A comparative analysis of fuzzy ART neural network implementations: the advantages of reconfigurable computing

Abstract

The paper analyzes the performance differences found between software and hardware/sofware implementations of a reformulated fuzzy ART neural network algorithm. This reformulated algorithm is a solution for a real time radar signal clustering problem. The software implementations run on a 50 MHz TMS320C40 DSP, and the hardware/sofware implementation runs on the same DSP for its software part, whereas the FPGA based application specific hardware accelerator is realized on MiroTech's X-CIM TIM40 module. This investigation of FPGA based acceleration gave excellent results for our application: acceleration factors up to 68.9 have been reached.