A Widely Linear Complex Autoregressive Process of Order One
A Widely Linear Complex Autoregressive Process of Order One
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DOI：
10.1109/tsp.2016.2599503
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发表时间：
2015-11
影响因子：
5.4
通讯作者：
A. Sykulski;S. Olhede;J. Lilly
中科院分区：
文献类型：
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作者：
A. Sykulski;S. Olhede;J. Lilly
我们提出了一个简单的随机过程建模不当或非圆形复值信号。该过程是复值自回归过程的自然扩展，扩展到包括广泛的线性自回归项。然后，该过程可以捕获双变量信号中的椭圆随机振荡，而不是圆形随机振荡。该过程是为了一个，是更吝啬比其他随机建模方法在文献中。我们给出了平稳性的条件，并导出了该模型的协方差和关系序列的形式。我们描述了如何在时域和频域中有效地进行参数估计。我们证明了实际效用的过程中捕捉椭圆振荡，自然存在于地震信号。
We propose a simple stochastic process for modeling improper or noncircular complex-valued signals. The process is a natural extension of a complex-valued autoregressive process, extended to include a widely linear autoregressive term. This process can then capture elliptical, as opposed to circular, stochastic oscillations in a bivariate signal. The process is order one and is more parsimonious than alternative stochastic modeling approaches in the literature. We provide conditions for stationarity, and derive the form of the covariance and relation sequence of this model. We describe how parameter estimation can be efficiently performed both in the time and frequency domain. We demonstrate the practical utility of the process in capturing elliptical oscillations that are naturally present in seismic signals.