Cited 8 time in webofscience Cited 8 time in scopus

An efficient GP approach to recognizing cognitive tasks from fNIRS neural signals

Title
An efficient GP approach to recognizing cognitive tasks from fNIRS neural signals
Authors
An, Jin UngLee, JongHyunAhn, ChangWook
DGIST Authors
An, Jin Ung
Issue Date
2013-10
Citation
Science China: Information Sciences, 56(10)
Type
Article
Article Type
Article
Keywords
ClassificationClassification (of Information)Cognitive TaskDestructive ProcessfNIRSForestryFunctional NeuroimagingGenetic ProgrammingInformation RetrievalMathematicsMulti-Class ProblemsMulti-Tree RepresentationNeural SignalsNon-StationarySub TreesTreesTrees (Mathematics)
ISSN
1674-733X
Abstract
This paper presents a new genetic programming (GP) approach to accurately classifying cognitive tasks from non-stationary and noisy fNIRS neural signals. To this end, a new GP that effectively handles multiclass problems is developed. In accordance with multi-tree structure, GP operators are innovated: crossover exchanges every subtree of parents without suffering from any incongruity problem and mutation fine-tunes candidate solutions by a less destructive process. Experimental results verifies the effectiveness of the proposed GP classifier over existing references. © 2013 Science China Press and Springer-Verlag Berlin Heidelberg.
URI
http://hdl.handle.net/20.500.11750/1602
DOI
10.1007/s11432-013-5001-8
Publisher
SCIENCE PRESS
Related Researcher
Files:
There are no files associated with this item.
Collection:
ETC1. Journal Articles


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