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FPGA implementation of blind source separation using a novel ICA algorithm

机译:FPGA使用新颖的ICA算法实现盲源分离

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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.
机译:独立分量分析(ICA)被认为是将个体源分离的强大技术,从输入源的线性混合中分离。这有动力使用ICA进行各种消费者和医疗应用。本文提出了一种基于Jacobian基质旋转的基于盲源分离的ICA。提出了使用系统发生器块块的Xilinx Virtex-5 FPGA上提出的ICA算法的硬件实现,并报告了性能结果。

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