FPGA implementation of neural network as processing element in ice detector

Author

Marouf, Mohamed ; Popovic-Bozovic, Jelena ; Popovic, Ivan

Author_Institution

Sch. of Electr. Eng., Univ. of Belgrade, Belgrade, Serbia

fYear

2012

fDate

20-22 Sept. 2012

Firstpage

81

Lastpage

84

Abstract

In this paper we propose usage of neural networks in the field of meteorology especially to detect ice formation on roads. Used algorithm for building and training network is based on the road and air conditions which define ice formation on road´s surface. The ability of self and supervised learning are both used to solve this problem. We used VHDL to build proposed neural network as a part of the ice detector. FPGA implementation of the neural network is done using Xilinx Spartan-3 device.

Keywords

field programmable gate arrays; hardware description languages; ice; learning (artificial intelligence); meteorology; neural nets; road safety; FPGA implementation; VHDL; Xilinx Spartan-3 device; air conditions; ice detector; ice formation detection; meteorology; neural network training; processing element; road conditions; road surface; self-learning; supervised learning; Field programmable gate arrays; Humidity; Ice; Neural networks; Neurons; Roads; Temperature distribution; FPGA implementation; Ice detection; Neural network; VHDL;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on

Conference_Location

Belgrade

Print_ISBN

978-1-4673-1569-2

Type

conf

DOI

10.1109/NEUREL.2012.6419970

Filename

6419970