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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/7316
Title: EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms
Authors: Ahirwal M.K.
Kumar A.
Singh, Girish Kumar
Published in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Abstract: This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively. © 2013 IEEE.
Citation: IEEE/ACM Transactions on Computational Biology and Bioinformatics (2013), 10(6): 1491-1504
URI: https://doi.org/10.1109/TCBB.2013.119
http://repository.iitr.ac.in/handle/123456789/7316
Issue Date: 2013
Keywords: ABC
Adaptive noise canceler
COA
EEG/ERP
Evolutionary techniques
PSO
ISSN: 15455963
Author Scopus IDs: 49361053400
57215268681
57193351909
Author Affiliations: Ahirwal, M.K., PanditDwarka Prasad Mishra Indian Institute of Information Technology, Design and Manufacturing Jabalpur, Dumna Airport Road, Khamaria, Jabalpur, Madhya Pradesh 482005, India
Kumar, A., PanditDwarka Prasad Mishra Indian Institute of Information Technology, Design and Manufacturing Jabalpur, Dumna Airport Road, Khamaria, Jabalpur, Madhya Pradesh 482005, India
Singh, G.K., Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
Corresponding Author: PanditDwarka Prasad Mishra Indian Institute of Information Technology, Design and Manufacturing Jabalpur, Dumna Airport Road, Khamaria, Jabalpur, Madhya Pradesh 482005, India
Appears in Collections:Journal Publications [EE]

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