DocumentCode :
1910022
Title :
FPGA implementation of neural network for linearization of thermistor characteristics
Author :
Sonowa, Durlav ; Bhuyan, Manabendra
Author_Institution :
Dept. of Electron. & Commun. Eng., Tezpur Univ., Tezpur, India
fYear :
2012
fDate :
15-16 March 2012
Firstpage :
422
Lastpage :
426
Abstract :
This paper presents an FPGA (Field Programmable Gate Array) implementation of an artificial neural network (ANN) for linearization of nonlinear characteristics of a thermistor. A feed forward ANN is used for linearization. The network is trained in MATLAB with back propagation algorithm; weights and biases are determined and then implemented in Spartan-III FPGA. Subroutines are developed for single precision floating point arithmetic in IEEE-754 format.
Keywords :
IEEE standards; backpropagation; electronic engineering computing; feedforward neural nets; field programmable gate arrays; floating point arithmetic; mathematics computing; thermistors; IEEE-754 format; MATLAB; Spartan-Ill FPGA; artificial neural network; backpropagation algorithm; biases; feedforward ANN; field programmable gate array; nonlinear characteristics; single precision floating point arithmetic; thermistor characteristics linearization; weights; Algorithms; Artificial neural networks; Backpropagation; Field programmable gate arrays; Neurons; Silicon; Table lookup; FPGA implementation of ANN; Floating Point FPGA; Sensor linearization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Devices, Circuits and Systems (ICDCS), 2012 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4577-1545-7
Type :
conf
DOI :
10.1109/ICDCSyst.2012.6188753
Filename :
6188753
Link To Document :
بازگشت