Parallel Fixed Point Implementation of a Radial Basis Function Network in an FPGA

被引：21
|
作者：
de Souza, Alisson C. D. [1 ]
Fernandes, Marcelo A. C. [1 ]
机构：
[1] Fed Univ Rio Grande Norte UFRN, Dept Comp Engn & Automat, Ctr Technol, BR-59078970 Natal, RN, Brazil
来源：
SENSORS | 2014年 / 14卷 / 10期
关键词：
artificial neural network; ANN; radial basis function; RBF; FPGA; fixed point; Simulink; system generator; ARTIFICIAL NEURAL-NETWORKS;
D O I：
10.3390/s141018223
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
This paper proposes a parallel fixed point radial basis function (RBF) artificial neural network (ANN), implemented in a field programmable gate array (FPGA) trained online with a least mean square (LMS) algorithm. The processing time and occupied area were analyzed for various fixed point formats. The problems of precision of the ANN response for nonlinear classification using the XOR gate and interpolation using the sine function were also analyzed in a hardware implementation. The entire project was developed using the System Generator platform (Xilinx), with a Virtex-6 xc6vcx240t-1ff1156 as the target FPGA.
引用
收藏
页码：18223 / 18243
页数：21
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