Testing for impropriety of multivariate complex random processes
Testing for impropriety of multivariate complex random processes
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多元复杂随机过程的不当性测试
DOI：
10.1109/icassp.2016.7472481
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
S. Bhaskar
中科院分区：
文献类型：
--
作者：
Jitendra Tugnait;S. Bhaskar
我们考虑检验一个复值向量随机序列是否为正规（合适）的问题。以往关于这个问题的研究仅限于独立高斯随机向量序列，而我们允许可以是非高斯的任意平稳向量序列。我们制定了一种二元假设检验方法，并利用增广序列的功率谱密度估计量推导出了广义似然比检验（GLRT）。提供了一种用于计算检验阈值的渐近解析解。通过仿真对结果进行了说明。
We consider the problem of testing whether a complex-valued vector random sequence is proper. Past work on this problem is limited to a sequence of independent Gaussian random vectors whereas we allow an arbitrary stationary vector sequence that can be non-Gaussian. A binary hypothesis testing approach is formulated and a generalized likelihood ratio test (GLRT) is derived using the power spectral density estimator of an augmented sequence. An asymptotic analytical solution for calculating the test threshold is provided. The results are illustrated via simulations.