FPGA implementation of blind source separation using a novel ICA algorithm

Abstract

Independent Component Analysis (ICA) is considered as a powerful technique to separate individual sources, from a linear mixture of input sources. This has motivated the use of ICA for various consumer and medical applications. A novel Jacobian Matrix rotation based ICA for blind source separation is proposed in this paper. Hardware implementation of proposed ICA algorithm on a Xilinx Virtex-5 FPGA using System Generator Blocksets is proposed and the performance results are reported.