On the study of feature extraction methods for an electronic nose

By C. Distante, M. Leo, P. Siciliano, K. C. Persaud. 2002

172 citations recorded by the source corpus.

Subfields: Bioengineering, Biomedical Engineering, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/b616d2e0d07a3dab21da51002f35634871a7af20

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Bioengineering

1. Agustin Gutierrez-Galvez
2. Santiago Marco

In Biomedical Engineering

1. Agustin Gutierrez-Galvez
2. Santiago Marco

In Spectroscopy

1. Agustin Gutierrez-Galvez
2. Santiago Marco

Citations in the corpus

• Signal and Data Processing for Machine Olfaction and Chemical Sensing: A Review (2012, methodology): “Among them, the Discrete Wavelet Transform for feature extraction has been frequently used since the late 90s [29],”
• Data analysis for electronic nose systems (2006, unknown): “[143–146].”
• Electronic Nose Feature Extraction Methods: A Review (2015, background): “The results showed that integral and derivatives methods have higher recognition rates than that of maximum values and they also concluded that the desorption stage is more informative than the adsorption stage of the original response curves [50].”