A T-PROPER KARHUNEN-LOÈVE EXPANSION AND ITS APPLICATION TO THE PROBLEM OF SIMULATION

R.M. Fernandez-Alcala; J. Navarro-Moreno; J. D. Jimenez-Lopez; C. Cheong Took; J. C. Ruiz-Molina

doi:10.1109/MLSP58920.2024.10734774

A T-PROPER KARHUNEN-LOÈVE EXPANSION AND ITS APPLICATION TO THE PROBLEM OF SIMULATION

R.M. Fernandez-Alcala
, J. Navarro-Moreno
, J. D. Jimenez-Lopez
, C. Cheong Took
, J. C. Ruiz-Molina

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

The paper addresses the Karhunen-Loeve series representation in the tessarine domain. Based on augmented statistics, a tessarine widely linear Karhunen-Loeve expansion is defined. Then, the impact of T-properness on this representation
is analyzed, leading to a T-proper Karhunen-Loeve expansion that means a dimensionality reduction. Furthermore, this series representation serves as a versatile simulation tool, valid for both stationary and non-stationary, Gaussian and non-Gaussian random signals. Finally, the applicability of the simulation technique proposed is examined numerically.

Original language	English
Title of host publication	2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	979-8-3503-7225-0
ISBN (Print)	979-8-3503-7226-7
DOIs	https://doi.org/10.1109/MLSP58920.2024.10734774
Publication status	Published - 4 Nov 2024

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10.1109/MLSP58920.2024.10734774

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Accepted author manuscript, 3.73 MBLicence: Other

Cite this

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title = "A T-PROPER KARHUNEN-LO{\`E}VE EXPANSION AND ITS APPLICATION TO THE PROBLEM OF SIMULATION",

abstract = "The paper addresses the Karhunen-Loeve series representation in the tessarine domain. Based on augmented statistics, a tessarine widely linear Karhunen-Loeve expansion is defined. Then, the impact of T-properness on this representation is analyzed, leading to a T-proper Karhunen-Loeve expansion that means a dimensionality reduction. Furthermore, this series representation serves as a versatile simulation tool, valid for both stationary and non-stationary, Gaussian and non-Gaussian random signals. Finally, the applicability of the simulation technique proposed is examined numerically.",

author = "R.M. Fernandez-Alcala and J. Navarro-Moreno and Jimenez-Lopez, \{J. D.\} and \{Cheong Took\}, C. and Ruiz-Molina, \{J. C.\}",

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AU - Fernandez-Alcala, R.M.

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AU - Jimenez-Lopez, J. D.

AU - Cheong Took, C.

AU - Ruiz-Molina, J. C.

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N2 - The paper addresses the Karhunen-Loeve series representation in the tessarine domain. Based on augmented statistics, a tessarine widely linear Karhunen-Loeve expansion is defined. Then, the impact of T-properness on this representation is analyzed, leading to a T-proper Karhunen-Loeve expansion that means a dimensionality reduction. Furthermore, this series representation serves as a versatile simulation tool, valid for both stationary and non-stationary, Gaussian and non-Gaussian random signals. Finally, the applicability of the simulation technique proposed is examined numerically.

AB - The paper addresses the Karhunen-Loeve series representation in the tessarine domain. Based on augmented statistics, a tessarine widely linear Karhunen-Loeve expansion is defined. Then, the impact of T-properness on this representation is analyzed, leading to a T-proper Karhunen-Loeve expansion that means a dimensionality reduction. Furthermore, this series representation serves as a versatile simulation tool, valid for both stationary and non-stationary, Gaussian and non-Gaussian random signals. Finally, the applicability of the simulation technique proposed is examined numerically.

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