The dictionary learning algorithm has been successfully applied to electronic noses
because of its high recognition rate. However, most dictionary learning algorithms use l0 …

Discriminative dictionary learning has been successfully applied in pattern recognition field.
In most of dictionary learning methods, ℓ 0-norm or ℓ 1-norm is used to regularize the sparse …

Rapid detection and identification of industrial gases is a challenging problem. They have a
complex composition and different specifications. This paper presents a method based on …

In this paper, an approach that can fast classify the data from the electronic nose is
presented. In this approach the gradient tree boosting algorithm is used to classify the gas …

Electronic nose is a kind of widely-used artificial olfactory system for the detection and
classification of volatile organic compounds. The high dimensionality of data collected by …

A novel sensor selection using pattern recognition technique in electronic nose (E-Nose) is
proposed in this paper. This paper studies the portable E-Nose based on metal oxide …

The sparse dictionary learning algorithm has extensive applications in various domains,
including electronic nose (EN) and pattern recognition. To address the challenges …

Electronic nose is the intelligent design to identify food flavors, cosmetics and different gas
odors, depending on sensors. The continuous developing of these sensors permit advanced …

As the acquisition unit of gas information, the sensor array directly determines the overall
performance of the electronic nose system (E-nose). This paper proposed a new method for …

Purpose The purpose of this paper is to design and validate an electronic nose (E-nose)
prototype using commercially available metal oxide gas sensors (MOX). This prototype has …