An Optimized Easi Algorithm

Jimin Ye; Haihong Jin; Shuntian Lou; Kejun You

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An Optimized Easi Algorithm

机译：优化的Easi算法

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摘要

This paper addresses the problem of blind source separation and presents a kind of optimized equivariant adaptive separation via independence (EASI) algorithms. According to the cumulant based approximation to the mutual information contrast function, the EASI learning rule is optimized by multiplying the symmetric part with an optimal time variant weight coefficient. Simulation results show the proposed optimized EASI algorithms outperform the existing algorithms in convergent speed and steady-state accuracy.

机译：本文针对盲源分离问题，提出了一种通过独立算法（EASI）优化的等变自适应分离。根据对互信息对比函数的基于累积量的近似，通过将对称部分与最佳时变权重系数相乘来优化EASI学习规则。仿真结果表明，所提出的优化EASI算法在收敛速度和稳态精度上均优于现有算法。

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来源
《Signal processing》 |2009年第3期|333-338|共6页
作者
Jimin Ye; Haihong Jin; Shuntian Lou; Kejun You;
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正文语种 eng
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关键词
blind source separation; cumulant based approximation of contrast; function; easi algorithm;

机译：盲源分离;基于累积量的对比度逼近;函数;简单算法;

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4. Step-Size Optimization EASI Algorithm for Blind Source Separation [C] . Fu, Weihong, Yang, Computational Intelligence and Security (CIS), 2007 International Conference on . 2007

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An Optimized Easi Algorithm

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