首页> 外文会议>Statistical Signal Processing, 2003 IEEE Workshop on >Blind separation and deconvolution of MIMO-FIR system with colored sound inputs using SIMO-model-based ICA
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Blind separation and deconvolution of MIMO-FIR system with colored sound inputs using SIMO-model-based ICA

机译:使用基于SIMO模型的ICA对带有彩色声音输入的MIMO-FIR系统进行盲分离和反卷积

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We propose a new two-stage blind separation and deconvolution algorithm for multiple-input multiple-output (MIMO)-FIR system driven by colored sound sources, in which a new single-input multiple-output (SIMO)-model-based ICA (SIMO-ICA) and blind multichannel inverse filtering are combined. SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources. After SIMO-ICA, a simple blind deconvolution technique for the SIMO model can be applied even when each source signal is temporally correlated. The simulation results reveal that the proposed algorithm can successfully achieve the separation and deconvolution for a convolutive mixture of speech.
机译:我们为有色声源驱动的多输入多输出(MIMO)-FIR系统提出了一种新的两阶段盲分离和反卷积算法,其中基于新的单输入多输出(SIMO)模型的ICA( SIMO-ICA)和盲多通道逆滤波相结合。 SIMO-ICA可以将混合信号分离为非单声道信号源,而可以分离为来自独立信号源的基于SIMO模型的信号。在SIMO-ICA之后,即使每个源信号在时间上相关,也可以为SIMO模型应用简单的盲反卷积技术。仿真结果表明,所提出的算法可以成功实现卷积语音混合的分离和反卷积。

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