Feature Extraction of Electronic Nose Signals Using QPSO-Based Multiple KFDA Signal Processing

The aim of this research was to enhance the classification accuracy of an electronic nose (E-nose) in different detecting applications. During the learning process of the E-nose to predict the types of different odors, the prediction accuracy was not quite satisfying because the raw features extract...

Descripción completa

Detalles Bibliográficos
Autores principales: Wen, Tailai, Yan, Jia, Huang, Daoyu, Lu, Kun, Deng, Changjian, Zeng, Tanyue, Yu, Song, He, Zhiyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855868/
https://www.ncbi.nlm.nih.gov/pubmed/29382146
http://dx.doi.org/10.3390/s18020388

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855868/
https://www.ncbi.nlm.nih.gov/pubmed/29382146
http://dx.doi.org/10.3390/s18020388

Ejemplares similares