Eigenvalue Decomposition of a Parahermitian Matrix: Extraction of Analytic Eigenvalues

An analytic parahermitian matrix admits an eigenvalue decomposition (EVD) with eigenvalues and eigenvectors except in the case of multiplexed data. In this paper, we propose iterative algorithm for estimation eigenvalues. Since these are generally transcendental, find a polynomial approximation defined error. Our approach operates discrete Fourier transform (DFT) domain every DFT length generates maximally smooth association through EVDs evaluated bins; outer loop iteratively grows order is shown, general, to converge simulations, compare our results existing approaches.