Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation

Adaptive filtering is an online signal processing application that is capable of estimating parameters for the characterization of a real time system. The estimation is done based on the mean-square error (MSE) minimization of the difference between some desired output and the output of the adaptiv...

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Main Author:	Cheah, Kah Wai
Format:	Thesis
Language:	English
Published:	2018
Subjects:	QA1-939 Mathematics
Online Access:	http://eprints.usm.my/43630/1/CHEAH%20KAH%20WAI.pdf
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id	my-usm-ep.43630
record_format	uketd_dc
spelling	my-usm-ep.436302019-04-12T05:24:51Z Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation 2018-04 Cheah, Kah Wai QA1-939 Mathematics Adaptive filtering is an online signal processing application that is capable of estimating parameters for the characterization of a real time system. The estimation is done based on the mean-square error (MSE) minimization of the difference between some desired output and the output of the adaptive filter. The unknown transfer function is assumed to be a known structure and is realized by three different structures which are commonly used in conventional adaptive filtering: (i) the finite-duration impulse response (FIR) filter, (ii) the infinite-duration impulse response (IIR) filter, and (iii) the nonlinear filter. 2018-04 Thesis http://eprints.usm.my/43630/ http://eprints.usm.my/43630/1/CHEAH%20KAH%20WAI.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Matematik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA1-939 Mathematics
spellingShingle	QA1-939 Mathematics Cheah, Kah Wai Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation
description	Adaptive filtering is an online signal processing application that is capable of estimating parameters for the characterization of a real time system. The estimation is done based on the mean-square error (MSE) minimization of the difference between some desired output and the output of the adaptive filter. The unknown transfer function is assumed to be a known structure and is realized by three different structures which are commonly used in conventional adaptive filtering: (i) the finite-duration impulse response (FIR) filter, (ii) the infinite-duration impulse response (IIR) filter, and (iii) the nonlinear filter.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Cheah, Kah Wai
author_facet	Cheah, Kah Wai
author_sort	Cheah, Kah Wai
title	Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation
title_short	Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation
title_full	Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation
title_fullStr	Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation
title_full_unstemmed	Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation
title_sort	reduced fuzzy recursive least-squares algorithm for real time estimation
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Matematik
publishDate	2018
url	http://eprints.usm.my/43630/1/CHEAH%20KAH%20WAI.pdf
_version_	1747821250596569088

Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation

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