Presentation 2005/9/9
Fast RLS Fourier Analyzers for Sinusoidal Signals in Noise
Yegui XIAO,
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Abstract(in English) Adaptive Fourier analyzers are used to estimate the coefficients of sine and cosine terms of noisy sinusoidal signals whose frequencies are usually assumed known a prior. The conventional recursive least square (RLS) Fourier analyzer provides 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. However, they require considerably less computations. Second, the performance of the proposed FRLS algorithms is analyzed in detail. Difference equations governing their dynamics as well as closed-form expressions for their steady-state mean square errors (MSE) are derived and compared with those of the LMS Fourier analyzer. Extensive simulations are provided to demonstrate the performance capabilities of the four FRLS and the original RLS algorithms, and the validity of the analytical findings.
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Keyword(in English) Adaptive Fourier analysis / RLS / Fast RLS / Performance analysis / Mean square error
Paper # SIP2005-81,SIS2005-30,SP2005-63
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Committee SIS
Conference Date 2005/9/9(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Fast RLS Fourier Analyzers for Sinusoidal Signals in Noise
Sub Title (in English)
Keyword(1) Adaptive Fourier analysis
Keyword(2) RLS
Keyword(3) Fast RLS
Keyword(4) Performance analysis
Keyword(5) Mean square error
1st Author's Name Yegui XIAO
1st Author's Affiliation Dept. of Management & Information Systems, Prefectural University of Hiroshima()
Date 2005/9/9
Paper # SIP2005-81,SIS2005-30,SP2005-63
Volume (vol) vol.105
Number (no) 294
Page pp.pp.-
#Pages 6
Date of Issue