DocumentCode :
2552866
Title :
Why a Complex Valued Solution for a Real Domain Problem
Author :
Mandic, Danilo P. ; Javidi, Soroush ; Souretis, George ; Goh, Vanessa S L
Author_Institution :
Imperial Coll., London
fYear :
2007
fDate :
27-29 Aug. 2007
Firstpage :
384
Lastpage :
389
Abstract :
An insight into the potential benefits of using complex valued models for real valued data is provided. The problem itself is not new; it is however timely and important to revisit this issue, due to a plethora of modern applications based on multidimensional and multichannel measurements which can be cast into an equivalent problem in the field of complex numbers C. The analysis and simulations highlight the duality between several classes of real domain problems and their complex valued representations. This is supported by case studies on image processing, modelling of point processes for brain prosthetics, and forecasting of vector fields.
Keywords :
signal processing; brain prosthetics; complex valued solution; image processing; multichannel measurement; multidimensional measurement; point processes modelling; real domain problem; real valued data; vector field forecasting; Biomedical measurements; Brain modeling; Data engineering; Educational institutions; Image processing; Machine learning; Multidimensional systems; Predictive models; Radar; Sonar;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing, 2007 IEEE Workshop on
Conference_Location :
Thessaloniki
ISSN :
1551-2541
Print_ISBN :
978-1-4244-1566-3
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2007.4414337
Filename :
4414337
Link To Document :
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