Hardware implementation of backpropagation algorithm based on CHEMFET sensor selectivity

Author

Abd Aziz, Norazreen ; Abdul Latif, Muhammad Al Kasyaf ; Abdullah, Wan Fazlida Hanim ; Md Tahir, Nooritawati ; Zolkapli, Maizatul

Author_Institution

Fac. of Electr. Eng., Univ. Teknol. MARA (UiTM), Shah Alam, Malaysia

fYear

2013

fDate

Nov. 29 2013-Dec. 1 2013

Firstpage

387

Lastpage

390

Abstract

In this study, modeling approach for interpretation of data logged from chemically field-effect transistor (CHEMFET) sensor is described. Firstly, backpropagation algorithm is used to train the proposed network by optimizing the parameters of the network. Then, by applying the optimized parameters obtained from the trained network, the feed forward neural network algorithm is implemented using C language for compatibility with 16-bit microcontroller board and the output is compared with the simulation output which has been simulated using MATLAB software. Initial findings showed that the neural the proposed method is able to provide excellence estimation of main ion concentration in mixed solution as well as capable to interpret and estimate the ion concentration in mixed solution.

Keywords

C language; backpropagation; electronic engineering computing; feedforward neural nets; ion sensitive field effect transistors; microcontrollers; 16-bit microcontroller board; C language; CHEMFET sensor selectivity; MATLAB software; backpropagation algorithm; chemically field-effect transistor; feedforward neural network algorithm; hardware implementation; ion concentration; Backpropagation algorithms; Conferences; Estimation; Feeds; Hardware; Microcontrollers; Neural networks; 16-bit microcontroller board; CHEMFET sensor; backpropagation algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Control System, Computing and Engineering (ICCSCE), 2013 IEEE International Conference on

Conference_Location

Mindeb

Print_ISBN

978-1-4799-1506-4

Type

conf

DOI

10.1109/ICCSCE.2013.6719995

Filename

6719995