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Adaptive Quasi-Newton Algorithm for Source Extraction via CCA Approach | IEEE Journals & Magazine | IEEE Xplore
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Adaptive Quasi-Newton Algorithm for Source Extraction via CCA Approach


Abstract:

This paper addresses the problem of adaptive source extraction via the canonical correlation analysis (CCA) approach. Based on Liu's analysis of CCA approach, we propose ...Show More

Abstract:

This paper addresses the problem of adaptive source extraction via the canonical correlation analysis (CCA) approach. Based on Liu's analysis of CCA approach, we propose a new criterion for source extraction, which is proved to be equivalent to the CCA criterion. Then, a fast and efficient online algorithm using quasi-Newton iteration is developed. The stability of the algorithm is also analyzed using Lyapunov's method, which shows that the proposed algorithm asymptotically converges to the global minimum of the criterion. Simulation results are presented to prove our theoretical analysis and demonstrate the merits of the proposed algorithm in terms of convergence speed and successful rate for source extraction.
Page(s): 677 - 689
Date of Publication: 16 September 2013

ISSN Information:

PubMed ID: 24807946

Funding Agency:


References

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