From the theorem, the algorithm introduced in  can be perfected by doing eigenvalue decomposition
once, and is not further mentioned.
2) GED algorithm: In , the BSS was formulated as a generalized eigenvalue decomposition
(GED) problem, when the signals are non-gaussian, non stationary or non-white.
We remark that L+kI has the eigenvalue decomposition
Smadi, "Low complexity and high accuracy angle of arrival estimation using eigenvalue decomposition
with extension to 2D AOA and power estimation," EURASIP Journal on Wireless Communications and Networking, vol.
Meanwhile, the possibility of fusing these two attractive optimized methods is certain: rank revealing QR factorization with eigenvalue decomposition
from Xu et al.'s algorithm  and orthogonal gradient descent approach from Tian et al.'s algorithm  to obtain a new optimized method to overcome the computational complexity.
Then MATLAB code is developed to realize the model integration and complex eigenvalue decomposition
algorithm in this paper.
Without eigenvalue decomposition
and matrix inversion, the computational load of TDCM is the lowest.
After the eigenvalue decomposition
of S, N eigenvalues [[lambda].sub.0], [[lambda].sub.1],..., [[lambda].sub.n-1] and corresponding eigenvectors [v.sub.0], [v.sub.1], ..., [v.sub.N-1] can be calculated.
Similar to Section 3.1, 19) can be considered as a generalized eigenvalue decomposition
The MPM algorithm requires neither spectral searching nor covariance matrix estimation and its eigenvalue decomposition
, which can reduce the computational load.
Equation (3) is known as eigenvalue decomposition
or matrix similarity transform [2, 14].
One of the main drawbacks of GLRAM is that one eigenvalue decomposition
is required at each iteration step.