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Multidimensional frequency estimation using LU decomposition eigenvector–based algorithm

  • Mohamed M. M. Omar
  • Khaled A. Eskaf
  • Basel A. GhreiwatiEmail author
Article
  • 12 Downloads

Abstract

Many algorithms have been proposed for multidimensional frequency estimation from a single snapshot or multiple snapshots of data mixture. Most of these algorithms fail when one or more identical frequencies are found in certain dimensions. In this paper, a multidimensional frequency estimation technique from a single datum snapshot is proposed. It applies LU decomposition (Gaussian Elimination) on an eigenvector-based algorithm for multidimensional frequency estimation. This proposed technique is simulated using a MATLAB code. The average root mean square error (RMSE) is investigated as a performance measure of the proposed technique. A comparison between original eigenvector-based (traditional) and the proposed techniques is introduced. The simulation results show that the RMSE of the proposed technique is less than the original one, and it has a more efficient solution for an identical frequency case but at the expense of complexity.

Keywords

Eigenvalue decomposition Least mean square errors Multidimensional frequency estimation Singular value decomposition 

Notes

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Copyright information

© Institut Mines-Télécom and Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Electronic and Communication EngineeringArab Academy for Science and Technology & MaritimeAlexandriaEgypt
  2. 2.Department of Computer ScienceArab Academy for Science and Technology & MaritimeAlexandriaEgypt

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