Imperial College London
Portrait Picture

ProfessorDaniloMandic

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Machine Intelligence
 
 
 
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Contact

 

+44 (0)20 7594 6271d.mandic Website

 
 
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Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
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Location

 

813Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Enshaeifar:2016:10.1109/TNSRE.2016.2625039,
author = {Enshaeifar, S and Took, CC and Park, C and Mandic, DP},
doi = {10.1109/TNSRE.2016.2625039},
journal = {IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING},
pages = {1278--1286},
title = {Quaternion Common Spatial Patterns},
url = {http://dx.doi.org/10.1109/TNSRE.2016.2625039},
volume = {25},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - A novel quaternion-valued common spatial patterns (QCSP) algorithm is introduced to model co-channel coupling of multi-dimensional processes. To cater for the generality of quaternion-valued non-circular data, we propose a generalized QCSP (G-QCSP) which incorporates the information on power difference between the real and imaginary parts of data channels. As an application, we demonstrate how G-QCSP can be used to provide high classification rates, even at a signal-to-noise ratio (SNR) as low as -10 dB. To illustrate the usefulness of our method in EEG analysis, we employ G-QCSP to extract features for discriminating between imagery left and right hand movements. The classification accuracy using these features is 70%. Furthermore, the proposed method is used to distinguish between Parkinson's disease (PD) patients and healthy control subjects, providing an accuracy of 87%.
AU  - Enshaeifar,S
AU  - Took,CC
AU  - Park,C
AU  - Mandic,DP
DO  - 10.1109/TNSRE.2016.2625039
EP  - 1286
PY  - 2016///
SN  - 1534-4320
SP  - 1278
TI  - Quaternion Common Spatial Patterns
T2  - IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
UR  - http://dx.doi.org/10.1109/TNSRE.2016.2625039
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000407478000021&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/52165
VL  - 25
ER  -
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