Efficient and stable joint eigenvalue decomposition based on generalized givens rotations
A Mesloub, A Belouchrani… - 2018 26th European …, 2018 - ieeexplore.ieee.org
A Mesloub, A Belouchrani, K Abed-Meraim
2018 26th European Signal Processing Conference (EUSIPCO), 2018•ieeexplore.ieee.orgIn the present paper, a new joint eigenvalue decomposition (JEVD) method is developed by
considering generalized Givens rotations. This method deals with a set of square matrices
sharing a same eigenstructure. Several Jacobi-like methods exist already for solving the
aforementioned problem. The differences reside in the way of estimating the Shear rotation.
Herein, we clarify these differences, highlight the weaknesses of the existing solutions and
develop a new robust method named Efficient and Stable Joint eigenvalue Decomposition …
considering generalized Givens rotations. This method deals with a set of square matrices
sharing a same eigenstructure. Several Jacobi-like methods exist already for solving the
aforementioned problem. The differences reside in the way of estimating the Shear rotation.
Herein, we clarify these differences, highlight the weaknesses of the existing solutions and
develop a new robust method named Efficient and Stable Joint eigenvalue Decomposition …
In the present paper, a new joint eigenvalue decomposition (JEVD) method is developed by considering generalized Givens rotations. This method deals with a set of square matrices sharing a same eigenstructure. Several Jacobi-like methods exist already for solving the aforementioned problem. The differences reside in the way of estimating the Shear rotation. Herein, we clarify these differences, highlight the weaknesses of the existing solutions and develop a new robust method named Efficient and Stable Joint eigenvalue Decomposition (ESJD). Simulation results are provided to highlight the effectiveness of the proposed technique especially in difficult scenario.
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