Optimized FPGA Implementation of ICA Based on Negentropy Maximation
Independent component analysis (ICA) is a technique which is used to separate mixed signals.This paper presents an ICA implementation on FPGA utilizing negentropy maximization criteria for updating un-mixing weighting vector.We use this method to separate 4-channel comparatively fast mixed communication signals at the receiver.And before ICA processing,the mixed signals are often required whitening to achieve a better separating performance.We optimized the architectures of whitening and weighting vector updating modules respectively to balance the hardware resource consumption and calculation precision and speed.The performances are evaluated on Xilinx Spartan6 using simulation tool ISim and analysis is presented at the end of this paper.
ICA negentropy whiten cyclic Jacobi FPGA
Ran Tang Hong Wu Yunsong Pak Yong Liu Qiqi Wang Yingxin Zhao
Tianjin Key Laboratory of Photonics Materials and Technology for Information Science, College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, China
国际会议
秦皇岛
英文
551-555
2015-09-18（万方平台首次上网日期，不代表论文的发表时间）