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Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine
Sensor drift is a common issue in E-Nose systems and various drift compensation methods have received fruitful results in recent years. Although the accuracy for recognizing diverse gases under drift conditions has been largely enhanced, few of these methods considered online processing scenarios. I...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876707/ https://www.ncbi.nlm.nih.gov/pubmed/29494543 http://dx.doi.org/10.3390/s18030742 |