Classification of Optical-Sensor Response Cues with a Bi-dimensional Wavelet-Transform Approach

被引:1
|
作者
Murguia, J. S. [1 ,2 ]
Vergara, A. [1 ]
Trincavelli, M. [1 ,3 ]
Vargas-Olmos, C. [2 ]
Huerta, R. [1 ]
机构
[1] Univ Calif San Diego, Bio Circuits Inst, San Diego, CA 92103 USA
[2] Autonoma San Luis Potosi, San Luis Potosi, Mexico
[3] Univ Orebro, AASS Res Ctr, Orebro, Sweden
关键词
Classification; Feature; extraction; Porous silicon optical gas sensor; Two-dimensional wavelet transform; Support vector machine;
D O I
10.1063/1.3626380
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In this work is used the two-dimensional discrete wavelet transform as a feature extractor of time responses from a porous silicon optical gas sensor for gas identification. The wavelet decomposition allows us to have a more in-deep sight of the sensor response. In addition, using a linear support vector machine (SVM) as classifier we evaluate our approach for a six-analyte discrimination problem.
引用
收藏
页码:255 / +
页数:2
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