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On quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering.

The strict Cauchy-Riemann-Fueter (CRF) analyticity conditions establish that only linear quaternion-valued functions are analytic, prohibiting the development of quaternion-valued nonlinear adaptive filters for the recurrent neural network architecture (RNN). In this work, the requirement of local...

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Main Authors: Che Ujang, Bukhari, Took, Clive Cheong, Mandic, Danilo P.
Format: Conference or Workshop Item
Language:English
English
Published: 2012
Online Access:http://psasir.upm.edu.my/id/eprint/31822/1/31822.pdf
http://psasir.upm.edu.my/id/eprint/31822/
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spelling my.upm.eprints.318222014-08-04T08:22:15Z http://psasir.upm.edu.my/id/eprint/31822/ On quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering. Che Ujang, Bukhari Took, Clive Cheong Mandic, Danilo P. The strict Cauchy-Riemann-Fueter (CRF) analyticity conditions establish that only linear quaternion-valued functions are analytic, prohibiting the development of quaternion-valued nonlinear adaptive filters for the recurrent neural network architecture (RNN). In this work, the requirement of local analyticity in gradient based learning is exercised and proposes to use the local analyticity condition (LAC) to introduce quaternion-valued nonlinear feedback adaptive filters. The introduced class of algorithms make full use of quaternion algebra and provide generic extensions of the corresponding real and complex solutions. Simulations in the prediction setting support the analysis presented. 2012 Conference or Workshop Item NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/31822/1/31822.pdf Che Ujang, Bukhari and Took, Clive Cheong and Mandic, Danilo P. (2012) On quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering. In: IEEE International Conference on Acoustics, Speech and Signal Processing , 25-31 Mar. 2012, Kyoto, Japan . (pp. 2117-2120). 10.1109/ICASSP.2012.6288329 English
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
English
description The strict Cauchy-Riemann-Fueter (CRF) analyticity conditions establish that only linear quaternion-valued functions are analytic, prohibiting the development of quaternion-valued nonlinear adaptive filters for the recurrent neural network architecture (RNN). In this work, the requirement of local analyticity in gradient based learning is exercised and proposes to use the local analyticity condition (LAC) to introduce quaternion-valued nonlinear feedback adaptive filters. The introduced class of algorithms make full use of quaternion algebra and provide generic extensions of the corresponding real and complex solutions. Simulations in the prediction setting support the analysis presented.
format Conference or Workshop Item
author Che Ujang, Bukhari
Took, Clive Cheong
Mandic, Danilo P.
spellingShingle Che Ujang, Bukhari
Took, Clive Cheong
Mandic, Danilo P.
On quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering.
author_facet Che Ujang, Bukhari
Took, Clive Cheong
Mandic, Danilo P.
author_sort Che Ujang, Bukhari
title On quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering.
title_short On quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering.
title_full On quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering.
title_fullStr On quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering.
title_full_unstemmed On quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering.
title_sort on quaternion analyticity : enabling quaternion-valued nonlinear adaptive filtering.
publishDate 2012
url http://psasir.upm.edu.my/id/eprint/31822/1/31822.pdf
http://psasir.upm.edu.my/id/eprint/31822/
_version_ 1643830433624883200
score 13.214268

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