ÇAVUŞLU, Mehmet Ali Y-Vizyon Sinyalizasyon Tic. Ltd. Şti, Turkey , KARAKUZU, Cihan Bilecik Üniversitesi, Gülümbe Yerleşkesi - Mühendislik Fakültesi - Bilgisayar Müh Böl, Turkey , ŞAHİN, Suhap Kocaeli Üniversitesi, Umuttepe Yerleşkesi - Mühendislik Fakültesi - Bilgisayar Müh Böl, Turkey

Hardware Implementation of Artificial Neural Network Training Using Particle Swarm Optimization on FPGA

15693

In this study, a new ANN training approximation on FPGA is presented using parallel processes according to the nature of ANN. Training is implemented on FPGA using particle swarm optimization (PSO) stochastic search algorithm which does not need any derivative information. All related parameter values and processes are defined with IEEE 754 floating point numbers format. Proposed approach has been realized on Altera EP2C35F672C6 FPGA based on a sample ANN architecture using VHDL language. Obtained results show that proposed approach has successfully achieved ANN training.

83

ANN training , PSO , FPGA , Floating point number

Journal Of Polytechnic

92