Convergence Analysis of EFOP Estimate Based on Frequency Domain Smoothing

The classic methods for frequency domain transfer function estimation such as the Empirical Transfer Function Estimate (ETFE) and cross spectral method do not work well when the noise signal is complex. Combines the time domain and frequency domain methods the Empirical Frequency-domain Optimal Para...

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Main Authors: Yulai Zhang, Kueiming Lo, Yang Su
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2013/781856
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author Yulai Zhang
Kueiming Lo
Yang Su
author_facet Yulai Zhang
Kueiming Lo
Yang Su
author_sort Yulai Zhang
collection DOAJ
description The classic methods for frequency domain transfer function estimation such as the Empirical Transfer Function Estimate (ETFE) and cross spectral method do not work well when the noise signal is complex. Combines the time domain and frequency domain methods the Empirical Frequency-domain Optimal Parameter (EFOP) Estimate was presented. It could improve the precision of system's transfer function estimation and identification efficiency. The convergence of the EFOP based on frequency domain smoothing is investigated in this paper. The transfer function is weighted by a frequency window and the GPE criterion is extended to the integral form. Convergence rate and consistent properties for the EFOP estimate are given. Finally, some simulation results are included to illustrate the advantage of the EFOP based smoothing method.
format Article
id doaj-art-7ecad6d06fe341adada15dd3aa058b78
institution Kabale University
issn 1110-757X
1687-0042
language English
publishDate 2013-01-01
publisher Wiley
record_format Article
series Journal of Applied Mathematics
spelling doaj-art-7ecad6d06fe341adada15dd3aa058b782025-08-20T03:35:40ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/781856781856Convergence Analysis of EFOP Estimate Based on Frequency Domain SmoothingYulai Zhang0Kueiming Lo1Yang Su2School of Software, Tsinghua University, Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, ChinaSchool of Software, Tsinghua University, Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, ChinaSchool of Software, Tsinghua University, Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, ChinaThe classic methods for frequency domain transfer function estimation such as the Empirical Transfer Function Estimate (ETFE) and cross spectral method do not work well when the noise signal is complex. Combines the time domain and frequency domain methods the Empirical Frequency-domain Optimal Parameter (EFOP) Estimate was presented. It could improve the precision of system's transfer function estimation and identification efficiency. The convergence of the EFOP based on frequency domain smoothing is investigated in this paper. The transfer function is weighted by a frequency window and the GPE criterion is extended to the integral form. Convergence rate and consistent properties for the EFOP estimate are given. Finally, some simulation results are included to illustrate the advantage of the EFOP based smoothing method.http://dx.doi.org/10.1155/2013/781856
spellingShingle Yulai Zhang
Kueiming Lo
Yang Su
Convergence Analysis of EFOP Estimate Based on Frequency Domain Smoothing
Journal of Applied Mathematics
title Convergence Analysis of EFOP Estimate Based on Frequency Domain Smoothing
title_full Convergence Analysis of EFOP Estimate Based on Frequency Domain Smoothing
title_fullStr Convergence Analysis of EFOP Estimate Based on Frequency Domain Smoothing
title_full_unstemmed Convergence Analysis of EFOP Estimate Based on Frequency Domain Smoothing
title_short Convergence Analysis of EFOP Estimate Based on Frequency Domain Smoothing
title_sort convergence analysis of efop estimate based on frequency domain smoothing
url http://dx.doi.org/10.1155/2013/781856
work_keys_str_mv AT yulaizhang convergenceanalysisofefopestimatebasedonfrequencydomainsmoothing
AT kueiminglo convergenceanalysisofefopestimatebasedonfrequencydomainsmoothing
AT yangsu convergenceanalysisofefopestimatebasedonfrequencydomainsmoothing