Convergence Decision Method Using Eigenvectors of QR Iteration 


Vol. 41,  No. 8, pp. 868-876, Aug.  2016


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  Abstract

MUSIC (multiple signal classification) algorithm is a representative algorithm estimating the angle of arrival using the eigenvalues and eigenvectors. Generally, the eigenvalues and eigenvectors are obtained through the eigen-analysis, but this analysis requires high computational complexity and late convergence time. For this reason, it is almost impossible to construct the real-time system with low-cost using this approach. Even though QR iteration is considered as the eigen-analysis approach to improve these problems, this is inappropriate to apply to the MUSIC algorithm. In this paper, we analyze the problems of conventional method based on the eigenvalues for convergence decision and propose the improved decision algorithm using the eigenvectors.

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  Cite this article

[IEEE Style]

D. Kim, J. Lee, S. Jeong, J. Lee, Y. Kim, "Convergence Decision Method Using Eigenvectors of QR Iteration," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 8, pp. 868-876, 2016. DOI: .

[ACM Style]

Daehyun Kim, Jingu Lee, Seonghee Jeong, Jaeeun Lee, and Younglok Kim. 2016. Convergence Decision Method Using Eigenvectors of QR Iteration. The Journal of Korean Institute of Communications and Information Sciences, 41, 8, (2016), 868-876. DOI: .

[KICS Style]

Daehyun Kim, Jingu Lee, Seonghee Jeong, Jaeeun Lee, Younglok Kim, "Convergence Decision Method Using Eigenvectors of QR Iteration," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 8, pp. 868-876, 8. 2016.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880