Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1172
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dc.contributor.authorAbeygunawardhana, P. K. W-
dc.contributor.authorFujiwara, M-
dc.contributor.authorSuzuki, S-
dc.contributor.authorIshimaru, I-
dc.date.accessioned2022-02-15T04:28:06Z-
dc.date.available2022-02-15T04:28:06Z-
dc.date.issued2014-10-22-
dc.identifier.citationP. K. W. Abeygunawardhana, M. Fujiwara, S. Suzuki and I. Ishimaru, "Signal conditioning for imaging type Fourier spectroscopy using Independent Component Analysis," 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings, 2014, pp. 77-80, doi: 10.1109/BioCAS.2014.6981649.en_US
dc.identifier.issn2163-4025-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1172-
dc.description.abstractBiomedical Signal Processing, in which Spectroscopic measurement plays a crucial role, has been the center of attraction by many researchers during the past few years. Two - dimensional imaging type Fourier spectroscopy is a technique which can limit the measuring depth into focal plane. Although the various substances including bio genic substances can be measured, measured results include two or more signals mixed together. In this paper, Independent Component Analysis known as ICA has been used to separate those mixed signals.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings;Pages 77-80-
dc.subjectSignal conditioningen_US
dc.subjectimaging typeen_US
dc.subjectFourier spectroscopyen_US
dc.subjectIndependenten_US
dc.subjectComponent Analysisen_US
dc.subjectBiomedical signal processingen_US
dc.titleSignal conditioning for imaging type Fourier spectroscopy using Independent Component Analysisen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/BioCAS.2014.6981649en_US
Appears in Collections:Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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