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An MDL Algorithm for Detecting More Sources Than Sensors Using Outer-Products of Array Output

机译:一种使用阵列输出外积检测比传感器更多源的MDL算法

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摘要

In this paper, we propose an algorithm for detecting the number of Gaussian sources received by an array of a number () of sensors. This algorithm is based on the minimum description length (MDL) principle using the outer-products of the array output. We show that as long as the covariance matrix of the array output has the full rank , the covariance matrix of a vectorized outer-product of the array output has the full rank -squared, which meets a validity condition of the MDL algorithm. We show by simulation that the MDL algorithm can perform substantially better than some relevant algorithms. A necessary identifiability condition is also obtained, for uncorrelated sources.
机译:在本文中,我们提出了一种算法,用于检测由(多个)传感器阵列接收的高斯源数量。该算法基于最小描述长度(MDL)原理,使用数组输出的外部乘积。我们证明,只要数组输出的协方差矩阵具有满秩,则数组输出的矢量化外积的协方差矩阵具有满秩平方,就可以满足MDL算法的有效性条件。通过仿真显示,MDL算法的性能远好于某些相关算法。对于不相关的来源,还获得了必要的可识别性条件。

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