A hybrid system based on information gain and principal component analysis for the classification of transcranial Doppler signals
- Author
- UGUZ, Harun1
[1] Department of Computer Engineering, Selçuk University, Konya, Turkey - Source
Computer methods and programs in biomedicine (Print). 2012, Vol 107, Num 3, pp 598-609, 12 p ; ref : 49 ref
- ISSN
- 0169-2607
- Scientific domain
- Biomedical engineering; Computer science
- Publisher
- Elsevier, Kidlington
- Publication country
- United Kingdom
- Document type
- Article
- Language
- English
- Author keyword
- Discrete wavelet transform Feature selection Information gain Principal component analysis Support vector machine
- Keyword (fr)
- Analyse composante principale Dopplérométrie Génie biomédical
- Keyword (en)
- Principal component analysis Doppler ultrasound study Biomedical engineering
- Keyword (es)
- Análisis componente principal Dopplerometría Ingeniería biomédica
- Classification
- Pascal
- 002 Biological and medical sciences / 002B Medical sciences / 002B26 Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects) / 002B26N Technology. Biomaterials. Equipments. Material. Instrumentation
- Discipline
- Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, speech therapy, crenotherapy. Dietary management and various treatments
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 26163668
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1016/j.cmpb.2011.03.013 
https://dx.doi.org/10.1016/j.cmpb.2011.03.013
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