FPGA Implementation of WRVFLN for Classification

Abstract

Now-a-days, field programmable gate array (FPGA) is used in various domain of research to design a computer-aided-diagnosis (CAD) system to classify the data in real-time. In this paper, weighted random vector functional link network (WRVFLN) is presented and implemented on a fast FPGA hardware platform to classify the data. The WRVFLN classifier produces better data classification accuracy in comparison to other existing prevalent methods. The remarkable data classification accuracy and faster learning speed of the WRVFLN classifier facilitates the hardware implementation of WRVFLN classifier. Moreover, the developed digital architecture of WRVFLN classifier is employed on a Xilinx Virtex-5 (ML506) FPGA hardware environment, aid to construct an embedded system for real-time data classification.