Implementation of the RN Method on FPGA using Xilinx System Generator for Nonlinear System Regression

Abstract

In this paper, we propose a new approach aiming to ameliorate the performances of the regularization networks (RN) method and speed up its computation time. A considerable rapidity in totaling calculation time and high performance were accomplished through conveying difficult calculation charges to FPGA. Using Xilinx System Generator, a successful HW/SW Co-Design was constructed to accelerate the Gramian matrix computation. Experimental results involving two real data sets of Wiener-Hammerstein benchmark with process noise prove the efficiency of the approach. The implementation results demonstrate the efficiency of the heterogeneous architecture, presenting a speed-up factor of 40-50 orders of time, comparing to the CPU simulation.

Authors and Affiliations

Intissar SAYEHI, Okba TOUALI, T. Saidani, B. Bouallegue, Mohsen MACHHOUT

Keywords

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  • EP ID EP259539
  • DOI 10.14569/IJACSA.2017.080619
  • Views 103
  • Downloads 0

How To Cite

Intissar SAYEHI, Okba TOUALI, T. Saidani, B. Bouallegue, Mohsen MACHHOUT (2017). Implementation of the RN Method on FPGA using Xilinx System Generator for Nonlinear System Regression. International Journal of Advanced Computer Science & Applications, 8(6), 148-158. https://europub.co.uk/articles/-A-259539