document: Quasi-Newton algorithm for adaptive minor component extraction An adaptive quasi-Newton algorithm is first developed to extract a single minor component corresponding to the smallest eigenvalue of a stationary sample covariance matrix . A deflation technique instead of the commonly used inflation method is then applied to extract the higher-order minor components . The algorithm enjoys the advantage of having a simpler computational complexity and a highly modular and parallel structure for efficient implementation . Simulation results are given to demonstrate the effectiveness of the proposed algorithm for extracting multiple minor components adaptively
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