Nonlinear Feature Extraction Through Manifold Learning in an Electronic Tongue Classification Task

Nonlinear Feature Extraction Through Manifold Learning in an Electronic Tongue Classification Task

A nonlinear feature extraction-based approach using manifold learning algorithms is developed in order to improve the classification accuracy in an electronic tongue sensor array. The developed signal processing methodology is composed of four stages: data unfolding, scaling, feature extraction, and...

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Bibliographic Details
Main Authors: Jersson X. Leon-Medina, Maribel Anaya, Francesc Pozo, Diego Tibaduiza
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Sensors
Subjects:
manifold learning
feature extraction
classification
electronic tongue
machine learning
t-SNE
Online Access:https://www.mdpi.com/1424-8220/20/17/4834

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