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Asymptotic normality of statistical-function estimators for generalized almost-cyclostationary processes

机译:广义半循环平稳过程统计函数估计量的渐近正态性

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The problem of estimating second-order statistical functions of generalized almost-cyclostationary (GACS) processes is addressed. The class of such nonstationary processes includes, as a special case, the almost-cyclostationary (ACS) processes. ACS processes filtered by Doppler channels and communications signals with time-varying parameters are further examples. It is shown that, for GACS processes, the cyclic correlogram is an asymptotically Normal mean-square consistent estimator of the cyclic autocorrelation function. Thus, well-known results for ACS processes can be obtained as a special case of the results of this paper.
机译:解决了估计广义近似循环平稳(GACS)过程的二阶统计函数的问题。这种非平稳过程的类别在特殊情况下包括几乎循环平稳(ACS)的过程。由多普勒信道过滤的ACS过程和具有时变参数的通信信号是进一步的示例。结果表明,对于GACS过程,循环相关图是循环自相关函数的渐近正态均方一致估计量。因此,作为本文结果的特例,可以获得ACS过程的众所周知的结果。

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