基于非线性预测方法的在线盲源提取算法

D. Mandic, A. Cichocki, U. Manmontri
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引用次数: 3

摘要

提出了一种基于梯度下降的瞬时混合信号在线盲源提取算法。该算法是在由提取和预测模块组成的结构中利用非线性自适应滤波器推导出来的。利用混合信号的可预测性,根据非线性自适应预测器的阶数提取源信号。为了提高基本算法的收敛性,在最小化后验预测误差的基础上进一步进行全局归一化。其次,对该算法进行了充分的自适应,以补偿其推导过程中的独立性和其他假设。给出了两个实例来说明算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An on-line algorithm for blind source extraction based on nonlinear prediction approach
A gradient descent based on-line algorithm for blind source extraction (BSE) of instantaneous signal mixtures is proposed. This algorithm is derived by utilising a nonlinear adaptive filter in a structure that consists of an extraction and prediction module. By exploiting the predictability property of a signal from the mixture, source signals are extracted based on the order of the nonlinear adaptive predictor. To improve the convergence of the basic algorithm, it is further globally normalised based on the minimisation of the a posteriori prediction error. Next, the algorithm is made fully adaptive to compensate for the independence and other assumptions in its derivation. Two examples are presented to illustrate the performance of the algorithms.
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