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

Citation

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).

Abstract

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.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1109/ICASSP.2012.6288329
Notes:	Full text are available at Special Collection Division Office.
Keywords:	Nonlinear adaptive filtering; Recurrent neural networks; Quaternion analyticity; IIR filters; RTRL.
Depositing User:	Samsida Samsudin
Date Deposited:	04 Aug 2014 08:22
Last Modified:	04 Aug 2014 08:22
URI:	http://psasir.upm.edu.my/id/eprint/31822
Statistic Details:	View Download Statistic

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