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Source Localization and Room Mapping Using Information Derived from Independent Component Analysis

机译:使用独立成分分析中的信息进行源代码本地化和房间映射

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Convolutive independent component analysis (ICA) algorithms, which have proven capable at separating convolutively mixed signals, can also provide information about the geometry of the setting. This geometry includes source location information and wall locations (room shape). From the multi-input/multi-output impulse responses learned from convolutive ICA, peaks indicating direct path or reflection delays are extracted. The location of sensors (or sources) is obtained using hyperbolic geometry based on direct path time delays. Delays from reflected paths learned from the impulses responses correspond geometrically to ellipses that are tangent at the reflecting point. Ellipse tangent directions are clustered to determine wall locations. Following a summary of the method, experiments are presented on actual room measurements.
机译:卷积独立分量分析(ICA)算法已被证明能够分离出卷积混合信号,也可以提供有关设置的几何信息。此几何形状包括源位置信息和墙位置(房间形状)。从从卷积ICA获悉的多输入/多输出脉冲响应中,提取出指示直接路径或反射延迟的峰值。传感器(或源)的位置是使用双曲线几何基于直接路径时间延迟获得的。从脉冲响应学到的反射路径的延迟在几何上对应于在反射点切线的椭圆。聚集椭圆切线方向以确定墙的位置。在对该方法进行了总结之后,我们将对实际房间进行实验。

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