NDLI: Feature selection with distinction sensitive learning vector quantisation and genetic algorithms

Content Provider	IEEE Xplore Digital Library
Author	Flotzinger, D. Pregenzer, M. Pfurtscheller, G.
Copyright Year	1994
Description	Author affiliation: Dept. of Med. Inf., Graz Univ. of Technol., Austria (Flotzinger, D.; Pregenzer, M.; Pfurtscheller, G.)
Abstract	Two feature selection methods, a distinction-sensitive learning vector quantizer (DSLVQ) and a genetic algorithm (GA) approach, are applied to multichannel electroencephalogram (EEG) patterns. It is shown how DSLVQ adjusts the influence of different input features according to their relevance for classification. Using a weighted distance function DSLVQ thereby performs feature selection along with classification. The results are compared with those of a GA which minimizes the number of features taken for classification while maximizing classification performance. The multichannel EEG patterns used in this paper stem from a study for the construction of a brain-computer interface, which is a system designed for handicapped persons to help them use their EEG for control of their environment. For such a system, reliable EEG classification, i.e. differentiation of several distinctive EEG patterns, is vital. In practice the number of electrodes for EEG recordings can be high (up to 56 and more) and different frequency bands and time intervals for each electrode can be used for classification simultaneously. This shows the importance of methods automatically selecting the most distinctive out of a number of available features.
Starting Page	3448
Ending Page	3451
File Size	322506
Page Count	4
File Format	PDF
ISBN	078031901X
DOI	10.1109/ICNN.1994.374888
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-06-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Genetic algorithms Electroencephalography Biological cells Biomedical informatics Electrodes Biomedical engineering Brain computer interfaces Control systems Frequency
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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