Description: Structured covariance estimation. The routine takes a covariance matrix as input and returns the Toeplitz matrix that lies closest to it, in the sense that it minimizes the Kullback-Leibler divergence between the two. Input must be a real, square, symmetric and positive semi-definite matrix.
- [arrival_angle_estimator] - The angles in degrees of the two spatial
- [kldiv] - KLDIV Kullback-Leibler or Jensen-Shannon
- [MLE] - 3 books about distance function and Maxi
- [toeplitz] - Toeplitz matrix and levinson algorithm
- [tff_a] - HDL example source code 1/5 tff_a
- [APM_Test] - Is used to automatically measure your op
File list (Check if you may need any files):
strcov.m
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