Canonical correlation analysis with neural network for inter subject variability realization of EEG data

Md Zakir Hossain; Md Jubayer Alam Rabin; A. F.M.Nokib Uddin; Md Shahjahan

doi:10.1109/ICIEV.2013.6572711

Canonical correlation analysis with neural network for inter subject variability realization of EEG data

Md Zakir Hossain, Md Jubayer Alam Rabin, A. F.M.Nokib Uddin, Md Shahjahan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

The detection of brain condition under different subjects is utmost important and it is a challenging task. EEG signals are such data that need to carefully analyze when it consists of series of different subjects. This paper explores the application of canonical correlation analysis with artificial neural networks for EEG data sets with different subjects and reference. We demonstrate the network's capabilities on EEG data to determine their subject to subject dependency in terms of correlation and then compare its effectiveness with that of a sine-cosine reference signals.

Original language	English
Title of host publication	2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013
DOIs	https://doi.org/10.1109/ICIEV.2013.6572711
Publication status	Published - 2013
Externally published	Yes
Event	2013 2nd International Conference on Informatics, Electronics and Vision, ICIEV 2013 - Dhaka, Bangladesh Duration: 17 May 2013 → 18 May 2013

Publication series

Name	2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013

Conference

Conference	2013 2nd International Conference on Informatics, Electronics and Vision, ICIEV 2013
Country/Territory	Bangladesh
City	Dhaka
Period	17/05/13 → 18/05/13

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10.1109/ICIEV.2013.6572711

Cite this

Hossain, M. Z., Rabin, M. J. A., Uddin, A. F. M. N., & Shahjahan, M. (2013). Canonical correlation analysis with neural network for inter subject variability realization of EEG data. In 2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013 Article 6572711 (2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013). https://doi.org/10.1109/ICIEV.2013.6572711

@inproceedings{a8009853c2df429891d8457bb5b7ca8d,

title = "Canonical correlation analysis with neural network for inter subject variability realization of EEG data",

abstract = "The detection of brain condition under different subjects is utmost important and it is a challenging task. EEG signals are such data that need to carefully analyze when it consists of series of different subjects. This paper explores the application of canonical correlation analysis with artificial neural networks for EEG data sets with different subjects and reference. We demonstrate the network's capabilities on EEG data to determine their subject to subject dependency in terms of correlation and then compare its effectiveness with that of a sine-cosine reference signals.",

keywords = "Artificial Neural Networks (ANN), Canonical Correlation Analysis (CCA), Electroencephalogram (EEG), Variability",

author = "Hossain, {Md Zakir} and Rabin, {Md Jubayer Alam} and Uddin, {A. F.M.Nokib} and Md Shahjahan",

year = "2013",

doi = "10.1109/ICIEV.2013.6572711",

language = "English",

isbn = "9781479903979",

series = "2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013",

booktitle = "2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013",

note = "2013 2nd International Conference on Informatics, Electronics and Vision, ICIEV 2013 ; Conference date: 17-05-2013 Through 18-05-2013",

}

Hossain, MZ, Rabin, MJA, Uddin, AFMN & Shahjahan, M 2013, Canonical correlation analysis with neural network for inter subject variability realization of EEG data. in 2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013., 6572711, 2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013, 2013 2nd International Conference on Informatics, Electronics and Vision, ICIEV 2013, Dhaka, Bangladesh, 17/05/13. https://doi.org/10.1109/ICIEV.2013.6572711

Canonical correlation analysis with neural network for inter subject variability realization of EEG data. / Hossain, Md Zakir; Rabin, Md Jubayer Alam; Uddin, A. F.M.Nokib et al.
2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013. 2013. 6572711 (2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Canonical correlation analysis with neural network for inter subject variability realization of EEG data

AU - Hossain, Md Zakir

AU - Rabin, Md Jubayer Alam

AU - Uddin, A. F.M.Nokib

AU - Shahjahan, Md

PY - 2013

Y1 - 2013

N2 - The detection of brain condition under different subjects is utmost important and it is a challenging task. EEG signals are such data that need to carefully analyze when it consists of series of different subjects. This paper explores the application of canonical correlation analysis with artificial neural networks for EEG data sets with different subjects and reference. We demonstrate the network's capabilities on EEG data to determine their subject to subject dependency in terms of correlation and then compare its effectiveness with that of a sine-cosine reference signals.

AB - The detection of brain condition under different subjects is utmost important and it is a challenging task. EEG signals are such data that need to carefully analyze when it consists of series of different subjects. This paper explores the application of canonical correlation analysis with artificial neural networks for EEG data sets with different subjects and reference. We demonstrate the network's capabilities on EEG data to determine their subject to subject dependency in terms of correlation and then compare its effectiveness with that of a sine-cosine reference signals.

KW - Artificial Neural Networks (ANN)

KW - Canonical Correlation Analysis (CCA)

KW - Electroencephalogram (EEG)

KW - Variability

UR - http://www.scopus.com/inward/record.url?scp=84883335135&partnerID=8YFLogxK

U2 - 10.1109/ICIEV.2013.6572711

DO - 10.1109/ICIEV.2013.6572711

M3 - Conference contribution

SN - 9781479903979

T3 - 2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013

BT - 2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013

T2 - 2013 2nd International Conference on Informatics, Electronics and Vision, ICIEV 2013

Y2 - 17 May 2013 through 18 May 2013

ER -

Hossain MZ, Rabin MJA, Uddin AFMN, Shahjahan M. Canonical correlation analysis with neural network for inter subject variability realization of EEG data. In 2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013. 2013. 6572711. (2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013). doi: 10.1109/ICIEV.2013.6572711

Canonical correlation analysis with neural network for inter subject variability realization of EEG data

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