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Proceedings Paper

Fast RLS Fourier analyzers for sinusoidal signals in noise and application
Author(s): Yegui Xiao; Liying Ma; Akira Ikuta
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Paper Abstract

The conventional recursive least square (RLS) Fourier analyzer enjoys excellent performance, but is computationally very intensive. In this paper, we first propose four fast RLS (FRLS) algorithms by utilizing the inherent characteristics of the estimation problem. The four new FRLS algorithms show almost the same performance and indicate estimation capabilities that are very similar to those of the original RLS, but require considerably less computations. Performance of the proposed FRLS algorithms is then analyzed in detail. Difference equations governing their dynamics as well as closed-form expressions for their steady-state mean squared errors (MSE) are derived and compared with those of the LMS Fourier analyzer. Extensive simulations as well as application to real noise signals are provided to demonstrate the validity of the analytical findings and the effectiveness of the proposed algorithms, respectively.

Paper Details

Date Published: 24 October 2006
PDF: 5 pages
Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63571O (24 October 2006); doi: 10.1117/12.716991
Show Author Affiliations
Yegui Xiao, Prefectural Univ. of Hiroshima (Japan)
Liying Ma, Tokyo Polytechnic Univ. (Japan)
Akira Ikuta, Prefectural Univ. of Hiroshima (Japan)


Published in SPIE Proceedings Vol. 6357:
Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence
Jiancheng Fang; Zhongyu Wang, Editor(s)

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