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Collaborative adaptive filtering approach for the identification of complex-valued improper signals

This paper proposes a novel hybrid filter for data-adaptive optimal identification and modeling of complex-valued real-world signals based on the convex combination approach. It is equipped with different complex domain characteristics of subfilter algorithm. The proposed hybrid filter takes advanta...

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Main Authors: Cyprian, Amadi Chukwuemena, Che Ujang, Che Ahmad Bukhari, Sali, Aduwati, Hashim, Fazirulhisyam
Format: Article
Language:English
Published: Birkhaeuser Science 2019
Online Access:http://psasir.upm.edu.my/id/eprint/80955/1/FILTERING.pdf
http://psasir.upm.edu.my/id/eprint/80955/
https://search.proquest.com/docview/2171093018/fulltextPDF/85873B3CEF9542A5PQ/1?accountid=27932
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spelling my.upm.eprints.809552020-10-14T19:46:12Z http://psasir.upm.edu.my/id/eprint/80955/ Collaborative adaptive filtering approach for the identification of complex-valued improper signals Cyprian, Amadi Chukwuemena Che Ujang, Che Ahmad Bukhari Sali, Aduwati Hashim, Fazirulhisyam This paper proposes a novel hybrid filter for data-adaptive optimal identification and modeling of complex-valued real-world signals based on the convex combination approach. It is equipped with different complex domain characteristics of subfilter algorithm. The proposed hybrid filter takes advantage of the complex nonlinear gradient descent (CNGD) algorithm that exhibits fast convergence and the steady state of the augmented complex nonlinear gradient descent (ACNGD) algorithm. The output of CNGD and ACNGD was combined to work in parallel, feeding each individual subfilter output into a mixing algorithm, which in the end produced a single hybrid filter output. The mixing parameter λ(k) within the hybrid filter architecture was made gradient adaptive in order to preserve the nature of inherent characteristics of the subfilters and to show its optimal performance in identifying and tracking second-order properness (circular) and improperness (noncircular) of the complex signals in real time. Further analysis was made on the properties of the algorithms, and the relationship between fast convergence and steady-state error was discussed. This analysis is supported by the complex-valued synthetic simulation and real-world application dataset as applied in renewable energy (wind). Birkhaeuser Science 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/80955/1/FILTERING.pdf Cyprian, Amadi Chukwuemena and Che Ujang, Che Ahmad Bukhari and Sali, Aduwati and Hashim, Fazirulhisyam (2019) Collaborative adaptive filtering approach for the identification of complex-valued improper signals. Circuits Systems and Signal Processing, 38 (8). pp. 3860-3879. ISSN 0278-081X; ESSN: 1531-5878 https://search.proquest.com/docview/2171093018/fulltextPDF/85873B3CEF9542A5PQ/1?accountid=27932 10.1007/s00034-019-01034-z
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This paper proposes a novel hybrid filter for data-adaptive optimal identification and modeling of complex-valued real-world signals based on the convex combination approach. It is equipped with different complex domain characteristics of subfilter algorithm. The proposed hybrid filter takes advantage of the complex nonlinear gradient descent (CNGD) algorithm that exhibits fast convergence and the steady state of the augmented complex nonlinear gradient descent (ACNGD) algorithm. The output of CNGD and ACNGD was combined to work in parallel, feeding each individual subfilter output into a mixing algorithm, which in the end produced a single hybrid filter output. The mixing parameter λ(k) within the hybrid filter architecture was made gradient adaptive in order to preserve the nature of inherent characteristics of the subfilters and to show its optimal performance in identifying and tracking second-order properness (circular) and improperness (noncircular) of the complex signals in real time. Further analysis was made on the properties of the algorithms, and the relationship between fast convergence and steady-state error was discussed. This analysis is supported by the complex-valued synthetic simulation and real-world application dataset as applied in renewable energy (wind).
format Article
author Cyprian, Amadi Chukwuemena
Che Ujang, Che Ahmad Bukhari
Sali, Aduwati
Hashim, Fazirulhisyam
spellingShingle Cyprian, Amadi Chukwuemena
Che Ujang, Che Ahmad Bukhari
Sali, Aduwati
Hashim, Fazirulhisyam
Collaborative adaptive filtering approach for the identification of complex-valued improper signals
author_facet Cyprian, Amadi Chukwuemena
Che Ujang, Che Ahmad Bukhari
Sali, Aduwati
Hashim, Fazirulhisyam
author_sort Cyprian, Amadi Chukwuemena
title Collaborative adaptive filtering approach for the identification of complex-valued improper signals
title_short Collaborative adaptive filtering approach for the identification of complex-valued improper signals
title_full Collaborative adaptive filtering approach for the identification of complex-valued improper signals
title_fullStr Collaborative adaptive filtering approach for the identification of complex-valued improper signals
title_full_unstemmed Collaborative adaptive filtering approach for the identification of complex-valued improper signals
title_sort collaborative adaptive filtering approach for the identification of complex-valued improper signals
publisher Birkhaeuser Science
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/80955/1/FILTERING.pdf
http://psasir.upm.edu.my/id/eprint/80955/
https://search.proquest.com/docview/2171093018/fulltextPDF/85873B3CEF9542A5PQ/1?accountid=27932
_version_ 1681490834415943680
score 13.211869

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