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一种前馈结构的卷积混合盲分离算法
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2009-06-11
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1998年，Torkkola提出了反馈分离结构的信息最大化算法，该算法对应于稳定的IIR滤波器，只能用于最小相位混合。而真实的环境往往包括非最小相位传输系统。本文在分析反馈分离算法的基础上，提出了一种在频域上用前馈结构的信息最大化算法，该算法对应于非因果FIR滤波器，为非最小相位系统的盲分离问题提供了一个解决方案。最后，我们将演示用这种方法分离实际环境下的两个自然信号。
关键词:盲源分离(BSS);信息最大化;卷积混合;自然梯度
Abstract: In 1998 , Torkkola gave information maximization rules of a feedback architecture which can only separate minimum phase mixtures,though working well on simulated data,they fail in real environment which usually involve non-minimum phase transfer systems. This paper analyses the rules of the feedback architecture and presents an informax maxization algorithm of a feedforward architecture in the frequency domain which corresponds to a non-causal FIR.The new algorithm can solve the non-minimum phase mixing problem well.At last, simulation experiments will prove that two natural signals in a real environment can be separated successfully.
Keywords: blind source separation(BSS); information maximization; convolved mixtures;
natural gradient
关键词:盲源分离(BSS);信息最大化;卷积混合;自然梯度
Abstract: In 1998 , Torkkola gave information maximization rules of a feedback architecture which can only separate minimum phase mixtures,though working well on simulated data,they fail in real environment which usually involve non-minimum phase transfer systems. This paper analyses the rules of the feedback architecture and presents an informax maxization algorithm of a feedforward architecture in the frequency domain which corresponds to a non-causal FIR.The new algorithm can solve the non-minimum phase mixing problem well.At last, simulation experiments will prove that two natural signals in a real environment can be separated successfully.
Keywords: blind source separation(BSS); information maximization; convolved mixtures;
natural gradient
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