DocumentCode :
134541
Title :
Implementation of nonlinear blind source separation for CHEMFET sensor arrays
Author :
Bt Abd Aziz, Nurhakimah ; Abdullah, Wan Fazlida Hanim ; Md Tahir, Nooritawati
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol. MARA (UiTM), Shah Alam, Malaysia
fYear :
2014
fDate :
7-9 March 2014
Firstpage :
238
Lastpage :
241
Abstract :
In this study, a method to improve selectivity of chemically field-effect transistor (CHEMFET) sensor towards the main ion concentration in mixed solution is discussed. The approach is based on artificial neural network (ANN) as a post processing stage that performs the estimation of ion concentration in a mixed solution. CHEMFET sensor is viewed as non-linear model producing signal fed to blind-source separation algorithm. To describe how the ions interfere with main ion, the source signal of CHEMFET sensor is generated based on CHEMFET model. The sensor response is converted to frequency by using voltage to frequency converter (VFC). Simulation results confirm that the algorithm is able to separate the mixing signal.
Keywords :
blind source separation; ion sensitive field effect transistors; neural nets; voltage-frequency convertors; CHEMFET model; CHEMFET sensor arrays; artificial neural network; chemically field-effect transistor sensor; ion concentration; mixed solution; nonlinear blind source separation; nonlinear model; sensor response; source signal; voltage to frequency converter; Blind source separation; Equations; Independent component analysis; Ions; Mathematical model; Signal processing algorithms; BSS; CHEMFET sensor; non-linear mixture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing & its Applications (CSPA), 2014 IEEE 10th International Colloquium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4799-3090-6
Type :
conf
DOI :
10.1109/CSPA.2014.6805756
Filename :
6805756
Link To Document :
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