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首页> 外文期刊>EURASIP journal on advances in signal processing >False Alarm Rate Estimation for Information-Theoretic-Based Source Enumeration Methods
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False Alarm Rate Estimation for Information-Theoretic-Based Source Enumeration Methods

机译:基于信息论的源枚举方法的虚警率估计

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摘要

The Tracy-Widom distribution is used to determine the false alarm rate of information theoretic methods that statistically estimate the number of sources in a multichannel receiver input. The Tracy-Widom distribution is the limiting distribution for the largest eigenvalue of a covariance matrix having a central white Wishart distribution. Such covariance matrices are produced by the output of multi-channel receivers whose signals can he characterized as zero-mean Gaussian processes. The Tracy-Widom distribution is used to estimate the false alarm rate of the Akaike Information Criterion and Minimum Description Length methods when no external sources are present. The Tracy-Widom distribution along with the eigenvalue inclusion principle is used to obtain an upper bound on the false alarm rate of the Akaike Information Criterion and Minimum Description Length when one external source is present. Monte-Carlo simulations were performed to demonstrate the effectiveness of both methods for cases where both the array and data sample sizes are small.
机译:Tracy-Widom分布用于确定信息理论方法的误报率,该信息理论方法统计地估计多通道接收器输入中的源数。 Tracy-Widom分布是具有中心白色Wishart分布的协方差矩阵的最大特征值的极限分布。这样的协方差矩阵是由多通道接收器的输出产生的,这些信号的信号可以表示为零均值高斯过程。如果没有外部来源,则使用Tracy-Widom分布估计Akaike信息准则和最小描述长度方法的误报率。当存在一个外部源时,使用Tracy-Widom分布以及特征值包含原理来获取Akaike信息准则和最小描述长度的误报率的上限。进行了蒙特卡洛模拟,以证明这两种方法在阵列和数据样本量均较小的情况下的有效性。

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