstract

Approximating function by using Spectral Graph Wavelets is an interesting direction in approximation theory. We essential to well choosing the space of functions that are approximated by Spectral Graph Wavelets. spaces of functions are fantastic choices to study It is more interesting to take the value . In this paper , new formulas of Spectral Graph Wavelets were constructed and proved to get good rates of approximation. Fundamental properties of Graph Wavelets transform ( GWT) are studied, such as, inversion , scaling Limit and approximation Wavelets. Finally , existence of best approximation can be concluded here for Graph functions in terms of SGWT.

References

  1. Hammond DK, Vandergheynst P, Gribonval R. Applied and computational harmonic Analysis, Wavelets on graphs via spectral graph theory. In: Contents lists available at Science-Direct. vol. 30; 2011. p. 129e50. no. 1. Link
  2. Graps Amara. An introduction to wavelets. In: Article in IEEE computational science and engineering; February 1995. Link
  3. Bhaya ES. On the constrained and unconstrained approximation”, PD thesis. University of Baghdad; 2003. Link
  4. Grossmann A, Morlet J. Decomposition of Hardy functions into square integrable wavelets of constant shape. SIAM J Math Anal 1984;15(4):723e36. Link
  5. Deutsch F. Best approximation in inner product spaces. In: Canadian Mathematical society (societe Mathematique du Canada). © Springer-Verlag New York, Inc; 2001. Link
  6. Walter RUDIN. Principles of mathematical analysis. In: Exclusive rights by McGraw-Hill Book Co. - Singapore for manufacture and export . International Editions. Third Edition 1976. Link
  7. Roughgarden T, Valiant G. Spectral graph theory,” the modern algorithmic toolbox. May 2, 2022. Link
  8. Wilson RJ. Introduction to graph theory. In: Produced through longman Malaysia. Fourth edition. Longman Group Ltd; 1998. Link
  9. Chen X. Understanding spectral graph neural network. Department of Mathematics, University of Manchester Manchester, M13 9PL, United Kingdom; 2020. p. 1e19. Link

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