基于线性正则变换的遍历随机信号估计

Liyun Xu
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引用次数: 0

摘要

线性正则变换(LCT)为解决光学和量子力学问题提供了一种通用的数学工具。对于LCT域中带宽有限的随机信号,线性正则相关函数和线性正则功率谱密度可以组成LCT对。用于定义卷积函数和相关函数的线性正则平移算子在随机信号估计的分析中也起着重要作用。首先讨论了线性正则平移下不变的特征函数及其一致性。其次,将LCT采样定理与von Neumann遍历定理在分布意义上联系起来,在LCT域内建立了一种估计啁啾平稳随机信号功率谱密度的方法。最后,对该方法的应用前景和今后的工作进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Random Signal Estimation by Ergodicity associated with Linear Canonical Transform
The linear canonical transform (LCT) provides a general mathematical tool for solving problems in optical and quantum mechanics. For random signals, which are bandlimited in the LCT domain, the linear canonical correlation function and the linear canonical power spectral density can form a LCT pair. The linear canonical translation operator, which is used to define the convolution and correlation functions, also plays a significant role in the analysis of the random signal estimation. Firstly, the eigenfunctions which are invariant under the linear canonical translation and the unitarity property of it are discussed. Secondly, it shows that all of these connect the LCT sampling theorem and the von Neumann ergodic theorem in the sense of distribution, which will develop an estimation method for the power spectral density of a chirp stationary random signal from one sampling signal in the LCT domain. Finally, the potential applications and future work are discussed.
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